Applications with Streamlit in Snowflake

Explore a hierarchical graph viewer that renders parent-child relationships as Graphviz graphs via Streamlit, with bubble charts, display and group options, and dynamic queries.

Extend your hierarchical data viewer with four interactive charts using Plotly in a Streamlit app, revealing parent–child relationships through treemap, icicle, sunburst, and sankey visuals.

Visualize Snowflake object dependencies across databases and schemas with Graphviz, showing tables, views, functions, and procedures, and query account usage dependencies from system views.

Build a data lineage viewer in Snowflake by creating a Streamlit app that queries the access history and account usage system views to display column-level data movements.

Learn to reverse engineer Snowflake database structures by generating create and alter table scripts from metadata, using show commands for databases, schemas, tables, columns, and keys.

This lecture demonstrates a visually appealing snowflake entity-relationship viewer in streamlit that renders primary key–foreign key diagrams, shows columns and data types, and generates graphviz code and sql scripts.

Build a small streamlit app that converts XML, YAML, or JSON to collapsible JSON, with syntax highlighting and one-line conversions, using XML to dict and YAML safe_load.

learn to generate exploratory data analysis reports with pandas profiling in a snowflake data context, producing a single html report with correlations, distributions, missing values, and descriptive statistics.

Use a streamlit json data profiler to infer schema from complex json data, including nested objects and arrays, showing mandatory versus optional fields (star marker), and data types with counts.

Learn to build a custom query profile in Snowflake by extracting operator stats, generating a graph with Graphviz, and exposing it in a Streamlit app.

Build a Streamlit chat bot using OpenAI's ChatGPT via REST API, with memory and Streamlit controls, plus secure Snowflake external access integrations and secrets.

Generate realistic fake data for Snowflake projects using the faker Python library and a Streamlit app; select providers and methods, set row count, and save results to a Snowpark table.

Compute a correlation matrix for numeric columns from a Snowflake query using Snowpark data frames and pandas. Visualize the results with a heatmap and compare Pearson, Spearman, and Kendall correlations.

Learn to detect exploding joins in Snowflake queries with a Streamlit app. Measure input vs output rows using a minimum multiplication factor and query operator stats from account usage history.

Explore clustering key analysis for Snowflake tables with Streamlit, visualizing clustering information and histograms to compare keys using an interactive inspector and non-destructive analyzer.

Explore an interactive Streamlit app that generates fast Snowflake queries with dynamic group by and pivot, using Snowpark data frames instead of in memory pandas for scalability.

Explore styling table columns in Streamlit for Snowflake data, applying read-only and editable grids with controls, sparklines, images, hyperlinks, progress bars, and arrays and lists for richer visuals.

Visualize Snowflake security by mapping the role hierarchy and privileges, including recursive grants, and build a Streamlit security inspector that queries account usage grants to reveal global and object privileges.

Build a streamlit app that renders snowflake query results as collapsible json, using object_construct with keep_nulls and aggregate array_agg to produce a single json object with per-row selection.