惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

N
News and Events Feed by Topic
S
Security @ Cisco Blogs
S
Secure Thoughts
Attack and Defense Labs
Attack and Defense Labs
cs.AI updates on arXiv.org
cs.AI updates on arXiv.org
Hacker News - Newest:
Hacker News - Newest: "LLM"
Recent Commits to openclaw:main
Recent Commits to openclaw:main
H
Hacker News: Front Page
博客园 - 叶小钗
H
Heimdal Security Blog
Microsoft Security Blog
Microsoft Security Blog
Forbes - Security
Forbes - Security
AI
AI
cs.CV updates on arXiv.org
cs.CV updates on arXiv.org
T
Troy Hunt's Blog
罗磊的独立博客
Application and Cybersecurity Blog
Application and Cybersecurity Blog
爱范儿
爱范儿
GbyAI
GbyAI
The Last Watchdog
The Last Watchdog
TaoSecurity Blog
TaoSecurity Blog
C
CXSECURITY Database RSS Feed - CXSecurity.com
D
DataBreaches.Net
Recent Announcements
Recent Announcements
Schneier on Security
Schneier on Security
C
Cisco Blogs
美团技术团队
D
Docker
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
WordPress大学
WordPress大学
月光博客
月光博客
雷峰网
雷峰网
Threat Intelligence Blog | Flashpoint
Threat Intelligence Blog | Flashpoint
H
Hackread – Cybersecurity News, Data Breaches, AI and More
A
Arctic Wolf
B
Blog RSS Feed
Cisco Talos Blog
Cisco Talos Blog
C
Cybersecurity and Infrastructure Security Agency CISA
V
Vulnerabilities – Threatpost
V2EX - 技术
V2EX - 技术
Y
Y Combinator Blog
N
News and Events Feed by Topic
www.infosecurity-magazine.com
www.infosecurity-magazine.com
W
WeLiveSecurity
Security Archives - TechRepublic
Security Archives - TechRepublic
G
GRAHAM CLULEY
Jina AI
Jina AI
Hugging Face - Blog
Hugging Face - Blog
酷 壳 – CoolShell
酷 壳 – CoolShell
The Hacker News
The Hacker News

