#rpython — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #rpython, aggregated by home.social.
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🚀🚀 "Tech genius discovers the astonishing speed of #RPython GC allocation... by writing *another* benchmark program. Because, clearly, the world was waiting with bated breath for this groundbreaking revelation instead of solving actual problems. 🙄"
https://pypy.org/posts/2025/06/rpython-gc-allocation-speed.html #TechGenius #Benchmarking #GCAllocation #GroundbreakingRevelation #ProblemSolving #HackerNews #ngated -
🚀🚀 "Tech genius discovers the astonishing speed of #RPython GC allocation... by writing *another* benchmark program. Because, clearly, the world was waiting with bated breath for this groundbreaking revelation instead of solving actual problems. 🙄"
https://pypy.org/posts/2025/06/rpython-gc-allocation-speed.html #TechGenius #Benchmarking #GCAllocation #GroundbreakingRevelation #ProblemSolving #HackerNews #ngated -
🚀🚀 "Tech genius discovers the astonishing speed of #RPython GC allocation... by writing *another* benchmark program. Because, clearly, the world was waiting with bated breath for this groundbreaking revelation instead of solving actual problems. 🙄"
https://pypy.org/posts/2025/06/rpython-gc-allocation-speed.html #TechGenius #Benchmarking #GCAllocation #GroundbreakingRevelation #ProblemSolving #HackerNews #ngated -
🚀🚀 "Tech genius discovers the astonishing speed of #RPython GC allocation... by writing *another* benchmark program. Because, clearly, the world was waiting with bated breath for this groundbreaking revelation instead of solving actual problems. 🙄"
https://pypy.org/posts/2025/06/rpython-gc-allocation-speed.html #TechGenius #Benchmarking #GCAllocation #GroundbreakingRevelation #ProblemSolving #HackerNews #ngated -
How fast can the RPython GC allocate?
https://pypy.org/posts/2025/06/rpython-gc-allocation-speed.html
#HackerNews #RPython #GC #Allocation #RPython #Performance #Memory #Management #Hacker #News
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How fast can the RPython GC allocate?
https://pypy.org/posts/2025/06/rpython-gc-allocation-speed.html
#HackerNews #RPython #GC #Allocation #RPython #Performance #Memory #Management #Hacker #News
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How fast can the RPython GC allocate?
https://pypy.org/posts/2025/06/rpython-gc-allocation-speed.html
#HackerNews #RPython #GC #Allocation #RPython #Performance #Memory #Management #Hacker #News
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How fast can the RPython GC allocate?
https://pypy.org/posts/2025/06/rpython-gc-allocation-speed.html
#HackerNews #RPython #GC #Allocation #RPython #Performance #Memory #Management #Hacker #News
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How fast can the RPython GC allocate?
https://pypy.org/posts/2025/06/rpython-gc-allocation-speed.html
#HackerNews #RPython #GC #Allocation #RPython #Performance #Memory #Management #Hacker #News
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I finally think I've figured out a basic #Nix heap using the #Haskell/#GHC technique of flagging every heap object to detect infinite loops. Cache invalidation really is hard... Fortunately, Nix is pure, so I don't have to invalidate any heap objects directly. #RPython makes it easy to hack, although it's still a bit of a slog to debug segfaults.
I think I might have to actually look at #CppNix now, or at least reread Eelco's thesis. I need to understand the differences between evaluation and instantiation.
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I finally think I've figured out a basic #Nix heap using the #Haskell/#GHC technique of flagging every heap object to detect infinite loops. Cache invalidation really is hard... Fortunately, Nix is pure, so I don't have to invalidate any heap objects directly. #RPython makes it easy to hack, although it's still a bit of a slog to debug segfaults.
I think I might have to actually look at #CppNix now, or at least reread Eelco's thesis. I need to understand the differences between evaluation and instantiation.
-
I finally think I've figured out a basic #Nix heap using the #Haskell/#GHC technique of flagging every heap object to detect infinite loops. Cache invalidation really is hard... Fortunately, Nix is pure, so I don't have to invalidate any heap objects directly. #RPython makes it easy to hack, although it's still a bit of a slog to debug segfaults.
I think I might have to actually look at #CppNix now, or at least reread Eelco's thesis. I need to understand the differences between evaluation and instantiation.
-
I finally think I've figured out a basic #Nix heap using the #Haskell/#GHC technique of flagging every heap object to detect infinite loops. Cache invalidation really is hard... Fortunately, Nix is pure, so I don't have to invalidate any heap objects directly. #RPython makes it easy to hack, although it's still a bit of a slog to debug segfaults.
I think I might have to actually look at #CppNix now, or at least reread Eelco's thesis. I need to understand the differences between evaluation and instantiation.
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I apparently was overly emotional last night and started an #RPython version of #Nix. I have about half a parser so far.
If I keep working on this, the goals will be to have a smaller footprint in terms of code and CPU (but not necessarily RAM) than CppNix. This sounds quite achievable because the RPython toolkit comes with a JIT generator: insert interpreter, receive JIT.
Contributions will be welcome once everything is available to the public. Wait a day or two, please.
