tarchetypes

Archetypes for targets and pipelines

Science Score: 36.0%

This score indicates how likely this project is to be science-related based on various indicators:

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CITATION.cff file
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codemeta.json file
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Links to: zenodo.org
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Low similarity (17.0%) to scientific vocabulary

Keywords

data-science high-performance-computing peer-reviewed pipeline r r-package r-targetopia reproducibility rstats targets workflow

Keywords from Contributors

make drake makefile ropensci jags rjags rstats-package carpentries data-carpentry data-wrangling

Last synced: 6 months ago · JSON representation

Repository

Archetypes for targets and pipelines

Basic Info

Host: GitHub
Owner: ropensci
License: other
Language: R
Default Branch: main
Homepage: https://docs.ropensci.org/tarchetypes
Size: 1.83 MB

Statistics

Stars: 146
Watchers: 7
Forks: 20
Open Issues: 0
Releases: 36

Topics

data-science high-performance-computing peer-reviewed pipeline r r-package r-targetopia reproducibility rstats targets workflow

Created over 5 years ago · Last pushed 6 months ago

Metadata Files

Readme Changelog Contributing License Codemeta

README.Rmd

---
output: github_document
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# tarchetypes 

[![ropensci](https://badges.ropensci.org/401_status.svg)](https://github.com/ropensci/software-review/issues/401)
[![zenodo](https://zenodo.org/badge/282774543.svg)](https://zenodo.org/badge/latestdoi/282774543)
[![R Targetopia](https://img.shields.io/badge/R_Targetopia-member-blue?style=flat&labelColor=gray)](https://wlandau.github.io/targetopia/)
[![CRAN](https://www.r-pkg.org/badges/version/tarchetypes)](https://CRAN.R-project.org/package=tarchetypes)
[![status](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)
[![check](https://github.com/ropensci/tarchetypes/actions/workflows/check.yaml/badge.svg)](https://github.com/ropensci/tarchetypes/actions?query=workflow%3Acheck)
[![codecov](https://codecov.io/gh/ropensci/tarchetypes/branch/main/graph/badge.svg?token=3T5DlLwUVl)](https://app.codecov.io/gh/ropensci/tarchetypes)

The `tarchetypes` R package is a collection of target and pipeline archetypes for the [`targets`](https://github.com/ropensci/targets) package. These archetypes express complicated pipelines with concise syntax, which enhances readability and thus reproducibility. Archetypes are possible because of the flexible metaprogramming capabilities of [`targets`](https://github.com/ropensci/targets). In [`targets`](https://github.com/ropensci/targets), one can define a target as an object outside the central pipeline, and the [`tar_target_raw()`](https://docs.ropensci.org/targets/reference/tar_target_raw.html) function completely avoids non-standard evaluation. That means anyone can write their own niche interfaces for specialized projects. `tarchetypes` aims to include the most common and versatile archetypes and usage patterns.

## Grouped data frames

`tarchetypes` has functions for easy dynamic branching over subsets of data frames:

* `tar_group_by()`: define row groups using `dplyr::group_by()` semantics.
* `tar_group_select()`: define row groups using `tidyselect` semantics.
* `tar_group_count()`: define a given number row groups.
* `tar_group_size()`: define row groups of a given size.

If you define a target with one of these functions, all downstream dynamic targets will automatically branch over the row groups.

```{r, echo = FALSE}
targets::tar_script({
  produce_data <- function() {
    expand.grid(var1 = c("a", "b"), var2 = c("c", "d"), rep = c(1, 2, 3))
  }
  list(
    tarchetypes::tar_group_by(data, produce_data(), var1, var2),
    tar_target(group, data, pattern = map(data))
  )
})
```

```{r, eval = FALSE}
# _targets.R file:
library(targets)
library(tarchetypes)
produce_data <- function() {
  expand.grid(var1 = c("a", "b"), var2 = c("c", "d"), rep = c(1, 2, 3))
}
list(
  tar_group_by(data, produce_data(), var1, var2),
  tar_target(group, data, pattern = map(data))
)
```

```{r}
# R console:
library(targets)
tar_make()

# First row group:
tar_read(group, branches = 1)

# Second row group:
tar_read(group, branches = 2)
```

## Literate programming

Consider the following R Markdown report.

```{r, echo = FALSE, comment = ""}
lines <- c(
  "---",
  "title: report",
  "output: html_document",
  "---",
  "",
  "```{r}",
  "library(targets)",
  "tar_read(dataset)",
  "```"
)
cat(lines, sep = "\n")
```

