A Python library that simplifies Smartsheet API workflows
Reason this release was yanked:
temporarily revoking release, pending release approval
Project description
Smartsheet Engine
A Python library that simplifies Smartsheet API workflows
Smartsheet Engine lets you perform high-level actions on a Smartsheet — such as updating rows or locking a column — using only one function call. And it represents Smartsheets as dataframes, so it can be seamlessly integrated into existing workflows that use dataframes.
Badges will go here
[!WARNING] This library is in beta and under active development. Please use it with care.
Table of Contents
- Smartsheet Engine
Features
Current
- Create, Read, Update, and Delete Smartsheet Data
- Get a Smartsheet as a Dataframe
- Append a Dataframe to a Smartsheet
- Update a Smartsheet From a Dataframe
- Delete Smartsheet Rows
- Modify Smartsheet Object Properties
- Set Column Formula
- Set Column Dropdown Options
- Lock or Unlock a Column
- Hide or Unhide a Column
- Share a Smartsheet
Coming Soon
- Create, Read, Update, and Delete Smartsheet Data
- Provision a Smartsheet
- Analyze Smartsheet Data
- Compare Two Dataframes and Identify Row Changes
- Compare Two Dataframes and Identify Column Changes
- Compare Two Dataframes and Identify Cell Value Changes
- Modify Smartsheet Object Properties
- Set Column Formatting
- Change a Shared User's Access Level
- Other
- Perform Bulk Actions on Many Smartsheets
- Command-Line Interface
Roadmap
See the roadmap for the master list of work to be done and features coming soon
Installation
- Download and install Python if needed
- Install
smartsheet-engine
From PyPI
pip install smartsheet-engine
From GitHub
git clone https://github.com/1npo/smartsheet-engine.git
cd smartsheet-engine
pip install .
From the Alteryx Python Tool
Alteryx.installPackage(package="smartsheet-engine")
Usage
To use smartsheet-engine in your script, Python Tool, or Notebook:
- Get your Smartsheet API key and save it to a variable, such as
smartsheet_api_key - Import the
SmartsheetEngineclass - Initialize a
SmartsheetEngineobject with your API key - Use the engine as needed in your workflow (see How-To Guides for examples)
from smartsheet_engine import SmartsheetEngine
S = SmartsheetEngine(api_key=smartsheet_api_key)
[!TIP]
SmartsheetEnginewill look in theSMARTSHEET_ACCESS_TOKENenvironment variable for your API key first. You don't need to specify an API key if your API key is stored in this environment variable.
[!CAUTION] Don't hardcode your API key into your script, Python Tool, or widget. Put it in a secret store or an environment variable instead.
How-to Guides
Create, Read, Update, and Delete Smartsheet Data
Get a Smartsheet as a Dataframe
# Gets the dataframe for the Smartsheet called `finished_test_grid`
# and prints the dataframe
df = S.get_sheet('finished_test_grid').sheet_df
print(df)
_ss_row_id number rating
0 123734752464772 1.0 Lowest
1 7876435046272900 2.0 Low
2 2246935512059780 3.0 Medium
3 2463203892629380 4.0 High
4 6966803519999876 5.0 Highest
[!WARNING] When you call
S.get_sheet(),SmartsheetEnginedownloads the contents of that Smartsheet and creates a dataframe from it. Then it adds a_ss_row_idcolumn to the dataframe, which contains the ID of the corresponding row in the Smartsheet. This is howSmartsheetEnginemaps dataframe rows to Smartsheet rows.This means:
- If you delete the
_ss_row_idcolumn, you won't be able to use the dataframe to update or delete rows on the Smartsheet.- If you update a Smartsheet with the dataframe, the data in each row of the dataframe will be inserted into the Smartsheet row that matches the ID in the
_ss_row_idcolumn.
Append a Dataframe to a Smartsheet
# Appends 2 rows from a dataframe to the Smartsheet named `test_grid`
df = pd.DataFrame({
'number': [4, 5],
'rating': [None, None],
'missing_col': ['data', 'ignored'], })
S.append_sheet_rows('test_grid', df)
| Before Appending | After Appending |
|---|---|
[!NOTE] Column values from a dataframe will only be updated on or appended to a Smartsheet if those columns exist in the Smartsheet. The column names need to match exactly. Any dataframe column that doesn't exist in the Smartsheet will be ignored.
