https://github.com/PredictiveEcology/lazyR

An R package for stashing objects in lazy load databases, analogous to lazy loaded packages
https://github.com/PredictiveEcology/lazyR

Last synced: 5 months ago
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An R package for stashing objects in lazy load databases, analogous to lazy loaded packages

• Host: GitHub
• URL: https://github.com/PredictiveEcology/lazyR
• Owner: PredictiveEcology
• Created: 2015-09-23T03:16:46.000Z (over 9 years ago)
• Default Branch: master
• Last Pushed: 2016-01-05T19:42:34.000Z (over 9 years ago)
• Last Synced: 2024-08-13T07:15:07.560Z (8 months ago)
• Language: R
• Size: 172 KB
• Stars: 5
• Watchers: 5
• Forks: 0
• Open Issues: 3
• Metadata Files:
  • Readme: README.md

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README

        
# lazyR

An R package for stashing objects in lazy load databases, analogous to lazy loaded packages.

This uses the `archivist` package for the back end, using the `.rda` files or raster-based files. The lazy mechanism is at loading time only, creating a promise to evaluate the `loadFromLocalRepo()` function when it is needed.

## Using manual lazy saving

The basic work flow is:

1. decide on a folder for the database, and set it using `lazyDir()`

2. save objects to a lazyR database using `lazySave(obj)`

    - optionally give it tags while saving: `lazySave(obj, tags=c("maps", "USA"))`

3. list the contents of the lazyR database with `lazyLs()`

4. re-load objects via name or tag using `lazyLoad2(tag="maps")`

5. remove objects via `lazyRm("objName")` or `lazyRm(lazyLs("tagname"))`

## Using caching (automatic lazy saving)

An alternative workflow is to use the `%<%` (`assignCache`) operator, which will automatically cache the object with its assigned object name. Caching, like with the archivist package, will first do a hash of the arguments in the function, compare with the hashed value of the objects in the database, and return the cached object, if the hash values are the same.

Example:

1. decide on a folder for the database, and set it using

    lazyDir(tempdir(), create=TRUE)

2. assign objects via `%<%`. See help(cacheAssign)

    a %<% seq(1,10,1)

## Common things to use:

- `lazyLs()` will list all objects in the database

- `lazyLs(tagType="all")` will list the full `archivist` `data.frame` with columns: `md5Hash`, `tag`, `dateCreated`.

- others to come

## Connection with `archivist` package

The `lazyDir` argument in the `lazyR` package is exactly the same as a repository in archivist.

Thus, all archivist functions work with the `lazyR` package. Simply use lazyDir and RepoDir interchangeably.

Notes:

- Some tags are done automatically

    - a full set of classes, a result of a call to `is(obj)`, prefixed by `class:` in the tags

    - the original object name, prefixed with `objectName:`    

    

- Objects of class `Raster*` are special because of their "sometimes on disk" nature. 

    

    - If there is a file backing the object, then this file will be copied to the lazyDir directory, with a subdirectory called "raster"

    - The original file will be used as part of the lazy loading.

    - If the original file is a temporary file, be sure to use `lazySave(..., copyRasterFile=TRUE)` to save it. This is also required to ensure portability of a `lazyR` database.