Package Health Score

67 / 100

security
Security review needed
popularity
Influential project
maintenance
Sustainable
community
Sustainable

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Popularity

Influential project

GitHub Stars: 1.52K
Forks: 222
Contributors: -

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package pygsheets, we found that it has been starred 1,517 times.

Security

Security review needed

Security and license risk for latest version

Release Date: Nov 30, 2022
Direct Vulnerabilities: 0
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0
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0
M
0
L
Indirect Vulnerabilities: 0
C
0
H
0
M
0
L
License Risk: 0
H
2
M
0
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All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

MIT

Security Policy

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Maintenance

Sustainable

Commit Frequency

Open Issues: 64
Open PR: 4
Last Release: 2 years ago
Last Commit: 10 months ago

Further analysis of the maintenance status of pygsheets based on released PyPI versions cadence, the repository activity, and other data points determined that its maintenance is Sustainable.

An important project maintenance signal to consider for pygsheets is that it hasn't seen any new versions released to PyPI in the past 12 months, and could be considered as a discontinued project, or that which receives low attention from its maintainers.

As a healthy sign for on-going project maintenance, we found that the GitHub repository had at least 1 pull request or issue interacted with by the community.

Community

Sustainable

Readme: Yes
Contributing.md: No
Code of Conduct: No
Contributors: 0
Funding: No

This project has seen only 10 or less contributors.

We found a way for you to contribute to the project! Looks like pygsheets is missing a Code of Conduct.

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Package

Python Versions Compatibility: >=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*

Age: 8 years
Latest Release: 2 years ago
Dependencies: 3 Direct / 22 Total
Versions: 17
Maintainers: 1
Wheels: OS Independent

Not sure how to use pygsheets?

To help you get started, we've collected the most common ways that pygsheets is being used within popular public projects.

avrae / avrae / test / sheets / autogsheet.py View on Github

def main():
    gc = pygsheets.authorize(service_file='./avrae-0b82f09d7ab3.json')

    template = gc.open_by_key(TEMPLATE_SPREADSHEET_ID)  # open template
    new_sheet = gc.create("TESTNew CharacterTEST", parent_id=PARENT_FOLDER_ID)  # create new character sheet

    template.sheet1.copy_to(new_sheet.id)  # copy character sheet over
    new_sheet.del_worksheet(new_sheet.sheet1)  # delete default worksheet
    new_sheet.worksheet().title = "v1.3"  # pretty it a little

    feature_cell_index = 0

    feature_cell_index = do_race(new_sheet.worksheet(), feature_cell_index)
    feature_cell_index = do_class_and_level(new_sheet.worksheet(), feature_cell_index)
    email = input("Please enter your Google account email: ")
    new_sheet.share(email, role='writer')  # give control to user

View more ways to use pygsheets

pygsheets - Google Spreadsheets Python API v4

A simple, intuitive library for google sheets which gets your work done.

Features:

Open, create, delete and share spreadsheets using title or key
Intuitive models - spreadsheet, worksheet, cell, datarange
Control permissions of spreadsheets.
Set cell format, text format, color, write notes
Named and Protected Ranges Support
Work with range of cells easily with DataRange and Gridrange
Data validation support. checkboxes, drop-downs etc.
Conditional formatting support
get multiple ranges with get_values_batch and update wit update_values_batch

Updates

version 2.0.6 released

Installation

From PyPi (Stable)

pip install pygsheets

If you are installing from pypi please see the docs here.

From GitHub (Recommended)

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

If you are installing from github please see the docs here.

Basic Usage

Basic features are shown here, for complete set of features see the full documentation here.

