README.md
In openpharma/GithubMetrics: Quickly Get Key Metrics on Github Repositories
GithubMetrics
It's now recomended to use this package instead: https://github.com/r-world-devs/GitStats
The aim of this package is to provide a wrapper on gh to quickly get
you key Github repo information you need.The code here is used within
Roche to quickly let me pull answer simple questions like:
- How many studies have more than 1 data scientist (and roughly what’s
the commit split)
- What are the common languages being used (proxied through file type
distribution within repos)
- Pull commit metadata to enrich other study info held in other
systems
Installation
You can install the released version of GithubMetrics from
CRAN with:
install.packages("GithubMetrics")
Setup
library(GithubMetrics)
library(tidyverse)
library(glue)
organisation <- "openpharma"
Repos in an org
Pull all the repos present within an org (that I can see).
repos_raw <- gh_repos_get(
org = organisation
)
repos_clean <- gh_repos_clean(repos_raw)
glimpse(repos_clean)
#> Rows: 14
#> Columns: 7
#> $ name <chr> "BBS-causality-training", "GithubMetrics", "facetsr", …
#> $ full_name <chr> "openpharma/BBS-causality-training", "openpharma/Githu…
#> $ size <int> 27, 118, 2163, 5435, 87, 939, 1817, 79487, 329, 0, 482…
#> $ updated_at <chr> "2021-01-29T18:01:35Z", "2021-02-03T07:07:43Z", "2020-…
#> $ default_branch <chr> "main", "master", "master", "master", "master", "maste…
#> $ language <chr> "R", "R", "R", "Unsure", "Python", "R", "C", "R", "R",…
#> $ MB <dbl> 0.0, 0.1, 2.1, 5.3, 0.1, 0.9, 1.8, 77.6, 0.3, 0.0, 0.5…
Realistically, research code is likely to be on Github Enterprise, so
the .api_url and .token parameters can be passed through to gh().
Commented code below shows how you can use an on-premise Github server.
# repos_raw <- gh_repos_get(
# org = organisation,
# .api_url = "https://github.roche.com/api/v3",
# .token = Sys.getenv("GITHUB_PAT_ROCHE")
# )
Commits
Get every commit for all the repos in this organisation.
repo_all_commits <- gh_commits_get(
repos_clean %>% filter(size > 0) %>% pull(full_name),
days_back = 365*10
)
glimpse(repo_all_commits)
#> Rows: 1,762
#> Columns: 5
#> $ full_name <chr> "openpharma/BBS-causality-training", "openpharma/BBS-c…
#> $ author <chr> "heinzmann537", "heinzmann537", "heinzmann537", "epiji…
#> $ datetime <chr> "2021-01-29T18:00:10Z", "2021-01-29T12:55:54Z", "2021-…
#> $ sha <chr> "5ac98df2a99db3b50abae114e37c00e433903094", "059569252…
#> $ commit_message <chr> "Update variable naming ADALM", "Small change", "First…
People
Pull all the people that have committed in r.
