dbpush 1.0.1

Import Excel / CSV files directly into MySQL or PostgreSQL from the terminal

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Import .csv and .xlsx files directly into PostgreSQL and MySQL

— from your terminal or Python code.

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What is DBSHEET?

DBSHEET is a zero-boilerplate CLI and Python utility that turns spreadsheet files into live database tables. No schema writing. No manual column mapping. No encoding headaches.

Point it at a file. Configure the database. Done. how to use cli tool

python -m dbpush.cli

The Old Way vs DBSHEET

Without DBSHEET	With DBSHEET
Open spreadsheet	pip install dbpush==1.0.0
Write a custom parser	dbpush (or 3 lines of Python)
Map columns manually	✅ Auto schema from headers
Write SQL CREATE TABLE	✅ Table created automatically
Write INSERT loops	✅ Rows inserted + upserted
Debug encoding issues	✅ Just works

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Features

✦ CSV import                ✦ Excel (.xlsx) import
✦ PostgreSQL support        ✦ MySQL support
✦ Auto table creation       ✦ Header-based schema generation
✦ Upsert on duplicate keys  ✦ Interactive CLI
✦ Python API                ✦ Config file support

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Installation

pip install dbpush

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Quick Start

Config File

Create a config.txt file:

db_type:postgres
host:localhost
port:5432
user:postgres
password:secret
database:mydb
file_name:./data.csv
sheet_name:Sheet1

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CLI

Launch the interactive terminal:

dbsheet

Typical workflow:

config_file      # load your config
connect          # connect to the database
create_table     # create table from spreadsheet headers
insert           # insert all rows
select           # view the data

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Python API

from dbpush.dbpush import dbpush

db = dbpush.create(
    db_type="postgres",
    host="localhost",
    user="postgres",
    password="secret",
    database="mydb",
    port=5432,
    file_name="./data.csv"
)

db.connect()
db.create_table()
db.insert()
db.select_all()

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Supported Formats

File Type	Supported
.csv	✅ Yes
.xlsx	✅ Yes

Supported Databases

Database	Supported
PostgreSQL	✅ Yes
MySQL	✅ Yes

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Example Input

CSV:

id,name,age,salary
1,ram,22,50000
2,radha,25,70000

DBSHEET will:

• Create a table named data
• Map each header to a column (id → primary key, rest → text)
• Insert all rows automatically
• Upsert if a row with the same primary key already exists

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CLI Commands

Command	Description
config	Configure database connection manually
config_file	Load configuration from a file
connect	Connect to the database
create_db	Create the database if it doesn't exist
create_table	Create a table from the spreadsheet headers
insert	Insert (or upsert) all rows from the file
select	Display all rows from the table
truncate	Remove all rows from the table (keep structure)
drop_table	Permanently delete the table
row_count	Print the number of rows in the spreadsheet
col_count	Print the number of columns in the spreadsheet
header	Display column names from the spreadsheet
sheet	Display the active sheet name
find	Search for a row by column value

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Python API Reference

dbpush.create(...)

Factory method to create a new Dbsheet instance.

db = dbpush.create(
    db_type="postgres",   # "postgres" or "mysql"
    host="localhost",
    user="postgres",
    password="secret",
    database="mydb",
    port=5432,
    file_name="./data.csv",
    sheet_name="Sheet1"   # optional, for .xlsx files
)

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create_db()

Creates the database if it does not already exist.

db.create_db()

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connect()

Establishes a connection to the database and prepares the cursor.

db.connect()

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create_table()

Reads the spreadsheet headers and creates a matching SQL table.

• The id column is set as the primary key
• All other columns are created as text fields

db.create_table()

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insert()

Reads all rows from the spreadsheet and inserts them into the table.

Handles duplicate primary keys via upsert — existing rows are updated, new rows are inserted.

db.insert()

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select_all()

Prints all rows currently in the table.

db.select_all()

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drop_table()

Permanently deletes the table from the database.

db.drop_table()

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truncate_table()

Removes all rows from the table while keeping the table structure intact.

db.truncate_table()

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row_count()

Prints the total number of data rows in the spreadsheet (excluding the header).

db.row_count()

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col_count()

Prints the total number of columns in the spreadsheet.

db.col_count()

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show_header()

Prints the list of column names from the spreadsheet header row.

db.show_header()

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show_sheet()

Prints the name of the active sheet (relevant for .xlsx files).

db.show_sheet()

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find(column, value)

Searches through the spreadsheet rows and returns rows where column matches value.

db.find("name", "ram")
# Returns all rows where the "name" column equals "ram"

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Full Examples

PostgreSQL

from dbpush.dbpush import dbpush

db = dbpush.create(
    db_type="postgres",
    host="localhost",
    user="postgres",
    password="secret",
    database="mydb",
    port=5432,
    file_name="./data.csv"
)

db.connect()
db.create_table()
db.insert()
db.select_all()

MySQL

from dbpush.dbpush import dbpush

db = dbpush.create(
    db_type="mysql",
    host="localhost",
    user="root",
    password="secret",
    database="mydb",
    port=3306,
    file_name="./data.xlsx",
    sheet_name="Sheet1"
)

db.connect()
db.create_table()
db.insert()
db.select_all()

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Use Cases

• 🌱 Seeding development and staging databases
• 🛠 Internal admin tools and dashboards
• ⚡ Rapid prototyping with real data
• 📦 Importing spreadsheets from clients
• 🔄 Lightweight ETL pipelines
• 📊 Data migration scripts

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Project Structure

dbsheet-public/
├── README.md
├── examples/
│   ├── postgres_example.py
│   └── mysql_example.py
├── screenshots/
│   ├── cli.png
│   └── demo.gif
└── roadmap.md

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Roadmap

• Better type inference (int, float, date detection)
• Connection URI support (postgresql://user:pass@host/db)
• Batch folder import (import entire directory of files)
• Improved error messages and validation
• Export database table → CSV
• SQLite support

See roadmap.md for full details.

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License

MIT © Sarthak sachdeva

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If dbpush saved you time, a ⭐ on the repo means a lot.

Built with ♥ by Sarthak sachdeva