Obtain OAuth2 credentials from Google Developers Console for google spreadsheet api and drive api and save the file as client_secret.json in same directory as project. read more here.
Start using pygsheets:

Sample scenario : you want to share a numpy array with your remote friend

import pygsheets
import numpy as np

gc = pygsheets.authorize()

# Open spreadsheet and then worksheet
sh = gc.open('my new sheet')
wks = sh.sheet1

# Update a cell with value (just to let him know values is updated ;) )
wks.update_value('A1', "Hey yank this numpy array")
my_nparray = np.random.randint(10, size=(3, 4))

# update the sheet with array
wks.update_values('A2', my_nparray.tolist())

# share the sheet with your friend
sh.share("myFriend@gmail.com")

Sample Scenario: you want to fill height values of students


## import pygsheets and open the sheet as given above

header = wks.cell('A1')
header.value = 'Names'
header.text_format['bold'] = True # make the header bold
header.update()

# or achive the same in oneliner
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 as DataRange object
heights.name = "heights"  # name the range
heights.update_values([[50],[60],[67],[66]]) # update the values
wks.update_value('B6','=average(heights)') # set the avg value of heights using named range

More Examples

Opening a Spreadsheet

# You can open a spreadsheet by its title as it appears in Google Docs 
sh = gc.open("pygsheetTest")

# If you want to be specific, use a key
sht1 = gc.open_by_key('1mwA-NmvjDqd3A65c8hsxOpqdfdggPR0fgfg5nXRKScZAuM')

# create a spreadsheet in a folder (by id)
sht2 = gc.create("new sheet", folder_name="my worksheets")

# open enable TeamDrive support
gc.drive.enable_team_drive("Dqd3A65c8hsxOpqdfdggPR0fgfg")

Operations on Spreadsheet doc

show code


import pygsheets
c = pygsheets.authorize()
sh = c.open('spreadsheet')

# create a new sheet with 50 rows and 60 colums
wks = sh.add_worksheet("new sheet",rows=50,cols=60)

# create a new sheet with 50 rows and 60 colums at the begin of worksheets
wks = sh.add_worksheet("new sheet",rows=50,cols=60,index=0)

# or copy from another worksheet
wks = sh.add_worksheet("new sheet", src_worksheet='')

# delete this wroksheet
sh.del_worksheet(wks)

# unshare the sheet
sh.remove_permissions("myNotSoFriend@gmail.com")

Selecting a Worksheet

show code

import pygsheets
c = pygsheets.authorize()
sh = c.open('spreadsheet')

# Select worksheet by id, index, title.
wks = sh.worksheet_by_title("my test sheet")

# By any property
wks = sh.worksheet('index', 0)

# Get a list of all worksheets
wks_list = sh.worksheets()

# Or just
wks = sh[0]

Operations on Worksheet doc

show code

# Get values as 2d array('matrix') which can easily be converted to an numpy aray or as 'cell' list
values_mat = wks.get_values(start=(1,1), end=(20,20), returnas='matrix')

# Get values of - rows A1 to B10, column C, 1st row, 10th row
wks.get_values_batch(['A1:B10', 'C', '1', (10, None)])

# Get all values of sheet as 2d list of cells
cell_matrix = wks.get_all_values(returnas='matrix')

# update a range of values with a cell list or matrix
wks.update_values(crange='A1:E10', values=values_mat)

# update multiple ranges with bath update
wks.update_values_batch(['A1:A2', 'B1:B2'], [[[1],[2]], [[3],[4]]])

# Insert 2 rows after 20th row and fill with values
wks.insert_rows(row=20, number=2, values=values_list)

# resize by changing rows and colums
wks.rows=30

# use the worksheet as a csv
for row in wks:
    print(row)

# get values by indexes
 A1_value = wks[0][0]

# clear all values
wks.clear()

# Search for a table in the worksheet and append a row to it
wks.append_table(values=[1,2,3,4])

# export a worksheet as csv
wks.export(pygsheets.ExportType.CSV)

# Find/Replace cells with string value
cell_list = worksheet.find("query string")

# Find/Replace cells with regexp
filter_re = re.compile(r'(small|big) house')
cell_list = worksheet.find(filter_re, searchByRegex=True)
cell_list = worksheet.replace(filter_re, 'some house', searchByRegex=True)

