circleci

作者: astronomer

在撰寫、編輯或審查Astronomer APC儲存庫的CircleCI設定時使用。涵蓋腳本組織、內聯與外部腳本,以及…

npx skills add https://github.com/astronomer/astronomer --skill circleci

CircleCI Configuration Guide

Critical Rules

  1. No long inline scripts — script logic for any language must not be written inline in .circleci/config.yml if the script has complicated flow control. Complicated scripts belong in bin/.
  2. Scripts live in bin/ — every script called from CircleCI must exist as a file in the bin/ directory with an appropriate extension (e.g. bin/my-script.sh, bin/my-script.py).
  3. Pin all versions — never use latest or unpinned tags for Docker images or installed tools. Always specify an exact version to prevent supply chain vulnerabilities and ensure reproducible builds.

Script Organization

Scripts invoked by CircleCI jobs must be committed to the repository under bin/ so they can be:

  • Linted and reviewed like any other source file
  • Tested and run locally without needing CI
  • Reused across multiple jobs or workflows
# ✅ CORRECT — call a script from bin/
steps:
  - run:
      name: Build Helm chart
      command: bin/build-helm-chart.sh
# ❌ WRONG — inline shell logic in the CircleCI config
steps:
  - run:
      name: Build Helm chart
      command: |
        helm package .
        mv astronomer-*.tgz /tmp/chart/

Config Generation Pipeline

.circleci/config.yml is never edited directly. It is a generated file produced by rendering the Jinja2 template .circleci/config.yml.j2 via bin/generate_circleci_config.py:

# Regenerate config.yml from the template
uv run bin/generate_circleci_config.py

The generator injects a small set of computed variables (e.g. ci_runner_version, kube_versions, machine_image_version, docker_images) into the template at render time. Always edit .circleci/config.yml.j2, then regenerate.


Version Pinning

Always pin exact versions for Docker images and any tools installed during a job. Using latest or loose tags introduces supply chain risk and makes builds non-reproducible.

All pinned versions must be declared as Jinja2 variables at the top of .circleci/config.yml.j2, not scattered inline throughout the file. This makes them easy to audit and update in one place. All version declarations must include a link to where the list of released versions can be found, so that updating them is straightforward and doesn't require searching online to find more recent releases.

{# ✅ CORRECT — versions declared at top of config.yml.j2 #}
{#- https://circleci.com/docs/guides/execution-managed/building-docker-images/#docker-version -#}
{%- set circleci_docker_version = 'docker23' -%}

{#- https://circleci.com/developer/machine/image/ubuntu-2404 -#}
{%- set machine_image_version = 'ubuntu-2404:2025.09.1' -%}
# Then referenced inline:
docker:
  - image: cimg/python:{{ python_image_version }}
# ❌ WRONG — version hardcoded inline, not declared at top
docker:
  - image: cimg/python:3.8.1
# ❌ WRONG — unpinned image
docker:
  - image: cimg/python:latest
# ✅ CORRECT — pinned tool version installed in a step
- run:
    name: Install helm
    command: bin/install-ci-tools.py 3.17.2

# ❌ WRONG — unversioned tool install
- run:
    name: Install helm
    command: curl https://raw.githubusercontent.com/helm/helm/main/scripts/get-helm-3 | bash

來自 astronomer 的更多技能

airflow
astronomer
查詢、管理及疑難排解 Apache Airflow 的 DAG、執行、任務與系統設定。支援 30 多種指令,涵蓋 DAG 檢查、執行管理、任務日誌、設定查詢及直接 REST API 存取。可管理多個 Airflow 實例並保留設定;自動探索本機與 Astro 部署。同步(等待完成)或非同步觸發 DAG 執行、診斷失敗、清除執行以重試,並透過重試/映射索引篩選存取任務日誌。輸出...
official
airflow-hitl
astronomer
使用可延遲運算子,在 Airflow DAG 中實現人工審批關卡、表單輸入與分支流程。包含四種運算子類型:ApprovalOperator 用於核准/拒絕決策、HITLOperator 用於多選項表單選擇、HITLBranchOperator 用於人工驅動的任務路由,以及 HITLEntryOperator 用於表單資料收集。所有運算子皆為可延遲,在等待人工回應時釋放工作槽位,可透過 Airflow UI 的「必要操作」標籤或 REST API 進行回應。支援選用功能,包括自訂...
official
airflow-state-store
astronomer
Persists task and asset state across retries and DAG runs using Airflow 3.3's AIP-103 key/value stores (`task_state_store`, `asset_state_store`) and the…
official
analyzing-data
astronomer
查詢您的資料倉儲,利用快取的模式與概念映射來回答商業問題。支援針對重複問題類型的模式查詢與快取,並記錄結果以改善未來查詢。包含概念到表格的映射快取,以及透過INFORMATION_SCHEMA或程式碼庫grep進行的表格結構探索。提供run_sql()與run_sql_pandas()核心函式,回傳Polars或Pandas DataFrame供分析使用。CLI指令可管理概念、模式與表格快取,以及...
official
annotating-task-lineage
astronomer
使用 inlets 和 outlets 為 Airflow 任務標註資料血緣。支援 OpenLineage Dataset 物件、Airflow Assets 與 Airflow Datasets,用於定義跨資料庫、資料倉儲及雲端儲存的輸入與輸出。當運算子缺乏內建 OpenLineage 提取器時,可作為備用方案;遵循四層優先級系統,其中自訂提取器與 OpenLineage 方法具有優先權。包含針對 Snowflake、BigQuery、S3 及 PostgreSQL 的資料集命名輔助工具,以確保一致性...
official
authoring-dags
astronomer
建立Apache Airflow DAG的引導式工作流程,包含驗證與測試整合。結構化六階段方法:探索環境與現有模式、規劃DAG結構、遵循最佳實踐進行實作、使用af CLI指令驗證、經使用者同意後測試,以及根據修正反覆迭代。用於探索的CLI指令(af config connections、af config providers、af dags list)與驗證指令(af dags errors、af dags get、af dags explore)可提供DAG的即時回饋。
official
authoring-go-sdk-tasks
astronomer
Writes Airflow task logic in Go using the Airflow Go SDK. Use when the user wants to implement Airflow tasks in Go, asks about `BundleProvider`/`RegisterDags`,…
official
authoring-java-sdk-tasks
astronomer
使用 Airflow Java SDK 以 Java、Kotlin 或任何 JVM 語言編寫 Airflow 任務邏輯。當使用者想要以 Java/JVM 實作 Airflow 任務時使用,詢問…
official