PEP 249 compliant DB-API driver for Excel files
Project description
excel-dbapi
A lightweight, Python DB-API 2.0 compliant connector for Excel files.
Use SQL to query, insert, update, and delete rows in .xlsx workbooks — no database server required.
Who is this for?
- Data analysts who want to query Excel files with SQL instead of manual filtering
- Citizen developers automating small workflows with familiar SQL syntax
- Educators teaching SQL concepts without setting up a database
- Prototypers building quick data pipelines before moving to a real database
Who is this NOT for?
- If you need JOINs, GROUP BY, subqueries, or advanced SQL → use SQLite or PostgreSQL
- If you need concurrent writes from multiple processes → use a real database
- If your Excel file has 100k+ rows → use pandas directly or a database
Features
- Python DB-API 2.0 compliant interface (PEP 249)
- Query Excel files using SQL syntax
- Supports SELECT, INSERT, UPDATE, DELETE
- Basic DDL support (CREATE TABLE, DROP TABLE)
- WHERE conditions with AND/OR and comparison operators
- ORDER BY and LIMIT for SELECT
- Sheet-to-Table mapping
- Pandas & Openpyxl engine selector
- Formula injection defense (enabled by default)
- Transaction simulation (commit/rollback)
Installation
pip install excel-dbapi
See CHANGELOG for release history.
Quick Start
from excel_dbapi.connection import ExcelConnection
# Open an Excel file and query it
with ExcelConnection("sample.xlsx") as conn:
cursor = conn.cursor()
cursor.execute("SELECT * FROM Sheet1")
print(cursor.fetchall())
Insert, Update, Delete
with ExcelConnection("sample.xlsx") as conn:
cursor = conn.cursor()
# Insert with parameter binding (recommended)
cursor.execute("INSERT INTO Sheet1 (id, name) VALUES (?, ?)", (1, "Alice"))
# Update
cursor.execute("UPDATE Sheet1 SET name = 'Ann' WHERE id = 1")
# Delete
cursor.execute("DELETE FROM Sheet1 WHERE id = 2")
Create and Drop Sheets
with ExcelConnection("sample.xlsx") as conn:
cursor = conn.cursor()
cursor.execute("CREATE TABLE NewSheet (id, name)")
cursor.execute("DROP TABLE NewSheet")
Engine Options
| Engine | Description | Dependency |
|---|---|---|
| openpyxl (default) | Fast sheet access | openpyxl |
| pandas | DataFrame-based operations | pandas, openpyxl |
conn = ExcelConnection("sample.xlsx", engine="openpyxl") # default
conn = ExcelConnection("sample.xlsx", engine="pandas")
Safety Defaults
Formula Injection Defense
By default, excel-dbapi sanitizes cell values on write (INSERT/UPDATE) to prevent
formula injection attacks.
Strings starting with =, +, -, @, \t, or \r are automatically prefixed
with a single quote (') so they are stored as plain text, not executed as formulas.
# Default: sanitization ON (recommended)
with ExcelConnection("sample.xlsx") as conn:
cursor = conn.cursor()
cursor.execute("INSERT INTO Sheet1 (id, name) VALUES (?, ?)",
(1, "=SUM(A1:A10)"))
# Stored as: '=SUM(A1:A10) (safe, not executed as formula)
# Opt out if you intentionally write formulas
with ExcelConnection("sample.xlsx", sanitize_formulas=False) as conn:
cursor = conn.cursor()
cursor.execute("INSERT INTO Sheet1 (id, formula) VALUES (?, ?)",
(1, "=SUM(A1:A10)"))
# Stored as: =SUM(A1:A10) (executed as formula in Excel)
Transaction Example
with ExcelConnection("sample.xlsx", autocommit=False) as conn:
cursor = conn.cursor()
cursor.execute("UPDATE Sheet1 SET name = 'Ann' WHERE id = 1")
conn.rollback()
When autocommit is enabled, rollback() is not supported.
Cursor Metadata
with ExcelConnection("sample.xlsx") as conn:
cursor = conn.cursor()
cursor.execute("SELECT id, name FROM Sheet1")
print(cursor.description)
print(cursor.rowcount)
Troubleshooting
"Column 'xyz' not found"
The column name in your SQL doesn't match any header in the sheet.
ProgrammingError: Column 'nmae' not found in Sheet1. Available columns: ['id', 'name', 'email']
Fix: Check the spelling. Column names must match the first row (header) of the sheet exactly.
"Table 'SheetX' not found"
The sheet name in your SQL doesn't match any sheet in the workbook.
ProgrammingError: Table 'Shee1' not found. Available sheets: ['Sheet1', 'Sheet2']
Fix: Check the sheet name spelling. Use the exact sheet name (case-sensitive) shown in your Excel file.
PandasEngine drops formatting
PandasEngine reads data into a DataFrame and writes it back. This process drops
Excel formatting, charts, images, and formulas.
Fix: Use the default openpyxl engine if you need to preserve formatting.
Integer vs. string comparison (Pandas)
The Pandas engine preserves Python types. If a column contains integers,
WHERE id = '2' (string) won't match — use WHERE id = 2 (no quotes).
Fix: Omit quotes around numeric values in WHERE clauses when using the Pandas engine.
Limitations and Operational Guidance
PandasEnginerewrites workbooks and may drop formatting, charts, and formulas.OpenpyxlEngineloads withdata_only=True, so formulas are evaluated to values when reading.- Use a single-writer model for writes. Avoid writing to the same file from multiple processes.
- Save is implemented with a temporary file + atomic replace (
os.replace) for safer persistence. - No support for JOIN, GROUP BY, HAVING, or subqueries.
Roadmap
- Remote file connection improvements
See Project Roadmap for details.
Related Projects
sqlalchemy-excel
sqlalchemy-excel is a higher-level toolkit that uses excel-dbapi as its core Excel I/O layer. It provides SQLAlchemy model-driven template generation, server-side validation, database import, and export.
- Which package should I use? See the decision guide
- Interface contract: See the compatibility documentation
Documentation
Examples
examples/basic_usage.pyexamples/write_operations.pyexamples/transactions.pyexamples/advanced_query.pyexamples/pandas_engine.py
License
MIT License
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