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.
- streamlit and sqlalchemy
- Sqlalchemy models needs a str method
- Id column should be called "id"
- 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:
Metadata
Release files for streamlit_sql 0.3.2
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