Try to use @vuepress/plugin-shiki

.vuepress/config.js

@@ -2,6 +2,7 @@ import path from 'path';
 import { defineUserConfig } from '@vuepress/cli';
 import { gitPlugin } from '@vuepress/plugin-git';
 import { feedPlugin } from 'vuepress-plugin-feed2';
+import { shikiPlugin } from '@vuepress/plugin-shiki';
 import { defaultTheme } from '@vuepress/theme-default';
 import { sitemapPlugin } from 'vuepress-plugin-sitemap2';
 import { docsearchPlugin } from '@vuepress/plugin-docsearch';
@@ -139,6 +140,21 @@ export default defineUserConfig({
  gitPlugin(),
  backToTopPlugin(),
  mediumZoomPlugin(),
+ shikiPlugin({
+ theme: 'dark-plus',
+ langs: [
+ 'nushell',
+ 'rust',
+ 'bash',
+ 'shell',
+ 'sh',
+ 'toml',
+ 'json',
+ 'python',
+ 'cpp',
+ 'powershell',
+ ],
+ }),
  docsearchPlugin({
  appId: 'GHCTOYCW6T',
  indexName: 'nushell',
@@ -162,7 +178,7 @@ export default defineUserConfig({
  : a.frontmatter.date,
  b.data.git?.createdTime
  ? new Date(b.data.git?.createdTime)
- : b.frontmatter.date
+ : b.frontmatter.date,
  );
  },
  }),
@@ -173,7 +189,7 @@ export default defineUserConfig({
  onPrepared: async (app) => {
  await app.writeTemp(
  'pages.js',
- `export default ${JSON.stringify(app.pages.map(({ data }) => data))}`
+ `export default ${JSON.stringify(app.pages.map(({ data }) => data))}`,
  );
  },
 });

README.md

@@ -34,13 +34,13 @@ Nushell is available as [downloadable binaries](https://github.com/nushell/nushe
 
 #### macOS / Linux:
 
-```console
+```shell
 $ brew install nushell
 ```
 
 #### Windows:
 
-```console
+```shell
 $ winget install nushell
 ```
 

book/dataframes.md

@@ -206,7 +206,7 @@ CSV file that will become our sample dataframe that we will be using along with
 the examples. In your favorite file editor paste the next lines to create out
 sample csv file.
 
-```csv
+```
 int_1,int_2,float_1,float_2,first,second,third,word
 1,11,0.1,1.0,a,b,c,first
 2,12,0.2,1.0,a,b,c,second

book/how_nushell_code_gets_run.md

@@ -176,7 +176,7 @@ std::string my_path("foo");
 
 or Rust
 
-```rust!
+```rust
 let my_path = "foo";
 use format!("{}::common", my_path);
 ```

cookbook/polars_v_pandas_v_nushell.md

@@ -8,11 +8,11 @@ A dataframe example based on https://studioterabyte.nl/en/blog/polars-vs-pandas
 
 ## 1. Opening the file and show the shape of the DataFrame
 
-```console
+```shell
 > let df = (dfr open NYCTaxi.csv)
 ```
 
-```console
+```shell
 > $df | shape
 ╭───┬─────────┬─────────╮
 │ # │ rows │ columns │
@@ -25,7 +25,7 @@ A dataframe example based on https://studioterabyte.nl/en/blog/polars-vs-pandas
 
 ## 2. Opening the file and show the first 5 rows
 
-```console
+```shell
 > $df | first 5
 ╭───┬───────────┬───────────┬───────────────┬───────────────┬───────────────┬───────────────┬───────────────┬───────────────┬───────────────┬──────────────┬──────────────╮
 │ # │ id │ vendor_id │ pickup_dateti │ dropoff_datet │ passenger_cou │ pickup_longit │ pickup_latitu │ dropoff_longi │ dropoff_latit │ store_and_fw │ trip_duratio │
@@ -49,7 +49,7 @@ A dataframe example based on https://studioterabyte.nl/en/blog/polars-vs-pandas
 
