How to import a CSV file using Google Sheets API V4

Question

Background

I\'m developing a Python 2.7 script that analyzes data from an SQL table and at the end, generates a CSV file.

Once the file is gener

Answer 1

I've spent couple of hours trying to make any of the other answers work. Libraries do not explain the authentication well, and don't work with google-provided way of handling credentials. On the other hand, Sam's answer doesn't elaborate on the details of using the API, which might be confusing at times. So, here is a full recipe of uploading CSVs to gSheets. It uses both Sam's and CapoChino's answers plus some of my own research.

1. Authenticate/Setup. Generally, refer to the docs
   • Big blue button will get you credentials.json with no extra steps
   • quickstart.py can easily be adapted into authenticate.py
   • scopes should contain https://www.googleapis.com/auth/spreadsheets

Hopefully by now you have your credentials stored, so let's move to the actual code

2. Recipe that should work out of the box:

import pickle
from googleapiclient.discovery import build

SPREADSHEET_ID = '1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms' # Get this one from the link in browser
worksheet_name = 'Sheet2'
path_to_csv = 'New Folder/much_data.csv'
path_to_credentials = 'Credentials/token.pickle'


# convenience routines
def find_sheet_id_by_name(sheet_name):
    # ugly, but works
    sheets_with_properties = API \
        .spreadsheets() \
        .get(spreadsheetId=SPREADSHEET_ID, fields='sheets.properties') \
        .execute() \
        .get('sheets')

    for sheet in sheets_with_properties:
        if 'title' in sheet['properties'].keys():
            if sheet['properties']['title'] == sheet_name:
                return sheet['properties']['sheetId']


def push_csv_to_gsheet(csv_path, sheet_id):
    with open(csv_path, 'r') as csv_file:
        csvContents = csv_file.read()
    body = {
        'requests': [{
            'pasteData': {
                "coordinate": {
                    "sheetId": sheet_id,
                    "rowIndex": "0",  # adapt this if you need different positioning
                    "columnIndex": "0", # adapt this if you need different positioning
                },
                "data": csvContents,
                "type": 'PASTE_NORMAL',
                "delimiter": ',',
            }
        }]
    }
    request = API.spreadsheets().batchUpdate(spreadsheetId=SPREADSHEET_ID, body=body)
    response = request.execute()
    return response


# upload
with open(path_to_credentials, 'rb') as token:
    credentials = pickle.load(token)

API = build('sheets', 'v4', credentials=credentials)

push_csv_to_gsheet(
    csv_path=path_to_csv,
    sheet_id=find_sheet_id_by_name(worksheet_name)
)

Good thing about directly using batchUpdate is that it uploads thousands of rows in a second. On a low level gspread does the same and should be as performant. Also there is gspread-pandas.

p.s. the code is tested with python 3.5, but this thread seemed to be most appropriate to submit it to.