tablemaster is a Python toolkit for moving and managing tabular data across databases, Feishu/Lark, Google Sheets, and local files with one consistent API.
Project description
tablemaster
tablemaster is a Python toolkit for moving and managing tabular data across databases, Feishu/Lark, Google Sheets, and local files with one consistent API.
Why tablemaster
- Unified DataFrame-first API across multiple data backends
- Production-friendly DB helpers (query, execute, chunked upload, upsert)
- Built-in Feishu and Google Sheets connectors
- Local CSV/Excel ingestion utilities
- Declarative two-way sync between Feishu Sheet and database table
- Configuration-first design for reproducible automation
Installation
Install core package:
pip install -U tablemaster
Install backend-specific extras as needed:
pip install -U "tablemaster[mysql]" # MySQL/TiDB database support
pip install -U "tablemaster[feishu]" # Feishu/Lark connectors
pip install -U "tablemaster[gspread]" # Google Sheets connectors
pip install -U "tablemaster[local]" # Local CSV/Excel helpers
pip install -U "tablemaster[all]" # Everything above
Configuration
Load configuration with:
import tablemaster as tm
cfg = tm.load_cfg()
Load config from another path:
import os
import tablemaster as tm
cfg = tm.load_cfg(path="C:/configs/tablemaster/prod.yaml")
cfg = tm.load_cfg(path="C:/configs/tablemaster")
os.environ["TM_CFG_PATH"] = "D:/ops/tablemaster/cfg.yaml"
cfg = tm.load_cfg()
load_cfg() resolves config file in this order:
- Explicit
pathargument TM_CFG_PATHenvironment variable./cfg.yaml~/.tablemaster/cfg.yaml
Example cfg.yaml:
mydb:
host: 10.0.0.1
user: admin
password: secret
database: bake_prod
port: 3306
db_type: mysql
db_tidb:
host: sh.internal
user: reader
password: xxx
database: analytics
db_type: tidb
use_ssl: true
ssl_ca: /path/to/ca.pem
feishu_prod:
feishu_app_id: cli_xxx
feishu_app_secret: yyy
gsheet:
service_account_path: /absolute/path/to/service_account.json
For Google Sheets authentication setup, see: https://docs.gspread.org/en/latest/oauth2.html
Quick Start
Query and execute SQL
import tablemaster as tm
cfg = tm.load_cfg()
df = tm.query("SELECT * FROM orders LIMIT 20", cfg.mydb)
tm.opt("ALTER TABLE orders RENAME COLUMN old_col TO new_col", cfg.mydb)
Manage database tables
import tablemaster as tm
cfg = tm.load_cfg()
tb = tm.ManageTable("orders", cfg.mydb)
tb.upload_data(df, add_date=True)
tb.upsert_data(df, key="order_id")
tb.par_del("order_date > '2023-01-01'")
Google Sheets
import tablemaster as tm
cfg = tm.load_cfg()
sheet = ("spreadsheet_id_or_name", "worksheet_name")
df = tm.gs_read_df(sheet, cfg.gsheet)
tm.gs_write_df(sheet, df, cfg.gsheet)
Feishu / Lark
import tablemaster as tm
cfg = tm.load_cfg()
feishu_sheet = ("spreadsheet_token", "sheet_id")
feishu_base = ("app_token", "table_id")
sheet_df = tm.fs_read_df(feishu_sheet, cfg.feishu_prod)
base_df = tm.fs_read_base(feishu_base, cfg.feishu_prod)
tm.fs_write_df(feishu_sheet, sheet_df, cfg.feishu_prod, loc="A1", clear_sheet=False)
tm.fs_write_base(feishu_base, base_df, cfg.feishu_prod, clear_table=False)
Local files
import tablemaster as tm
single_df = tm.read("*orders_2026*")
merged_df = tm.batch_read("*orders_2026*")
df_list = tm.read_dfs("*orders_2026*")
Declarative two-way sync
import tablemaster as tm
cfg = tm.load_cfg()
feishu_sheet = ("spreadsheet_token", "sheet_id")
merged = tm.sync(
source=("feishu", feishu_sheet, cfg.feishu_prod),
target=("db", cfg.mydb, "orders"),
on_conflict="upsert",
key="order_id",
)
CLI
tablemaster now ships with a built-in CLI:
tablemaster --help
python -m tablemaster --help
Commands:
tablemaster version-info
tablemaster config list --cfg-path ./cfg.yaml
tablemaster config show mydb --cfg-path ./cfg.yaml
tablemaster db query "SELECT * FROM orders LIMIT 20" --cfg-key mydb --cfg-path ./cfg.yaml
tablemaster db query "SELECT * FROM orders" --cfg-key mydb --output ./out/orders.csv
tablemaster local read "*orders_2026*" --limit 10
tablemaster local read "*orders_2026*" --no-det-header
CLI command groups:
version-info: Print installed package version.-
config show <cfg_key>: Print one config entry as JSON.db query <sql>: Run SQL with--cfg-key; use--limitto control stdout preview and--outputto export full result as CSV.local read <pattern>: Read one local CSV/Excel match and print preview; use--det-header/--no-det-headerto control header detection.config list: List top-level keys from config.
--cfg-path accepts either a config file path or a directory containing cfg.yaml.
Public API
- Database:
query,opt,ManageTable - Feishu/Lark:
fs_read_df,fs_write_df,fs_read_base,fs_write_base - Google Sheets:
gs_read_df,gs_write_df - Local files:
read,batch_read,read_dfs - Sync:
sync - Config:
load_cfg
Notes
- Python 3.9+ is required.
- CLI entrypoint is
tablemaster; usetablemaster --helpfor command details. tm.cfgandread_cfg()are backward-compatible but deprecated in favor ofload_cfg().- PostgreSQL upsert is supported by code path; install PostgreSQL driver dependencies separately when needed.
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