Showing 2 open source projects for "python programming language"

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  • Stigg | SaaS Monetization and Entitlements API Icon
    Stigg | SaaS Monetization and Entitlements API

    For developers in need of a tool to launch pricing plans faster and build better buying experiences

    A monetization platform is a standalone middleware that sits between your application and your business applications, as part of the modern enterprise billing stack. Stigg unifies all the APIs and abstractions billing and platform engineers had to build and maintain in-house otherwise. Acting as your centralized source of truth, with a highly scalable and flexible entitlements management, rolling out any pricing and packaging change is now a self-service, risk-free, exercise.
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  • Transform months of data modeling and coding into days. Icon
    Transform months of data modeling and coding into days.

    Automatically generate, document, and govern your entire data architecture.

    Efficiently model your business and data models, and generate code for your data pipelines, data lakehouse, and analytical applications
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  • 1
    Orchest

    Orchest

    Build data pipelines, the easy way

    ...From idea to scheduled pipeline in hours, not days. Interactively build your data science pipelines in our visual pipeline editor. Versioned as a JSON file. Run scripts or Jupyter notebooks as steps in a pipeline. Python, R, Julia, JavaScript, and Bash are supported. Parameterize your pipelines and run them periodically on a cron schedule. Easily install language or system packages. Built on top of regular Docker container images. Creation of multiple instances with up to 8 vCPU & 32 GiB memory. A free Orchest instance with 2 vCPU & 8 GiB memory. ...
    Downloads: 0 This Week
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  • 2
    nonechucks

    nonechucks

    Deal with bad samples in your dataset dynamically

    nonechucks is a library that provides wrappers for PyTorch's datasets, samplers and transforms to allow for dropping unwanted or invalid samples dynamically. What if you have a dataset of 1000s of images, out of which a few dozen images are unreadable because the image files are corrupted? Or what if your dataset is a folder full of scanned PDFs that you have to OCRize, and then run a language detector on the resulting text, because you want only the ones that are in English? Or maybe you...
    Downloads: 0 This Week
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