Streamlit Snowflake
When & Why to Use This Skill
This Claude skill empowers developers to build, configure, and deploy Streamlit applications natively within the Snowflake Data Cloud. It provides comprehensive support for snowflake.yml scaffolding, Snowpark session integration, and Snowflake Marketplace publishing. By automating project structure and addressing 14 common deployment errors, it streamlines the creation of secure, high-performance data applications and Native Apps directly on Snowflake's infrastructure.
Use Cases
- Scaffolding and deploying native Snowflake data dashboards with optimized snowflake.yml configurations.
- Migrating Streamlit apps to Snowflake Container Runtime to reduce compute costs and utilize external PyPI packages.
- Implementing secure, multi-tenant data isolation using the Caller's Rights privilege model (v1.53.0+).
- Publishing Streamlit-based data products as Native Apps to the Snowflake Marketplace.
- Troubleshooting complex environment issues such as Snowflake Anaconda Channel restrictions and Snowpark DataFrame performance bottlenecks.
| name | streamlit-snowflake |
|---|---|
| description | | |
| user-invocable | true |
| license | MIT |
| last_verified | 2026-01-21 |
| streamlit_version | 1.53.0 |
| errors_prevented | 14 |
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.ymlwith 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.txtorpyproject.tomlwith 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:
- Convert to Native App - Use
templates-native-app/templates - Create Provider Profile - Required for Marketplace listings
- 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
WHERE language = 'python'
ORDER BY package_name;
-- Search for specific package
SELECT * FROM information_schema.packages
WHERE language = 'python'
AND package_name ILIKE '%plotly%';
Common available packages:
- pandas, numpy, scipy
- plotly, altair (4.0), matplotlib
- scikit-learn, xgboost
- snowflake-snowpark-python
- streamlit (1.22.0 default, 1.35.0 with explicit version)
Not available:
- Packages from conda-forge
- Custom/private packages
- Packages requiring native compilation
See: Snowpark Python Packages Explorer
Known Limitations
Data & Size Limits
- 32 MB message size between backend/frontend (affects large
st.dataframe) - 200 MB file upload limit via
st.file_uploader - No
.sofiles - Native compiled libraries unsupported - No external stages - Internal stages only (client-side encryption)
UI Restrictions
st.set_page_config-page_title,page_icon,menu_itemsnot supportedst.bokeh_chart- Not supported- Custom Streamlit components - Only components without external service calls
- Content Security Policy - Blocks external scripts, styles, fonts, iframes
eval()blocked - CSP prevents unsafe JavaScript execution
Caching (Warehouse Runtime)
- Session-scoped only -
st.cache_dataandst.cache_resourcedon't persist across users - Container runtime has full caching support across viewers
Package Restrictions (Warehouse Runtime)
- Snowflake Anaconda Channel only - No conda-forge, no pip
- Container runtime allows PyPI packages
Network & Access
- No Azure Private Link / GCP Private Service Connect
- No replication of Streamlit objects
Authentication (Important - 2026 Deadline)
Password-only authentication is being deprecated:
| Milestone | Date | Requirement |
|---|---|---|
| Milestone 1 | Sept 2025 - Jan 2026 | MFA required for Snowsight users |
| Milestone 2 | May - July 2026 | All new users must use MFA |
| Milestone 3 | Aug - Oct 2026 | All users must use MFA or key-pair/OAuth |
Recommended authentication methods:
- Key-pair authentication (for service accounts)
- OAuth client credentials (for M2M)
- Workload Identity Federation (for cloud-native apps)
See references/authentication.md for implementation patterns.
Resources
Official Documentation
- Streamlit in Snowflake
- Snowflake CLI Streamlit Commands
- Native Apps with Streamlit
- Marketplace Publishing
Examples
Tools
- Snowpark Python Packages Explorer
- Snowflake MCP Server (for Claude integration)