contributors <- repo_all_commits %>%
group_by(author) %>%
summarise(
commits = n()
) %>%
filter(!author %in% c(".gitconfig missing email","actions-user"))
contributors <- contributors %>%
left_join(
gh_user_get(contributors$author),
by = c("author"="username")
)
contributors %>%
arrange(-commits) %>%
mutate(
last_active = Sys.Date() - last_active,
contributor = glue('<img src="{avatar}" alt="" height="30"> {author}'),
blog = case_when(
blog == "" ~ "",
TRUE ~ as.character(glue('<a href="{blog}">link</a>'))
)
) %>%
select(contributor,commits,name,last_active,company,location,blog) %>%
knitr::kable(
)
| contributor | commits | name | last_active | company | location | blog |
| :--------------------------------------------------------------------------------------------------- | ------: | :------------------ | :----------- | :--------------------------------- | :---------------------- | :------------------------------------------------------- |
| 
evanmiller | 936 | Evan Miller | 17 days | NA | Chicago, IL | link |
| 
SHAESEN2 | 127 | Steven Haesendonckx | 20 days | NA | NA | |
| 
diego-s | 122 | Diego S | 255 days | NA | NA | |
| 
bailliem | 109 | Mark Baillie | 0 days | NA | Basel, CH | link |
| 
epijim | 89 | James Black | 5 days | Roche | Basel, Switzerland | link |
| 
jaredhobbs | 70 | Jared Hobbs | 89 days | YearEnd, Inc. | Salt Lake City, UT | link |
| 
kalimu | 42 | Kamil Wais | 9 days | 7N / Roche | Rzeszów | link |
| 
Jonnie-Bevan | 28 | NA | 63 days | NA | NA | |
| 
cschaerfe | 21 | Charlotta | 118 days | NA | NA | |
| 
davidanthoff | 12 | David Anthoff | 1 days | University of California, Berkeley | Berkeley, CA | link |
| 
jar1karp | 12 | Jari Karppinen | 154 days | NA | NA | link |
| 
mikmart | 12 | Mikko Marttila | 2 days | NA | NA | link |
| 
reikoch | 8 | NA | 6 days | NA | NA | |
| 
afeld | 6 | Aidan Feldman | 0 days | @GSA and personal projects | Brooklyn, NY | link |
| 
erblast | 6 | Björn Oettinghaus | 22 days | NA | Switzerland | link |
| 
lionel- | 6 | Lionel Henry | 70 days | @rstudio | NA | |
| 
bpfoley | 5 | Brian Foley | 94 days | NA | Seattle, Washington | |
| 
rebecca-albrecht | 4 | NA | 5 days | NA | NA | |
| 
dazim | 3 | Tim Treis | 23 days | NA | Heidelberg, Germany | |
| 
heinzmann537 | 3 | NA | 5 days | NA | NA | |
| 
kentm4 | 3 | Matt Kent | 2 days | Genesis Research | NA | |
| 
PaulJordan57 | 3 | NA | 19 days | NA | NA | |
| 
galachad | 2 | Adam Foryś | 20 days | @Roche | Warsaw, Poland | link |
| 
gerph | 2 | Charles Ferguson | 8 days | NA | NA | |
| 
hadley | 2 | Hadley Wickham | 0 days | @rstudio | Houston, TX | link |
| 
kawap | 2 | NA | 289 days | Roche / 7N | NA | |
| 
kleschenko | 2 | Kostya Leschenko | 5 days | @datarobot | Lviv, Ukraine | |
| 
kshedden | 2 | Kerby Shedden | 1 days | NA | NA | |
| 
kurt-vd | 2 | Kurt Van Dijck | 63 days | NA | NA | |
| 
mrocklin | 2 | Matthew Rocklin | 2 days | @coiled | San Juan Capistrano, CA | link |
| 
thomas-neitmann | 2 | Thomas Neitmann | 1 days | Roche | Basel, Switzerland | link |
| 
waddella | 2 | Adrian Waddell | 27 days | NA | NA | link |
| 
ararslan | 1 | Alex Arslan | 0 days | Beacon Biosignals | Seattle, WA | |
| 
ginberg | 1 | NA | 14 days | NA | Remote | link |
| 
ivarref | 1 | Ivar Refsdal | 13 days | NA | Bergen, Norway | |
| 
jonathon-love | 1 | Jonathon Love | 1 days | NA | NA | link |
| 
Karissa | 1 | NA | 363 days | NA | NA | |
| 
thanos-siadimas | 1 | NA | 1 days | NA | NA | |
Files
Pull a specific file using gh_file_get().
desc_formatted <- gh_file_get(
repo = "GithubMetrics",
org = "OpenPharma",
file = "DESCRIPTION"
) %>%
# format the description
desc::desc(text = .)
