9.6 KiB
9.6 KiB
Analysis of matrix spec bias-rumors
MTRNord
- Fetching the MSCs
- Get Employee association from Github and Gitlab
- Get times for state transitions
- MSCs by Company (all kind)
- Merged MSCs by Company
The following data is based purely on public knowledge. This means data is fetched from github and gitlab as best as I was able to.
Fetching the MSCs
# Setup things
library(gh)
library(tidyverse)
library(ggplot2)
# Set theme
theme_set(theme_bw())
# gh_whoami()
cleanup_data <- function(prs_gql) {
prs_gql <- prs_gql[[1]][[1]][[1]][[2]]
for (i in 1:length(prs_gql)) {
prs_gql[[i]] <- prs_gql[[i]]$node
prs_gql[[i]]$temp_labels <- NA
if (length(prs_gql[[i]]$labels$edges) >= 1) {
prs_gql[[i]]$temp_labels <- list()
for (y in 1:length(prs_gql[[i]]$labels$edges)) {
prs_gql[[i]]$temp_labels[[y]] <- prs_gql[[i]]$labels$edges[[y]]$node
}
prs_gql[[i]]$temp_labels <- map(prs_gql[[i]]$temp_labels, as.data.frame)
prs_gql[[i]]$temp_labels <- do.call(rbind, prs_gql[[i]]$temp_labels)
}
prs_gql[[i]]$labels <- NA
prs_gql[[i]]$labels <- prs_gql[[i]]$temp_labels
prs_gql[[i]]$temp_labels <- NULL
}
prs_gql <- as.data.frame(do.call(rbind, prs_gql))
if (!("mergedAt" %in% colnames(prs_gql))) {
prs_gql$mergedAt <- NA
prs_gql$isPR <- FALSE
} else {
prs_gql$isPR <- TRUE
}
for (i in rownames(prs_gql)) {
author <- prs_gql[i, "author"]
if (!is.null(author)) {
prs_gql[i, "author"] <- do.call(rbind.data.frame, author)
}
}
return(prs_gql)
}
if (!exists("issues_gql_all")) {
issue_query <- 'query($after: String) {
repository(owner: "matrix-org", name: "matrix-spec-proposals") {
issues(
states: [OPEN, CLOSED]
orderBy: {field: CREATED_AT, direction: ASC}
first: 100
after: $after
) {
pageInfo {
startCursor
endCursor
hasNextPage
hasPreviousPage
}
edges {
node {
title
url
author {
login
}
closedAt
createdAt
labels(first: 100) {
pageInfo {
startCursor
endCursor
hasNextPage
hasPreviousPage
}
edges {
node {
name
createdAt
}
}
}
}
}
}
}
}'
pr_query <- 'query($after: String) {
repository(owner: "matrix-org", name: "matrix-spec-proposals") {
pullRequests(
states: [OPEN, CLOSED, MERGED]
orderBy: {field: CREATED_AT, direction: ASC}
first: 100
after: $after
) {
pageInfo {
startCursor
endCursor
hasNextPage
hasPreviousPage
}
edges {
node {
title
url
author {
login
}
closedAt
mergedAt
createdAt
labels(first: 100) {
pageInfo {
startCursor
endCursor
hasNextPage
hasPreviousPage
}
edges {
node {
name
createdAt
}
}
}
}
}
}
}
}'
issues_gql <- gh_gql(issue_query)
issues_gql_pageinfo <- issues_gql[[1]][[1]][[1]][[1]]
issues_gql <- cleanup_data(issues_gql)
gql_data <- list(issues_gql)
# Paginate API
while (issues_gql_pageinfo$hasNextPage) {
variables <- list()
variables$after <- issues_gql_pageinfo$endCursor
issues_gql <- gh_gql(issue_query, variables = variables)
issues_gql_pageinfo <- issues_gql[[1]][[1]][[1]][[1]]
issues_gql <- cleanup_data(issues_gql)
gql_data[[length(gql_data) + 1]] <- issues_gql
}
prs_gql <- gh_gql(pr_query)
prs_gql_pageinfo <- prs_gql[[1]][[1]][[1]][[1]]
prs_gql <- cleanup_data(prs_gql)
gql_data[[length(gql_data) + 1]] <- prs_gql
# Paginate API
while (prs_gql_pageinfo$hasNextPage) {
variables <- list()
variables$after <- prs_gql_pageinfo$endCursor
prs_gql <- gh_gql(pr_query, variables = variables)
prs_gql_pageinfo <- prs_gql[[1]][[1]][[1]][[1]]
prs_gql <- cleanup_data(prs_gql)
gql_data[[length(gql_data) + 1]] <- prs_gql
}
issues_gql_all <- do.call(rbind, gql_data)
# Cleanup
rm(issues_gql, prs_gql, gql_data, variables, issues_gql_pageinfo, prs_gql_pageinfo)
issues_gql_all <- issues_gql_all |>
rowwise()
}
Get Employee association from Github and Gitlab
Please note that in the current PDF this is not yet hooked up to gitlab or checking the github workplace field. It may also exclude some users that are not detectable.