DEV Community

Authentication Security Deep Dive: From Brute Force to Salted Hashing (With Java Examples) Why AI Systems Don’t Fail — They Drift Spilling beans for how i learn for exam😁"Reinforcement Learning Cheat Sheet" I Replaced Chrome with Safari for AI Browser Automation. Here's What Broke (and What Finally Worked) How Python Borrows Other People's Work The $40 Architecture: Processing 1 Billion API Requests with 99.99% Uptime Vibe Coding: A Workflow Guide (From Zero to SaaS) Most webhook security guides protect the wrong side. The scary part is delivery. Headless CMS for TanStack Start: Build a Blog with Cosmic EU Age Verification App "Hacked in 2 Minutes" — What Actually Happened Comfy Cloud’s delete function does not actually remove files Running AI Models on GPU Cloud Servers: A Beginner Guide Event-driven media intelligence with AWS Step Functions and Bedrock I scored 500 AI prompts across 8 quality dimensions — here's what broke How to Call Google Gemini API from Next.js (Free Tier, No Backend Needed) The Portal Protocol: Reclaiming Human Connection in the Age of AI How to Fix Your Team's Scattered Knowledge Problem With a Self-Hosted Forum Intro to tc Cloud Functors: A Graph-First Mental Model for the Modern Cloud Designing Multi-Tenant Backends With Both Ownership and Team Access I Built a Neumorphic CSS Library with 77+ Components — Here's What I Learned PostgreSQL Performance Optimization: Why Connection Pooling Is Critical at Scale Cómo construí un SaaS multi-rubro para gestionar expensas en Argentina con FastAPI + Vue 3 🚀 I Built an Ethical Hacking Scanner Tool – Open Source Project I Replaced /usage and /context in Claude Code With a Single Statusline A Pythonic Way to Handle Emails (IMAP/SMTP) with Auto-Discovery and AI-Ready Design I Collected 8.9 Million Polymarket Price Points — Here's What I Found About How Markets Really Move EcoTrack AI — Carbon Footprint Tracker & Dashboard Everyone's Using AI. No One Agrees How. 5 self-hosted ebook managers worth trying in 2026 Building Your First AI Agent with LangChain: From Chatbot to Autonomous Assistant Common SOC 2 Failures (Real World) Stop Vibe-Checking Your AI App: A Practical Guide to Evals How to Use SonarQube and SonarScanner Locally to Level Up Your Code Quality Your Next To-Do App Is Dead — I Replaced Mine with an OpenClaw AI Sign a Nostr event in 60 lines of Python using coincurve — no nostr-sdk, no nbxplorer, no rust toolchain ITGC Audit Explained Like You’re in Big 4 Patch Tuesday abril 2026: Microsoft parcha 163 vulnerabilidades y un zero-day en SharePoint Stop scraping everything: a better way to track competitor price changes Listing on MCPize + the Official MCP Registry while routing payments OUTSIDE the marketplace — how I kept 100% of my x402 revenue Building an AI-Powered Risk Intelligence System Using Serverless Architecture Why We Ripped Function Overloading Out of Our AI Toolchain Testing AI-Generated Code: How to Actually Know If It Works SaaS Churn Is Killing Your Business. Here Is What to Do About It (Without a Support Team) The Speed of AI Is No Longer Linear - And Self-Improving Models Are Why How to Implement RBAC for MCP Tools: A Practical Guide for Engineering Teams From Standard Quote to Persuasive Proposal: AI Automation for Arborists I built a CLI that scaffolds complete multi-tenant SaaS apps Axios CVE-2025–62718: The Silent SSRF Bug That Could Be Hiding in Your Node.js App Right Now The dashboard that ended our friendship Data Pipelines Explained Simply (and How to Build Them with Python) The Hidden Cost of AI Systems Nobody Talks About. undefined vs undeclared, and how typeof behaves Switching from file-based jobs to NATS/Kafka in Rust without changing code io_uring Adventures: Rust Servers That Love Syscalls Why Agentic AI is Killing the Traditional Database The POUR principles of web accessibility for developers and designers Quantum Neural Network 3D — A Deep Dive into Interactive WebGL Visualization How To Install Caveman In Codex On macOS And Windows Automation Pipeline Reliability: Why Your Workflow Breaks When Nobody Is Watching I Built an 'Open World' AI Coding Agent — It Works From ANY Folder From Freelancing to Product: A Tech Service Company's SaaS Transformation China's AI Giants: Adding Tencent Hunyuan & ByteDance Doubao to AI University (74 Providers) On the Vibe Coders and Their Lies clerk: Auto-Summarize Your Claude Code Sessions AI Weekly — 2026/04/10–04/17 | The Model Lockdown Is Here, but the Toolchain Is the Real Battleground AI 週報 — 2026/04/10–2026/04/17 模型封鎖潮來了,但工具鏈才是真戰場 Maybe this is how Open-Source apps are born... 🚀 Fine-Tune LLMs with LoRA and QLoRA: 2026 Guide tRPC v11 + Next.js App Router: End-to-End Type Safety Without the Boilerplate ShadCN UI in 2026: Why I Stopped Installing Component Libraries and Started Owning My Components SaaS Billing in React Server Components: Stripe + Supabase Without a Single `useEffect` Join our DEV Weekend Challenge — $1,000 in Prizes Across TEN winners! Submissions Due April 20 at 6:59 AM UTC. Implementing FSRS Spaced Repetition in Flutter + Supabase — Adding Memory Science to an AI Learning App "I Texted My Localhost From the Train — Claude Code Fixed the Bug Before I Got Home" I Built a Sales Prep AI and It Went Deeper Than Expected Design to Code #2: One JSON, Eleven Outputs Solving the 100M-Row Problem: A Summary Table Pattern for High-Volume Push Notification Logs Flutter Web With Wasm: What Actually Changes For Developers I Built 50 Royalty-Free Soundtracks for My Side Project in a Weekend Using AI Music Generation The Vibe Coding Security Checklist: 7 Things to Check Before You Ship Stop Letting Googlebot Guess Fix Your React App's SEO Right Desconstruindo o Streaming do LinkedIn: Como Criar um Engine de Extração de Vídeo de Alta Performance com HLS e FFmpeg (EDA Part-1) EDA (Exploratory Data Analysis) Explained With Real Life — Why Looking at Your Data Is the Most Important Step in Machine Learning Brand Relationship Management at Scale: Our 4-Touch Outreach System for 200+ Brands Why String.fromEnvironment() Might Return an Empty String in Dart JGuardrails 1.0.0 — Hardening Java LLM Apps Against Jailbreaks, Toxicity, and Prompt Injection Plan and Schedule a Full Week of Threads Content From One Claude Conversation Coding Cat Oran Ep3, Five Tables Changed Everything Updated: BFF Pattern I'm done watching freelancers get buried by 200 proposals. So I'm building the alternative. This is my first post BFS Algorithm in Java Step by Step Tutorial with Examples Tracking LLM Pricing Monthly: An Open Dataset for 22 AI Models How We Measure Content ROI on a Comparison Site: Revenue Attribution Without Perfect Data Introducing Nova AI Ops: The AI-Native Operating System for SRE Teams I built a free desktop video downloader for Windows — Grabbit How Talkie OCR Helps Vision-Impaired & Dyslexic Users Read the World Around Them VRCFaceTracking安装和iPhone面捕配置教程,有bug Even CrowdStrike Can't See Your Agents The Automation Gold Rush: What n8n Workflows and Claude Are Opening Up for Developers Right Now
Testcontainer(s) for Gleam: yes, without the 's' : what it is, how it works, why it exists
Daniele · 2026-04-29 · via DEV Community

