The following code adds data from a dataframe to a sheet in Smartsheet -- this should be enough to at least get you started. If you still can't get the desired result using this code, please update your original post to include the code you're using, the outcome you're wanting, and a detailed description of the issue you encountered. (Add a comment to this answer if you update your original post, so I'll be notified and will know to look.)
# target sheet
sheet_id = 3932034054809476
sheet = smartsheet_client.Sheets.get_sheet(sheet_id)
# translate column names to column id
column_map = {}
for column in sheet.columns:
column_map[column.title] = column.id
df = pd.DataFrame({'item_id': [111111, 222222],
'item_color': ['red', 'yellow'],
'item_location': ['office', 'kitchen']})
data_dict = df.to_dict('index')
rowsToAdd = []
# each object in data_dict represents 1 row of data
for i, i in data_dict.items():
# create a new row object
new_row = smartsheet_client.models.Row()
new_row.to_top = True
# for each key value pair, create & add a cell to the row object
for k, v in i.items():
# create the cell object and populate with value
new_cell = smartsheet_client.models.Cell()
new_cell.column_id = column_map[k]
new_cell.value = v
# add the cell object to the row object
new_row.cells.append(new_cell)
# add the row object to the collection of rows
rowsToAdd.append(new_row)
# add the collection of rows to the sheet in Smartsheet
result = smartsheet_client.Sheets.add_rows(sheet_id, rowsToAdd)
UPDATE #1 - re Bad Request error
Seems like the error you've described in your first comment below is perhaps being caused by the fact that some of the cells in your dataframe don't have a value. When you add a new row using the Smartsheet API, each cell that's specified for the row must specify a value for the cell -- otherwise you'll get the Bad Request error you've described. Maybe try adding an if statement inside the for loop to skip adding the cell if the value of v is None?
for k,v in i.items():
# skip adding this cell if there's no value
if v is None:
continue
...
UPDATE #2 - re further troubleshooting
In response to your second comment below: you'll need to debug further using the data in your dataframe, as I'm unable to repro the issue you describe using other data.
To simplify things -- I'd suggest that you start by trying to debug with just one item in the dataframe. You can do so by adding the line (statement) break at the end of the for loop that's building the dict -- that way, only the first device will be added.
for device in list_of_devices:
try:
...
except KeyError:
dict1['Lan_Ip'] = "NA"
temp = pd.DataFrame.from_dict(dict1)
alldata = alldata.append(temp)
# break out of loop after one item is added
break
alldata.reset_index(drop=True, inplace=True)
# print dataframe contents
print (alldata)
If you get the same error when testing with just one item, and can't recognize what it is about that data (or the way it's stored in your dataframe) that's causing the Smartsheet error, then feel free to add a print (alldata) statement after the for loop (as I show in the code snippet above) to your code and update your original post again to include the output of that statement (changing any sensitive data values, of course) -- and then I can try to repro/troubleshoot using that data.
UPDATE #3 - repro'd issue
Okay, so I've reproduced the error you've described -- by specifying None as the value of a field in the dict.
The following code successfully inserts two new rows into Smartsheet -- because every field in each dict it builds contains a (non-None) value. (For simplicity, I'm manually constructing two dicts in the same manner as you do in your for loop.)
