affaan-m/ECC

django-celery

Review django-celery's use cases, installation, workflow, and original source instructions.

57Collecting
See source evidenceView GitHub source
npx skills add https://github.com/affaan-m/ECC --skill "docs/ja-JP/skills/django-celery"
Source profileDocumentationCatalog only

Source checked Jul 28, 2026·Refresh due Oct 26, 2026

Limited to facts supported by the pinned source

What the pinned source establishes about django-celery

Django でのバックグラウンドジョブと非同期処理。

npx skills add https://github.com/affaan-m/ECC --skill "docs/ja-JP/skills/django-celery"
Check the pinned source

The pinned source contains about 55 English words and 9 usable sections. That evidence supports a source profile, not a complete guide.

55 source words · 9 usable sections

What the source actually contains

3 verifiable source sections for django-celery

Sections are extracted automatically from the pinned SKILL.md and link back to the source.

01

使用時期

メール送信をバックグラウンドで実行

SKILL.md · 使用時期
メール送信をバックグラウンドで実行重い処理をスケジュール定期的なタスクを実行(日報、クリーンアップ)
02

セットアップ

Review the “セットアップ” section in the pinned source before continuing.

SKILL.md · セットアップ
Review and apply the “セットアップ” source section.
03

1. Celery インストール

Review the “1. Celery インストール” section in the pinned source before continuing.

SKILL.md · 1. Celery インストール
Review and apply the “1. Celery インストール” source section.

Choose a different workflow

When another Skill is the better fit

FAQ

How do I install django-celery?

The source record exposes this install command: npx skills add https://github.com/affaan-m/ECC --skill "docs/ja-JP/skills/django-celery". Inspect the command and pinned source before running it.

Repository stars
234,327
Repository forks
35,711
Quality
57/100
Source repository last pushed

Quality breakdown

Based on traceable docs and repository signals; stars are not treated as quality.

57/100
Documentation18/30
Specificity7/25
Maintenance20/20
Trust signals12/25

Compare before choosing

Related Agent Skills and source variants

These links are selected from shared tasks, functions, stacks, platforms, and same-name variants. Compare the source owner, documentation, permissions, and maintenance signals.

django-celery by affaan-m

Django + Celery async task patterns — configuration, task design, beat scheduling, retries, canvas workflows, monitoring, and testing. Use when adding background jobs, scheduled tasks, or async processing to a Django app.

dask by k-dense-ai

Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.

medchem by k-dense-ai

Medicinal chemistry filters for compound triage. Apply drug-likeness rules (Lipinski, Veber, CNS), structural alert catalogs (PAINS, NIBR, ChEMBL), complexity metrics, and the medchem query language for library filtering.

neurokit2 by k-dense-ai

Use NeuroKit2 to build or audit reproducible research workflows for physiological time-series preprocessing, event/interval analysis, multimodal alignment, variability, and complexity. Trigger when code imports neurokit2 or needs its current APIs, schemas, and method-aware validation—not for diagnosis or device validation.

plan-orchestrate by affaan-m

Read a plan document, decompose it into steps, design a per-step agent chain from the ECC catalogue, and emit ready-to-paste /orchestrate custom prompts. Generative only — never invokes /orchestrate itself. Use when the user has a multi-step plan and wants to drive it through orchestrate without composing chains by hand.

View original Skill.mdThis page is parsed directly from the repository SKILL.md without editorial rewriting. Collected: Jul 28, 2026 · about 1 min

Django + Celery 非同期タスク

Django でのバックグラウンドジョブと非同期処理。

使用時期

  • メール送信をバックグラウンドで実行
  • 重い処理をスケジュール
  • 定期的なタスクを実行(日報、クリーンアップ)
  • 外部API呼び出しをキューイング
  • 複雑なワークフローを調整

セットアップ

1. Celery インストール

pip install celery redis

2. タスク定義

from celery import shared_task

@shared_task
def send_email(recipient):
    # メール送信ロジック
    pass

3. ワーカー起動

celery -A myapp worker -l info

タスク

非同期実行

send_email.delay(recipient)  # すぐにキューに追加、非同期実行

スケジューリング

from celery.schedules import crontab

app.conf.beat_schedule = {
    'send-report-daily': {
        'task': 'app.tasks.send_report',
        'schedule': crontab(hour=9, minute=0),
    },
}

エラーハンドリング

  • リトライロジック実装
  • デッドレター処理
  • ロギング構成
  • モニタリング設定(Flower)

詳細については、ドキュメントを参照してください。

Source repo
affaan-m/ECC
Skill path
docs/ja-JP/skills/django-celery/SKILL.md
Commit SHA
4e973d3eaf92
Repository license
MIT
Data collected