If you haven't yet authorized your app, read :doc:`oauth2` first.
You can open a spreadsheet by its title as it appears in Google Docs:
sh = gc.open('My poor gym results')
Note
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')
Use :meth:`~gspread.Client.create` to create a new blank spreadsheet:
sh = gc.create('A new spreadsheet')
Note
If you're using a :ref:`service account <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.
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 :meth:`~gspread.models.Spreadsheet.share` documentation for a full list of accepted parameters.
Select worksheet by index. Worksheet indexes start from zero:
worksheet = sh.get_worksheet(0)
Or by title:
worksheet = sh.worksheet("January")
Or the most common case: Sheet1:
worksheet = sh.sheet1
To get a list of all worksheets:
worksheet_list = sh.worksheets()
worksheet = sh.add_worksheet(title="A worksheet", rows=100, cols=20)
sh.del_worksheet(worksheet)
worksheet.update_title("December Transactions")
worksheet.update_tab_color({"red": 1, "green": 0.5, "blue": 0.5})
Using A1 notation:
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
Get the Unformatted value from a cell. Example: cells formatted as currency will display with the selected currency but they actual value is regular number.
Get the formatted (as displayed) value:
worksheet.get("A1:B2")
Results in: [['$12.00']]
Get the unformatted value:
from gspread.utils import ValueRenderOption
worksheet.get("A1:B2", value_render_option=ValueRenderOption.unformatted)
Results in: [[12]]
Get the formula from a cell instead of the resulting value:
from gspread.utils import ValueRenderOption
worksheet.get("G6", value_render_option=ValueRenderOption.formula)
Resulsts in: [['=1/1024']]
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)
Note
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 :exc:`~gspread.exceptions.APIError` 429 RESOURCE_EXHAUSTED.
Here are the methods that may help you to reduce API calls:
- :meth:`~gspread.models.Worksheet.get_all_values` fetches values from all of the cells of the sheet.
- :meth:`~gspread.models.Worksheet.get` fetches all values from a range of cells.
- :meth:`~gspread.models.Worksheet.batch_get` can fetch values from multiple ranges of cells with one API call.
- :meth:`~gspread.models.Worksheet.update` lets you update a range of cells with a list of lists.
- :meth:`~gspread.models.Worksheet.batch_update` lets you update multiple ranges of cells with one API call.
list_of_lists = worksheet.get_all_values()
list_of_dicts = worksheet.get_all_records()
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
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 one or multiple cells ranges at once:
worksheet.batch_clear(["A1:B1", "C2:E2", "my_named_range"])
Clear the entire worksheet:
worksheet.clear()
Each cell has a value and coordinates properties:
value = cell.value
row_number = cell.row
column_number = cell.col
Using A1 notation:
worksheet.update_acell('B1', 'Bingo!')
Or row and column coordinates:
worksheet.update_cell(1, 2, 'Bingo!')
Update a range
worksheet.update([[1, 2], [3, 4]], 'A1:B2')
You can add a strict validation to a cell.
ws.add_validation(
'A1',
ValidationConditionType.number_greater,
[10],
strict=True,
inputMessage='Value must be greater than 10',
)
Or add validation with a drop down.
worksheet.add_validation(
'C2:C7',
ValidationConditionType.one_of_list,
['Yes',
'No',]
showCustomUi=True
)
Check out the api docs for DataValidationRule and CondtionType for more details.
Gspread provides a function to extract a data table. A data table is defined as a rectangular table that stops either on the first empty cell or the enge of the sheet.
You can extract table from any address by providing the top left corner of the desired table.
Gspread provides 3 directions for searching the end of the table:
:attr:`~gspread.utils.TableDirection.right`: extract a single row searching on the right of the starting cell
:attr:`~gspread.utils.TableDirection.down`: extract a single column searching on the bottom of the starting cell
:attr:`~gspread.utils.TableDirection.table`: extract a rectangular table by first searching right from starting cell, then searching down from starting cell.
Note
Gspread will not look for empty cell inside the table. it only look at the top row and first column.
Example extracting a table from the below sample sheet:
ID | Name | Universe | Super power |
---|---|---|---|
1 | Batman | DC | Very rich |
2 | DeadPool | Marvel | self healing |
3 | Superman | DC | super human |
- | - | - | |
5 | Lavigne958 | maintains Gspread | |
6 | Alifee | maintains Gspread |
Using the below code will result in rows 2 to 4:
worksheet.expand("A2")
[
["Batman", "DC", "Very rich"],
["DeadPool", "Marvel", "self healing"],
["Superman", "DC", "super human"],
]
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 :meth:`~gspread.models.Worksheet.format` is a dictionary containing the fields to update. A full specification of format options is available at CellFormat in Sheet API Reference.
Tip
for more complex formatting see :ref:`gspread-formating-label`.
pandas is a popular library for data analysis. The simplest way to get data from a sheet to a pandas DataFrame is with :meth:`~gspread.models.Worksheet.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 :meth:`~gspread.models.Worksheet.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 community section :ref:`gspread-pandas-label`
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(array.tolist(), 'A2')