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https://github.com/dominikrafacz/deepdep
Visualise and Explore Deep Dependencies of R packages
https://github.com/dominikrafacz/deepdep
dependencies package plot r visualization
Last synced: 4 days ago
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Visualise and Explore Deep Dependencies of R packages
- Host: GitHub
- URL: https://github.com/dominikrafacz/deepdep
- Owner: DominikRafacz
- License: gpl-3.0
- Created: 2019-10-22T12:28:12.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2024-05-27T08:10:20.000Z (6 months ago)
- Last Synced: 2024-10-03T06:51:02.194Z (about 1 month ago)
- Topics: dependencies, package, plot, r, visualization
- Language: HTML
- Homepage: https://dominikrafacz.github.io/deepdep/
- Size: 13.8 MB
- Stars: 73
- Watchers: 5
- Forks: 8
- Open Issues: 20
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
Awesome Lists containing this project
README
# Visualise and Explore Deep Dependencies of R Packages 
[](https://CRAN.R-project.org/package=deepdep)
[](https://circleci.com/gh/DominikRafacz/deepdep)
[](https://ci.appveyor.com/project/DominikRafacz/deepdep)
[](https://codecov.io/gh/DominikRafacz/deepdep?branch=master)
[](https://www.tidyverse.org/lifecycle/#maturing)
## Overview
The `deepdep` package provides tools for exploration of package
dependencies. The main `deepdep()` function allows to acquire deep
dependencies of any package and plot them in an elegant way. It also
adds some popularity measures for the packages e.g. in the form of
download count through the `cranlogs` package. Uses the [CRAN metadata
database](http://crandb.r-pkg.org) and [Bioconductor
metadata](http://bioconductor.org).
**Exploration tools:**
- `deepdep()`
- `get_dependencies()`
- `get_downloads()`
- `get_description()`
**Visualisation tools:**
- `plot_dependencies()`
- `plot_downloads()`
- `deepdep_shiny()` runs shiny application that helps to produce a nice
**deepdep plot**
## Installation
``` r
# Install from CRAN:
install.packages("deepdep")
# Install the development version from GitHub:
devtools::install_github("DominikRafacz/deepdep")
```
## Examples [**introduction to the deepdep package**](https://dominikrafacz.github.io/deepdep/articles/deepdep-package.html)
``` r
library(deepdep)
dd <- deepdep("ggplot2", depth = 2)
head(dd)
```
## origin name version type origin_level dest_level
## 1 ggplot2 cli Imports 0 1
## 2 ggplot2 glue Imports 0 1
## 3 ggplot2 gtable >= 0.1.1 Imports 0 1
## 4 ggplot2 isoband Imports 0 1
## 5 ggplot2 lifecycle > 1.0.1 Imports 0 1
## 6 ggplot2 MASS Imports 0 1
``` r
plot_dependencies(dd, "circular")
```
``` r
plot_dependencies("bayes4psy", show_version = TRUE,
dependency_type = c("Depends", "Imports", "Suggests", "LinkingTo"))
```
``` r
dd_xgboost <- deepdep("xgboost", dependency_type = "Imports", downloads = TRUE)
head(dd_xgboost)
```
## origin name version type last_day last_week last_month last_quarter last_half grand_total origin_level dest_level
## 1 xgboost Matrix >= 1.1-0 Imports 5669 78043 317730 1030313 2307023 10546730 0 1
## 2 xgboost data.table >= 1.9.6 Imports 21766 196875 768217 2494588 5294010 43848884 0 1
## 3 xgboost jsonlite >= 1.0 Imports 19405 249759 1048356 3110597 7056167 68812509 0 1
``` r
plot_downloads(dd_xgboost)
```
``` r
plot_dependencies(dd_xgboost, "tree", show_version = TRUE)
```