# TODO also check against gitlab
# TODO also check workplace thingy
# Compile a list of who is who
if (!exists("element_employee") || !exists("famedly_employee") || !exists("beeper_employee")) {
element_employee <- list()
sct_employee <- c("ara4n", "erikjohnston", "richvdh", "dbkr", "uhoreg", "anoadragon453", "turt2live", "KitsuneRal", "matrixbot")
famedly_employee <- list("deepbluev7", "Sorunome", "MTRNord")
beeper_employee <- list("Fizzadar")
users <- list()
# Get orgs of users on github
for (i in rownames(issues_gql_all)) {
user <- issues_gql_all[i, "author"]
user <- paste(unlist(user), collapse = "")
if (is.na(user) || is.null(user) || user == "") {
next
}
if ((user %in% users) || (user %in% sct_employee)) {
next
}
orgs_raw <- gh(sprintf("GET /users/%s/orgs", user))
orgs <- as.data.frame(do.call(rbind, orgs_raw))
if ("vector-im" %in% orgs$login) {
element_employee[[length(element_employee) + 1]] <- user
} else if ("beeper" %in% orgs$login) {
beeper_employee[[length(beeper_employee) + 1]] <- user
} else if ("Famedly" %in% orgs$login) {
famedly_employee[[length(famedly_employee) + 1]] <- user
}
users[[length(users) + 1]] <- user
}
rm(orgs, orgs_raw, user, author, i, users)
}
Get times for state transitions
opened_to_proposal <- issues_gql_all
MSCs by Company (all kind)
Note that this does not adjust for private vs company MSCs.
# Filter MSCs by company
mscs_element <- issues_gql_all |>
filter(!is.null(author) && is.element(author, element_employee)) |>
nrow()
mscs_sct <- issues_gql_all |>
filter(!is.null(author) && is.element(author, sct_employee)) |>
nrow()
mscs_famedly <- issues_gql_all |>
filter(!is.null(author) && is.element(author, famedly_employee)) |>
nrow()
mscs_beeper <- issues_gql_all |>
filter(!is.null(author) && is.element(author, beeper_employee)) |>
nrow()
mscs_other <- nrow(issues_gql_all) - mscs_element - mscs_beeper - mscs_famedly - mscs_sct
column_names <- c("Count")
# Display Data
data <- data.frame(column_names = column_names, Element = mscs_element, Beeper = mscs_beeper, Famedly = mscs_famedly, SCT = mscs_sct, Other = mscs_other)
data2 <- data.frame(t(data[-1]))
colnames(data2) <- data[, 1]
data <- data2
data <- cbind(Company = rownames(data), data)
rownames(data) <- 1:nrow(data)
rownames(data) <- NULL
rm(data2)
# Basic piechart
ggplot(data, aes(x = Company, y = Count, fill = Company)) +
geom_bar(stat = "identity") +
labs(
title = str_wrap("Number of MSCs by Contributors associated with companies", 40),
subtitle = str_wrap(
"Note that people may have gotten mixed or people with multiple hats may have MSCs landing in the wrong category",
60
),
caption = "source: Github API"
)
Merged MSCs by Company
Note that this does not adjust for private vs company MSCs.
# Filter for only merged MSCs
merged_mscs <- issues_gql_all |>
filter(!is.na(labels) && is.element("proposal", labels$name) && (is.element("disposition-merge", labels$name) || is.element("merged", labels$name)))
# Filter MSCs by company
merged_element <- merged_mscs |>
filter(!is.null(author) && is.element(author, element_employee)) |>
nrow()
merged_sct <- merged_mscs |>
filter(!is.null(author) && is.element(author, sct_employee)) |>
nrow()
merged_famedly <- merged_mscs |>
filter(!is.null(author) && is.element(author, famedly_employee)) |>
nrow()
merged_beeper <- merged_mscs |>
filter(!is.null(author) && is.element(author, beeper_employee)) |>
nrow()
merged_other <- nrow(merged_mscs) - merged_element - merged_beeper - merged_famedly - merged_sct
# Display Data
column_names <- c("Count")
# Display Data
data <- data.frame(column_names = column_names, Element = merged_element, Beeper = merged_beeper, Famedly = merged_famedly, SCT = merged_sct, Other = merged_other)
data2 <- data.frame(t(data[-1]))
colnames(data2) <- data[, 1]
data <- data2
data <- cbind(Company = rownames(data), data)
rownames(data) <- 1:nrow(data)
rownames(data) <- NULL
rm(data2)
# Basic piechart
ggplot(data, aes(x = Company, y = Count, fill = Company)) +
geom_bar(stat = "identity") +
labs(
title = str_wrap("Number of merged MSCs by Contributors associated with companies", 40),
subtitle = str_wrap(
"Note that people may have gotten mixed or people with multiple hats may have MSCs landing in the wrong category",
60
),
caption = "source: Github API"
)