run2_scala-circe-json
Using circe for JSON tokenization in Scala, including printing, cursor navigation, and path-based access.
- License 许可
- MIT
- 最近更新
- 2026-10-02
- Stars
- ★ 93
- Forks
- 8
01 前言 Front Matter
- name
- run2_scala-circe-json
- description
- Using circe for JSON tokenization in Scala, including printing, cursor navigation, and path-based access.
03 SKILL.md 正文
Circe JSON for Tokenization
Printing
import io.circe.{Json, Printer}
val compact = Printer.noSpaces.print(json)
val pretty = Printer.spaces2.print(json)
Path-Based Navigation with ACursor
import io.circe.ACursor
def navigate(json: Json, path: String): Option[Json] = {
val cursor = path.split("\\.").foldLeft(json.hcursor: ACursor) { (c, part) =>
if (part.forall(_.isDigit)) c.downN(part.toInt)
else c.downField(part)
}
cursor.focus
}
Key Differences from Python json module
- circe uses
JsonADT instead of Python's dynamic types - No need for recursive
JsonValuetype alias -Jsonis already recursive - Printing via
Printerinstances rather thanjson.dumpskwargs
04 同仓库更多 Skills
object_counter
Count occurrences of an object in the image using computer vision algorithm.
travel-planning-workflow
Invoke this skill when performing travel planning. It defines a structured workflow for generating itineraries. Following this workflow is essential to ensure the final plan satisfies user requirements.
bundled-dataset-search-tool
invoke this skill when you need to perform database search for travel planning. This skill provides some useful pre-packaged tools to look up accommodations, attractions, cities, driving distance, flights, and restaurants from the bundled dataset.
glm-output
Output-processing guidance for GLM tasks. Especially useful after glm-basics and glm-calibration when you need verifier-matching metrics from output.nc and a final /root/metrics.json.
glm-calibration
Calibration guidance for GLM tasks. Often most effective after glm-basics has clarified the setup; glm-output is the companion skill for exact final metric computation.
glm-basics
A good starting point for GLM calibration tasks. Use to inspect glm3.nml, confirm how GLM runs, and identify the relevant files before moving on to calibration and output evaluation.