# Move a worksheet in the same spreadsheet (update index)
wks.index = 2 # index start at 1 , not 0

# Update title
wks.title = "NewTitle"

# Update hidden state
wks.hidden = False

# working with named ranges
wks.create_named_range('A1', 'A10', 'prices')
wks.get_named_range('prices')
wks.get_named_ranges()  # will return a list of DataRange objects
wks.delete_named_range('prices')

# apply format
wks.apply_format(['A1:B1', 'D:E'], ["NUMBER", "TEXT"])

# Plot a chart/graph
wks.add_chart(('A1', 'A6'), [('B1', 'B6')], 'Health Trend')

# create drop-downs
wks.set_data_validation(start='C4', end='E7', condition_type='NUMBER_BETWEEN', condition_values=[2,10], strict=True, inputMessage="inut between 2 and 10")

# set a formula and extend it to more cells
cell = wks.cell('C1')
cell.value = '=A1+B1'
wks.apply_format('C1:C10', cell, 'userEnteredValue.formulaValue')

Pandas integration

If you work with pandas, you can directly use the dataframes

#set the values of a pandas dataframe to sheet
wks.set_dataframe(df,(1,1))

#you can also get the values of sheet as dataframe
df = wks.get_as_df()

Cell Object doc

Each cell has a value and cordinates (row, col, label) properties.

Getting cell objects

show code

c1 = Cell('A1',"hello")  # create a unlinked cell
c1 = worksheet.cell('A1')  # creates a linked cell whose changes syncs instantanously
cl.value  # Getting cell value
c1.value_unformatted #Getting cell unformatted value
c1.formula # Getting cell formula if any
c1.note # any notes on the cell
c1.address # address object with cell position

cell_list = worksheet.range('A1:C7')  # get a range of cells 
cell_list = worksheet.col(5, returnas='cell')  # return all cells in 5th column(E)

Most of the functions has returnas param, if whose value is cell it will return a list of cell objects. Also you can use label or (row,col) tuple interchangbly as a cell adress

Cell Operations

Each cell is directly linked with its cell in spreadsheet, hence changing the value of cell object will update the corresponding cell in spreadsheet unless you explictly unlink it Also not that bu default only the value of cell is fetched, so if you are directly accessing any cell properties call cell.fetch() beforehand.

Different ways of updating Cells

show code

# using linked cells
c1 = worksheet.cell('B1') # created from worksheet, so linked cell
c1.col = 5  # Now c1 correponds to E1
c1.value = "hoho"  # will change the value of E1

# Or onliner
worksheet.update_value('B1', 'hehe')

# get a range of cells
cell_list = worksheet.range('A1:C7')
cell_list = worksheet.get_values(start='A1', end='C7', returnas='cells')
cell_list = worksheet.get_row(2, returnas='cells')


# add formula
c1.formula = 'A1+C2'
c1.formula # '=A1+C2'

# get neighbouring cells
c2 = c1.neighbour('topright') # you can also specify relative position as tuple eg (1,1)

# set cell format
c1.set_number_format(pygsheets.FormatType.NUMBER, '00.0000')

# write notes on cell
c1.note = "yo mom"

# set cell color
c1.color = (1.0, 1.0, 1.0, 1.0) # Red, Green, Blue, Alpha

# set text format
c1.text_format['fontSize'] = 14
c1.set_text_format('bold', True)

# sync the changes
 c1.update()

# you can unlink a cell and set all required properties and then link it
# So yu could create a model cell and update multiple sheets
c.unlink()
c.note = "offine note"
c.link(wks1, True)
c.link(wks2, True)

DataRange Object doc

The DataRange is used to represent a range of cells in a worksheet. They can be named or protected. Almost all get_ functions has a returnas param, set it to range to get a range object.

