3 projects for "real" with 2 filters applied:

  • Train ML Models With SQL You Already Know Icon
    Train ML Models With SQL You Already Know

    BigQuery automates data prep, analysis, and predictions with built-in AI assistance.

    Build and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
    Try Free
  • Save Up to 91% on Cloud Compute With Spot VMs Icon
    Save Up to 91% on Cloud Compute With Spot VMs

    Automatic sustained-use discounts. One free VM per month. No negotiation needed.

    Run batch jobs at 60-91% off with Spot VMs. Long-running workloads get automatic discounts with sustained use.
    Try Free
  • 1
    Loop Engineering

    Loop Engineering

    Practical patterns, starters & CLI tools for loop engineering with AI

    ...It explains core building blocks such as scheduling, worktrees, skills, plugins, connectors, sub-agents, and persistent memory or state. The repository includes production loop patterns, quickstarts, starters, checklists, safety notes, and real-world stories. It also provides CLI tools such as loop-audit, loop-init, and loop-cost to scaffold, evaluate, and estimate agent loop workflows.
    Downloads: 9 This Week
    Last Update:
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  • 2
    TestSprite

    TestSprite

    AI-powered automated testing from your terminal

    TestSprite is the official command-line interface for TestSprite’s AI-powered testing platform. It lets developers and coding agents run automated tests against live frontend and backend applications from the terminal. The CLI is designed as a verification layer for agentic coding workflows, so an AI agent can create tests, run them, inspect failures, fix code, and rerun checks. It returns structured failure bundles that can include failing steps, screenshots, DOM snapshots, test source,...
    Downloads: 1 This Week
    Last Update:
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  • 3
    glom

    glom

    Python's nested data operator

    glom is a Python library and command-line tool for accessing, restructuring, and transforming nested data. It is designed for real-world data structures where dictionaries, objects, and lists are deeply nested and difficult to handle cleanly. Developers can use path-based access to retrieve values without writing long chains of fragile indexing code. The library also provides readable error messages, which makes debugging broken paths much easier. Its declarative specification style lets users describe the output shape they want instead of manually building transformation logic. glom is especially useful for data processing, API response cleanup, configuration handling, and scripts that need reliable nested data manipulation.
    Downloads: 0 This Week
    Last Update:
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