Packages
Defines the interface contract that Snakemake report plugins must implement to integrate with Snakemake's reporting system.
Provides a stable interface specification for building Snakemake scheduler plugins, allowing developers to implement custom job scheduling logic that integrates with Snakemake's workflow execution engine.
Provides a stable interface specification and base classes for building Snakemake storage plugins that interact with various storage backends.
If you are a Snakemake end-user, install only if your workflow uses a custom storage plugin that depends on it.
Enables Snakemake workflows to read from and write to Google Cloud Storage as a storage backend.
Enables Snakemake workflows to read from and write to S3-compatible storage (AWS S3, MinIO, and others) as a pluggable storage backend.
SnakeMD generates Markdown files programmatically from Python, letting you build documentation, README files, and other Markdown content through a Python API instead of writing raw Markdown text.
Install it if you need to generate Markdown files from Python code.
SnakeViz is a web-based viewer for Python profiling data that displays call stacks and execution time hierarchies in an interactive browser interface.
Install it if you regularly profile Python code and want a better way to explore the results than command-line tools.
Snappi is an auto-generated Python SDK for controlling traffic generators that conform to the Open Traffic Generator API, allowing you to write test scripts that configure, transmit, and measure network traffic.
Executes traffic generation test scripts against IxNetwork, Keysight's implementation of the Open Traffic Generator specification, using a unified Python API.
Registers runtime hooks in AWS Lambda SnapStart-enabled Python functions to execute code before snapshots are taken and after snapshots are restored.
Snapshot testing library that captures API responses or other serializable outputs and compares them against stored reference snapshots, supporting pytest, unittest, Django, and nose test runners.
However, it has been dormant since 2020-09-29 with no recent commits—if you need active maintenance, bug fixes, or support for cutting-edge test frameworks, consider…
Snaptime transforms timestamps using a simple DSL inspired by Splunk's relative time modifiers, allowing you to snap to time boundaries and apply time deltas in a single chained expression.
Python SDK client for SnapTrade's brokerage connection API, enabling live account access, position queries, and order placement across multiple brokerages.
Merges multiple ONNX neural network models into a single combined model by connecting specified output and input operators, with optional operator name prefixing to avoid conflicts.
Removes specified nodes from ONNX model graphs via CLI or Python API, outputting a modified model file or in-memory graph.
Extracts subgraphs from ONNX model files by specifying input and output operation names, generating smaller ONNX files without the overhead of standard extraction methods.
Install it if you work with ONNX models and need to extract subgraphs or partition files by operation boundaries.
Automatically generates and assigns operation names to unnamed operators in ONNX model files, converting old-format ONNX graphs to have properly named operations.
Detects which async library (asyncio, Trio, etc.) your code is currently running under, enabling libraries to support multiple async frameworks with a single runtime check.
Install it if you're building multi-framework async support; skip it if you're only targeting one framework.
SniTun is an SNI proxy with TCP multiplexer that encrypts traffic end-to-end using Fernet tokens and AES ciphers, forwarding external TLS connections through an encrypted multiplexed channel to local endpoints.
Install only if your project can comply with copyleft terms and your deployment targets Python 3.13+.
SNMP Simulator creates a pure-Python SNMP agent simulator that responds to SNMP queries (v1/v2c/v3) as if it were multiple real network devices, using configurable data files or plugins.
Install it if you need to test against SNMP agents without physical devices or if you're developing SNMP client code.
Snob analyzes your Python project's dependency graph to intelligently select which tests to run based on code changes, reducing test suite execution time by skipping unaffected tests.
snoop adds decorator-based and context-manager tracing to Python functions, logging which lines execute, when variables change, and their values—a lightweight alternative to setting up a full debugger.
Provides stemming algorithms for 34 languages, reducing word variants to a common stem for text search and indexing applications.
Install it if you need stemming for search or text indexing.
Snowfakery generates fake relational data from YAML recipes, writing output to stdout, databases via SQLAlchemy, or Salesforce orgs when embedded in CumulusCI.
Unified Python API for Snowflake workloads, providing access to data engineering, Snowpark, Snowpark ML, and client application resources through a single namespace package.
Snowflake CLI is a command-line tool for developers to create, manage, and deploy applications on Snowflake, including Streamlit apps, native apps, Snowpark services, and SQL operations.
This package has been renamed and is now a redirect to snowflake-cli; installing it pulls in the current Snowflake CLI tool for managing Snowflake resources from the command line.
Connects Python applications to Snowflake data warehouses using the DB API 2.0 specification, enabling SQL queries, data transfers, and warehouse operations.
Provides Python access to Snowflake entity metadata and resource management, allowing you to create, delete, and modify Snowflake resources programmatically.
Install it if you need to automate Snowflake object lifecycle operations from Python; skip it if you only need to query data (use snowflake-connector-python directly…
Generates and parses Snowflake IDs, distributed unique identifiers composed of timestamp, instance, and sequence components.
A deprecated MCP server that previously integrated Snowflake Cortex AI services (Search, Analyst, Agent), object management, and SQL execution into the Model Context Protocol—no longer maintained; users should migrate to the official Snowflake MCP Server.
Provides temporary backward compatibility for code that imports the old unrelated `snowflake` package, allowing it to read from `/etc/snowflake` or an alternative path; this is a migration bridge, not a primary tool.
Snowflake ML Python provides SDKs and infrastructure to build, train, manage, and deploy machine learning models directly within Snowflake, covering data preprocessing, feature engineering, model development, experiment tracking, and model registry.
Snowpark Python provides APIs to query and process data directly in Snowflake without moving data to your local system, with support for both native Snowpark and pandas-compatible interfaces.
Install it if you use Snowflake and want to process data without moving it to your application layer.
Snowflake SQLAlchemy is a SQLAlchemy dialect that enables SQLAlchemy applications to connect to and query Snowflake databases using standard SQLAlchemy ORM and Core APIs.
Install it if you are building a Python application that needs to connect to Snowflake and prefer SQLAlchemy's abstraction layer over raw SQL or the connector API.
Emits telemetry data from Python UDFs, UDTFs, and Stored Procedures running in Snowflake, using the OpenTelemetry API and SDK.
Install only if you're already using Snowflake's Python compute—it has no value outside that context.
Snowpark Connect for Spark lets you run Spark workloads directly against Snowflake's compute engine using the Spark Connect protocol, without managing a separate Spark cluster.
Bundles Apache Spark 3.5.6 JAR files required by Snowpark Connect, eliminating the need to download Spark separately.
Provides JAR dependencies for Snowpark Connect, bundling Scala, Jackson, Commons, and other required Java libraries as a Python package.
Streams data in real-time into Snowflake tables via a Python SDK with a Rust-based core for high performance.
Install only if you have streaming requirements; it is not a general-purpose data tool.