Skip to main content

Simple interface for tabulated data and .csv files

Project description

What is tabler?

The tabler package provides the Table class which is intended to make the creation and maniplulation of tabulated data intuitive.

It can:
  • Open various spreadsheet files from a relative path, absolute path or url.

  • Update text in cells.

  • Write files in various formats.

Compatible formats:
  • .csv

  • Open Spreadsheet Format .ods

  • Microsoft Excel .xlsx

  • HTML (Write only)

  • Other filetypes can be added by subclassing the BaseTableType class.

Quick Start

Creating a Table (Basic)

Import the Tabler class from the tabler package and instanciate it with a header and data:

from tabler import Table

table = Tabler(
    header=['SKU', 'Item Title', 'Price'],
    data=[[009, 'Item 1', 5.00], [010, 'Item 2', 9.99]])

Or pass the path to a file to open:

from tabler import Table

Table('path/to/some/file.csv')
This will recognise filetypes with the following extensions:
  • .csv (UTF-8 encoded and comma delimited).

  • .txt (UTF-8 encoded and comma delimited).

  • .xlsx

  • .ods

To explicitly open a file of a specifict type a Table Type object must be provided.:

from tabler import Table
from tabler.tabletypes import CSV

Table('path/to/some/file.csv', table_type=CSV(delimiter='\t'))

These are subclasses of BaseTableType and allow the method of reading the file to be customised.

Reading a Table (Basic)

At its base, Tabler is a two dimensional list. Therefore the simplest way to access a cell is by providing two indexes:

first_cell = table[0][0]

Rows can be indexed by row number (zero based) Tabler will always treat the first line of any supplied data as column headers. This means that a column can be specified by index number or title:

first_item_title = table[0]["Item Title"]

Editing a Table (Basic)

A cell can be edited using the equals = operator:

table[2]["Item Title"] = 'USB Hub'

Cell content can be string, int or float.

Loading Data into a Table (Basic)

Data can be loaded into an empty Tabler object by passing a list of rows in the form of lists of cell data using the Tabler().load_from_array(data, header) method. A list of column headers must be passed as the second argument:

header = ["SKU", "Item Title", "Price"]

data = [
    ["001", "USB Hub", 7.00],
    ["002", "Raspberry Pi 3", 29.99],
    ["003", Arduino Uno", 20.00]
]

table = Tabler()
table.load_from_array(data, header)

Writing a Table to a File (Basic)

Writing a file is similar to reading a file. Table Types are used in the same way to manage writing files:

table.write('path/to/save.csv', table_type=CSV(delimiter='\t')

The table type will be set automatically for reconised file extensions if not explicitly set.

Contact

All comments and queries can be sent to Luke Shiner at luke@lukeshiner.com

License

Distributed with MIT License.

Credits

Created by Luke Shiner (luke@lukeshiner.com)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

tabler-2.1.1.tar.gz (23.7 kB view details)

Uploaded Source

Built Distribution

tabler-2.1.1-py3-none-any.whl (26.9 kB view details)

Uploaded Python 3

File details

Details for the file tabler-2.1.1.tar.gz.

File metadata

  • Download URL: tabler-2.1.1.tar.gz
  • Upload date:
  • Size: 23.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for tabler-2.1.1.tar.gz
Algorithm Hash digest
SHA256 1ddeeff8c4fa9068fd9d6ce6238a0a19bea8af88415846eb387c95246b1d02db
MD5 8ba1d99836d4c11435e58347f17a4633
BLAKE2b-256 30783de63f40c142470af281c1b775f8803cdaee293819d324652307293014b1

See more details on using hashes here.

File details

Details for the file tabler-2.1.1-py3-none-any.whl.

File metadata

File hashes

Hashes for tabler-2.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 bd96656d12205f3e463e3a9c0e6ac17208f28af958cc93608f6adabe562e2b24
MD5 d4016e6eec8a4836a6ab7fef33cb7a30
BLAKE2b-256 ebea8fc9552b074bfc2e73e7177b373d3cdb941ec38d11dc46f41a636dcad5cd

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page