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loadtxt reviews and mentions
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What libraries do you miss from other languages?
It really depends on what part of Numpy you're using. You can easily leave Numpy's text parsing in the dust. And if you're doing element-wise operations on arrays, you can easily see 2-3x improvement with just numba.
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Experience with heap bloat
Amdahl's Law will catch up with you really fast as you add threads with this strategy, but it's simple and is amenable to formats where you may have a delimiter in the middle of a record. For situations where you need maximum scaling and don't have the possibility of delimiters scattered into records, you can use the strategy I used to implement a faster numpy.loadtxt: https://github.com/saethlin/loadtxt/blob/master/src/inner.rs#L84 The general idea is that you divide the file among thread boundaries by splitting it on byte boundaries, then seeking from that byte offset to the end of the next record. This gets you non-interleaved sections so there's no duplicate parsing.
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The primary programming language of loadtxt is Rust.
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