To install for usage: pip install gserializer
To import upon installation: import gserializer
Google Sheets Serializer
Author: Paul Shao
a Python library that converts online google sheets into serializable tabular data that can be directly manipulated as Python lists
Version: beta 1.0.6
Get Started:
If you are using this library the first time, please follow the steps below to ensure you have the required libraries and dependencies installed:
- Go to Google Developers Link for Sheets API and enable the Google Sheets API through your developer console (It doesn't matter which language for the API you are enabling it from).
- Download the generated
credentials.json
file - Use the command
pip show google-sheets-serializer
to determine the location of the installed library - Go inside the main directory for serializer package, and put the
credentials.json
file there.
Basic Usages:
The serializer mainly makes use of 2 objects, Reader
and Filter
. A Reader
is an object that performs the basic operation of reading in a google sheet given its spreadsheet ID and the name of the sheet.
- To find these two values for a given google sheet, follow the general guidelines below:
- For example, if I am currently using a spreadsheet, I should be able to get its ID by looking at the current link in my browser:
- The link should take the form of
https://docs.google.com/spreadsheets/d/<spreadsheetId>/edit#...
Where the placeholder <spreadsheetId>
is the spreadsheet ID. The name of the sheet refers to the name of the current tab of the sheet that you are working on. That can be found usually at the bottom left of the google sheets application.
General Methods:
Here are some of the methods currently supported by this library:
To use the package upon installation, import via:
import gserializer
The main package comes with 2 functions:
-
create_reader()
: creates aReader
object -
create_filter(reader)
: creates aFilter
object that takes inReader
object initialized with data
Methods supported by the 2 classes of objects are specified as below:
-
Reader
-
read_from_sheet(spreadsheetId, sheetName)
: takes in a spreadsheet ID and sheet name and returns a Reader object
-
-
Filter
- Note: the initialization of a
Filter
object requires aReader
object as an input, and you should generally load theReader
object with the sheets data by calling the methodread_from_sheet
before usingFilter
on top of it. -
num_cols()
: number of columns -
num_rows()
: number of rows -
int_values()
: converts all data in the google sheet to be integers if possible -
float_values()
: converts all data in the google sheet to be floating point numbers if possible -
col_names()
: a list of all the column names -
values()
: the data of the google sheet (without the column header) -
print_formatted()
: prints out all the data in a row-major and aligned order -
map(f)
: applies the functionf
to all of the data section of the sheet -
filter(major_order, f, numerical)
: filter the google sheet by the predicate functionf
. Eliminating any row or column that contains at least 1 value that doesn't obey the predicate. Here are some more detailed specifications for each of the parameters:-
major_order
: can take on values 0 or 1, 0 for row-major, and 1 for column-major -
f
: the predicate function, should always return a boolean; by defaultf
is set to always returnTrue
if not specified -
numerical
: indicates whether the data needs to be pre-formatted. 0 for leaving it as it is; 1 for converting all data to integers; 2 for converting all data to floating point numbers
-
-
reduce(major_order, f, numerical)
: reduce the google sheet by accumulating and combining cells using the functionf
. Here are the specifications for each of the parameters:-
major_order
: can take on values 0 or 1, 0 for row-major, and 1 for column-major -
f
: the combiner function, should take in 2 arguments (representing the values in 2 adjacent cells, either row-major or column-major) -
numerical
: indicates whether the data needs to be pre-formatted. 0 for leaving it as it is; 1 for converting all data to integers; 2 for converting all data to floating point numbers
-
- Note: the initialization of a