NumPy 1.x Is Officially End-of-Life: What Now?

As of September 2025, NumPy 1.x is no longer supported. That means:

• No more security fixes
• No more bug patches
• No more community maintenance
  
  

If your org is still running production workloads on NumPy 1.x, you’re now officially exposed to vulnerabilities, compliance gaps, and operational risk.

Meanwhile, NumPy 2.x has arrived with major upgrades—new data type promotion rules, a cleaned-up namespace, a more consistent integer default, and a modernized C-API. These changes improve long-term stability and performance but also introduce breaking changes.

In short: upgrading isn’t just a version bump.

Why Staying on NumPy 1.x Without Support Is a Risk

EOL software isn’t just old—it’s unprotected. From this point forward:

• Any newly discovered CVE won’t be patched.
  
  
• Compliance auditors will flag unsupported software.
  
  
• Legacy dependencies could lock you into fragile systems.
  
  

For industries handling sensitive data (finance, healthcare, government), this isn’t optional risk—it’s a dealbreaker.

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The Migration Wall

The official NumPy 2.0 migration guide outlines some big hurdles:

• Data type promotion changes (NEP 50): results of mixed dtypes may differ, leading to precision shifts or unexpected errors.
  
  
• Namespace cleanup (NEP 52): ~100 functions have been moved or removed—like np.float_ (use np.float64) or np.complex_ (use np.complex128).
  
  
• C-API updates: libraries written in C or Cython may need to adopt new macros and accessor functions.
  
  
• Integer default change: np.intp is now the default on 64-bit systems, which may impact compiled integrations.
  
  

These are all good changes for the future—but they mean most enterprises can’t just run pip install numpy==2.0 and call it a day.

That’s the NumPy EOL trap: you can’t upgrade quickly, but you can’t afford to stay still.

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HeroDevs NES for NumPy 1.x

This is where HeroDevs’ Never-Ending Support (NES) for NumPy comes in.

NES extends the life of NumPy 1.x beyond EOL, keeping your systems patched, secure, and compliant—while giving you time to plan your 2.x migration on your terms.

With NES for NumPy, you get:

• Ongoing security patches for newly discovered CVEs
  
  
• Compliance coverage across industries and regulations
  
  
• Breathing room to modernize when your roadmap allows
  
  
• Confidence in legacy code, even after community EOL
  
  

Don’t Treat EOL as Optional

NumPy powers everything from data pipelines to machine learning workloads. Letting it go unpatched after EOL isn’t just technical debt—it’s a liability.

With NES, you don’t have to choose between:

• Rushing an unstable upgrade → risking breakage with new dtype rules, C-API changes, or namespace removals.
• Running insecure code → leaving production workloads open to CVEs and audit failures.
  
  

Instead, you get the coverage you need today, and the space to modernize tomorrow.

Explore pricing.