Python and google sheets

Examples of gspread Usage¶

You can open a spreadsheet by its title as it appears in Google Docs:

sh = gc.open('My poor gym results') 

If you have multiple Google Sheets with the same title, only the latest sheet will be opened by this method without throwing an error. It’s recommended to open the sheet using its unique ID instead (see below)

If you want to be specific, use a key (which can be extracted from the spreadsheet’s url):

sht1 = gc.open_by_key('0BmgG6nO_6dprdS1MN3d3MkdPa142WFRrdnRRUWl1UFE') 

Or, if you feel really lazy to extract that key, paste the entire spreadsheet’s url

sht2 = gc.open_by_url('https://docs.google.com/spreadsheet/ccc?key=0Bm. FE&hl') 

Creating a Spreadsheet¶

Use create() to create a new blank spreadsheet:

sh = gc.create('A new spreadsheet') 

If you’re using a service account , this new spreadsheet will be visible only to this account. To be able to access newly created spreadsheet from Google Sheets with your own Google account you must share it with your email. See how to share a spreadsheet in the section below.

Sharing a Spreadsheet¶

If your email is otto@example.com you can share the newly created spreadsheet with yourself:

sh.share('otto@example.com', perm_type='user', role='writer') 

See share() documentation for a full list of accepted parameters.

Selecting a Worksheet¶

Select worksheet by index. Worksheet indexes start from zero:

worksheet = sh.get_worksheet(0) 

worksheet = sh.worksheet("January") 

Or the most common case: Sheet1:

To get a list of all worksheets:

worksheet_list = sh.worksheets() 

Creating a Worksheet¶

worksheet = sh.add_worksheet(title="A worksheet", rows=100, cols=20) 

Deleting a Worksheet¶

Getting a Cell Value¶

val = worksheet.acell('B1').value 

Or row and column coordinates:

val = worksheet.cell(1, 2).value 

If you want to get a cell formula:

cell = worksheet.acell('B1', value_render_option='FORMULA').value # or cell = worksheet.cell(1, 2, value_render_option='FORMULA').value 

Getting All Values From a Row or a Column¶

Get all values from the first row:

values_list = worksheet.row_values(1) 

Get all values from the first column:

values_list = worksheet.col_values(1) 

So far we’ve been fetching a limited amount of data from a sheet. This works great until you need to get values from hundreds of cells or iterating over many rows or columns.

Under the hood, gspread uses Google Sheets API v4. Most of the time when you call a gspread method to fetch or update a sheet gspread produces one HTTP API call.

HTTP calls have performance costs. So if you find your app fetching values one by one in a loop or iterating over rows or columns you can improve the performance of the app by fetching data in one go.

What’s more, Sheets API v4 introduced Usage Limits (as of this writing, 300 requests per 60 seconds per project, and 60 requests per 60 seconds per user). When your application hits that limit, you get an APIError 429 RESOURCE_EXHAUSTED .

Here are the methods that may help you to reduce API calls:

• get_all_values() fetches values from all of the cells of the sheet.
• get() fetches all values from a range of cells.
• batch_get() can fetch values from multiple ranges of cells with one API call.
• update() lets you update a range of cells with a list of lists.
• batch_update() lets you update multiple ranges of cells with one API call.

Getting All Values From a Worksheet as a List of Lists¶

list_of_lists = worksheet.get_all_values() 

Getting All Values From a Worksheet as a List of Dictionaries¶

list_of_dicts = worksheet.get_all_records() 

Finding a Cell¶

Find a cell matching a string:

cell = worksheet.find("Dough") print("Found something at R%sC%s" % (cell.row, cell.col)) 

Find a cell matching a regular expression

amount_re = re.compile(r'(Big|Enormous) dough') cell = worksheet.find(amount_re) 

find returns None if value is not Found

Finding All Matched Cells¶

Find all cells matching a string:

cell_list = worksheet.findall("Rug store") 

Find all cells matching a regexp:

criteria_re = re.compile(r'(Small|Room-tiering) rug') cell_list = worksheet.findall(criteria_re) 

Clear A Worksheet¶

Clear one or multiple cells ranges at once:

worksheet.batch_clear(["A1:B1", "C2:E2", "my_named_range"]) 

Clear the entire worksheet:

Cell Object¶

Each cell has a value and coordinates properties:

value = cell.value row_number = cell.row column_number = cell.col 

Updating Cells¶

Or row and column coordinates:

worksheet.update_cell(1, 2, 'Bingo!') 

worksheet.update('A1:B2', [[1, 2], [3, 4]]) 

Formatting¶

Here’s an example of basic formatting.

