To distribute a macOS app with an embedded Python machine-learning sidecar, build for every architecture you support, place code in standard bundle locations, sign nested components from the inside out, enable Hardened Runtime, submit for notarization, and test the exact quarantined download users will open. A successful build or signing command alone does not establish that Gatekeeper will accept the delivered app.
The details depend on your Python packager, ML framework and model runtime, distribution channel, and minimum supported macOS version. The steps below describe release risks, not a universal entitlement or dependency recipe.
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1. Put code and data in the right bundle locations
Use macOS’s expected bundle layout rather than inventing a hierarchy inside locations that the signing system treats as code. Apple’s archived Code Signing Tasks guide places helper apps and tools in Contents/MacOS or Contents/Helpers, frameworks and dynamic libraries in Contents/Frameworks, and scripts and other non-Mach-O executables in Contents/Resources.
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2. Choose architectures based on the whole dependency graph
A universal main executable does not make a thin Python extension or ML library run on both Intel and Apple Silicon. Audit the architecture of the interpreter, every native extension, ML framework library, and helper binary as a set. Your choices may include thin x86_64, thin arm64, or universal2 builds, depending on what your dependencies actually provide.
PyInstaller’s macOS multi-architecture notes document these targets and explain that its default follows the architecture of the running Python process. An Apple Silicon machine running Python under Rosetta can therefore produce an x86_64 target. Verify the build process and inspect the collected binaries; don’t infer compatibility from the host Mac or interpreter label alone.
There is no universally best architecture choice. Supporting more architectures can broaden hardware coverage, but only if compatible versions of the native dependencies are available and included. The cited PyInstaller behavior is specific to PyInstaller and should not be assumed for other bundlers.
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3. Re-sign binaries after any rewriting
Packaging tools may rewrite binary load paths or otherwise process collected libraries. PyInstaller documents that such processing can invalidate binary signatures and describes regenerating signatures for collected binaries on macOS. Treat all transformations as happening before your final signing stage, then check signatures on the finished artifact.
This is a release-pipeline issue, not a reason to trust signatures from an earlier build step: any later change to a signed binary requires the relevant code to be signed again.
4. Sign every nested component before the app
The outer app signature seals the bundle’s contents, but it does not replace the signatures required on nested code. Sign the deepest libraries, frameworks, helpers, and embedded tools first; sign containing components as you work outward; sign the app bundle last. Apple’s archived code-signing guide describes signing individual components without gaps and explains that resources are sealed by the app signature.
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Plan the sequence after assembling the final bundle. If you change a nested component after signing, the enclosing signature no longer describes the final contents.
5. Don’t use codesign --deep as the signing plan
Apple says: “Don’t pass the --deep option to codesign when you sign code.” Its distribution-signing guidance warns against deep signing complex products because it applies the same options to nested code. That can be wrong when the host app and an embedded command-line sidecar need different entitlements. It can also miss code outside expected bundle locations.
Use explicit signing steps for each component and its appropriate options. Deep mode has a role in verification; that does not make it a sound substitute for an intentional inside-out signing sequence.
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6. Keep Hardened Runtime and library validation deliberate
Apple’s Hardened Runtime documentation says library validation is enabled by default. Under that policy, an app can load Apple system libraries and libraries signed with the same Team ID as the main executable. A third-party plug-in or framework signed under a different identity can therefore be denied.
When a library fails to load, identify the specific denied binary and inspect its signature identity before changing entitlements. The disable-library-validation entitlement permits arbitrary plug-ins or frameworks, but weakens that restriction and brings additional Gatekeeper scrutiny. If your actual plug-in design requires the exception, document the dependency and scope the entitlement to the executable that needs it rather than applying it indiscriminately.
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Python may generate bytecode files alongside source files, and an ML app may also create caches, logs, downloaded models, or mutable state. Apple’s embedding guidance uses Python bytecode generation as an example of a runtime change that can break the bundle’s code-signature seal. Treat the signed app as immutable: direct writable state to appropriate user-data locations outside sealed bundle contents.
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The right location for model files depends on your update and privacy design; the cited guidance does not prescribe a particular model-storage scheme. Whatever you choose, do not let normal app use modify the signed bundle.
8. Treat notarization as a separate distribution step
Signing and notarization are not interchangeable. For direct distribution, Apple’s notarization guide calls for valid signatures on distributed executables, a Developer ID signing identity, Hardened Runtime, and a secure timestamp. Apple describes notarization as an automated scan for malicious content and code-signing issues—not App Review. As Apple puts it, “Notarization of macOS software is not App Review.”
For submission, current Apple instructions use notarytool; the older altool and Xcode 13-or-earlier submission path has been retired. Check Apple’s current submission instructions when preparing a release because tooling requirements can change. Direct Developer ID distribution and Mac App Store distribution are different channels; confirm the requirements for the channel you intend to use rather than assuming one submission path covers both.
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Run checks against the finished app and the exact disk image, installer, or package you plan to distribute—not just an intermediate build directory. Apple’s archived code-signing guide recommends checking signatures with codesign, assessing policy with spctl, and testing the packaged app in a first-launch flow that invokes Gatekeeper, such as after download or transfer.
For every supported architecture and minimum macOS target, include the actual delivery path in release testing:
- Inspect signatures: use
codesignchecks on the app and nested code after all binary processing and signing are complete. - Assess policy: use
spctlon the distributed artifact to check the system’s policy assessment. - Exercise first launch: test the quarantined download or transferred package as a user would, then launch the app and its sidecar.
- Test product behavior separately: validate the ML runtime, model loading, and any framework-specific behavior on the supported OS and architecture combinations.
Passing signature and Gatekeeper checks does not establish model correctness, performance, or framework support. Those require product-specific tests; the sources cited here do not establish a compatibility matrix for a particular ML framework, runtime, Python version, or GPU/Metal configuration.
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