email.Rmd

---
output: blastula::blastula_email
---

```{r echo=FALSE, warning=FALSE, message=FALSE}
library(glue)
library(lubridate)
library(connectapi)
library(ggplot2)
library(dplyr)
library(janitor)
library(stringr)
library(scales)
library(forcats)

knitr::opts_chunk$set(
  echo=FALSE,
  warning=FALSE,
  message=FALSE
)

colour_mapping_lang <- c(
  "Python" = "#FFD43B",
  "R" = "#276BBE",
  "Quarto" = "#75AADB",
  "Unknown" = "#C4C7C9"
)
colour_mapping_type <- c(
  "Document" = "#447099",
  "Web App" = "#72994E",
  "API" = "#EE6331",
  "Unknown" = "#C4C7C9"
)

client <- connect()
content <- get_content(client)
```

```{r}
content <- content |>
  # Classify content
  mutate(
    language = case_when(
      !is.na(r_version) ~ "R",
      !is.na(py_version) ~ "Python",
      !is.na(quarto_version) ~ "Quarto",
      TRUE ~ "Unknown"
    ),
    app_type = case_when(
      str_ends(app_mode, "static") ~ "Document",
      str_ends(app_mode, "api") ~ "API",
      str_ends(app_mode, "shiny") ~ "Web App",
      str_ends(app_mode, "streamlit") ~ "Web App",
      str_ends(app_mode, "bokeh") ~ "Web App",
      str_ends(app_mode, "dash") ~ "Web App",
      TRUE ~ "Unknown"
    )
  ) |> 
  # Orgnize factors
  mutate(
    language = factor(language, levels = c("Unknown", "QUarto", "Python", "R")),
    app_type = factor(app_type, levels = c("Unknown", "API", "Web App", "Document"))
  )
```

# Connect Content Report for `r today()`

This report includes a summary of all the content that is currently published on Connect. As of today, Connect has **`r comma(nrow(content))`** items deployed:

```{r fig.align='center'}
content |> 
  group_by(language, app_type) |>
  summarise(n = n(), .groups = "drop") |> 
  ggplot(aes(x = app_type, y = n)) +
  geom_col(aes(fill = language)) +
  scale_fill_manual(values = colour_mapping_lang) +
  scale_y_continuous(label=comma) +
  labs(
    title = "Distribution of Content Deployed on Colorado",
    subtitle = "By Langauge and Type",
    x = "Type",
    y = "Count",
    fill = "Language"
  ) +
  coord_flip()
```

```{r fig.align='center'}
content |> 
  tabyl(app_mode) |> 
  arrange(desc(n)) |> 
  mutate(app_mode = fct_reorder(factor(app_mode), n)) |> 
  ggplot(aes(x = app_mode, y = n)) +
  geom_col() +
  geom_label(aes(label = percent(percent, accuracy = 1)), nudge_y = 100) +
  scale_y_continuous(label=comma) +
  labs(
    title = "Distribution of Content Deployed on Colorado",
    subtitle = "By App Mode",
    x = "App Mode",
    y = "Count"
  ) +
  coord_flip()
```

```{r fig.align='center'}
content |> 
  mutate(create_year_month = floor_date(created_time, unit = "month")) |> 
  group_by(language, create_year_month) |> 
  summarise(count = n(), .groups = "drop") |> 
  ggplot(aes(x = create_year_month, y = count)) +
  geom_col(aes(fill = language)) + 
  scale_fill_manual(values = colour_mapping_lang) + 
  scale_y_continuous(label=comma) +
  labs(
    title = "Content Creation Over Time",
    subtitle = "By langauge",
    x = "Month",
    y = "Count",
    fill = "Language"
  )
```

```{r fig.align='center'}
content |> 
  mutate(create_year_month = floor_date(created_time, unit = "month")) |> 
  group_by(app_type, create_year_month) |> 
  summarise(count = n(), .groups = "drop") |> 
  ggplot(aes(x = create_year_month, y = count)) +
  geom_col(aes(fill = app_type)) + 
  scale_fill_manual(values = colour_mapping_type) +
  scale_y_continuous(label=comma) +
  labs(
    title = "Content Creation Over Time",
    subtitle = "By app type",
    x = "Month",
    y = "Count",
    fill = "App Type"
  )
```