I built testcontainers for Gleam and the name was already taken. Twice.

Let me start with the name, because it tells you everything.

The canonical testcontainers library for the JVM ecosystem is called testcontainers. There is also one for Elixir, and it is called testcontainers. Then someone built a Gleam wrapper around the Elixir one and published it as testcontainers_gleam. By the time I showed up wanting to build something native for Gleam, both testcontainers and testcontainers_gleam were gone.

So the library is called testcontainer. Singular. Not because I think one container is enough. Because I arrived third.

So, why build it at all

testcontainers_gleam is not a bad library. I want to be clear about that. It does what it says. It wraps the Elixir Testcontainers implementation and exposes it to Gleam code. If you are already in a mixed Elixir/Gleam project where that Elixir dep is sitting in your tree anyway, it is a completely reasonable choice and it probably saves you an afternoon.

But it is a wrapper. It is Elixir-shaped. The API leaks the abstraction underneath. And if you want idiomatic Gleam, typed errors, opaque builders, the use syntax doing its thing... you are fighting against the grain of it.

Gleam deserved something native. Not a translation layer. A library that starts from what Gleam is good at.

That is the itch. I scratched it.

pago - the mascotte

Meet Pago

Every good library deserves a mascot. testcontainer has Pago.

Pago is a paguro, a hermit crab. He carries a Docker container on his shell. He does not complain about it. He just carries it, cleans it up when the test is done, and goes home.

That is the philosophy in one image. The container lifecycle is something your tests should carry without thinking about, not something they should wrestle with. You declare what you need, you write your assertions, you close the use block, and Pago handles the rest.


Let's start: How it works

The core API is a use block. You describe a container with a builder, you start it with with_container, and it is gone when the block ends. Automatic cleanup, even if your test process crashes, because a linked guard process is watching in the background.

import testcontainer
import testcontainer/container
import testcontainer/port
import testcontainer/wait

pub fn redis_test() {
  use redis <- testcontainer.with_container(
    container.new("redis:7-alpine")
    |> container.expose_port(port.tcp(6379))
    |> container.wait_for(wait.log("Ready to accept connections")),
  )

  let assert Ok(host_port) = container.host_port(redis, port.tcp(6379))
  // connect to 127.0.0.1:host_port
  Ok(Nil)
}

Enter fullscreen mode Exit fullscreen mode

A few things worth pointing out here. Ports are typed: port.tcp/1 and port.udp/1 are different things. The builder is opaque, so you cannot pass a half-constructed ContainerSpec somewhere it does not belong. Wait strategies are composable. Errors always carry context.

The library also talks to Docker over the Unix socket directly via gen_tcp, no HTTP client pulled in as a dependency. Fast. Lightweight. No surprises in your dep tree.