# Print it
desc_formatted$get(c("Package","Title","Version")) %>%
tibble::enframe() %>%
knitr::kable()
| name | value |
| :------ | :--------------------------------------------- |
| Package | GithubMetrics |
| Title | Quickly get key metrics on Github repositaries |
| Version | 0.1.0 |
Get all of the files present in the last commit of all the repos using
gh_repo_files_get().
repo_files <- gh_repo_files_get(
repo_commits = repo_all_commits,
only_last_commit = TRUE
)
#> Pulling files in latest commit from 13 repos
glimpse(repo_files)
#> Rows: 1,311
#> Columns: 6
#> $ repo <chr> "openpharma/visR-docs", "openpharma/visR-docs", "openpharm…
#> $ file <chr> "readme.md", "docs", "docs/404.html", "docs/code_of_conduc…
#> $ sha_repo <chr> "5b35fdbc39b87a154c9426e363c8f5a2c83d66b0", "5b35fdbc39b87…
#> $ sha_commit <chr> "642856728e165746076a17c6522b9264f693f37d", "642856728e165…
#> $ extension <chr> "md", "docs", "html", "html", "html", "html", "png", "png"…
#> $ lang <chr> "Markdown", NA, "HTML", "HTML", "HTML", "HTML", NA, NA, NA…
repo_files %>%
group_by(repo) %>%
summarise(
Files = n(),
`R files` = sum(lang %in% "R"),
`Python files` = sum(lang %in% c("Python","Jupyter Notebook"))
) %>% knitr::kable(
caption = "Types of files in the organisation"
)
| repo | Files | R files | Python files |
| :-------------------------------- | ----: | ------: | -----------: |
| openpharma/BBS-causality-training | 4 | 2 | 0 |
| openpharma/CTP | 100 | 30 | 0 |
| openpharma/facetsr | 63 | 13 | 0 |
| openpharma/GithubMetrics | 43 | 22 | 0 |
| openpharma/openpharma.github.io | 76 | 1 | 0 |
| openpharma/pypharma_nlp | 131 | 0 | 49 |
| openpharma/RDO | 105 | 11 | 0 |
| openpharma/ReadStat | 207 | 0 | 0 |
| openpharma/sas7bdat | 8 | 0 | 2 |
| openpharma/simaerep | 145 | 32 | 0 |
| openpharma/syntrial | 67 | 24 | 0 |
| openpharma/visR | 177 | 81 | 0 |
| openpharma/visR-docs | 185 | 0 | 0 |
Types of files in the organisation
results <- gh_repo_search(
code = "tidyverse",
organisation = organisation
)
glimpse(results)
#> Rows: 12
#> Columns: 7
#> $ full_name <chr> "openpharma/GithubMetrics", "openpharma/GithubMetrics", "op…
#> $ name <chr> "GithubMetrics", "GithubMetrics", "GithubMetrics", "GithubM…
#> $ file_name <chr> "README.md", "README.Rmd", "DESCRIPTION", "test-gh_repos_XX…
#> $ path <chr> "README.md", "README.Rmd", "DESCRIPTION", "tests/testthat/t…
#> $ url <chr> "https://github.com/openpharma/GithubMetrics/blob/fa7764869…
#> $ score <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1
#> $ lang <chr> "Markdown", "R", NA, "R", "Markdown", "R", "Markdown", "R",…
helper_gh_repo_search <- function(x, org = "openpharma"){
## Slow it down! as search has 30 calls a minute rate limit.
## If you prem the search rate limit is higher, so usually not needed
if(interactive()){message("Wait 5 seconds")}
Sys.sleep(5)
## End slow down
results <- gh_repo_search(
code = x,
organisation = org
)
if(is.na(results)) {
results <- return()
}
results %>%
mutate(Package = x, Organisation = org) %>%
group_by(Organisation,Package) %>%
summarise(
Repos = n_distinct(full_name), .groups = "drop"
)
}
packages <- c(
"tidyverse","pkgdown","dplyr","data.table"
)
package_use <- bind_rows(
packages %>%
map_df(
helper_gh_repo_search, org = "PHCAnalytics"
),
packages %>%
map_df(
helper_gh_repo_search, org = "openpharma"
),
packages %>%
map_df(
helper_gh_repo_search, org = "AstraZeneca"
),
packages %>%
map_df(
helper_gh_repo_search, org = "Roche"
),
packages %>%
map_df(
helper_gh_repo_search, org = "Genentech"
),
packages %>%
map_df(
helper_gh_repo_search, org = "Novartis"
)
)
#> pkgdown does not appear in PHCAnalytics.
