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Adam Perry @ OpenAI
6e7ab52929
## Why `just test` currently uses the CI-oriented nextest profile, which serializes app-server integration tests even on developer machines that can run several safely. Bounded local parallelism substantially shortens this common iteration loop without changing CI behavior. Eight-worker experiments were faster, but keeping them reliable required relaxing several test deadlines. Four workers for integration tests is a solid tradeoff that speeds up local testing without needing to change test logic. ## What changed - Add a `local` nextest profile that inherits the existing defaults. - Allow up to four app-server integration tests to run concurrently under that profile. - Make `just test` select the local profile on Unix and Windows. - Keep the default CI profile serialized and leave all test deadlines unchanged. The tests use separate processes, randomized temporary `CODEX_HOME` directories, and ephemeral ports. The remaining shared constraints are system resources; each app-server also uses a multi-thread Tokio runtime, and fuzzy-search tests can create additional worker threads, so the local cap remains intentionally conservative. ## Performance and validation All measurements below are warm, execution-only app-server runs with nextest retries disabled. On the current rebased branch, an AMD EPYC 7763 machine with 16 logical CPUs and 62 GiB RAM completed three consecutive runs: | Run | Nextest time | Wall time | Result | | --- | ---: | ---: | --- | | 1 | 142.941s | 145.17s | 836/836 passed | | 2 | 143.402s | 145.59s | 836/836 passed | | 3 | 142.870s | 145.08s | 836/836 passed | The mean wall time was 145.28s. The slow-inventory, approval replay, and zsh-fork tests all passed with their original deadlines. Earlier measurements on the same Linux machine, before the suite grew, showed the scaling that motivated the change: | App-server concurrency | Nextest time | Result | | --- | ---: | --- | | 1 | 369.5s | 572/572 passed | | 2 | 194.5s | 572/572 passed | | 4 | 111.0s mean over 3 runs | 3/3 clean | Four workers reduced that execution time by about 70%, a roughly 3.3x speedup over serialization.
6e7ab52929
·
2026-06-09 12:48:04 -07:00
7,260 Commits
Codex CLI is a coding agent from OpenAI that runs locally on your computer.
If you want Codex in your code editor (VS Code, Cursor, Windsurf), install in your IDE.
If you want the desktop app experience, run
codex app or visit the Codex App page.
If you are looking for the cloud-based agent from OpenAI, Codex Web, go to chatgpt.com/codex.
Quickstart
Installing and running Codex CLI
Run the following on Mac or Linux to install Codex CLI:
curl -fsSL https://chatgpt.com/codex/install.sh | sh
Run the following on Windows to install Codex CLI:
powershell -ExecutionPolicy ByPass -c "irm https://chatgpt.com/codex/install.ps1 | iex"
Codex CLI can also be installed via the following package managers:
# Install using npm
npm install -g @openai/codex
# Install using Homebrew
brew install --cask codex
Then simply run codex to get started.
You can also go to the latest GitHub Release and download the appropriate binary for your platform.
Each GitHub Release contains many executables, but in practice, you likely want one of these:
- macOS
- Apple Silicon/arm64:
codex-aarch64-apple-darwin.tar.gz - x86_64 (older Mac hardware):
codex-x86_64-apple-darwin.tar.gz
- Apple Silicon/arm64:
- Linux
- x86_64:
codex-x86_64-unknown-linux-musl.tar.gz - arm64:
codex-aarch64-unknown-linux-musl.tar.gz
- x86_64:
Each archive contains a single entry with the platform baked into the name (e.g., codex-x86_64-unknown-linux-musl), so you likely want to rename it to codex after extracting it.
Using Codex with your ChatGPT plan
Run codex and select Sign in with ChatGPT. We recommend signing into your ChatGPT account to use Codex as part of your Plus, Pro, Business, Edu, or Enterprise plan. Learn more about what's included in your ChatGPT plan.
You can also use Codex with an API key, but this requires additional setup.
Docs
This repository is licensed under the Apache-2.0 License.