Оглавление

You can write your script so it works in both environments without changes. The trick is to check whether the context object is available:

from seatable_api import Base

try:
    from seatable_api import context
    base = Base(context.api_token, context.server_url)
except:
    base = Base('your-api-token', 'https://cloud.seatable.io')

base.auth()

SeaTable Cloud runs Python 3.12 with the following third-party libraries pre-installed:

  • seatable-api – SeaTable API client
  • requests – HTTP requests
  • Pillow – Image processing
  • pandas – Data analysis
  • numpy – Numerical computing
  • scipy – Scientific computing
  • openai – OpenAI API
  • beautifulsoup4 – HTML/XML parsing
  • python-dateutil – Date utilities
  • PyPDF – PDF processing
  • pdfmerge – PDF merging
  • qrcode – QR code generation
  • python-barcode – Barcode generation
  • pillow-heif – HEIC image support
  • ldap3 – LDAP operations
  • markdown – Markdown conversion

On SeaTable Cloud, you are limited to the pre-installed libraries listed above.

On a self-hosted SeaTable Server, you can install additional libraries in your Python Runner. See the Admin Manual for details.

The base.list_rows() method returns a maximum of 1,000 rows by default. To process more rows, use one of these approaches:

Option 1: Loop with offset

all_rows = []
offset = 0
while True:
    rows = base.list_rows(TABLE_NAME, start=offset, limit=1000)
    if not rows:
        break
    all_rows.extend(rows)
    offset += 1000

Option 2: Use SQL query

rows = base.query("SELECT * FROM `Table1` LIMIT 10000")

SQL queries support up to 10,000 rows per request.

Use json.dumps() with indentation to pretty-print dictionaries and lists:

import json
metadata = base.get_metadata()
print(json.dumps(metadata, indent=2))

For the complete function reference, visit the SeaTable Developer Manual .