---
title: "Get popularity metrics from CRAN or Bioconductor package"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Get popularity metrics from CRAN or Bioconductor package}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

knitr::opts_chunk$set(fig.width = 12, fig.height = 5, out.width = "100%" ) 
```

```{r setup, include = FALSE}
library(risk.assessr)
library(ggplot2)
library(dplyr)

suppressMessages({
  library(kableExtra)
  library(knitr)
})

suppressWarnings({
  library(htmltools)
  library(htmlwidgets)
})
```

## CRAN download

```{r cran-data, eval=FALSE}
download_cran_df <- get_package_download_cran("admiral", years = 5)
head(download_cran_df)
```

```{r, echo=FALSE, cran-data-viz, eval=FALSE}
monthly_downloads <- download_cran_df %>%
  mutate(month = format(date, "%Y-%m")) %>%
  group_by(month) %>%
  summarise(
    downloads = sum(count),
    .groups = "drop"
  ) %>%
  mutate(month = as.Date(paste0(month, "-01")))

head(monthly_downloads)
```

```{r, eval=FALSE}
version_infos <- check_and_fetch_cran_package("admiral")
```

```{r, echo=FALSE, eval=FALSE}
version_dates <- bind_rows(lapply(version_infos$all_versions, as.data.frame)) %>%
  mutate(date = as.Date(date))

ggplot(monthly_downloads, aes(x = month, y = downloads)) +
  geom_line(color = "#2C3E50") +
  geom_point(color = "#E74C3C", size = 1) +
  geom_vline(
    data = version_dates,
    aes(xintercept = as.numeric(date)),
    color = "blue",
    linetype = "dashed",
    linewidth = 0.5
  ) +
  labs(
    title = "Monthly Downloads of 'admiral' Package",
    x = "Month",
    y = "Number of Downloads"
  ) +
  theme_minimal(base_size = 14) +
  theme(
    plot.title = element_text(face = "bold", hjust = 0.5, margin = margin(b = 10, t = 20)),
    axis.text.x = element_text(angle = 45, hjust = 1),
    plot.margin = margin(t = 30, r = 20, b = 20, l = 20)
  )
```

## GitHub commit activity

```{r github-meta, eval=FALSE}
repo_info <- get_github_data("tidyverse", "ggplot2")
repo_info
```

```{r github-data, eval=FALSE}
df_commit <- get_commits_since("tidyverse", "ggplot2", years = 1)
head(df_commit)
```

```{r, echo=FALSE, github-data-viz, eval=FALSE}
df_commit <- df_commit %>%
  arrange(week_start) %>%
  mutate(cumulative_commits = cumsum(n_commits))

ggplot(df_commit, aes(x = week_start)) +
  geom_col(aes(y = n_commits), fill = "#1ABC9C") +
  geom_line(aes(y = cumulative_commits), color = "#34495E", linewidth = 1, linetype = "dashed") +
  labs(
    title = "Weekly Commits on GitHub (ggplot2)",
    x = "Week",
    y = "Number of Commits"
  ) +
  theme_minimal(base_size = 14) +
  theme(
    plot.title = element_text(face = "bold", hjust = 0.5),
    axis.text.x = element_text(angle = 45, hjust = 1)
  )
```

## Bioconductor download

```{r}
download_bio_df <- get_package_download_bioconductor("limma")
head(download_bio_df$all_data)
```

```{r, echo=FALSE, message=FALSE, eval=FALSE}
html_content <- fetch_bioconductor_releases()
release_data <- parse_bioconductor_releases(html_content)
info <- get_bioconductor_package_url("limma", release_data = release_data)
```

```{r bioconductor-data, eval=FALSE}
download_bio_df <- get_package_download_bioconductor("DESeq2")
head(download_bio_df$all_data)
```

```{r, echo=FALSE, bioconductor-data-viz, eval=FALSE}
ggplot(download_bio_df$all_data, aes(x = Date, y = Nb_of_downloads)) +
  geom_line(color = "#9B59B6") +
  geom_point(color = "#2980B9") +
  labs(
    title = "Bioconductor Downloads",
    x = "Month",
    y = "Number of Downloads"
  ) +
  theme_minimal(base_size = 14) +
  theme(
    plot.title = element_text(
      face = "bold",
      hjust = 0.5,
      margin = margin(b = 10, t = 20)  
    ),
    plot.margin = margin(t = 30, r = 20, b = 20, l = 20), 
    axis.text.x = element_text(angle = 45, hjust = 1)
  )
```
