# -*- coding: utf-8 -*-
from distutils.core import setup

packages = \
['simple_smartsheet', 'simple_smartsheet.models']

package_data = \
{'': ['*']}

install_requires = \
['attrs>=18.2,<19.0',
 'cattrs>=0.9.0,<0.10.0',
 'marshmallow>=3.0.0b19,<4.0.0',
 'mypy-extensions>=0.4.1,<0.5.0',
 'pendulum>=2.0,<3.0',
 'python-decouple>=3.1,<4.0',
 'requests>=2.20,<3.0']

setup_kwargs = {
    'name': 'simple-smartsheet',
    'version': '0.1.6',
    'description': 'Python library to interact with Smartsheet objects',
    'long_description': '## Simple Smartsheet\nPython library to interact with Smartsheet API easily\n\n### Installation\nRequires Python 3.6+  \n`pip install simple-smartsheet`\n\n### Why not smartsheet-python-sdk\n`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).  \n`simple-smartsheet` library is focused on user experience first in expense of feature coverage. \nAs of now, you can only interact with Sheets and nested objects (rows, columns, cells).\n\n### Usage\n```python\nfrom datetime import date\nfrom pprint import pprint\n\nfrom simple_smartsheet import Smartsheet\nfrom simple_smartsheet.models import Sheet, Column, Row, Cell\n\nTOKEN = "my-secret-token"\nsmartsheet = Smartsheet(TOKEN)\n\n# creating new Sheet\nnew_sheet = Sheet(\n    name="My New Sheet",\n    columns=[\n        Column(primary=True, title="Full Name", type="TEXT_NUMBER"),\n        Column(title="Number of read books", type="TEXT_NUMBER"),\n        Column(title="Birth date", type="DATE"),\n    ],\n)\n\n# print the sheet object as a dictionary which will be used in REST API\npprint(new_sheet.dump())\n\n# adding the sheet via API\nsmartsheet.sheets.create(new_sheet)\n\n# getting a simplified view of sheets\nsheets = smartsheet.sheets.list()\npprint(sheets)\n\n# getting the sheet by name\nsheet = smartsheet.sheets.get("My New Sheet")\n\n# printing the sheet object attributes\npprint(sheet.__dict__)\n# or printing the sheet object as a dictionary which will be used in REST API\npprint(sheet.dump())\n\n# getting columns details by column title (case-sensitive)\nfull_name_column = sheet.get_column("Full Name")\npprint(full_name_column.__dict__)\nnum_books_column = sheet.get_column("Number of read books")\npprint(num_books_column.__dict__)\n\n# adding rows (cells created using different ways):\nsheet.add_rows(\n    [\n        Row(\n            to_top=True,\n            cells=[\n                Cell(column_id=full_name_column.id, value="Alice Smith"),\n                Cell(column_id=num_books_column.id, value=5),\n            ],\n        ),\n        Row(\n            to_top=True,\n            cells=sheet.make_cells(\n                {"Full Name": "Bob Lee", "Number of read books": 2}\n            )\n        ),\n        Row(\n            to_top=True,\n            cells=[\n                sheet.make_cell("Full Name", "Charlie Brown"),\n                sheet.make_cell("Number of read books", 1),\n                sheet.make_cell("Birth date", date(1990, 1, 1)),\n            ],\n        ),\n    ]\n)\n\n# sort rows now by column "Full Name" descending / returns updated sheet\nsheet = sheet.sort_rows([{"column_title": "Full Name", "descending": True}])\n\n# or getting an updated sheet again\n# sheet = smartsheet.sheets.get("My New Sheet")\nprint("\\nSheet after adding rows:")\n# all sheet attributes\npprint(sheet.