Formulas: the part that actually excited me

Here is where things get interesting.

A raw container gives you a running process and a mapped port. If you are starting Postgres, that means you get back a host and a port number. And then every single test file has to reassemble a connection URL from scratch: host, port, user, password, database, driver prefix. It is noise. It is copy-pasted noise.

The solution is what I call a Formula.

pub opaque type Formula(output)

Enter fullscreen mode Exit fullscreen mode

A Formula(output) is two things combined: a ContainerSpec that describes how to start the container, and an extraction function that takes the running Container and produces a typed output. When you call with_formula, the library starts the container, runs the extraction, and hands your test body a fully typed service record.

import testcontainer
import testcontainer_formulas/postgres

pub fn user_repository_test() {
  use pg <- testcontainer.with_formula(
    postgres.new()
    |> postgres.with_database("myapp_test")
    |> postgres.with_password("secret")
    |> postgres.formula(),
  )

  // pg is a PostgresContainer
  // pg.connection_url, pg.host, pg.port: all there, already built
  Ok(Nil)
}

Enter fullscreen mode Exit fullscreen mode

The output type parameter is the interesting bit. Formula(PostgresContainer) and Formula(RedisContainer) are different types. The compiler knows. You cannot accidentally pass one where the other is expected. No runtime surprise, no casting, just the type system doing its job.

The extraction function is a small contract:

pub fn new(
  spec: container.ContainerSpec,
  extract: fn(container.Container) -> Result(output, error.Error),
) -> Formula(output)

Enter fullscreen mode Exit fullscreen mode

You get a running container. You return your typed output or an error. That is the entire surface of the abstraction.


Why formulas live in a separate package

The core library defines Formula(output) and with_formula. That is all it knows. It has no idea what Postgres is.

The actual formulas live in testcontainer_formulas, a companion package that ships with:

  • testcontainer_formulas/postgres
  • testcontainer_formulas/redis
  • testcontainer_formulas/mysql
  • testcontainer_formulas/rabbitmq
  • testcontainer_formulas/mongo

The separation is intentional, and the reason is not packaging convenience. It is about the community.

The formula surface is small enough that anyone can write one. The pattern is clear. You define a config type, a builder pipeline, an extraction function, and you are done. That means if you need Kafka, Elasticsearch, LocalStack, a very specific internal service, something completely bizarre, you can open a PR against testcontainer_formulas and it just fits. No changes needed to the core. No coordination required with me. The abstraction holds.

I want testcontainer_formulas to grow into a community-curated archive. Official formulas, opinionated formulas, weird ones. The contract is small enough that this is realistic. If you have an idea for one, open a PR. That is what the repository is for.


The Formula Builder

There is a third piece: testcontainer_formulas_builder.

It is a block-based visual tool. You add blocks for the services you need (Postgres, Redis, MySQL, RabbitMQ, MongoDB, or a custom module), configure each one, set up the shared network if needed, and it generates the Gleam code as you go. You can copy it directly with y in Vim navigation mode... So, YES There is also a vim navigation mode, because of course there is.

There is a live version you can try right now, tagged as experimental: lupodevelop.github.io/testcontainer_formulas_builder

It is aimed at people who want to get a working formula snippet without reading all the docs first, or who want to understand the structure before writing one from scratch. Either way it lowers the barrier for contribution, which is the whole point.


Multi-container setups

For integration tests that need multiple services talking to each other, there are networks and stacks.

use net <- testcontainer.with_stack(
  testcontainer.stack("app-test-net", fn(n) { Ok(n) }),
)
use pg <- testcontainer.with_formula(
  postgres.new()
  |> postgres.on_network(net)
  |> postgres.formula(),
)
// pg and any other container share the same Docker network

Enter fullscreen mode Exit fullscreen mode

Stacks own the network lifecycle. Each container inside still gets its own guard process, so teardown is ordered and nothing leaks.


Get started

gleam add testcontainer
gleam add testcontainer_formulas

Enter fullscreen mode Exit fullscreen mode

If you write a formula for something not in the package yet, open a PR. That is exactly what testcontainer_formulas is there for.

Pago is watching. Pago approves.

So if you want to contribute, my Ko-fi is waiting for you.