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Welcome to Data Validator!

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Data Validator is your go-to tool for clean data ingestion and validation, seamlessly integrating Streamlit and Panderas to make your data processing tasks a breeze.

Features

  • Easy Data Ingestion: Select your file format (CSV or JSON) and provide a URL to a Panderas schema.
  • Streamlined Validation: With just a few clicks, submit your selections and validate your data effortlessly.

streamlit-pandera

Installation instructions

pip install streamlit-pandera

Usage instructions

import streamlit as st

from  import run_validate_file


def validate():
    standards = {
        "store_schema": ("https://raw.githubusercontent.com/resilientinfrastructure/standards/main/panderas_schema.yml")
    }
    st.set_page_config(
        page_title="Data Validator Home",
        page_icon="📊",
    )
    validated_df = run_validate_file(standards=standards)
    # TODO: DO SOMETHING ELSE WITH VALIDATED_DF

Instructions

Step 1: Select File Format

Choose the file format you want to ingest. Whether it's CSV or JSON, streamlit-pandera has got you covered.

Step 2: Provide Panderas Schema URL

Enter the URL to the Panderas schema you want to use for validation. Don't worry, we support various schema sources to suit your needs.

Step 3: Submit and Validate

Hit that submit button and let streamlit-pandera work its magic! Your data will be validated against the specified schema in no time.

Go to Demo

Video

Run Tests

To ensure everything is functioning smoothly, run the tests using the following commands:

poetry install
poetry run playwright install
poetry run pytest e2e

Run the App

Ready to see streamlit-pandera in action? Simply run the following command:

poetry run streamlit run streamlit_pandera/Home.py

Contributions

We welcome contributions from the community! If you have any ideas, bug fixes, or enhancements, feel free to submit a pull request.

Feedback

We'd love to hear your feedback! Whether you have suggestions for improvement or just want to share your experience using streamlit-pandera, don't hesitate to reach out.

Happy data ingesting with streamlit-pandera!

Feel free to customize it further to better suit your project's tone and style!

Metadata

Release files for streamlit_pandera 0.0.2

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Source distribution for streamlit_pandera 0.0.2
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Table of built distributions (wheels) for streamlit_pandera 0.0.2
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streamlit_pandera-0.0.2-py3-none-any.whl Python 3 none any Details

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