Streamlit in Snowflake Skill

Build and deploy Streamlit apps natively within Snowflake, including Marketplace publishing as Native Apps.

Quick Start

1. Initialize Project

Copy the templates to your project:

# Create project directory
mkdir my-streamlit-app && cd my-streamlit-app

# Copy templates (Claude will provide these)

2. Configure snowflake.yml

Update placeholders in snowflake.yml:

definition_version: 2
entities:
  my_app:
    type: streamlit
    identifier: my_streamlit_app        # ← Your app name
    stage: my_app_stage                 # ← Your stage name
    query_warehouse: my_warehouse       # ← Your warehouse
    main_file: streamlit_app.py
    pages_dir: pages/
    artifacts:
      - common/
      - environment.yml

3. Deploy

# Deploy to Snowflake
snow streamlit deploy --replace

# Open in browser
snow streamlit deploy --replace --open

When to Use This Skill

Use when:

• Building data apps that run natively in Snowflake
• Need Snowpark integration for data access
• Publishing apps to Snowflake Marketplace
• Setting up CI/CD for Streamlit in Snowflake

Don't use when:

• Hosting Streamlit externally (use Streamlit Community Cloud)
• Building general Snowpark pipelines (use a Snowpark-specific skill)
• Need custom Streamlit components (not supported in SiS)

Runtime Environments

Snowflake offers two runtime options for Streamlit apps:

Warehouse Runtime (Default)

• Creates a personal instance for each viewer
• Uses environment.yml with Snowflake Anaconda Channel
• Python 3.9, 3.10, or 3.11
• Streamlit 1.22.0 - 1.35.0
• Best for: Sporadic usage, isolated sessions

Container Runtime (Preview)

• Creates a shared instance for all viewers
• Uses requirements.txt or pyproject.toml with PyPI packages
• Python 3.11 only
• Streamlit 1.49+
• Significantly lower cost (~$2.88/day vs ~$48/day for equivalent compute)
• Best for: Frequent usage, cost optimization

Container Runtime Configuration:

CREATE STREAMLIT my_app
  FROM '@my_stage/app_folder'
  MAIN_FILE = 'streamlit_app.py'
  RUNTIME_NAME = 'SYSTEM$ST_CONTAINER_RUNTIME_PY3_11'
  COMPUTE_POOL = my_compute_pool
  QUERY_WAREHOUSE = my_warehouse;

Key difference: Container runtime allows external PyPI packages - not limited to Snowflake Anaconda Channel.

See: Runtime Environments

Security Model

Streamlit apps support two privilege models:

Owner's Rights (Default)

• Apps execute with the owner's privileges, not the viewer's
• Apps use the warehouse provisioned by the owner
• Viewers can interact with data using all owner role privileges

Security implications:

• Exercise caution when granting write privileges to app roles
• Use dedicated roles for app creation/viewing
• Viewers can access any data the owner role can access
• Best for: Internal tools with trusted users

Caller's Rights (v1.53.0+)

• Apps execute with the viewer's privileges
• Each viewer sees only data they have permission to access
• Provides data isolation in multi-tenant scenarios

Use caller's rights when:

• Building public or external-facing apps
• Need per-user data access control
• Multi-tenant applications requiring data isolation

See Caller's Rights Connection pattern below.

Project Structure

my-streamlit-app/
├── snowflake.yml           # Project definition (required)
├── environment.yml         # Package dependencies (required)
├── streamlit_app.py        # Main entry point
├── pages/                  # Multi-page apps
│   └── data_explorer.py
├── common/                 # Shared utilities
│   └── utils.py
└── .gitignore

Key Patterns

Snowpark Session Connection

import streamlit as st

# Get Snowpark session (native SiS connection)
conn = st.connection("snowflake")
session = conn.session()

# Query data
df = session.sql("SELECT * FROM my_table LIMIT 100").to_pandas()
st.dataframe(df)

Caller's Rights Connection (v1.53.0+)

Execute queries with viewer's privileges instead of owner's privileges:

import streamlit as st

# Use caller's rights for data isolation
conn = st.connection("snowflake", type="callers_rights")

# Each viewer sees only data they have permission to access
df = conn.query("SELECT * FROM sensitive_customer_data")
st.dataframe(df)

Security comparison:

Connection Type	Privilege Model	Use Case
type="snowflake" (default)	Owner's rights	Internal tools, trusted users
type="callers_rights" (v1.53.0+)	Caller's rights	Public apps, data isolation

Source: Streamlit v1.53.0 Release

Caching Expensive Queries

@st.cache_data(ttl=600)  # Cache for 10 minutes
def load_data(query: str):
    conn = st.connection("snowflake")
    return conn.session().sql(query).to_pandas()

# Use cached function
df = load_data("SELECT * FROM large_table")

Warning: In Streamlit v1.22.0-1.53.0, params argument is not included in cache key. Use ttl=0 to disable caching when using parametrized queries, or upgrade to 1.54.0+ when available (Issue #13644).