We want to define a target to render the report. And because the report calls `tar_read(dataset)`, this target needs to depend on `dataset`. Without `tarchetypes`, it is cumbersome to set up the pipeline correctly.

```{r, eval = FALSE}
# _targets.R
library(targets)
list(
  tar_target(dataset, data.frame(x = letters)),
  tar_target(
    report, {
      # Explicitly mention the symbol `dataset`.
      list(dataset)
      # Return relative paths to keep the project portable.
      fs::path_rel(
        # Need to return/track all input/output files.
        c( 
          rmarkdown::render(
            input = "report.Rmd",
            # Always run from the project root
            # so the report can find _targets/.
            knit_root_dir = getwd(),
            quiet = TRUE
          ),
          "report.Rmd"
        )
      )
    },
    # Track the input and output files.
    format = "file",
    # Avoid building small reports on HPC.
    deployment = "main"
  )
)
```

With `tarchetypes`, we can simplify the pipeline with the `tar_render()` archetype.

```{r, eval = FALSE}
# _targets.R
library(targets)
library(tarchetypes)
list(
  tar_target(dataset, data.frame(x = letters)),
  tar_render(report, "report.Rmd")
)
```

Above, `tar_render()` scans code chunks for mentions of targets in `tar_load()` and `tar_read()`, and it enforces the dependency relationships it finds. In our case, it reads `report.Rmd` and then forces `report` to depend on `dataset`. That way, `tar_make()` always processes `dataset` before `report`, and it automatically reruns `report.Rmd` whenever `dataset` changes.

## Alternative pipeline syntax

[`tar_plan()`](https://docs.ropensci.org/tarchetypes/reference/tar_plan.html) is a drop-in replacement for [`drake_plan()`](https://docs.ropensci.org/drake/reference/drake_plan.html) in the [`targets`](https://github.com/ropensci/targets) ecosystem. 
It lets users write targets as name/command pairs without having to call [`tar_target()`](https://docs.ropensci.org/targets/reference/tar_target.html).

```{r, eval = FALSE}
tar_plan(
  tar_file(raw_data_file, "data/raw_data.csv", format = "file"),
  # Simple drake-like syntax:
  raw_data = read_csv(raw_data_file, col_types = cols()),
  data =raw_data %>%
    mutate(Ozone = replace_na(Ozone, mean(Ozone, na.rm = TRUE))),
  hist = create_plot(data),
  fit = biglm(Ozone ~ Wind + Temp, data),
  # Needs tar_render() because it is a target archetype:
  tar_render(report, "report.Rmd")
)
```

## Installation

Type | Source | Command
---|---|---
Release | CRAN | `install.packages("tarchetypes")`
Development | GitHub | `remotes::install_github("ropensci/tarchetypes")`
Development | rOpenSci | `install.packages("tarchetypes", repos = "https://dev.ropensci.org")`

## Documentation

For specific documentation on `tarchetypes`, including the help files of all user-side functions, please visit the [reference website](https://docs.ropensci.org/tarchetypes/). For documentation on [`targets`](https://github.com/ropensci/targets) in general, please visit the [`targets` reference website](https://docs.ropensci.org/targets/). Many of the linked resources use `tarchetypes` functions such as [`tar_render()`](https://docs.ropensci.org/tarchetypes/reference/tar_render.html).

## Help

Please read the [help guide](https://books.ropensci.org/targets/help.html) to learn how best to ask for help using `targets` and `tarchetypes`.

## Code of conduct

Please note that this package is released with a [Contributor Code of Conduct](https://ropensci.org/code-of-conduct/).

## Citation

```{r}
citation("tarchetypes")
```

```{r, echo = FALSE}
unlink("_targets.R")
tar_destroy()
```

Owner

Name: rOpenSci
Login: ropensci
Kind: organization
Email: info@ropensci.org
Location: Berkeley, CA

Website: https://ropensci.org/
Twitter: rOpenSci
Repositories: 307
Profile: https://github.com/ropensci

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GitHub Events

Total

Create event: 5
Release event: 5
Issues event: 18
Watch event: 12
Delete event: 3
Issue comment event: 25
Push event: 43
Pull request event: 5
Pull request review event: 5
Pull request review comment event: 5
Fork event: 3

Last Year

Create event: 5
Release event: 5
Issues event: 18
Watch event: 12
Delete event: 3
Issue comment event: 25
Push event: 43
Pull request event: 5
Pull request review event: 5
Pull request review comment event: 5
Fork event: 3