 ## 3. Opening the file and get the length of all strings in the "id" column
 
-```console
+```shell
 > let ids = ($df | first 5 | get id | str-lengths)
 > $df | first 5 | append $ids | rename id_x vendor_id_length
 ╭───┬───────────┬───────────┬──────────────┬──────────────┬─────────────┬─────────────┬─────────────┬─────────────┬─────────────┬─────────────┬─────────────┬─────────────╮
@@ -71,8 +71,10 @@ A dataframe example based on https://studioterabyte.nl/en/blog/polars-vs-pandas
 │ │ │ │ ime │ time │ ount │ itude │ tude │ gitude │ itude │ wd_flag │ on │ ength │
 ╰───┴───────────┴───────────┴──────────────┴──────────────┴─────────────┴─────────────┴─────────────┴─────────────┴─────────────┴─────────────┴─────────────┴─────────────╯
 ```
+
 Here's an alternate approach using `with-column`
-```console
+
+```shell
 > $df | first 5 | with-column ($df | first 5 | get id | str-lengths) --name vendor_id_length
 ╭───┬───────────┬───────────┬──────────────┬──────────────┬─────────────┬─────────────┬─────────────┬─────────────┬─────────────┬─────────────┬─────────────┬─────────────╮
 │ # │ id │ vendor_id │ pickup_datet │ dropoff_date │ passenger_c │ pickup_long │ pickup_lati │ dropoff_lon │ dropoff_lat │ store_and_f │ trip_durati │ vendor_id_l │
@@ -96,7 +98,7 @@ Here's an alternate approach using `with-column`
 
 ## 4. Opening the file and apply a function to the "trip_duration" to divide the number by 60 to go from the second value to a minute value
 
-```console
+```shell
 > $df | first 5 | with-column ((col trip_duration) / 60.0)
 ╭───┬───────────┬───────────┬───────────────┬───────────────┬───────────────┬───────────────┬───────────────┬───────────────┬───────────────┬──────────────┬──────────────╮
 │ # │ id │ vendor_id │ pickup_dateti │ dropoff_datet │ passenger_cou │ pickup_longit │ pickup_latitu │ dropoff_longi │ dropoff_latit │ store_and_fw │ trip_duratio │
@@ -117,9 +119,10 @@ Here's an alternate approach using `with-column`
 │ │ │ │ me │ ime │ nt │ ude │ de │ tude │ ude │ d_flag │ n │
 ╰───┴───────────┴───────────┴───────────────┴───────────────┴───────────────┴───────────────┴───────────────┴───────────────┴───────────────┴──────────────┴──────────────╯
 ```
+
 ## 5. Opening the file and filtering out all rows with a trip duration shorther than 500 seconds
 
-```console
+```shell
 > $df | filter-with ((col trip_duration) >= 500) | first 5
 ╭───┬───────────┬───────────┬───────────────┬───────────────┬───────────────┬───────────────┬───────────────┬───────────────┬───────────────┬──────────────┬──────────────╮
 │ # │ id │ vendor_id │ pickup_dateti │ dropoff_datet │ passenger_cou │ pickup_longit │ pickup_latitu │ dropoff_longi │ dropoff_latit │ store_and_fw │ trip_duratio │
@@ -140,9 +143,10 @@ Here's an alternate approach using `with-column`
 │ │ │ │ me │ ime │ nt │ ude │ de │ tude │ ude │ d_flag │ n │
 ╰───┴───────────┴───────────┴───────────────┴───────────────┴───────────────┴───────────────┴───────────────┴───────────────┴───────────────┴──────────────┴──────────────╯
 ```
+
 ## 6. Opening the file, filtering out all the rows with a "Y" store_and_fwd_flag value, group by ID and calculate the mean duration time
 
-```console
+```shell
 > $df | filter-with ((col store_and_fwd_flag) == "N") | group-by id | agg (col trip_duration | mean) | sort-by id | first 5
 ╭───┬───────────┬───────────────╮
 │ # │ id │ trip_duration │
@@ -155,4 +159,4 @@ Here's an alternate approach using `with-column`
 ├───┼───────────┼───────────────┤
 │ # │ id │ trip_duration │
 ╰───┴───────────┴───────────────╯
-```
+```

package.json

@@ -17,15 +17,17 @@
  "@vuepress/plugin-docsearch": "2.0.0-beta.67",
  "@vuepress/plugin-git": "2.0.0-beta.67",
  "@vuepress/plugin-medium-zoom": "2.0.0-beta.67",
+ "@vuepress/plugin-shiki": "^2.0.0-beta.67",
  "@vuepress/theme-default": "2.0.0-beta.67",
  "lefthook": "^1.4.10",
  "prettier": "^3.0.3",
+ "shiki": "^0.14.4",
  "vuepress": "2.0.0-beta.67",
  "vuepress-plugin-feed2": "2.0.0-beta.237",
  "vuepress-plugin-sitemap2": "2.0.0-beta.237"
  },
- "engines" : {
- "npm" : ">=9.0.0",
- "node" : ">=18.12.0"
+ "engines": {
+ "npm": ">=9.0.0",
+ "node": ">=18.12.0"
  }
 }

zh-CN/book/dataframes.md

@@ -201,7 +201,7 @@ $res
 
 在看到了可以用`DataFrame`命令完成的事情之后，现在是时候开始测试它们了。首先，让我们创建一个样本 CSV 文件，该文件将成为我们的样本 DataFrame，并与示例一起使用。在你喜欢的编辑器中粘贴下面几行来创建样本 csv 文件：
 
-```csv
+```
 int_1,int_2,float_1,float_2,first,second,third,word
 1,11,0.1,1.0,a,b,c,first
 2,12,0.2,1.0,a,b,c,second