This document is intended for experienced developers coming from OO or FP backgrounds and are interested in learning Rust. It is my attempt at saving fellow travellers from slogging through the same bogs I did!
If you're coming from C/C++ you will probably learn Rust faster than someone coming from a memory managed runtime because you are used to thinking about where
| use futuresdr::anyhow::Result; | |
| use futuresdr::macros::async_trait; | |
| use futuresdr::runtime::BlockMeta; | |
| use futuresdr::runtime::BlockMetaBuilder; | |
| use futuresdr::runtime::Kernel; | |
| use futuresdr::runtime::MessageIo; | |
| use futuresdr::runtime::MessageIoBuilder; | |
| use futuresdr::runtime::StreamIo; | |
| use futuresdr::runtime::StreamIoBuilder; | |
| use futuresdr::runtime::TypedBlock; |
| use std::ffi::CString; | |
| use std::process::exit; | |
| use std::ptr; | |
| use gdal::errors::Result; | |
| use gdal::spatial_ref::SpatialRef; | |
| use gdal::Dataset; | |
| use gdal_sys::{ | |
| CPLErr, CSLSetNameValue, GDALCreateWarpOptions, GDALDestroyWarpOptions, GDALResampleAlg, | |
| GDALWarpInitDefaultBandMapping, GDALWarpInitDstNoDataReal, |
| use std::fmt::{Display, Formatter}; | |
| use serde::{Deserialize, Serialize}; | |
| use std::num::NonZeroUsize; | |
| /// Represents a band index, which may be either one-based (Fortran-style, as used by GDAL) | |
| /// or zero-based (C-style, as used by collection libraries). | |
| #[derive(Debug, Clone, Copy, PartialEq, Serialize, Deserialize)] | |
| #[repr(u8)] | |
| pub enum BIdx { | |
| /// Zero-based indexing (i.e. C-style) |
| RUSTDOCFLAGS="-Zunstable-options --nocapture" cargo +nightly test --doc |
| [package] | |
| name = "ext-err" | |
| version = "0.1.0" | |
| edition = "2021" | |
| [dependencies] | |
| extend = "1.1.2" |
ORG=not-important
REPO=gdal-pinned
brew tap-new $ORG/$REPO
brew extract --version 2.4.4 gdal $ORG/$REPO
brew install $ORG/$REPO/[email protected]
Source: @amontalenti
There's a zoo of tools available for defining and managing Python environments, and for maintaining code quality. Here's one common and durable mix of third-party toos that do a good job with packaging, deployment, testing & linting.
For local development & local dependency environments, pyenv with its pyenv-virtualenv is very future-proof. Plus, pyenv has support for miniconda, Python 2 vs 3 issues, PyPy, etc. for situations where you need that. It's also a good choice for simple Python "environment-based" deployments to remote servers. See this StackOverflow link entry on why this is a solid choice. If you stick with pyenv and its built-in virtualenv/venv plugin, you'll be very future-proofed and very standard.
| import geotrellis.raster._ | |
| import geotrellis.vector.Extent | |
| import org.apache.spark.sql._ | |
| import org.apache.spark.sql.functions._ | |
| import org.locationtech.jts.geom.Point | |
| import org.locationtech.rasterframes._ | |
| import org.locationtech.rasterframes.datasource.raster._ | |
| import org.locationtech.rasterframes.encoders.CatalystSerializer._ | |
| object ExplodeWithLocation extends App { |