python-bitable

A Python package to operate with Feishu/Lark bitable

Install

pip install bitable

Usage

Quick Start

from bitable import Table

table = Table(BASE_ID, AUTH_TOKEN, 'TABLE_NAME')
# you may also use table_id: Table(BASE_ID, AUTH_TOKEN, table_id=TABLE_ID)

# select records
records = table.select() # select all records
records = table.select({'field_name1': 'value1', 'field_name2': 'value2'}) # select with conditions
records = table.select(Greater('FieldValue', 90))
records = table.select(Or(Greater('FieldValue', 90), And({'FieldSingle': 'A'}, Contain('FieldText', 'text_value')))) # select with complex conditions

# insert records
table.insert({'field_name1': 'value1', 'field_name2': 'value2'}) # insert a record
table.insert([{'field_name1': 'value1', 'field_name2': 'value2'}, {'field_name1': 'value3', 'field_name2': 'value4'}]) # insert multiple records

# update records
table.update({'FieldMultiple': ['B', 'A'], 'FieldDate':'2024-12-21'}, where={'FieldText': 'text_value'}) # update records with where conditions
result = table.select({'FieldText': 'HelloTestUpdate'})[0]
result['FieldText'] = 'new_value'
table.update(result) # update records with record object

# delete records
self.table.delete(where={'FieldText': 'HelloDelete'}) # with where condition
result = table.select({'FieldText': 'HelloTestUpdate'})[0]
self.table.delete(results) # with selected object

Load a table

from bitable import Table

table = Table(BASE_ID, BASE_TOKEN, 'TABLE_NAME')

BASE_ID can be found at the bitable's URL after 'base/'

AUTH_TOKEN can be found following these steps:

1. click the "Base extensions" icon on the top right:

2. click "Customize" on the bottom right

3. click "Get Authorization Code"

Select Records

select all records with just select():

records = table.select()

every record is a dict of field name => value. With '_id' key for the record id additionally.

simple conditions like x==y can be passed in as a dict:

records = table.select({'field_name1': 'value1', 'field_name2': 'value2'})  

use operators to construct complex conditions:

records = table.select(Greater('FieldValue', 90))
records = table.select(Or(Greater('FieldValue', 90), And({'FieldSingle': 'A'}, Contain('FieldText', 'text_value'))))

list of operators:

• Equal: "==" operator
• Not: "!=" operator
• Contain: if a string field contains a substring, or a multiple-select field contains an element
• NotContain
• Empty
• NotEmpty
• Greater: ">" operator
• GreaterEqual ">=" operator
• Less
• LessEqual

for date fields, use 'YYYY-mm-dd' format, or one of the following: Today(), Yesterday(), Tomorrow(), CurrentWeek(), LastWeek(), CurrentMonth(), LastMonth(), Past7Days(), Next7Days(), Past30Days(), Next30Days()

Insert Records

insert a record with insert():

table.insert({'field_name1': 'value1', 'field_name2': 'value2'})

insert multiple records with a list:

table.insert([{'field_name1': 'value1', 'field_name2': 'value2'}, {'field_name1': 'value3', 'field_name2': 'value4'}])

Update Records

if record is a record dict selected from the table, you can change its content, and update it with update():

(in fact, it uses '_id' key to locate the record)

table.update(record)

you can also update records with where conditions:

table.update({'field_name1': 'new_value1', 'field_name2':'new_value2'}, where={'condition_field_name': 'text_value'})

Delete Records

delete a record selected from the table with delete():

(similar to update(), it uses '_id' key to locate which record to delete)

table.delete(record)

batch delete records with where conditions:

table.delete(where={'field_name': 'field_value'})