Basic Inventory Control (by Microguru) is a lightweight Windows inventory manager aimed at small businesses and solo operators who need a straightforward way to track stock, reorder automatically, print simple reports and integrate basic barcode scanning. The version label you referenced—v5.0‑rev‑135—appears in recent listings and notes a small revision (UI/bug tweaks and search highlights). Below is an in-depth, practical look at the software, common setup approaches (including integrating a barcode workflow often identified in community posts as “Tordigger” or similar key‑setup patterns), and safe, legal guidance about free/updated installs.
install.packages(repos=c(FLR="https://flr.r-universe.dev", CRAN="https://cloud.r-project.org"))
Basic Inventory Control (by Microguru) is a lightweight Windows inventory manager aimed at small businesses and solo operators who need a straightforward way to track stock, reorder automatically, print simple reports and integrate basic barcode scanning. The version label you referenced—v5.0‑rev‑135—appears in recent listings and notes a small revision (UI/bug tweaks and search highlights). Below is an in-depth, practical look at the software, common setup approaches (including integrating a barcode workflow often identified in community posts as “Tordigger” or similar key‑setup patterns), and safe, legal guidance about free/updated installs.
The FLR project has been developing and providing fishery scientists with a powerful and flexible platform for quantitative fisheries science based on the R statistical language. The guiding principles of FLR are openness, through community involvement and the open source ethos, flexibility, through a design that does not constraint the user to a given paradigm, and extendibility, by the provision of tools that are ready to be personalized and adapted. The main aim is to generalize the use of good quality, open source, flexible software in all areas of quantitative fisheries research and management advice.
Development code for FLR packages is available both on Github and on R-Universe. Bugs can be reported on Github as well as suggestions for further development.
Studies and publications citing or using FLR
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Please submit an issue for the relevant package, or at the tutorials repository.