show code

# Getting a Range object
rng = wks.get_values('A1', 'C5', returnas='range')
rng.start_addr = 'A' # make the range unbounded on rows 
drange.end_addr = None # make the range unbounded on both axes 

# Named ranges
rng.name = 'pricesRange'  # will make this range a named range
rng = wks.get_named_ranges('commodityCount') # directly get a named range
rng.name = ''  # will delete this named range

#Protected ranges
rng.protected = True
rng.editors = ('users', 'someemail@gmail.com')

# Setting Format
 # first create a model cell with required properties
model_cell = Cell('A1')
model_cell.color = (1.0,0,1.0,1.0) # rose color cell
model_cell.format = (pygsheets.FormatType.PERCENT, '')

 # Setting format to multiple cells in one go
rng.apply_format(model_cell)  # will make all cell in this range rose color and percent format
# Or if you just want to apply format, you can skip fetching data while creating datarange
Datarange('A1','A10', worksheet=wks).apply_format(model_cell)

# get cells in range
cell = rng[0][1]

Batching calls

If you are calling a lot of spreadsheet modification functions (non value update). you can merge them into a single call. By doing so all the requests will be merged into a single call.

gc.set_batch_mode(True)
wks.merge_cells("A1", "A2")
wks.merge_cells("B1", "B2")
Datarange("D1", "D5", wks).apply_format(cell)
gc.run_batch() # All the above requests are executed here
gc.set_batch_mode(False)

Batching also happens when you unlink worksheet. But in that case the requests are not merged.

How to Contribute

This library is still in development phase.

Follow the Contributing to Open Source Guide.
Branch off of the staging branch, and submit Pull Requests back to that branch. Note that the master branch is used for version bumps and hotfixes only.
For quick testing the changes you have made to source, run the file tests/manual_testing.py. It will give you an IPython shell with lastest code loaded.

Report Issues/Features

Please report bugs and suggest features via the GitHub Issues.
Before opening an issue, search the tracker for possible duplicates.
If you have any usage questions, ask a question on stackoverflow with pygsheets Tag

Run Tests

install pip install -r requirements-dev.txt
run make test

Now that you have scrolled all the way down, finding this library useful?

pygsheets dependencies

enum34 google-api-python-client google-auth-oauthlib

FAQs

What is pygsheets?

Google Spreadsheets Python API v4. Visit Snyk Advisor to see a full health score report for pygsheets, including popularity, security, maintenance & community analysis.

Is pygsheets popular?

The python package pygsheets receives a total of 533,265 weekly downloads. As such, pygsheets popularity was classified as an influential project. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is pygsheets well maintained?

We found indications that pygsheets maintenance is sustainable demonstrating some project activity. We saw a total of 0 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is pygsheets safe to use?

While scanning the latest version of pygsheets, we found that a security review is needed. A total of 0 vulnerabilities or license issues were detected. See the full security scan results.

Last updated on 19 November-2024, at 11:46 (UTC).

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Direct Usage Popularity

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Check your requirements.txt

Snyk Vulnerability Scanner

Not sure how to use pygsheets?

pygsheets - Google Spreadsheets Python API v4

Updates

Installation

From PyPi (Stable)

From GitHub (Recommended)

Basic Usage

More Examples

Opening a Spreadsheet

Operations on Spreadsheet doc

Selecting a Worksheet

Operations on Worksheet doc

Pandas integration

Cell Object doc

Cell Operations

DataRange Object doc

Batching calls

How to Contribute

Report Issues/Features

Run Tests

pygsheets dependencies

FAQs

What is pygsheets?

Is pygsheets popular?

Is pygsheets well maintained?

Is pygsheets safe to use?

Build a secure application checklist

Select a recommended open source package

Scan your app for vulnerabilities

Source Code

Open Source

Container

Config

Fix identified vulnerabilities

Monitor for new issues