Changes between Version 1 and Version 2 of Conda_GDAL_lite
- Timestamp:
- 08/03/24 21:58:30 (3 months ago)
Legend:
- Unmodified
- Added
- Removed
- Modified
-
Conda_GDAL_lite
v1 v2 1 Introducing Lightweight Versions of GDAL and PDAL 1 2 == Introducing Lightweight Versions of GDAL and PDAL 2 3 Quansight 3 4 · Jul 25, 2024 4 5 5 See how Hobu teamed with Quansight to fund the transition to a deferred plugin system in both GDAL and PDAL. The new architecture was implemented in GDAL 3.9.1 and PDAL 2.7.2. 6 See how Hobu teamed with Quansight to fund the transition to a deferred plugin system in both GDAL and PDAL. The new architecture was implemented in GDAL 3.9.1 and PDAL 2.7.2. (this article was originally published on the Quansight Blog by Isuru Fernando). 6 7 7 Th is article was originally published on the Quansight Blog by Isuru Fernando.8 The evolution of geospatial data processing has taken a significant step forward with the introduction of lightweight versions of the Geospatial Data Abstraction Library (**GDAL**) and the Point Data Abstraction Library (**PDAL**). This new architecture addresses the long-standing issue of dependency bloat, significantly improving solve times, download speeds, and overall package manageability for users. This post delves into the history, technical implementation, and benefits of this transition. 8 9 9 The evolution of geospatial data processing has taken a significant step forward with the introduction of lightweight versions of the Geospatial Data Abstraction Library (GDAL) and the Point Data Abstraction Library (PDAL). This new architecture addresses the long-standing issue of dependency bloat, significantly improving solve times, download speeds, and overall package manageability for users. This post delves into the history, technical implementation, and benefits of this transition.10 **GDAL** (Geospatial Data Abstraction Library) is a translator library for raster and vector geospatial data formats. Being a translator library supporting multiple different geospatial data formats, it has a lot of libraries as dependencies. For example The `hdf5` for HDF5 package format support. PDAL (Point Data Abstraction Library) is a library built on top of GDAL and has similar support for package formats. 10 11 11 GDAL (Geospatial Data Abstraction Library) is a translator library for raster and vector geospatial data formats. Being a translator library supporting multiple different geospatial data formats, it has a lot of libraries as dependencies. For example The `hdf5` for HDF5 package format support. PDAL (Point Data Abstraction Library) is a library built on top of GDAL and has similar support for package formats.12 12 13 A Little Bit of History13 == A Little Bit of History 14 14 conda-forge was started by a few people, including a couple of oceanographers, who wanted a way to distribute gdal easily. Hence `gdal-feedstock` is one of the first feedstocks to be made on conda-forge and was the 49th PR on staged-recipes. The initial commit to the `gdal-feedstock` which builds the conda package, only used a few packages, including `hdf4`, `hdf5`, , `postgresql`, `libnetcdf`, `kealib`. 15 15 … … 18 18 This is where the partnership with Hobu and Quansight comes in to fund the transition to a deferred plugin system in both GDAL and PDAL. The new architecture was implemented in GDAL 3.9.1 and PDAL 2.7.2. 19 19 20 Deferred C++ plugin loading 20 21 == Deferred C++ plugin loading 21 22 GDAL RFC 96 enables the support of deferred plugins. Plugins in GDAL support the various raster and vector geospatial data formats. These plugins are usually built into the core library, `libgdal.(dylib/so/dll)` , but RFC 96 introduced deferred plugins that build these plugins separately such that only the necessary plugin dependencies are needed. 22 23 … … 28 29 This concept was first used for `libarrow/libparquet` dependency since it is a large dependency and especially because gdal supports four different major versions on conda-forge. By separating this dependency, only the plugin needs to be built for the four different arrow/parquet versions as opposed to the core libgdal library being built for the four different versions. The conda package for the plugin was called `libgdal-arrow-parquet` and depended on the core library conda package `libgdal` which included the rest of the plugins. 29 30 30 libgdal-core and libgdal 31 32 == libgdal-core and libgdal 31 33 In order to generalize the above strategy to more plugins, we are now introducing a `libgdal-core` conda package and more plugins as conda packages with all plugins (except arrow/parquet) being installable with `libgdal` . We also made the python bindings depend on `libgdal-core` instead of `libgdal` so that users can select the plugins that they need. 32 34 … … 70 72 Similar to `libgdal` and `libgdal-core` , we have introduced `libgdal` and `libgdal-core` conda packages. Previously the `pdal` conda package provided only the C++ library, but now it also provides the python package to match the `gdal` conda package. 71 73 72 pdal conda packages 74 75 == pdal conda packages 73 76 74 77 – `libpdal-core` — core C++ library … … 77 80 – `pdal` — python library and all plugins 78 81 79 pdal plugin conda packages 82 83 == pdal plugin conda packages 80 84 81 85 – `libpdal-trajectory` : `filters.trajectory` driver as a plugin
