I’m not sure why but after getting a new install of windows and a new pycharm install and trying to run some previously functional code I am now getting the above error with the code below. Is it a setup issue or has something changed that now makes this code not function? Error happens on the last line. The error doesn’t make sense to me as there should be no conversion required for ndarray to ndarray.
<code>import numpy as np
import pyodbc
import pandas as pd
import sqlalchemy as SQL
import torch
import datetime
# Setup your SQL connection
server = [hidden for security]
database = [hidden for security]
username = [hidden for security]
password = [hidden for security]
# This is using the pyodbc connection
cnxn = pyodbc.connect(
'DRIVER={SQL Server};SERVER=' + server + ';DATABASE=' + database + ';UID=' + username + ';PWD=' + password)
cursor = cnxn.cursor()
# This is using the SQLAlchemy connection
engine_str = SQL.URL.create(
drivername="mssql+pyodbc",
username=username,
password=password,
host=server,
port=1433,
database=database,
query={
"driver": "ODBC Driver 17 for SQL Server",
"TrustServerCertificate": "no",
"Connection Timeout": "30",
"Encrypt": "yes",
},
)
engine = SQL.create_engine(engine_str)
storeemployee = []
regionalemployee = []
regionid = []
storeid = []
# get table from dev
with engine.connect() as connection:
result = connection.execute(SQL.text("SELECT StoreId, R_Num, RegionalMerchandiserEmployeeId, StoreMerchandiserEmployeeId from Staging.StoreMerchandiserInput"))
for row in result:
# set your variables = to the results
storeemployee.append(row.StoreMerchandiserEmployeeId)
regionalemployee.append(row.RegionalMerchandiserEmployeeId)
regionid.append(row.R_Num)
storeid.append(row.StoreId)
storeemployee = np.array(storeemployee)
regionalemployee = np.array(regionalemployee)
regionid = np.array(regionid)
storeid = np.array(storeid)
# StoreMerchandiserEmail
data = {'StoreMerchandiserEmployeeId': storeemployee, 'RegionalMerchandiserEmployeeId': regionalemployee,
"R_Num": regionid, "StoreId":storeid}
FinalData = pd.DataFrame(data, columns=['StoreMerchandiserEmployeeId', 'RegionalMerchandiserEmployeeId', 'R_Num', 'StoreId'])
</code>
<code>import numpy as np
import pyodbc
import pandas as pd
import sqlalchemy as SQL
import torch
import datetime
# Setup your SQL connection
server = [hidden for security]
database = [hidden for security]
username = [hidden for security]
password = [hidden for security]
# This is using the pyodbc connection
cnxn = pyodbc.connect(
'DRIVER={SQL Server};SERVER=' + server + ';DATABASE=' + database + ';UID=' + username + ';PWD=' + password)
cursor = cnxn.cursor()
# This is using the SQLAlchemy connection
engine_str = SQL.URL.create(
drivername="mssql+pyodbc",
username=username,
password=password,
host=server,
port=1433,
database=database,
query={
"driver": "ODBC Driver 17 for SQL Server",
"TrustServerCertificate": "no",
"Connection Timeout": "30",
"Encrypt": "yes",
},
)
engine = SQL.create_engine(engine_str)
storeemployee = []
regionalemployee = []
regionid = []
storeid = []
# get table from dev
with engine.connect() as connection:
result = connection.execute(SQL.text("SELECT StoreId, R_Num, RegionalMerchandiserEmployeeId, StoreMerchandiserEmployeeId from Staging.StoreMerchandiserInput"))
for row in result:
# set your variables = to the results
storeemployee.append(row.StoreMerchandiserEmployeeId)
regionalemployee.append(row.RegionalMerchandiserEmployeeId)
regionid.append(row.R_Num)
storeid.append(row.StoreId)
storeemployee = np.array(storeemployee)
regionalemployee = np.array(regionalemployee)
regionid = np.array(regionid)
storeid = np.array(storeid)
# StoreMerchandiserEmail
data = {'StoreMerchandiserEmployeeId': storeemployee, 'RegionalMerchandiserEmployeeId': regionalemployee,
"R_Num": regionid, "StoreId":storeid}
FinalData = pd.DataFrame(data, columns=['StoreMerchandiserEmployeeId', 'RegionalMerchandiserEmployeeId', 'R_Num', 'StoreId'])
</code>
import numpy as np
import pyodbc
import pandas as pd
import sqlalchemy as SQL
import torch
import datetime
# Setup your SQL connection
server = [hidden for security]
database = [hidden for security]
username = [hidden for security]
password = [hidden for security]
# This is using the pyodbc connection
cnxn = pyodbc.connect(
'DRIVER={SQL Server};SERVER=' + server + ';DATABASE=' + database + ';UID=' + username + ';PWD=' + password)
cursor = cnxn.cursor()
# This is using the SQLAlchemy connection
engine_str = SQL.URL.create(
drivername="mssql+pyodbc",
username=username,
password=password,
host=server,
port=1433,
database=database,
query={
"driver": "ODBC Driver 17 for SQL Server",
"TrustServerCertificate": "no",
"Connection Timeout": "30",
"Encrypt": "yes",
},
)
engine = SQL.create_engine(engine_str)
storeemployee = []
regionalemployee = []
regionid = []
storeid = []
# get table from dev
with engine.connect() as connection:
result = connection.execute(SQL.text("SELECT StoreId, R_Num, RegionalMerchandiserEmployeeId, StoreMerchandiserEmployeeId from Staging.StoreMerchandiserInput"))
for row in result:
# set your variables = to the results
storeemployee.append(row.StoreMerchandiserEmployeeId)
regionalemployee.append(row.RegionalMerchandiserEmployeeId)
regionid.append(row.R_Num)
storeid.append(row.StoreId)
storeemployee = np.array(storeemployee)
regionalemployee = np.array(regionalemployee)
regionid = np.array(regionid)
storeid = np.array(storeid)
# StoreMerchandiserEmail
data = {'StoreMerchandiserEmployeeId': storeemployee, 'RegionalMerchandiserEmployeeId': regionalemployee,
"R_Num": regionid, "StoreId":storeid}
FinalData = pd.DataFrame(data, columns=['StoreMerchandiserEmployeeId', 'RegionalMerchandiserEmployeeId', 'R_Num', 'StoreId'])
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