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Agent skill

Django Queryset Batch Processing

by hashgraph-online in hashgraph-online/awesome-codex-plugins

Process large Django querysets and write-heavy jobs with memory-safe reads, values/valueslist, iterator chunking, set-based update/delete, bulkcreate, bulkupdate, F expressions, Func expressions…

MITAuto-check passedBackend & APIs

Install Django Queryset Batch Processing

skills CLI
$ npx skills add hashgraph-online/awesome-codex-plugins --skill django-queryset-batch-processing -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install hashgraph-online/awesome-codex-plugins django-queryset-batch-processing --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/LVTD-LLC/skills/skills/django-queryset-batch-processing .claude/skills/django-queryset-batch-processing && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
django-queryset-batch-processing
GitHub stars
1.2k
Token cost
~604 tokens
SKILL.md length
229 words
Files
2 (incl. references)
Skills in repo
736
Repo updated
First seen
Licence
MIT

At a glance

Process large Django querysets and write-heavy jobs with memory-safe reads, values/valueslist, iterator chunking, set-based update/delete, bulkcreate, bulkupdate, F expressions, Func expressions…

  • Works in 4 steps: Identify the per-row work. → Choose the read pattern. → Choose the write pattern. → …
  • A Django command
  • SKILL.md covers Workflow, Safety Notes and Verification
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Django Queryset Batch Processing is an agent skill from hashgraph-online/awesome-codex-plugins. Process large Django querysets and write-heavy jobs with memory-safe reads, values/valueslist, iterator chunking, set-based update/delete, bulkcreate, bulkupdate, F expressions, Func expressions, and batch sizing. Use when a Django command, task, migration, report, or loop reads or writes many rows and is slow, memory-heavy, or query-heavy.

Its SKILL.md is about 600 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/batch-patterns.md`). Compatibility notes: Codex, Claude Code, and other Agent Skills-compatible clients.

It sits in Backend & APIs, covering Backend development and Data pipelines and ETL. It works with Django. The repository describes itself as: A curated list of awesome OpenAI Codex / ChatGPT plugins, skills, and resources. The 1 Codex Marketplace. See live plugins at: https://hol.org/plugins/best-codex-plugins. The licence is MIT.

When your agent uses it

  • A Django command
  • Writes many rows and is slow

Example prompts

  • “/django-queryset-batch-processing”

Requirements

  • Compatibility (from SKILL.md): Codex, Claude Code, and other Agent Skills-compatible clients.

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Identify the per-row work.
  2. Choose the read pattern.
  3. Choose the write pattern.
  4. Control batch size.

What it can do on your machine

Read from SKILL.md and the folder at commit 16b4156. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Codex, Claude Code, and other Agent Skills-compatible clients.

    From compatibility in the SKILL.md frontmatter.

Context cost

Django Queryset Batch Processing loads about 604 tokens when it runs, and up to ~1.2k if it reads all its reference files. Until then it costs about 95 tokens; SKILL.md has 229 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~95
When it runs · the whole SKILL.md, loaded when a task matches
~604
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from hashgraph-online/awesome-codex-plugins at commit 16b4156, republished under its MIT licence (© hashgraph-online). 229 words, ~604 tokens.

Download SKILL.mdSave it as .claude/skills/django-queryset-batch-processing/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
django-queryset-batch-processing
description
Process large Django querysets and write-heavy jobs with memory-safe reads, values/values_list, iterator chunking, set-based update/delete, bulk_create, bulk_update, F expressions, Func expressions, and batch sizing. Use when a Django command, task, migration, report, or loop reads or writes many rows and is slow, memory-heavy, or query-heavy.
compatibility
Codex, Claude Code, and other Agent Skills-compatible clients.
license
MIT
metadata.version
0.1.0
metadata.displayName
Django QuerySet Batch Processing
metadata.category
Django
metadata.tags
django,querysets,batch-processing,orm,performance

Django QuerySet Batch Processing

Use this skill when Django code processes many rows. The goal is to avoid loading unnecessary model instances, avoid queryset result-cache blowups, and move writes into set-based database operations when behavior allows.

Workflow

  1. Identify the per-row work.

    • Is it read-only export/reporting?
    • Does it need model methods, validation, or signals?
    • Can the database compute or update the value directly?

  2. Choose the read pattern.

    • Use values() or values_list() for scalar exports and reports.
    • Use iterator(chunk_size=...) when model instances are needed but queryset caching is not.
    • Keep ordering deliberate; unnecessary ordering costs work.

  3. Choose the write pattern.

    • Use QuerySet.update() with F() or expressions for uniform updates.
    • Use bulk_update() when each object has a different value.
    • Use bulk_create() for inserts, with conflict options only when the project supports their semantics.
    • Fall back to per-instance save() only when hooks, validation, side effects, or signals are required.

