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www.pythonmorsels.com | ||
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lincolnmullen.com
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| | | | | Recently I've been writing a fair bit of code in Go for a project I am working on. There is a lot to like about the language. But the thought occurred to me that maybe I like Go because it fits my (unjustifiably) beleaguered sense of self. If I used to like Ruby because it was fun, then maybe I like Go now for these reasons: Go is a minimalist language. I would prefer that we just get down to work without any fuss. Go is a high performance language for concurrency. There is too much to do and it all has to be done at once, so I guess we better do it quickly. Go is strongly typed. Please tell me what you expect up front, then stick to it. Go makes you check for errors explicitly (if err != nil). Bad things will inevitably happen, so I guess we better plan for them up front and do our best to deal with them. | |
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danielpecos.com
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| | | | | Function composition is one the key features (among others) of functional programming. Programming languages that offer higher order functions as a feature can potentially use function composition. But, still, programmers need to be aware of some key concepts to successfully apply this pattern in our code. Function composition, as defined on Wikipedia, isan act or mechanism to combine simple functions to build more complicated ones. In other words, we can define new functions, equivalent to the result of... | |
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rgoswami.me
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| | | | | A meta-post on an oral presentation around Fortran and languages Background I was a participant at the 2021 Les Houches school of physics on "Green's function approach to multiple scattering theory in electronic structure and spectroscopies". I opted to give a student talk on programming languages and elementary functions as a cautionary tale for IEEE 754. Details Title Programming Language Interstices Abstract In this short talk I will discuss the changing landscape of programming languages from the viewpoint of "mixed language" bindings. That is, the representations of various programming languages and their standardisations to aid making library calls and generating wrappers between languages. In particular I will demonstrate the LFortran compilers' ASR (Abstract Semantic Representation) and outline its usage for generating strictly correct Python wrappers; and discuss recent changes and future plans for the venerable f2py wrapper generator. f2py is currently part of Python's numpy and is best known for being used extensively to generate scipy's calls to BLAS and LAPACK; thus it forms a cornerstone of the fast growing Scientific Python ecosystem. Error analysis and the pitfalls of precision take a central role. Time permitting, some discussion of the Python-C and Fortran-C bindings will also take place. The context of these is to be concrete use cases directly applicable to the applied computational sciences. | |
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mcjones.org
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