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[REVIEW]: HRDS: A Python package for hierarchical raster datasets #1112
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referenced this issue
Nov 30, 2018
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Dec 3, 2018
I'm happy to say that I've finished my review of
It is a well-written piece of code that solves a clearly stated problem. 'HRDS' provides a clean interface to mesh together multiple files with different resolutions and create manageable input files for variable resolution geophysical modelling.
While I've opened a number of issues in the code repository, they are all quite minor, and none of them should prevent publication of the paper. With perhaps one exception - it would be a shame to publish the paper before the typos are fixed.
I had very little difficulty obtaining a working version of the code. The dependencies were clearly identified. I encountered only one problem, and the documentation has now been updated to guide users around that issue. The test suite worked straight out of the box.
My only disappointment regarding the testing is the lack of a code coverage tool. The
The python code is laid out in a clear and logical way. I found it quite easy to work out what each piece of code does.
My biggest concern with this submission is the lack of a real-life worked example. However, @jhill1 has obtained the necessary data and has committed to implementing one soon. Once the data is included, the test suite could be altered to use those datasets instead of the proprietary ones that @jhill1 uses locally.
The overarching documentation is currently limited to the readme. However, given the nature of the software, this is perfectly acceptable. API documentation is contained in docstrings for the various methods and classes. Having extensive docstrings means that Sphinx based documentation could be added in the future without too much extra effort.
Review of the HRDS software package:
Overall, this looks like a small, but useful package for raster data processing. But there are some issues with the package structure, tests, and documentation, outlines below.
I recommend that the package be published once the below issues are addressed.
From the README:
"These instructions assume a Debian-based Linux. HDRS should work on other
There are a lot of users out there that are not running Debian-based Linux -- this project should attempt to provide some guidance for other platforms. UNfotunately, the GDAL stack is pretty ugly to install, so perhaps recommending conda and conda-forge would be a good way to get people rolling in a platform independent way.
I notice that conda is (partially) being used for the CI -- so could full conda instuctions could be provided.
I am testing on OS-X with conda and conda-forge, Python 3.7
In fact, I highly recommend that the project authors make hrds available in conda-forge: https://conda-forge.org/#add_recipe
Documentation and Examples:
In the main README, after providing Debian-only install instructions, the primary example is using the
The hrds package is using a standard setuptools / setup.py install. However, there are some issues:
The tests are put in a package that is next to the hrds package, and the setup.py uses setuptools.find_packages to to identify the packages to install. So when run, you get a top-level package called "tests" with the hrds tests in it. This is not good.
Here are some thoughts on where to put tests:
I've provided a PR here that puts the tests internal to the package:
I also added formatting, etc changes to the setup.py in that PR.
PR for fixes to the file finding, and PEP8 compliance fixes is here:
NOTE: computer memory is pretty huge these days -- are the buffer files even needed -- maybe only used when the rasters are really big?
The JOSS paper is fine as it goes, but there are a few issues:
The only user docs I could find is the README and docstrings. Some more comprehensive user and reference docs would be good. Also, the docstrings are not complete nor PEP 257 compliant.
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