Set A1:B1 text format to bold:

worksheet.format('A1:B1', 'textFormat': 'bold': True>>) 

Color the background of A2:B2 cell range in black, change horizontal alignment, text color and font size:

worksheet.format("A2:B2",  "backgroundColor":  "red": 0.0, "green": 0.0, "blue": 0.0 >, "horizontalAlignment": "CENTER", "textFormat":  "foregroundColor":  "red": 1.0, "green": 1.0, "blue": 1.0 >, "fontSize": 12, "bold": True > >) 

The second argument to format() is a dictionary containing the fields to update. A full specification of format options is available at CellFormat in Sheet API Reference.

gspread-formatting offers extensive functionality to help you when you go beyond basics.

Using gspread with pandas¶

pandas is a popular library for data analysis. The simplest way to get data from a sheet to a pandas DataFrame is with get_all_records() :

import pandas as pd dataframe = pd.DataFrame(worksheet.get_all_records()) 

Here’s a basic example for writing a dataframe to a sheet. With update() we put the header of a dataframe into the first row of a sheet followed by the values of a dataframe:

import pandas as pd worksheet.update([dataframe.columns.values.tolist()] + dataframe.values.tolist()) 

For advanced pandas use cases check out these libraries:

Using gspread with NumPy¶

NumPy is a library for scientific computing in Python. It provides tools for working with high performance multi-dimensional arrays.

Read contents of a sheet into a NumPy array:

import numpy as np array = np.array(worksheet.get_all_values()) 

The code above assumes that your data starts from the first row of the sheet. If you have a header row in the first row, you need replace worksheet.get_all_values() with worksheet.get_all_values()[1:] .

Write a NumPy array to a sheet:

import numpy as np array = np.array([[1, 2, 3], [4, 5, 6]]) # Write the array to worksheet starting from the A2 cell worksheet.update('A2', array.tolist()) 

© Copyright 2023, Anton Burnashev Revision e0fbbe88 .

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pygsheets¶

A simple, intuitive python library to access google spreadsheets through the Google Sheets API v4. So for example if you have few csv files which you want to export to google sheets and then plot some graphs based on the data. You can use this library to automate that.

Features¶

• Google Sheets API v4 support.
• Limited Google Drive API v3 support.
• Open and create spreadsheets by title.
• Add or remove permissions from you spreadsheets.
• Simple calls to get a row, column or defined range of values.
• Change the formatting properties of a cell.
• Supports named ranges & protected ranges.
• Queue up requests in batch mode and then process them in one go.

Updates¶

New version 2.0.0 released. Please see changelog to migrate from 1.x.

Small Example¶

First example — Share a numpy array with a friend:

import pygsheets client = pygsheets.authorize() # Open the spreadsheet and the first sheet. sh = client.open('spreadsheet-title') wks = sh.sheet1 # Update a single cell. wks.update_value('A1', "Numbers on Stuff") # Update the worksheet with the numpy array values. Beginning at cell 'A2'. wks.update_values('A2', my_numpy_array.to_list()) # Share the sheet with your friend. (read access only) sh.share('friend@gmail.com') # sharing with write access sh.share('friend@gmail.com', role='writer') 

Second example — Store some data and change cell formatting:

# open a worksheet as in the first example. header = wks.cell('A1') header.value = 'Names' header.text_format['bold'] = True # make the header bold header.update() # The same can be achieved in one line wks.cell('B1').set_text_format('bold', True).value = 'heights' # set the names wks.update_values('A2:A5',[['name1'],['name2'],['name3'],['name4']]) # set the heights heights = wks.range('B2:B5', returnas='range') # get the range heights.name = "heights" # name the range heights.update_values([[50],[60],[67],[66]]) # update the values wks.update_value('B6','=average(heights)') # set get the avg value 

Installation¶

pip install https://github.com/nithinmurali/pygsheets/archive/master.zip 

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