  4. Control batch size.

    • Keep transactions bounded.
    • Avoid huge IN lists and oversized CASE updates.
    • Monitor locks, replication lag, and memory for production jobs.

See batch-patterns.md for examples and caveats.

Safety Notes

  • Bulk update/delete operations do not call each model instance's save() or delete() methods.
  • Bulk operations can skip application-level side effects and signals.
  • Long transactions can hold locks and delay vacuum or replication.

Verification

Measure rows processed per second, query count, memory, transaction duration, and correctness on a representative batch.

© hashgraph-online, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in plugins/LVTD-LLC/skills/skills/django-queryset-batch-processing of hashgraph-online/awesome-codex-plugins.

  • SKILL.md
  • references/batch-patterns.md

Open the folder on GitHubat commit 16b4156

Compare with similar skills

Django Queryset Batch Processing next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Django Queryset Batch Processing compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Django Queryset Batch Processing this skillhashgraph-online/awesome-codex-plugins1.2k—~604Automated safety check: PassMIT
Django Celery Expertvintasoftware/django-ai-plugins150—~1.2kAutomated safety check: PassNone
Saleor Django Schema Migrationsaleor/saleor23k—~1kAutomated safety check: PassBSD-3-Clause
Django Access Reviewgetsentry/skills1k3 repos~2.6kAutomated safety check: NotesApache-2.0
Silk Profilerbaserow/baserow6.1k—~2.9kAutomated safety check: PassCustom licence
Arch Wikiahmedemad3/arch-wiki249—~5.1kAutomated safety check: PassNone

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Works with

Categories

Questions about Django Queryset Batch Processing

What does Django Queryset Batch Processing do?

Process large Django querysets and write-heavy jobs with memory-safe reads, values/valueslist, iterator chunking, set-based update/delete, bulkcreate, bulkupdate, F expressions, Func expressions…. Django Queryset Batch Processing is an agent skill from hashgraph-online/awesome-codex-plugins. Process large Django querysets and write-heavy jobs with memory-safe reads, values/valueslist, iterator chunking, set-based update/delete, bulkcreate, bulkupdate, F expressions, Func expressions, and batch sizing.

When should I use Django Queryset Batch Processing?

Django Queryset Batch Processing fits situations like: A Django command; writes many rows and is slow.

How do I install Django Queryset Batch Processing in Claude Code?

Run `npx skills add hashgraph-online/awesome-codex-plugins --skill django-queryset-batch-processing -a claude-code`. Or copy the skill folder (plugins/LVTD-LLC/skills/skills/django-queryset-batch-processing in hashgraph-online/awesome-codex-plugins) into .claude/skills/django-queryset-batch-processing in your project. Claude Code loads it when a task matches its description.

How do I install Django Queryset Batch Processing in Codex?

Run `npx skills add hashgraph-online/awesome-codex-plugins --skill django-queryset-batch-processing -a codex`. Or copy the skill folder (plugins/LVTD-LLC/skills/skills/django-queryset-batch-processing in hashgraph-online/awesome-codex-plugins) into .agents/skills/django-queryset-batch-processing in your project. Codex loads it when a task matches its description.

Can I use Django Queryset Batch Processing in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add hashgraph-online/awesome-codex-plugins --skill django-queryset-batch-processing -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/django-queryset-batch-processing, .gemini/skills/django-queryset-batch-processing, .github/skills/django-queryset-batch-processing and .opencode/skills/django-queryset-batch-processing in your project.

What does Django Queryset Batch Processing need to run?

SKILL.md names no scripts, command-line tools or credentials: Django Queryset Batch Processing is instructions for the agent only. Compatibility (from SKILL.md): Codex, Claude Code, and other Agent Skills-compatible clients..

Does Django Queryset Batch Processing access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Django Queryset Batch Processing safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Django Queryset Batch Processing use?

Django Queryset Batch Processing is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Django Queryset Batch Processing use?

About 604 tokens (SKILL.md is roughly 2.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 555 tokens, read only when the agent opens those files.

What are the alternatives to Django Queryset Batch Processing?

Skills that share tags, products or a category with Django Queryset Batch Processing: Django Celery Expert (vintasoftware/django-ai-plugins, 150 stars), Saleor Django Schema Migration (saleor/saleor, 23k stars), Django Access Review (getsentry/skills, 1k stars) and Silk Profiler (baserow/baserow, 6.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Django Queryset Batch Processing?

hashgraph-online (a GitHub organization) maintains it in hashgraph-online/awesome-codex-plugins, which has 1,232 GitHub stars. The repository holds 736 skills in this directory. The repository was last updated on October 6, 2026.

Source: hashgraph-online/awesome-codex-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.