simple-smartsheet 0.1.4

Python library to interact with Smartsheet objects

Simple Smartsheet

Python library to interact with Smartsheet API easily

Installation

Requires Python 3.6+
pip install simple-smartsheet

Why not smartsheet-python-sdk

smartsheet-python-sdk has very wide object coverage and maps to Smartsheet API very nicely, but it does not have any additional features (for example, easy access to cells by column titles).
simple-smartsheet library is focused on user experience first in expense of feature coverage. As of now, you can only interact with Sheets and nested objects (rows, columns, cells).

Usage

from simple_smartsheet import Smartsheet
from simple_smartsheet.models import Sheet, Column, Row, Cell
from pprint import pprint

TOKEN = 'my-smartsheet-token'
smartsheet = Smartsheet(TOKEN)

# creating new Sheet
new_sheet = Sheet(
    name="My New Sheet",
    columns=[
        Column(primary=True, title="Full Name", type="TEXT_NUMBER"),
        Column(title="Number of read books", type="TEXT_NUMBER"),
    ],
)

# print the sheet object as a dictionary which will be used in REST API
pprint(new_sheet.dump())

# adding the sheet via API
smartsheet.sheets.create(new_sheet)

# getting a simplified view of sheets
sheets = smartsheet.sheets.list()
pprint(sheets)

# getting the sheet by name
sheet = smartsheet.sheets.get("My New Sheet")

# printing the sheet object attributes
pprint(sheet.__dict__)
# or printing the sheet object as a dictionary which will be used in REST API
pprint(sheet.dump())

# getting columns details by column title (case-sensitive)
full_name_column = sheet.get_column("Full Name")
pprint(full_name_column.__dict__)
num_books_column = sheet.get_column("Number of read books")
pprint(num_books_column.__dict__)

# adding rows (cells created using different ways):
sheet.add_rows(
    [
        Row(
            to_top=True,
            cells=[
                Cell(column_id=full_name_column.id, value="Alice Smith"),
                Cell(column_id=num_books_column.id, value=5),
            ],
        ),
        Row(
            to_top=True,
            cells=sheet.make_cells(
                {"Full Name": "Bob Lee", "Number of read books": 2}
            )
        ),
        Row(
            to_top=True,
            cells=[
                sheet.make_cell("Full Name", "Charlie Brown"),
                sheet.make_cell("Number of read books", 1),
            ],
        ),
    ]
)

# getting an updated sheet
sheet = smartsheet.sheets.get("My New Sheet")
print("\nSheet after adding rows:")
# all sheet attributes
pprint(sheet.__dict__)
# or just a list of dictionaries containing column titles and values
pprint(sheet.as_list())

# getting a specific cell and updating it:
row_id_to_delete = None
rows_to_update = []
for row in sheet.rows:
    full_name = row.get_cell("Full Name").value
    num_books = row.get_cell("Number of read books").value
    print(f"{full_name} has read {num_books} books")
    if full_name.startswith("Charlie"):
        num_books_cell = row.get_cell("Number of read books")
        num_books_cell.value += 1
        rows_to_update.append(row)
    elif full_name.startswith("Bob"):
        row_id_to_delete = row.id  # used later

# update rows
sheet.update_rows(rows_to_update)
# or a single row
# sheet.update_rows(rows_to_update[0])

# getting an updated sheet
sheet = smartsheet.sheets.get("My New Sheet")
print("\nSheet after updating rows:")
pprint(sheet.as_list())

# deleting row by id
sheet.delete_row(row_id_to_delete)

# getting an updated sheet
sheet = smartsheet.sheets.get("My New Sheet")
print("\nSheet after deleting rows:")
pprint(sheet.as_list())

# deleting Sheet
# sheet = smartsheet.sheets.delete('My New Sheet')
sheets = smartsheet.sheets.list()
pprint(sheets)

Docs

While a separate docs page is work in progress, available public API is described here

Class simple_smartsheet.Smartsheet

This class a main entry point for the library
Methods:

• def __init__(token: str): constructor for the class

Attributes:

• token: Smartsheet API token, obtained in Personal Settings -> API access
• session: requests.Session object which stores headers based on the token
• sheets: simple_smartsheet.models.sheet.SheetsCRUD object which provides methods to interact with Sheets

Class simple_smartsheet.models.sheet.SheetsCRUD

Methods:

• def get(name: Optional[str], id: Optional[int], index_keys: Optional[Dict[str, Any]]): fetches Sheet by name or ID. It can also build an index for several fields to do quick rows lookup (see section "Custom Indexes")
• def list(): fetches a list of all sheets (summary only)
• def create(obj: Sheet): adds a new sheet
• def update(obj: Sheet): updates a sheet
• def delete(name: Optional[str], id: Optional[int]): deletes a sheet by name or ID

Class simple_smartsheet.models.Sheet

Attributes (converted from camelCase to snake_case):

• http://smartsheet-platform.github.io/api-docs/#sheets

Methods:

• def update_index(): rebuilds mapping tables for rows and columns for quick lookup
• def get_row(row_num: Optional[int], row_id: Optional[int], filter: Optional[Dict[str, Any]]): returns a Row object by row number, ID or by filter, if a unique index was built (see section "Custom Indexes")
• def get_rows(index_query: Dict[str, Any]): returns list of Row objects by filter, if an index was built (see section "Custom Indexes")
• def get_column(column_title: Optional[str], column_id: Optional[int]): returns a Column object by column title or id
• def add_rows(rows: Sequence[Row]): adds rows to the sheet
• def add_row(row: Row): add a single row to the sheet
• def update_rows(rows: Sequence[Row]): updates several rows in the sheet
• def update_row(row: Row): updates a single row
• def delete_rows(row_ids: Sequence[int]): delete several rows with provided ids
• def delete_row(row_id: int): delete a single row with a provided id
• def make_cell(column_title: str, field_value: Union[float, str, datetime, None]): creates a Cell object with provided column title and an associated value
• def make_cells(fields: Dict[str, Union[float, str, datetime, None]]): creates a list of Cell objects from an input dictionary where column title is key associated with the field value
• def as_list(): returns a list of dictionaries where column title is key associated with the field value

Class simple_smartsheet.models.Row

Attributes (converted from camelCase to snake_case):

• http://smartsheet-platform.github.io/api-docs/#rows
• rowNumber is mapped to num

Methods:

• def get_cell(column_title: Optional[str], column_id: Optional[int]) - returns a Cell object by column title (case-sensitive) or column id
• def as_dict() - returns a dictionary of column title to cell value mappings

Class simple_smartsheet.models.Column

Attributes (converted from camelCase to snake_case):

• http://smartsheet-platform.github.io/api-docs/#columns

Class simple_smartsheet.models.Cell

Attributes (converted from camelCase to snake_case):

• http://smartsheet-platform.github.io/api-docs/#cells

Custom Indexes

When you are retrieving a smartsheet, it is possible to build an index to enable quick rows lookups. This is controlled using index_key argument in get method. This argument is a dictionary with two keys columns and unique. columns should contain a tuple with column titles (case sensitive). unique controls if the index always points to a single row (value True, lookups are done using get_row method) or multiple rows (value False, lookups are done using get_rows method).

Below you can find a code example:

from simple_smartsheet import Smartsheet
from pprint import pprint

TOKEN = 'my-token'
smartsheet = Smartsheet(TOKEN)

INDEX_KEYS = [
    {"columns": ("Company Name",), "unique": False},
    {"columns": ("Company Name", "Full Name"), "unique": True},
    {"columns": ("Email Address",), "unique": True},
]
sheet = smartsheet.sheets.get("Index Test Sheet", index_keys=INDEX_KEYS)

pprint(sheet.indexes)
# >
# defaultdict(<class 'dict'>,
#             {('Company Name',): {('ACME',): [Row(id=525791232583556, num=1),
#                                              Row(id=5029390859954052, num=2)],
#                                  ('Globex',): [Row(id=2777591046268804, num=3)]},
#              ('Company Name', 'Full Name'): {('ACME', 'Alice Smith'): Row(id=525791232583556, num=1),
#                                              ('ACME', 'Bob Lee'): Row(id=5029390859954052, num=2),
#                                              ('Globex', 'Charlie Brown'): Row(id=2777591046268804, num=3)},
#              ('Email Address',): {('[e-mail]',): Row(id=525791232583556, num=1),
#                                   ('[e-mail]',): Row(id=5029390859954052, num=2),
#                                   ('[e-mail]',): Row(id=2777591046268804, num=3)}})

pprint([row.as_dict() for row in sheet.rows])
# >
# [{'Company Name': 'ACME',
#   'Email Address': '[e-mail]',
#   'Full Name': 'Alice Smith'},
#  {'Company Name': 'ACME',
#   'Email Address': '[e-mail]',
#   'Full Name': 'Bob Lee'},
#  {'Company Name': 'Globex',
#   'Email Address': '[e-mail]',
#   'Full Name': 'Charlie Brown'}]

pprint(sheet.get_row(filter={"Email Address": "[e-mail]"}).as_dict())
# >
# {'Company Name': 'Globex',
#  'Email Address': '[e-mail]',
#  'Full Name': 'Charlie Brown'}

pprint(
    sheet.get_row(filter={"Full Name": "Alice Smith", "Company Name": "ACME"}).as_dict()
)
# >
# {'Company Name': 'ACME',
#  'Email Address': '[e-mail]',
#  'Full Name': 'Alice Smith'}

pprint([row.as_dict() for row in sheet.get_rows(filter={"Company Name": "ACME"})])
# >
# [{'Company Name': 'ACME',
#   'Email Address': '[e-mail]',
#   'Full Name': 'Alice Smith'},
#  {'Company Name': 'ACME',
#   'Email Address': '[e-mail]',
#   'Full Name': 'Bob Lee'}]