You can choose to only update/append certain columns, or NOT to update/append certain columns, by using the
include_colsandexclude_colsarguments.For example, in this how-to guide --
numberis the only column that will be updated, becauseratingcontains no data, andmissing_coldoesn't exist as a column in the Smartsheet.So you can achieve the same effect as this:
S.append_sheet_rows('test_grid', df)By only including the
numbercolumn:S.append_sheet_rows('test_grid', df, include_cols=['number'])Or excluding the
ratingandmissing_colcolumns:S.append_sheet_rows('test_grid', df, exclude_cols=['rating', 'missing_col'])
Update a Smartsheet From a Dataframe
# Gets the dataframe for the Smartsheet named `test_grid`, changes the
# dropdown options for the `rating` column, and then updates the column
import numpy as np
df = S.get_sheet('test_grid').sheet_df
S.update_column_dropdown('test_grid', 'rating', ['Lowest', 'Low', 'Medium', 'High', 'Highest'])
conditions = [
df['number'] == 1,
df['number'] == 2,
df['number'] == 3,
df['number'] == 4,
df['number'] == 5,
]
choices = [
'Lowest',
'Low',
'Medium',
'High',
'Highest',
]
df['rating'] = np.select(conditions, choices)
S.update_sheet_rows('test_grid', df)
| Before Updating | After Updating |
|---|---|
Delete Smartsheet Rows
[!CAUTION] Before you run
S.delete_sheet_rows(sheet_name, df), make sure thatdfonly includes the rows you want to delete from the Smartsheet. Because when you run that function, every Smartsheet row that has an ID listed indf._ss_row_idwill be deleted from the Smartsheet.
# Gets the dataframe for the Smartshet named `test_grid`, selects
# only the rows that have the number 2 or 3 in the number column,
# and then deletes them
df = S.get_sheet('test_grid').sheet_df
df = df[df['number'].isin([2,3])]
S.delete_sheet_rows('test_grid', df)
| Before Deleting | After Deleting |
|---|---|
Provision a Smartsheet
[!NOTE]
Coming soon!
Analyze Smartsheet Data
Compare Two Dataframes and Identify Row Changes
[!NOTE]
Coming soon!
Compare Two Dataframes and Identify Column Changes
[!NOTE]
Coming soon!
Compare Two Dataframes and Identify Cell Value Changes
[!NOTE]
Coming soon!
Modify Smartsheet Object Properties
Set Column Formula
# Changes the column formula for the `month_rated` column to "=MONTH([date_rated]@row)"
# on the Smartsheet named `test_grid`.
S.set_column_formula('test_grid', 'month_rated', '=MONTH([date_rated]@row)')
Set Column Dropdown Options
# Changes the dropdown options for the `rating` column
# to `Low, Medium, and High` on the Smartsheet named `test_grid`
S.set_column_dropdown('test_grid', 'rating', ['Low', 'Medium', 'High'])
Set Column Formatting
[!NOTE]
Coming soon!
Lock or Unlock a Column
# Locks and then unlock the `rating` column on the Smartsheet
# named `test_grid`
S.lock_column('test_grid', 'rating')
S.unlock_column('test_grid', 'rating')
Hide or Unhide a Column
# Hide and then unhide the `rating` column on the Smartsheet
# named `test_grid`
S.hide_column('test_grid', 'rating')
S.unhide_column('test_grid', 'rating')
Share a Smartsheet
# Share a Smartsheet named `test_grid` with a list of email addresses, giving
# those users the EDITOR_SHARE access level, and send them an email notification
# that the sheet has been shared with them
S.share_sheet('test_grid',
['alice@acme.com', 'bob@acme.com'],
'EDITOR_SHARE',
send_email=True)
[!NOTE]
- One or more email addresses must be provided as either a string or a list. When providing multiple emails as a string, each email address must be separated by a semicolon.
- The cess level is VIEWER if no access level is specified. See the Smartsheet API documentation for a list of valid Access Levels.
S.share_sheet()will NOT send email notifications by default. If you want Smartsheet to notify the user(s) that the Sheet has been shared with them, then you MUST setsend_emailto True.
Update a Shared User's Sheet Permissions
[!NOTE]
Coming soon!
System Design
[!NOTE] This documentation will be refined, expanded, and eventually migrated into Sphinx docs that will be hosted on GitHub Pages.
Architecture Diagram
SmartsheetEngine Class
Provides a set of high-level Smartsheet actions, such as appending dataframe rows to a Smartsheet or locking a column
- Uses the
SmartsheetAPIClientclass to interact with the Smartsheet API - Uses the
GridRepositoryclass to manage the Smartsheet SDK Sheet objects that represent all the Smartsheets that are available to the user
SmartsheetAPIClient Class
Simplifies using Smartsheet's Python SDK
- Converts dataframes to lists of Smartsheet SDK Row, Column, and Cell objects, and vice-versa
- Sends the lists of SDK objects to the API
- Retrieves data from the API and returns it to the user
GridRepository Class
Stores, retrieves, and modifies SmartsheetGrid objects
- Simple in-memory repository
- Stores
SmartsheetGrids in a list - Can create, read, and update
SmartsheetGridobjects
SmartsheetGrid Dataclass
Contains a Smartsheet Sheet object, relevant metadata, and a dataframe representation of the Sheet
- Sheet Name, ID, and user's access level
- Column map (between English column name and Smartsheet Column ID)
- The Smartsheet SDK Sheet object
- The pandas dataframe representation of the Sheet
- Created and modified timestamps
- Flags for whether or not the Sheet exists in a folder or a workspace
- Name and ID of the folder or workspace
Acknowledgements
- The architecture diagram was made with Lucidchart
Contributors
Thanks and kudos to any contributors will go here
License
smartsheet-engine is made available under the MIT License
Contributing
See CONTRIBUTING for instructions on how to contribute to smartsheet-engine
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