Viewing Runtime Caches

Problem

You want to enumerate a list of content runtime caches created by Connect. For more information, see the Runtime Caches section of the Admin Guide.

Solution

Python

Call Connect’s API using the SDK. The API returns a JSON response that can be easily transformed into a DataFrame.

from posit import connect
imports polars as pl

client = connect.Client()

response = client.get("/v1/system/caches/runtime")
caches_df = pl.DataFrame(response.json()["caches"])

The data includes information on the language and version of the cache. For Connect servers using off-host execution, the image_name column includes the name of the execution image. The name Local indicates that the cache is for local execution mode.

>>> import polars as pl
>>> pl.DataFrame(caches_df)
shape: (23, 3)
┌──────────┬─────────┬────────────┐
│ language ┆ version ┆ image_name │
│ ---      ┆ ---     ┆ ---        │
│ str      ┆ str     ┆ str        │
╞══════════╪═════════╪════════════╡
│ R        ┆ 3.0.2   ┆ Local      │
│ R        ┆ 3.1.0   ┆ Local      │
│ R        ┆ 3.1.2   ┆ Local      │
│ R        ┆ 3.1.3   ┆ Local      │
│ R        ┆ 3.2.0   ┆ Local      │
│ …        ┆ …       ┆ …          │
│ Python   ┆ 3.10.10 ┆ Local      │
│ Python   ┆ 3.11.3  ┆ Local      │
│ Python   ┆ 3.7.6   ┆ Local      │
│ Python   ┆ 3.8.1   ┆ Local      │
│ Python   ┆ 3.9.7   ┆ Local      │
└──────────┴─────────┴────────────┘

R

Call Connect’s runtime caches API using connectapi and transform the response into a data frame.

library(connectapi)
library(purrr)

client <- connect()

response <- client$GET("/v1/system/caches/runtime")
caches_df <- map_dfr(response$caches, ~.x)

The data includes information on the language and version of the cache. For Connect servers using off-host execution, the image_name column includes the name of the execution image. The name Local indicates that the cache is for local execution mode.

> caches_df
# A tibble: 23 × 3
   language version image_name
   <chr>    <chr>   <chr>
 1 R        3.0.2   Local
 2 R        3.1.0   Local
 3 R        3.1.2   Local
 4 R        3.1.3   Local
 5 R        3.2.0   Local
 6 R        3.2.1   Local
 7 R        3.2.2   Local
 8 R        3.3.3   Local
 9 R        3.4.0   Local
10 R        3.4.4   Local
# ℹ 13 more rows
# ℹ Use `print(n = ...)` to see more rows