Name	Email	Commits
wlandau	w**u@g**m	540
wlandau	w**s@g**m	98
mutlusun	m****n	22
Bill Denney	w**y@h**m	2
rmflight	r**9@g**m	1
Noam Ross	n**s@g**m	1
Mike Mahoney	m**8@g**m	1
Maëlle Salmon	m**n@y**e	1
Florian Kohrt	f**t@a**o	1

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Last synced: 6 months ago

All Time

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Total pull requests: 24
Average time to close issues: 17 days
Average time to close pull requests: 5 days
Total issue authors: 39
Total pull request authors: 8
Average comments per issue: 2.78
Average comments per pull request: 1.75
Merged pull requests: 22
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 10
Pull requests: 7
Average time to close issues: 13 days
Average time to close pull requests: 5 days
Issue authors: 9
Pull request authors: 3
Average comments per issue: 1.1
Average comments per pull request: 1.86
Merged pull requests: 7
Bot issues: 0
Bot pull requests: 0

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Issue Labels

type: new feature (52) type: bug (7) type: edge case (6) type: trouble (4) depends: external prerequisite (3) topic: literate programming (2) type: use case (1) depends: another issue (1) status: out of scope (1) status: incompatible (1) topic: reproducibility (1) type: maintenance (1)

Pull Request Labels

type: new feature (3) topic: branching (1) topic: literate programming (1) topic: reproducibility (1)

Packages

Total packages: 2
Total downloads:
- cran 2,821 last-month
Total docker downloads: 194

Total dependent packages: 2
(may contain duplicates)
Total dependent repositories: 36
(may contain duplicates)
Total versions: 47
Total maintainers: 1

cran.r-project.org: tarchetypes

Archetypes for Targets

Homepage: https://docs.ropensci.org/tarchetypes/
Documentation: http://cran.r-project.org/web/packages/tarchetypes/tarchetypes.pdf
License: MIT + file LICENSE
Latest release: 0.13.1
published 10 months ago

Versions: 33
Dependent Packages: 2
Dependent Repositories: 35
Downloads: 2,821 Last month
Docker Downloads: 194

Rankings

Stargazers count: 3.7%

Dependent repos count: 4.4%

Forks count: 5.2%

Downloads: 9.3%

Average: 10.7%

Dependent packages count: 18.1%

Docker downloads count: 23.7%

Maintainers (1)

will.landau.oss@gmail.com

Last synced: 6 months ago

conda-forge.org: r-tarchetypes

Homepage: https://docs.ropensci.org/tarchetypes/
License: MIT
Latest release: 0.7.2
published over 3 years ago

Versions: 14
Dependent Packages: 0
Dependent Repositories: 1

Rankings

Dependent repos count: 24.4%

Stargazers count: 34.4%

Average: 38.1%

Forks count: 41.8%

Dependent packages count: 51.6%

Last synced: 6 months ago

Dependencies

DESCRIPTION cran

R >= 3.5.0 depends
digest >= 0.6.25 imports
dplyr >= 1.0.0 imports
fs >= 1.4.2 imports
rlang >= 0.4.7 imports
targets >= 0.11.0 imports
tibble >= 3.0.1 imports
tidyselect >= 1.1.0 imports
utils * imports
vctrs >= 0.3.4 imports
withr >= 2.1.2 imports
curl >= 4.3 suggests
knitr >= 1.28 suggests
quarto >= 1.0 suggests
rmarkdown >= 2.1 suggests
testthat >= 3.0.0 suggests
xml2 >= 1.3.2 suggests

.github/workflows/check.yaml actions

actions/checkout v3 composite
quarto-dev/quarto-actions/setup v2 composite
r-lib/actions/check-r-package v2 composite
r-lib/actions/setup-pandoc v2 composite
r-lib/actions/setup-r v2 composite
r-lib/actions/setup-r-dependencies v2 composite

.github/workflows/cover.yaml actions

actions/checkout v3 composite
quarto-dev/quarto-actions/setup v2 composite
r-lib/actions/setup-r v2 composite
r-lib/actions/setup-r-dependencies v2 composite

.github/workflows/lint.yaml actions

actions/checkout v3 composite
r-lib/actions/setup-r v2 composite
r-lib/actions/setup-r-dependencies v2 composite

tarchetypes

Science Score: 36.0%

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README.Rmd

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cran.r-project.org: tarchetypes

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conda-forge.org: r-tarchetypes

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