#> query = 'pkgdown in:file user:PHCAnalytics'
#> tidyverse does not appear in AstraZeneca.
#> query = 'tidyverse in:file user:AstraZeneca'
#> pkgdown does not appear in AstraZeneca.
#> query = 'pkgdown in:file user:AstraZeneca'
#> data.table does not appear in AstraZeneca.
#> query = 'data.table in:file user:AstraZeneca'
package_use %>%
pivot_wider(names_from = "Package", values_from = "Repos") %>%
mutate(Total = rowSums(.[,-1], na.rm = TRUE)) %>%
arrange(-Total) %>%
knitr::kable(
caption = "Package use detected within repositaries in Pharma orgs"
)
| Organisation | tidyverse | dplyr | data.table | pkgdown | Total |
| :----------- | --------: | ----: | ---------: | ------: | ----: |
| Novartis | 4 | 10 | 12 | 6 | 32 |
| openpharma | 4 | 6 | 2 | 6 | 18 |
| Roche | 3 | 2 | 3 | 3 | 11 |
| Genentech | 3 | 3 | 3 | 2 | 11 |
| PHCAnalytics | 2 | 4 | 4 | NA | 10 |
| AstraZeneca | NA | 1 | NA | NA | 1 |
Package use detected within repositaries in Pharma orgs
openpharma/GithubMetrics documentation built on Dec. 1, 2023, 12:52 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
GithubMetrics
It's now recomended to use this package instead: https://github.com/r-world-devs/GitStats
The aim of this package is to provide a wrapper on gh to quickly get
you key Github repo information you need.The code here is used within
Roche to quickly let me pull answer simple questions like:
- How many studies have more than 1 data scientist (and roughly what’s the commit split)
- What are the common languages being used (proxied through file type distribution within repos)
- Pull commit metadata to enrich other study info held in other systems
Installation
You can install the released version of GithubMetrics from CRAN with:
install.packages("GithubMetrics")
Setup
library(GithubMetrics)
library(tidyverse)
library(glue)
organisation <- "openpharma"
Repos in an org
Pull all the repos present within an org (that I can see).
repos_raw <- gh_repos_get(
org = organisation
)
repos_clean <- gh_repos_clean(repos_raw)
glimpse(repos_clean)
#> Rows: 14
#> Columns: 7
#> $ name <chr> "BBS-causality-training", "GithubMetrics", "facetsr", …
#> $ full_name <chr> "openpharma/BBS-causality-training", "openpharma/Githu…
#> $ size <int> 27, 118, 2163, 5435, 87, 939, 1817, 79487, 329, 0, 482…
#> $ updated_at <chr> "2021-01-29T18:01:35Z", "2021-02-03T07:07:43Z", "2020-…
#> $ default_branch <chr> "main", "master", "master", "master", "master", "maste…
#> $ language <chr> "R", "R", "R", "Unsure", "Python", "R", "C", "R", "R",…
#> $ MB <dbl> 0.0, 0.1, 2.1, 5.3, 0.1, 0.9, 1.8, 77.6, 0.3, 0.0, 0.5…
Realistically, research code is likely to be on Github Enterprise, so
the .api_url and .token parameters can be passed through to gh().
Commented code below shows how you can use an on-premise Github server.