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I apparently was overly emotional last night and started an #RPython version of #Nix. I have about half a parser so far.
If I keep working on this, the goals will be to have a smaller footprint in terms of code and CPU (but not necessarily RAM) than CppNix. This sounds quite achievable because the RPython toolkit comes with a JIT generator: insert interpreter, receive JIT.
Contributions will be welcome once everything is available to the public. Wait a day or two, please.
-
I apparently was overly emotional last night and started an #RPython version of #Nix. I have about half a parser so far.
If I keep working on this, the goals will be to have a smaller footprint in terms of code and CPU (but not necessarily RAM) than CppNix. This sounds quite achievable because the RPython toolkit comes with a JIT generator: insert interpreter, receive JIT.
Contributions will be welcome once everything is available to the public. Wait a day or two, please.
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I apparently was overly emotional last night and started an #RPython version of #Nix. I have about half a parser so far.
If I keep working on this, the goals will be to have a smaller footprint in terms of code and CPU (but not necessarily RAM) than CppNix. This sounds quite achievable because the RPython toolkit comes with a JIT generator: insert interpreter, receive JIT.
Contributions will be welcome once everything is available to the public. Wait a day or two, please.
-
I apparently was overly emotional last night and started an #RPython version of #Nix. I have about half a parser so far.
If I keep working on this, the goals will be to have a smaller footprint in terms of code and CPU (but not necessarily RAM) than CppNix. This sounds quite achievable because the RPython toolkit comes with a JIT generator: insert interpreter, receive JIT.
Contributions will be welcome once everything is available to the public. Wait a day or two, please.
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New blog post: Which Interpreters are Faster, AST or Bytecode?
It gives a high-level overview over our OOPLSA paper, which investigates interpreters on top of metacompilation systems.
Will be presented next week at @splashcon.https://stefan-marr.de/2023/10/ast-vs-bytecode-interpreters/
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New blog post: Which Interpreters are Faster, AST or Bytecode?
It gives a high-level overview over our OOPLSA paper, which investigates interpreters on top of metacompilation systems.
Will be presented next week at @splashcon.https://stefan-marr.de/2023/10/ast-vs-bytecode-interpreters/
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New blog post: Which Interpreters are Faster, AST or Bytecode?
It gives a high-level overview over our OOPLSA paper, which investigates interpreters on top of metacompilation systems.
Will be presented next week at @splashcon.https://stefan-marr.de/2023/10/ast-vs-bytecode-interpreters/
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New blog post: Which Interpreters are Faster, AST or Bytecode?
It gives a high-level overview over our OOPLSA paper, which investigates interpreters on top of metacompilation systems.
Will be presented next week at @splashcon.https://stefan-marr.de/2023/10/ast-vs-bytecode-interpreters/
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Apparently not a joke. A lot of people seem to be quite enthused about this.
#Pypy, a Python runtime in Python, tried this ages ago. Their #RPython cross-compilation toolchain was extremely useful, built up to target #WASM as a back-end. Really helped push Web Assembly forward.
Conclusion: it's not worth it. It's almost never worth it.
Instead: transpile to ES6 for native runtime, zero download overhead, and zero startup overhead. JavaScripthon is an excellent one I've even contributed to.
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Apparently not a joke. A lot of people seem to be quite enthused about this.
#Pypy, a Python runtime in Python, tried this ages ago. Their #RPython cross-compilation toolchain was extremely useful, built up to target #WASM as a back-end. Really helped push Web Assembly forward.
Conclusion: it's not worth it. It's almost never worth it.
Instead: transpile to ES6 for native runtime, zero download overhead, and zero startup overhead. JavaScripthon is an excellent one I've even contributed to.
-
Apparently not a joke. A lot of people seem to be quite enthused about this.
#Pypy, a Python runtime in Python, tried this ages ago. Their #RPython cross-compilation toolchain was extremely useful, built up to target #WASM as a back-end. Really helped push Web Assembly forward.
Conclusion: it's not worth it. It's almost never worth it.
Instead: transpile to ES6 for native runtime, zero download overhead, and zero startup overhead. JavaScripthon is an excellent one I've even contributed to.
-
Apparently not a joke. A lot of people seem to be quite enthused about this.
#Pypy, a Python runtime in Python, tried this ages ago. Their #RPython cross-compilation toolchain was extremely useful, built up to target #WASM as a back-end. Really helped push Web Assembly forward.
Conclusion: it's not worth it. It's almost never worth it.
Instead: transpile to ES6 for native runtime, zero download overhead, and zero startup overhead. JavaScripthon is an excellent one I've even contributed to.
-
Apparently not a joke. A lot of people seem to be quite enthused about this.
#Pypy, a Python runtime in Python, tried this ages ago. Their #RPython cross-compilation toolchain was extremely useful, built up to target #WASM as a back-end. Really helped push Web Assembly forward.
Conclusion: it's not worth it. It's almost never worth it.
Instead: transpile to ES6 for native runtime, zero download overhead, and zero startup overhead. JavaScripthon is an excellent one I've even contributed to.