Showing 2 open source projects for "flat file databases"

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    Supercharge Your Manufacturing with Easy MRP and MES Software

    Designed for SME manufacturers who want to reduce wasteful manual processing, save time and increase profits.

    Flowlens eliminates stock-outs, shortage and overstocks, avoiding costly production delays. Stay in control of inventory levels and keep production running smoothly with real-time visibility and easy-to-use stock management. Import bulk data with ease.
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  • Ditto Edge Server is a lightweight standalone server for resource-constrained edge environments, based on the core Ditto Edge SDK. Icon
    Ditto Edge Server is a lightweight standalone server for resource-constrained edge environments, based on the core Ditto Edge SDK.

    With Ditto Edge Server, you can join devices as small as a Raspberry Pi to a local mesh network and synchronize data across edge environments.

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  • 1
    sf (Simple Features)

    sf (Simple Features)

    Simple Features for R

    ...It allows spatial vector data (points, lines, polygons etc.) to be represented as records in data frames (or tibbles) with geometry list columns, and performs spatial operations (geometry operations, coordinate reference system transformations, reading/writing spatial data, integration with spatial databases etc.). It interfaces to GDAL, GEOS, PROJ libraries for robust operations. Reading and writing spatial vector data via many file formats/drivers through GDAL, and spatial databases (PostGIS etc.) Supports all standard simple feature geometry types (points, linestrings, polygons, multi-geometries etc.) in various dimensions (XY, XYZ, XYM, XYZM).
    Downloads: 0 This Week
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  • 2
    DataScienceR

    DataScienceR

    a curated list of R tutorials for Data Science, NLP

    ...Many of the modules demonstrate best practices in R, such as using the tidyverse, R Markdown, modular scripting, and reproducible workflows. The repository also shows examples of linking R with external resources — APIs, databases, and file formats — and integrating into larger pipelines. It acts as a learning scaffold for students or beginners transitioning to more advanced data science work in R, offering a hands-on, example-driven approach. The structure encourages modularity, readability, and reproducible practices, making it a useful reference repository for learners and educators alike.
    Downloads: 0 This Week
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