# repos_raw <- gh_repos_get(
# org = organisation,
# .api_url = "https://github.roche.com/api/v3",
# .token = Sys.getenv("GITHUB_PAT_ROCHE")
# )
Commits
Get every commit for all the repos in this organisation.
repo_all_commits <- gh_commits_get(
repos_clean %>% filter(size > 0) %>% pull(full_name),
days_back = 365*10
)
glimpse(repo_all_commits)
#> Rows: 1,762
#> Columns: 5
#> $ full_name <chr> "openpharma/BBS-causality-training", "openpharma/BBS-c…
#> $ author <chr> "heinzmann537", "heinzmann537", "heinzmann537", "epiji…
#> $ datetime <chr> "2021-01-29T18:00:10Z", "2021-01-29T12:55:54Z", "2021-…
#> $ sha <chr> "5ac98df2a99db3b50abae114e37c00e433903094", "059569252…
#> $ commit_message <chr> "Update variable naming ADALM", "Small change", "First…
People
Pull all the people that have committed in r.
contributors <- repo_all_commits %>%
group_by(author) %>%
summarise(
commits = n()
) %>%
filter(!author %in% c(".gitconfig missing email","actions-user"))
contributors <- contributors %>%
left_join(
gh_user_get(contributors$author),
by = c("author"="username")
)
contributors %>%
arrange(-commits) %>%
mutate(
last_active = Sys.Date() - last_active,
contributor = glue('<img src="{avatar}" alt="" height="30"> {author}'),
blog = case_when(
blog == "" ~ "",
TRUE ~ as.character(glue('<a href="{blog}">link</a>'))
)
) %>%
select(contributor,commits,name,last_active,company,location,blog) %>%
knitr::kable(
)
| contributor | commits | name | last_active | company | location | blog |
| :--------------------------------------------------------------------------------------------------- | ------: | :------------------ | :----------- | :--------------------------------- | :---------------------- | :------------------------------------------------------- |
|
Files
Pull a specific file using gh_file_get().
desc_formatted <- gh_file_get(
repo = "GithubMetrics",
org = "OpenPharma",
file = "DESCRIPTION"
) %>%
# format the description
desc::desc(text = .)
# Print it
desc_formatted$get(c("Package","Title","Version")) %>%
tibble::enframe() %>%
knitr::kable()
| name | value | | :------ | :--------------------------------------------- | | Package | GithubMetrics | | Title | Quickly get key metrics on Github repositaries | | Version | 0.1.0 |
Get all of the files present in the last commit of all the repos using
gh_repo_files_get().
repo_files <- gh_repo_files_get(
repo_commits = repo_all_commits,
only_last_commit = TRUE
)
#> Pulling files in latest commit from 13 repos
glimpse(repo_files)
#> Rows: 1,311
#> Columns: 6
#> $ repo <chr> "openpharma/visR-docs", "openpharma/visR-docs", "openpharm…
#> $ file <chr> "readme.md", "docs", "docs/404.html", "docs/code_of_conduc…
#> $ sha_repo <chr> "5b35fdbc39b87a154c9426e363c8f5a2c83d66b0", "5b35fdbc39b87…
#> $ sha_commit <chr> "642856728e165746076a17c6522b9264f693f37d", "642856728e165…
#> $ extension <chr> "md", "docs", "html", "html", "html", "html", "png", "png"…
#> $ lang <chr> "Markdown", NA, "HTML", "HTML", "HTML", "HTML", NA, NA, NA…
repo_files %>%
group_by(repo) %>%
summarise(
Files = n(),
`R files` = sum(lang %in% "R"),
`Python files` = sum(lang %in% c("Python","Jupyter Notebook"))
) %>% knitr::kable(
caption = "Types of files in the organisation"
)
