Auto-generate Streamlit UI elements from Pydantic models.
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Streamlit-pydantic makes it easy to auto-generate UI elements from Pydantic models or dataclasses. Just define your data model and turn it into a full-fledged UI form. It supports data validation, nested models, and field limitations. Streamlit-pydantic can be easily integrated into any Streamlit app.
Beta Version: Only suggested for experimental usage.
Try out and explore various examples in our playground here.
- 🪄 Auto-generated UI elements from Pydantic models & Dataclasses.
- 📇 Out-of-the-box data validation.
- 📑 Supports nested Pydantic models.
- 📏 Supports field limits and customizations.
- 🎈 Easy to integrate into any Streamlit app.
Requirements: Python 3.6+.
pip install streamlit-pydantic-
Create a script (
my_script.py) with a Pydantic model and render it viapydantic_form:import streamlit as st from pydantic import BaseModel import streamlit_pydantic as sp class ExampleModel(BaseModel): some_text: str some_number: int some_boolean: bool data = sp.pydantic_form(key="my_form", model=ExampleModel) if data: st.json(data.json())
-
Run the streamlit server on the python script:
streamlit run my_script.py -
You can find additional examples in the examples section below.
👉 Try out and explore these examples in our playground here
The following collection of examples demonstrate how Streamlit Pydantic can be applied in more advanced scenarios. You can find additional - even more advanced - examples in the examples folder or in the playground.
import streamlit as st
from pydantic import BaseModel
import streamlit_pydantic as sp
class ExampleModel(BaseModel):
some_text: str
some_number: int
some_boolean: bool
data = sp.pydantic_form(key="my_form", model=ExampleModel)
if data:
st.json(data.json())import streamlit as st
from pydantic import BaseModel, Field, HttpUrl
from pydantic.color import Color
import streamlit_pydantic as sp
class ExampleModel(BaseModel):
url: HttpUrl
color: Color
email: str = Field(..., max_length=100, regex=r"^\S+@\S+$")
data = sp.pydantic_form(key="my_form", model=ExampleModel)
if data:
st.json(data.json())import dataclasses
import json
import streamlit as st
from pydantic.json import pydantic_encoder
import streamlit_pydantic as sp
@dataclasses.dataclass
class ExampleModel:
some_number: int
some_boolean: bool
some_text: str = "default input"
data = sp.pydantic_form(key="my_form", model=ExampleModel)
if data:
st.json(json.dumps(data, default=pydantic_encoder))from enum import Enum
from typing import Set
import streamlit as st
from pydantic import BaseModel, Field, ValidationError, parse_obj_as
import streamlit_pydantic as sp
class OtherData(BaseModel):
text: str
integer: int
class SelectionValue(str, Enum):
FOO = "foo"
BAR = "bar"
class ExampleModel(BaseModel):
long_text: str = Field(..., description="Unlimited text property")
integer_in_range: int = Field(
20,
ge=10,
lt=30,
multiple_of=2,
description="Number property with a limited range.",
)
single_selection: SelectionValue = Field(
..., description="Only select a single item from a set."
)
multi_selection: Set[SelectionValue] = Field(
..., description="Allows multiple items from a set."
)
single_object: OtherData = Field(
...,
description="Another object embedded into this model.",
)
data = sp.pydantic_form(key="my_form", model=ExampleModel)
if data:
st.json(data.json())from pydantic import BaseModel
import streamlit_pydantic as sp
class ExampleModel(BaseModel):
some_text: str
some_number: int = 10 # Optional
some_boolean: bool = True # Option
input_data = sp.pydantic_input("model_input", ExampleModel, use_sidebar=True)import datetime
from pydantic import BaseModel, Field
import streamlit_pydantic as sp
class ExampleModel(BaseModel):
text: str = Field(..., description="A text property")
integer: int = Field(..., description="An integer property.")
date: datetime.date = Field(..., description="A date.")
instance = ExampleModel(text="Some text", integer=40, date=datetime.date.today())
sp.pydantic_output(instance)import streamlit as st
from pydantic import BaseModel
import streamlit_pydantic as sp
class ExampleModel(BaseModel):
some_text: str
some_number: int = 10
some_boolean: bool = True
with st.form(key="pydantic_form"):
sp.pydantic_input(key="my_input_model", model=ExampleModel)
submit_button = st.form_submit_button(label="Submit")| Type | Channel |
|---|---|
| 🚨 Bug Reports |  |
| 🎁 Feature Requests |  |
| 👩💻 Usage Questions |  |
| 📢 Announcements | |
The API documentation can be found here. To generate UI elements, you can use the high-level pydantic_form method. Or the more flexible lower-level pydantic_input and pydantic_output methods. See the examples section on how to use those methods.
- Pull requests are encouraged and always welcome. Read our contribution guidelines and check out help-wanted issues.
- Submit Github issues for any feature request and enhancement, bugs, or documentation problems.
- By participating in this project, you agree to abide by its Code of Conduct.
- The development section below contains information on how to build and test the project after you have implemented some changes.
To build the project and run the style/linter checks, execute:
make install
make checkRun make help to see additional commands for development.
Licensed MIT. Created and maintained with ❤️ by developers from Berlin.
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