Skip to main content

CRUD interface for sqlalchemy using streamlit

Project description

streamlit_sql

Introduction

Creating a CRUD interface can be a tedious and repetitive task. This package is intended to replace all of that with a few lines of code that involves simply creating a sqlalchemy statement and calling the main SqlUi class with only 3 required arguments. All extra and advanced features are available by supplying non-required arguments to the class initialization.

When the main class is initialized, it will display the database table data with most of the expected features of a crud interface, so the user will be able to read, filter, update, create and delete rows with many useful features.

It also offers useful information about the data as property like:

  • df: The Dataframe displayed in the screen
  • selected_rows: The position of selected rows. This is not the row id
  • qtty_rows: The quantity of all rows after filtering

Demo

See the package in action here.

Features

READ

  • Display as a regular st.dataframe
  • Add pagination, displaying only a set of rows each time
  • Set the dataframe to be displayed using standard sqlalchemy select statement, where you can JOIN, ORDER BY, WHERE, etc.
  • Add a column to show the rolling sum of a numeric column
  • Conditional styling if the DataFrame based on each row value. For instance, changing its background color
  • Format the number display format.
  • Display multiple CRUD interfaces in the same page using unique base_key.
  • Show many-to-one relation in edit forms with basic editing.
  • Log database modification to stderr or to your prefered loguru handler. (can be disabled)

FILTER

  • Filter the data by some columns before presenting the table.
  • Let users filter the columns by selecting conditions in the filter expander
  • Give possible candidates when filtering using existing values for the columns
  • Let users select ForeignKey's values using the string representation of the foreign table, instead of its id number

UPDATE

  • Users update rows with a dialog opened by selecting the row and clicking the icon
  • Text columns offers candidates from existing values
  • ForeignKey columns are added by the string representation instead of its id number
  • In Update form, list all ONE-TO-MANY related rows with pagination, where you can directly create and delete related table rows.
  • Log updates to database to stderr or in anyway loguru can handle

CREATE

  • Users create new rows with a dialog opened by clicking the create button
  • Text columns offers candidates from existing values
  • Hide columns to fill by offering default values
  • ForeignKey columns are added by the string representation instead of its id number

DELETE

  • Delete one or multiple rows by selecting in DataFrame and clicking the corresponding button. A dialog will list selected rows and confirm deletion.

Requirements

All the requirements you should probably have anyway.

  1. streamlit and sqlalchemy
  2. Sqlalchemy models needs a str method
  3. Id column should be called "id"
  4. Relationships should be added for all ForeignKey columns

Basic Usage

Install the package using pip:

pip install streamlit_sql

Run show_sql_ui as the example below:

from streamlit_sql import show_sql_ui
from sqlalchemy import select

conn = st.connection("sql", url="<db_url>")

stmt = (
    select(
        db.Invoice.id,
        db.Invoice.Date,
        db.Invoice.amount,
        db.Client.name,
    )
    .join(db.Client)
    .where(db.Invoice.amount > 1000)
    .order_by(db.Invoice.date)
)

show_sql_ui(conn=conn,
            read_instance=stmt,
            edit_create_model=db.Invoice,
            available_filter=["name"],
            rolling_total_column="amount",
)

show_sql_ui(conn, model_opts)

!!! warning In the statement, always include the primary_key column, that should be named id

Interface

  • Filter: Open the "Filter" expander and fill the inputs
  • Add row: Click on "plus" button (no dataframe row can be selected)
  • Edit row: Click on "pencil" button (one and only one dataframe row should be selected)
  • Delete row: Click on "trash" button (one or more dataframe rows should be selected)

Customize

You can adjust the CRUD interface by the select statement you provide to read_instance arg and giving optional arguments to the show_sql_ui function. See the docstring for more information or at documentation webpage:

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

streamlit_sql-0.3.1.tar.gz (18.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

streamlit_sql-0.3.1-py3-none-any.whl (19.5 kB view details)

Uploaded Python 3

File details

Details for the file streamlit_sql-0.3.1.tar.gz.

File metadata

  • Download URL: streamlit_sql-0.3.1.tar.gz
  • Upload date:
  • Size: 18.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.5.29

File hashes

Hashes for streamlit_sql-0.3.1.tar.gz
Algorithm Hash digest
SHA256 25050bd104f1df774735fe4124893e58bc4d405bbd8c27b6340be9c6b7e9c9e7
MD5 b3ac13f817a994bc6843376c2a633a8f
BLAKE2b-256 34d728f4a4917416e4b26b0593eb50fa6a3bad5a77da558168318723b096f202

See more details on using hashes here.

File details

Details for the file streamlit_sql-0.3.1-py3-none-any.whl.

File metadata

File hashes

Hashes for streamlit_sql-0.3.1-py3-none-any.whl
Algorithm Hash digest
SHA256 c6a4835bb356065e9f8ab84882390b9cb23d34666d60eeca7a148870763189b3
MD5 76a6004f1ddf9aff8f62f2515a502113
BLAKE2b-256 a72a741760fb8f2630f9e951f926fff6148b482e73272c0928a1b2757ae86ae8

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page