| repo | Files | R files | Python files | | :-------------------------------- | ----: | ------: | -----------: | | openpharma/BBS-causality-training | 4 | 2 | 0 | | openpharma/CTP | 100 | 30 | 0 | | openpharma/facetsr | 63 | 13 | 0 | | openpharma/GithubMetrics | 43 | 22 | 0 | | openpharma/openpharma.github.io | 76 | 1 | 0 | | openpharma/pypharma_nlp | 131 | 0 | 49 | | openpharma/RDO | 105 | 11 | 0 | | openpharma/ReadStat | 207 | 0 | 0 | | openpharma/sas7bdat | 8 | 0 | 2 | | openpharma/simaerep | 145 | 32 | 0 | | openpharma/syntrial | 67 | 24 | 0 | | openpharma/visR | 177 | 81 | 0 | | openpharma/visR-docs | 185 | 0 | 0 |
Types of files in the organisation
results <- gh_repo_search(
code = "tidyverse",
organisation = organisation
)
glimpse(results)
#> Rows: 12
#> Columns: 7
#> $ full_name <chr> "openpharma/GithubMetrics", "openpharma/GithubMetrics", "op…
#> $ name <chr> "GithubMetrics", "GithubMetrics", "GithubMetrics", "GithubM…
#> $ file_name <chr> "README.md", "README.Rmd", "DESCRIPTION", "test-gh_repos_XX…
#> $ path <chr> "README.md", "README.Rmd", "DESCRIPTION", "tests/testthat/t…
#> $ url <chr> "https://github.com/openpharma/GithubMetrics/blob/fa7764869…
#> $ score <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1
#> $ lang <chr> "Markdown", "R", NA, "R", "Markdown", "R", "Markdown", "R",…
helper_gh_repo_search <- function(x, org = "openpharma"){
## Slow it down! as search has 30 calls a minute rate limit.
## If you prem the search rate limit is higher, so usually not needed
if(interactive()){message("Wait 5 seconds")}
Sys.sleep(5)
## End slow down
results <- gh_repo_search(
code = x,
organisation = org
)
if(is.na(results)) {
results <- return()
}
results %>%
mutate(Package = x, Organisation = org) %>%
group_by(Organisation,Package) %>%
summarise(
Repos = n_distinct(full_name), .groups = "drop"
)
}
packages <- c(
"tidyverse","pkgdown","dplyr","data.table"
)
package_use <- bind_rows(
packages %>%
map_df(
helper_gh_repo_search, org = "PHCAnalytics"
),
packages %>%
map_df(
helper_gh_repo_search, org = "openpharma"
),
packages %>%
map_df(
helper_gh_repo_search, org = "AstraZeneca"
),
packages %>%
map_df(
helper_gh_repo_search, org = "Roche"
),
packages %>%
map_df(
helper_gh_repo_search, org = "Genentech"
),
packages %>%
map_df(
helper_gh_repo_search, org = "Novartis"
)
)
#> pkgdown does not appear in PHCAnalytics.
#> query = 'pkgdown in:file user:PHCAnalytics'
#> tidyverse does not appear in AstraZeneca.
#> query = 'tidyverse in:file user:AstraZeneca'
#> pkgdown does not appear in AstraZeneca.
#> query = 'pkgdown in:file user:AstraZeneca'
#> data.table does not appear in AstraZeneca.
#> query = 'data.table in:file user:AstraZeneca'
package_use %>%
pivot_wider(names_from = "Package", values_from = "Repos") %>%
mutate(Total = rowSums(.[,-1], na.rm = TRUE)) %>%
arrange(-Total) %>%
knitr::kable(
caption = "Package use detected within repositaries in Pharma orgs"
)
| Organisation | tidyverse | dplyr | data.table | pkgdown | Total | | :----------- | --------: | ----: | ---------: | ------: | ----: | | Novartis | 4 | 10 | 12 | 6 | 32 | | openpharma | 4 | 6 | 2 | 6 | 18 | | Roche | 3 | 2 | 3 | 3 | 11 | | Genentech | 3 | 3 | 3 | 2 | 11 | | PHCAnalytics | 2 | 4 | 4 | NA | 10 | | AstraZeneca | NA | 1 | NA | NA | 1 |
Package use detected within repositaries in Pharma orgs
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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