# target sheet
sheet_id = 37558492129156
sheet = smartsheet_client.Sheets.get_sheet(sheet_id)
# translate column names to column id
column_map = {}
for column in sheet.columns:
column_map[column.title] = column.id
#----
# start: repro SO question's building of dataframe
#----
alldata = pd.DataFrame()
dict1 = {'Name': ['name1'],
"Serial_No": ['serial_no1'],
'MAC': ['mac1'],
'Network_Id': ['networkId1'],
'Product_Type': ['productType1'],
'Model': ['model1'],
'Tags': ['tags1'],
'Lan_Ip': ['lanIp1'],
'Configuration_Updated_At': ['configurationUpdatedAt1'],
'Firmware': ['firmware1'],
'URL': ['url1']
}
temp = pd.DataFrame.from_dict(dict1)
alldata = alldata.append(temp)
dict2 = {'Name': ['name2'],
"Serial_No": ['serial_no2'],
'MAC': ['mac2'],
'Network_Id': ['networkId2'],
'Product_Type': ['productType2'],
'Model': ['model2'],
'Tags': ['tags2'],
'Lan_Ip': ['lanIp2'],
'Configuration_Updated_At': ['configurationUpdatedAt2'],
'Firmware': ['firmware2'],
'URL': ['URL2']
}
temp = pd.DataFrame.from_dict(dict2)
alldata = alldata.append(temp)
alldata.reset_index(drop=True, inplace=True)
#----
# end: repro SO question's building of dataframe
#----
data_dict = alldata.to_dict('index')
rowsToAdd = []
# each object in data_dict represents 1 row of data
for i, i in data_dict.items():
# create a new row object
new_row = smartsheet_client.models.Row()
new_row.to_top = True
# for each key value pair, create & add a cell to the row object
for k, v in i.items():
# create the cell object and populate with value
new_cell = smartsheet_client.models.Cell()
new_cell.column_id = column_map[k]
new_cell.value = v
# add the cell object to the row object
new_row.cells.append(new_cell)
# add the row object to the collection of rows
rowsToAdd.append(new_row)
result = smartsheet_client.Sheets.add_rows(sheet_id, rowsToAdd)
However, running the following code (where the value of the URL field in the second dict is set to None) results in the same error you've described:
{"response": {"statusCode": 400, "reason": "Bad Request", "content": {"detail": {"index": 1}, "errorCode": 1012, "message": "Required object attribute(s) are missing from your request: cell.value.", "refId": "dw1id3oj1bv0"}}}
Code that causes this error (identical to the successful code above except that the value of the URL field in the second dict is None):
# target sheet
sheet_id = 37558492129156
sheet = smartsheet_client.Sheets.get_sheet(sheet_id)
# translate column names to column id
column_map = {}
for column in sheet.columns:
column_map[column.title] = column.id
#----
# start: repro SO question's building of dataframe
#----
alldata = pd.DataFrame()
dict1 = {'Name': ['name1'],
"Serial_No": ['serial_no1'],
'MAC': ['mac1'],
'Network_Id': ['networkId1'],
'Product_Type': ['productType1'],
'Model': ['model1'],
'Tags': ['tags1'],
'Lan_Ip': ['lanIp1'],
'Configuration_Updated_At': ['configurationUpdatedAt1'],
'Firmware': ['firmware1'],
'URL': ['url1']
}
temp = pd.DataFrame.from_dict(dict1)
alldata = alldata.append(temp)
dict2 = {'Name': ['name2'],
"Serial_No": ['serial_no2'],
'MAC': ['mac2'],
'Network_Id': ['networkId2'],
'Product_Type': ['productType2'],
'Model': ['model2'],
'Tags': ['tags2'],
'Lan_Ip': ['lanIp2'],
'Configuration_Updated_At': ['configurationUpdatedAt2'],
'Firmware': ['firmware2'],
'URL': [None]
}
temp = pd.DataFrame.from_dict(dict2)
alldata = alldata.append(temp)
alldata.reset_index(drop=True, inplace=True)
#----
# end: repro SO question's building of dataframe
#----
data_dict = alldata.to_dict('index')
rowsToAdd = []
# each object in data_dict represents 1 row of data
for i, i in data_dict.items():
# create a new row object
new_row = smartsheet_client.models.Row()
new_row.to_top = True
# for each key value pair, create & add a cell to the row object
for k, v in i.items():
# create the cell object and populate with value
new_cell = smartsheet_client.models.Cell()
new_cell.column_id = column_map[k]
new_cell.value = v
# add the cell object to the row object
new_row.cells.append(new_cell)
# add the row object to the collection of rows
rowsToAdd.append(new_row)
result = smartsheet_client.Sheets.add_rows(sheet_id, rowsToAdd)
Finally, note that the error message I received contains {"index": 1} -- this implies that the value of index in this error message indicates the (zero-based) index of the problematic row. The fact that your error message contains {"index": 0} implies that there's a problem with the data in the first row you're trying to add to Smartsheet (i.e., the first item in the dataframe). Therefore, following the troubleshooting guidance I posted in my previous update (Update #2 above) should allow you to closely examine the data for the first item/row and hopefully spot the problematic data (i.e., where the value is missing).