__dict__)\n# or just a list of dictionaries containing column titles and values\npprint(sheet.as_list())\n\n# getting a specific cell and updating it:\nrow_id_to_delete = None\nrows_to_update = []\nfor row in sheet.rows:\n    full_name = row.get_cell("Full Name").value\n    num_books = row.get_cell("Number of read books").value\n    print(f"{full_name} has read {num_books} books")\n    if full_name.startswith("Charlie"):\n        num_books_cell = row.get_cell("Number of read books")\n        num_books_cell.value += 1\n        rows_to_update.append(row)\n    elif full_name.startswith("Bob"):\n        row_id_to_delete = row.id  # used later\n\n# update rows\nsheet.update_rows(rows_to_update)\n# or a single row\n# sheet.update_rows(rows_to_update[0])\n\n# getting an updated sheet\nsheet = smartsheet.sheets.get("My New Sheet")\nprint("\\nSheet after updating rows:")\npprint(sheet.as_list())\n\n# deleting row by id\nsheet.delete_row(row_id_to_delete)\n\n# getting an updated sheet\nsheet = smartsheet.sheets.get("My New Sheet")\nprint("\\nSheet after deleting rows:")\npprint(sheet.as_list())\n\n# deleting Sheet\n# sheet = smartsheet.sheets.delete(\'My New Sheet\')\nsheets = smartsheet.sheets.list()\npprint(sheets)\n```\n\n### Docs\nWhile a separate docs page is work in progress, available public API is described here\n#### Class `simple_smartsheet.Smartsheet`\nThis class a main entry point for the library  \nMethods:\n  * `def __init__(token: str)`: constructor for the class\n  \nAttributes:\n  * `token`: Smartsheet API token, obtained in Personal Settings -> API access\n  * `session`: requests.Session object which stores headers based on the token\n  * `sheets`: `simple_smartsheet.models.sheet.SheetsCRUD` object which provides methods to interact with Sheets\n  \n#### Class `simple_smartsheet.models.sheet.SheetsCRUD`\nMethods:\n  * `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")\n  * `def list()`: fetches a list of all sheets (summary only)\n  * `def create(obj: Sheet)`: adds a new sheet\n  * `def update(obj: Sheet)`: updates a sheet\n  * `def delete(name: Optional[str], id: Optional[int])`: deletes a sheet by name or ID\n\n#### Class `simple_smartsheet.models.Sheet`\nAttributes (converted from camelCase to snake_case):\n  * [http://smartsheet-platform.github.io/api-docs/#sheets](http://smartsheet-platform.github.io/api-docs/#sheets)\n  \nMethods:\n  * `def update_index()`: rebuilds mapping tables for rows and columns for quick lookup\n  * `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")\n  * `def get_rows(index_query: Dict[str, Any])`: returns list of Row objects by filter, if an index was built (see section "Custom Indexes")\n  * `def get_column(column_title: Optional[str], column_id: Optional[int])`: returns a Column object by column title or id\n  * `def add_rows(rows: Sequence[Row])`: adds rows to the sheet\n  * `def add_row(row: Row)`: add a single row to the sheet\n  * `def update_rows(rows: Sequence[Row])`: updates several rows in the sheet\n  * `def update_row(row: Row)`: updates a single row\n  * `def delete_rows(row_ids: Sequence[int])`: delete several rows with provided ids\n  * `def delete_row(row_id: int)`: delete a single row with a provided id\n  * `def sort_rows(order: List[Dict[str, Any]])`: sorts sheet rows with the specified order. An argument example:  \n```\n[\n    {"column_title": "Birth date", "descending": True},\n    {"column_title": "Full Name"}\n]\n```\n  * `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\n  * `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\n  * `def as_list()`: returns a list of dictionaries where column title is key associated with the field value\n  \n#### Class `simple_smartsheet.models.Row`\nAttributes (converted from camelCase to snake_case):\n  * [http://smartsheet-platform.github.io/api-docs/#rows](http://smartsheet-platform.github.io/api-docs/#rows)\n  * `rowNumber` is mapped to `num`\n  \nMethods:\n  * `def get_cell(column_title: Optional[str], column_id: Optional[int])` - returns a Cell object by column title (case-sensitive) or column id\n  * `def as_dict()` - returns a dictionary of column title to cell value mappings\n\n#### Class `simple_smartsheet.models.Column`\nAttributes (converted from camelCase to snake_case):\n  * [http://smartsheet-platform.github.io/api-docs/#columns](http://smartsheet-platform.github.io/api-docs/#columns)\n\n#### Class `simple_smartsheet.models.Cell`\nAttributes (converted from camelCase to snake_case):\n  * [http://smartsheet-platform.github.io/api-docs/#cells](http://smartsheet-platform.github.io/api-docs/#cells)\n  \n### Custom Indexes\nWhen you are retrieving a smartsheet, it is possible to build an index to enable quick rows lookups.\nThis 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).\n\nBelow you can find a code example:\n```python\nfrom simple_smartsheet import Smartsheet\nfrom pprint import pprint\n\nTOKEN = \'my-token\'\nsmartsheet = Smartsheet(TOKEN)\n\nINDEX_KEYS = [\n    {"columns": ("Company Name",), "unique": False},\n    {"columns": ("Company Name", "Full Name"), "unique": True},\n    {"columns": ("Email Address",), "unique": True},\n]\nsheet = smartsheet.sheets.get("Index Test Sheet", index_keys=INDEX_KEYS)\n\npprint(sheet.indexes)\n# >\n# defaultdict(<class \'dict\'>,\n#             {(\'Company Name\',): {(\'ACME\',): [Row(id=525791232583556, num=1),\n#                                              Row(id=5029390859954052, num=2)],\n#                                  (\'Globex\',): [Row(id=2777591046268804, num=3)]},\n#              (\'Company Name\', \'Full Name\'): {(\'ACME\', \'Alice Smith\'): Row(id=525791232583556, num=1),\n#                                              (\'ACME\', \'Bob Lee\'): Row(id=5029390859954052, num=2),\n#                                              (\'Globex\', \'Charlie Brown\'): Row(id=2777591046268804, num=3)},\n#              (\'Email Address\',): {(\'alice.smith@acme.com\',): Row(id=525791232583556, num=1),\n#                                   (\'bob.lee@acme.com\',): Row(id=5029390859954052, num=2),\n#                                   (\'charlie.brown@globex.com\',): Row(id=2777591046268804, num=3)}})\n\npprint([row.as_dict() for row in sheet.rows])\n# >\n# [{\'Company Name\': \'ACME\',\n#   \'Email Address\': \'alice.smith@acme.com\',\n#   \'Full Name\': \'Alice Smith\'},\n#  {\'Company Name\': \'ACME\',\n#   \'Email Address\': \'bob.lee@acme.com\',\n#   \'Full Name\': \'Bob Lee\'},\n#  {\'Company Name\': \'Globex\',\n#   \'Email Address\': \'charlie.brown@globex.com\',\n#   \'Full Name\': \'Charlie Brown\'}]\n\npprint(sheet.get_row(filter={"Email Address": "charlie.brown@globex.com"}).as_dict())\n# >\n# {\'Company Name\': \'Globex\',\n#  \'Email Address\': \'charlie.brown@globex.com\',\n#  \'Full Name\': \'Charlie Brown\'}\n\npprint(\n    sheet.get_row(filter={"Full Name": "Alice Smith", "Company Name": "ACME"}).as_dict()\n)\n# >\n# {\'Company Name\': \'ACME\',\n#  \'Email Address\': \'alice.smith@acme.com\',\n#  \'Full Name\': \'Alice Smith\'}\n\npprint([row.as_dict() for row in sheet.get_rows(filter={"Company Name": "ACME"})])\n# >\n# [{\'Company Name\': \'ACME\',\n#   \'Email Address\': \'alice.smith@acme.com\',\n#   \'Full Name\': \'Alice Smith\'},\n#  {\'Company Name\': \'ACME\',\n#   \'Email Address\': \'bob.lee@acme.com\',\n#   \'Full Name\': \'Bob Lee\'}]\n``` ',
    'author': 'Dmitry Figol',
    'author_email': 'git@dmfigol.me',
    'url': 'https://github.com/dmfigol/simple-smartsheet',
    'packages': packages,
    'package_data': package_data,
    'install_requires': install_requires,
    'python_requires': '>=3.6',
}


setup(**setup_kwargs)
