GSpreadPlus 0.5.3

A high-level wrapper library for Google Sheets API v4

GSpreadPlus - Google Spreadsheets GSpreadPlus

---

Made on top of the orginal gspread Python API Wrapper, this wrapper (wrapper of a wrapper) targets at specific use cases such as returning row after finding column for a value. You'll get it if you use it.

Installation

---

Using PIP

Windows - Command Prompt:

python -m pip install GSpreadPlus

OR

Linux/MacOs - Terminal

python3 -m pip install GSpreadPlus

Done!!!

Project Status

• Alpha Beta
• Open Source

Tutorial

1. Import & Initializing

Import:

from GSpreadPlus import Spreadclient

Intialising:

client = Spreadclient('credentials.json')

OR

from json import loads
creds = loads('credentials.json')
client = Spreadclient(creds)

2. Connecting to Document/Sheet

To connect to the document, you need either one of the following Identifiers:

• Document Name
• Document Unique ID (Can be found in URL)
• Document URL

Connecting to Document:

client.connect_document('Banana Sales')
# OR
client.connect_document('4n5Dk5nfSxW1kNKG6vjZOAulDKgMb7JgcKEVlJb4mMpY')
# OR
client.connect_document('https://docs.google.com/spreadsheets/d/4n5Dk5nfSxW1kNKG6vjZOAulDKgMb7JgcKEVlJb4mMpY')

Connecting to Worksheet:

• By Name
• By Index (Pythonic)

client.connect_sheet('Monkey Employees')
# OR
client.connect_sheet(0)

Extra Attributes for Databases:

1. Orientation - orientation
   • If you are treating the spreadsheet like a database, you can set the orientation to either 'vertical'(default) or 'horizontal'
   • This will automatically get the headers depending on the orientation
   • If the data is propagating vertically, that would be the orientation ;
2. Headers Depth - headers_depth
   • If your databases have headers that are not starting from the first row/column you can change the depth
   • For example if your headers are at row 3, the headers depth would be 3

client.connect_sheet(
    'Monkey Employees',
    orientation='horizontal',
    headers_depth=3
)

3. Reading Data

Accessing the listed and headers attribute will gain access to their respective properties.

listed returns a list of list, where each list represents a row and each element in the inner list represents a cell

headers returns the headers based on the orientation

Refreshing:

Refreshing the data will send a request to the server for the new data and will push new local commits(changes).

Do note that refreshing will overwrite listed and it will overwrite the live spreadsheet regardless of its state.

In essence, we are assuming the live spreadsheet data doesn't get changed between the last fetched data and that instance.

client.refresh_sheet()

data = client.listed
print(f"There are {len(data)} rows in this sheet")

headers = client.headers
print(f"This spreadsheets' headers: {headers}")

Do note that client.refresh_sheet() should be used sparingly in order to reduce requests sent to the server and ultimately avoiding TOO_MANY_REQUESTS

4. Querying Data

Since this package is for sheets that work/act as databases, the following functions exist to assist in such tasks

Included Refreshing

For ALL query functions, and optional parameter refresh=False is available.

When set to True, self.refresh_sheet() will be invoked before executing the relevant function

---

A. Get Row by Column

get_row_by_column(self, value: Union[str, int], column: Union[str, int] = 0, refresh: bool = False)->list[Any]

Parameters

• value: Union[str, int]
  • This is the value that will be searched.
  • Returns a list of element for the first row that <column> matches value (case-sensitive)
• column: Union[str, int]
  • This is the column that value will be searched in
  • column can be column name (e.g. 'A') or index (Pythonic, e.g. 0)

---

B. Get Dimension by Header Name

get_dime_by_header(self, value: Union[str,int], header: Union[str, int], refresh: bool = False)->list[Any]

Parameters

• value: Union[str, int]
  • This is the value that will be searched.
  • Returns a list of element for the first row/column that <header attribute> matches value (case-sensitive)
• header: Union[str, int]
  • This is the header for the column that value will be searched in
  • header is case-sensitive

---

C. Get Rows by Function

get_rows_by_func(self, function: Callable, refresh: bool = False)->list[Any]

Parameters

• function: Callable
  • function should accept 1 parameter which is the row (i.e. list of cells in each row)
  • Should return a boolean value

matches = client.get_rows_by_func(
    lambda r:'pizza' in r[
            client.get_header_index('Fav Food')
        ].lower(),
    refresh = True
)

---

D. Commit/Add New Row

commit_new_row(self, values: Union[list,dict], offset:int=0, refresh=True)->list[gspread.models.Cell]

Parameters

• values: Union[list,dict]
  • Add new row of values based on dict keys or just by listical order
  • If refresh=False, the update will NOT be LIVE until refresh_sheet() is called again.

Returns list of Cells that have been added to self.commits