For the output array you need to use append or allocate it with an initial capacity to match the size of input. // before the loop output := make([]string, len(input)) would be my recommendation because append causes a bunch of needless reallocations and you already know what capacity you need since it’s based on the … Read more
[T; n] is an array of length n, represented as n adjacent T instances. &[T; n] is purely a reference to that array, represented as a thin pointer to the data. [T] is a slice, an unsized type; it can only be used through some form of indirection. &[T], called a slice, is a sized … Read more
I’d suggest using the byteorder crate (which also works in a no-std environment): use byteorder::{BigEndian, ReadBytesExt}; // 1.2.7 fn main() { let mut buf: &[u8] = &[0, 0, 0, 1]; let num = buf.read_u32::<BigEndian>().unwrap(); assert_eq!(1, num); } This handles oddly-sized slices and automatically advances the buffer so you can read multiple values. As of Rust … Read more
It prints every yth element from the list / array >>> a = [1,2,3,4,5,6,7,8,9] >>> a[::3] [1, 4, 7] The additional syntax of a[x::y] means get every yth element starting at position x ie. >>> a[2::3] [3, 6, 9]
def contiguous(seq): seq = iter(seq) all(x is None for x in seq) # Burn through any Nones at the beginning any(x is None for x in seq) # and the first group return all(x is None for x in seq) # everthing else (if any) should be None. Here are a couple of examples. You … Read more
Slice notation “[a:b:c]” means “count in increments of c starting at a inclusive, up to b exclusive”. If c is negative you count backwards, if omitted it is 1. If a is omitted then you start as far as possible in the direction you’re counting from (so that’s the start if c is positive and … Read more
You can use numpy’s r_ “slicing trick”: df = pd.DataFrame({‘a’:range(10,100)}) df.iloc[pd.np.r_[10:12, 25:28]] NOTE: this now gives a warning The pandas.np module is deprecated and will be removed from pandas in a future version. Import numpy directly instead. To do that, you can import numpy as np and then slice the following way: df.iloc[np.r_[10:12, 25:28]] This … Read more
Nobody mentioned Object.entries() yet, which might be the most flexible way to do it. This method uses the same ordering as for..in when enumerating properties, i.e. the order that properties were originally entered in the object. You also get subarrays with both property and value so you can use whichever or both. Finally you don’t … Read more
You can use operator.itemgetter: >>> from operator import itemgetter >>> bar = [‘a’,’b’,’c’,’x’,’y’,’z’] >>> itemgetter(0, 3, 4)(bar) (‘a’, ‘x’, ‘y’) So for your example you would do the following: >>> v1, v2, v3 = itemgetter(0, 3, 4)(bar)
The rule is simple: if multiple goroutines access a variable concurrently, and at least one of the accesses is a write, then synchronization is required. Your example does not violate this rule. You don’t write the slice value (the slice header), you only read it (implicitly, when you index it). You don’t read the slice … Read more