Optimizing Snowpark DataFrame Performance

When using Snowpark DataFrames with charts or tables, select only required columns to avoid fetching unnecessary data:

# ❌ Fetches all 50 columns even though chart only needs 2
df = session.table("wide_table")  # 50 columns
st.line_chart(df, x="date", y="value")

# ✅ Fetch only needed columns for better performance
df = session.table("wide_table").select("date", "value")
st.line_chart(df, x="date", y="value")
# 5-10x faster for wide tables

Why it matters: st.dataframe() and chart components call df.to_pandas() which evaluates ALL columns, even if the visualization only needs some. Pre-selecting columns reduces data transfer and improves performance (Issue #11701).

Environment Configuration

environment.yml (required format):

name: sf_env
channels:
  - snowflake          # REQUIRED - only supported channel
dependencies:
  - streamlit=1.35.0   # Explicit version (default is old 1.22.0)
  - pandas
  - plotly
  - altair=4.0         # Version 4.0 supported in SiS
  - snowflake-snowpark-python

Error Prevention

This skill prevents 14 documented errors:

Error	Cause	Prevention
PackageNotFoundError	Using conda-forge or external channel	Use channels: - snowflake (or Container Runtime for PyPI)
Missing Streamlit features	Default version 1.22.0	Explicitly set streamlit=1.35.0 (or use Container Runtime for 1.49+)
ROOT_LOCATION deprecated	Old CLI syntax	Use Snowflake CLI 3.14.0+ with FROM source_location
Auth failures (2026+)	Password-only authentication	Use key-pair or OAuth (see references/authentication.md)
File upload fails	File >200MB	Keep uploads under 200MB limit
DataFrame display fails	Data >32MB	Paginate or limit data before display
page_title not supported	SiS limitation	Don't use page_title, page_icon, or menu_items in st.set_page_config()
Custom component error	SiS limitation	Only components without external service calls work
_snowflake module not found	Container Runtime migration	Use from snowflake.snowpark.context import get_active_session instead of from _snowflake import get_active_session (Migration Guide)
Cached query returns wrong data with different params	params not in cache key (v1.22.0-1.53.0)	Use ttl=0 to disable caching for parametrized queries, or upgrade to 1.54.0+ when available (Issue #13644)
Invalid connection_name 'default' with kwargs only	Missing secrets.toml or connections.toml	Create minimal .streamlit/secrets.toml with [connections.snowflake] section (Issue #9016)
Native App upgrades unexpectedly	Implicit default Streamlit version (BCR-1857)	Explicitly set streamlit=1.35.0 in environment.yml to prevent automatic version changes (BCR-1857)
File paths fail in Container Runtime subdirectories	Some commands use entrypoint-relative paths	Use pathlib to resolve absolute paths: Path(__file__).parent / "assets/logo.png" (Runtime Docs)
Slow performance with wide Snowpark DataFrames	st.dataframe() fetches all columns even if unused	Pre-select only needed columns: df.select("col1", "col2") before passing to Streamlit (Issue #11701)

Deployment Commands

Basic Deployment

# Deploy and replace existing
snow streamlit deploy --replace

# Deploy and open in browser
snow streamlit deploy --replace --open

# Deploy specific entity (if multiple in snowflake.yml)
snow streamlit deploy my_app --replace

CI/CD Deployment

See references/ci-cd.md for GitHub Actions workflow template.

Marketplace Publishing (Native App)

To publish your Streamlit app to Snowflake Marketplace:

1. Convert to Native App - Use templates-native-app/ templates
2. Create Provider Profile - Required for Marketplace listings
3. Submit for Approval - Snowflake reviews before publishing

See templates-native-app/README.md for complete workflow.

Native App Structure

my-native-app/
├── manifest.yml            # Native App manifest
├── setup.sql               # Installation script
├── streamlit/
│   ├── environment.yml
│   ├── streamlit_app.py
│   └── pages/
└── README.md

Package Availability

Only packages from the Snowflake Anaconda Channel are available:

-- Query available packages
SELECT * FROM information_schema.packages