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--- other:python:jyp_steps [2023/12/15 16:40] – [Using NetCDF files with Python] Rewrote the beginning of the section jypeter
+++ other:python:jyp_steps [2024/03/07 11:15] – Added a Protocol Buffers section to the file formats jypeter
@@ Line 164: / Line 164: @@
 ===== Using NetCDF files with Python =====
-<note tip>People using CMIPn and model data on the IPSL servers can easily search and process NetCDF files using:
-  * the [[https://climaf.readthedocs.io/|Climate Model Assessment Framework (CliMAF)]] environment
-  * and the [[https://github.com/jservonnat/C-ESM-EP/wiki|CliMAF Earth System Evaluation Platform (C-ESM-EP)]]
-</note>
@@ Line 178: / Line 173: @@
   * There may be different ways of dealing with NetCDF files, depending on which [[other:python:starting#some_python_distributions|python distribution]] you have access to
+==== CliMAF and C-ESM-EP ====
+People using **//CMIPn// and model data on the IPSL servers** can easily search and process NetCDF files using:
+  * the [[https://climaf.readthedocs.io/|Climate Model Assessment Framework (CliMAF)]] environment
+  * and the [[https://github.com/jservonnat/C-ESM-EP/wiki|CliMAF Earth System Evaluation Platform (C-ESM-EP)]]
 ==== xarray ====
-Summary: [[https://docs.xarray.dev/|xarray]] makes working with labelled multi-dimensional arrays in Python simple, efficient, and fun! [...] It is particularly tailored to working with netCDF files
+[[https://docs.xarray.dev/|xarray]] makes working with labelled multi-dimensional arrays in Python simple, efficient, and fun! [...] It is particularly tailored to working with netCDF files
 === Some xarray related resources ===
@@ Line 193: / Line 199: @@
   * [[https://uxarray.readthedocs.io/|uxarray]]: provide xarray styled functionality for unstructured grid datasets following [[https://ugrid-conventions.github.io/ugrid-conventions/|UGRID Conventions]]
+==== netCDF4 ====
+[[http://unidata.github.io/netcdf4-python/|netCDF4]] is a Python interface to the netCDF C library
 ==== cdms2 ====
-<note important>''cdms2'' is unfortunately not maintained anymore and is slowly being **phased out in favor of a combination of [[#xarray|xarray]] and [[https://xcdat.readthedocs.io/|xCDAT]]**</note>
+<note important>
+  * ''cdms2'' is unfortunately not maintained anymore and is slowly being **phased out in favor of a combination of [[#xarray|xarray]] and [[https://xcdat.readthedocs.io/|xCDAT]]**
-Summary: cdms2 can read/write netCDF files (and read //grads// dat+ctl files) and provides a higher level interface than netCDF4. cdms2 is available in the [[other:python:starting#cdat|CDAT distribution]], and can theoretically be installed independently of CDAT (e.g. it will be installed when you install [[https://cmor.llnl.gov/mydoc_cmor3_conda/|CMOR in conda)]]. When you can use cdms2, you also have access to //cdtime//, that is very useful for handling time axis data.
+  * ''cdms2'' will [[https://github.com/CDAT/cdms/issues/449|not be compatible with numpy after numpy 1.23.5]] :-(
+</note>
+[[https://cdms.readthedocs.io/en/docstanya/|cdms2]] can read/write netCDF files (and read //grads// dat+ctl files) and provides a higher level interface than netCDF4. ''cdms2'' is available in the [[other:python:starting#cdat|CDAT distribution]], and can theoretically be installed independently of CDAT (e.g. it will be installed when you install [[https://cmor.llnl.gov/mydoc_cmor3_conda/|CMOR in conda)]]. When you can use cdms2, you also have access to //cdtime//, that is very useful for handling time axis data.
 How to get started:
@@ Line 206: / Line 221: @@
     - you have to replace //cdms// with **cdms2**, and //MV// with **MV2** (sooorry about that, the tutorial was written when CDAT was based on //Numeric// instead of //numpy// to handle array data)
   - read the [[http://cdms.readthedocs.io/en/docstanya/index.html|official cdms documentation]] (link may change)
-==== netCDF4 ====
-Summary: //netCDF4 can read/write netCDF files and is available in most python distributions//
-Where: [[http://unidata.github.io/netcdf4-python/]]
-===== CDAT-related resources =====
-Some links, in case they can't be found easily on the [[https://cdat.llnl.gov|CDAT]] web site...
-  * [[https://cdat.llnl.gov/tutorials.html|Tutorials in ipython notebooks]]
-  * [[http://cdat-vcs.readthedocs.io/en/latest/|VCS: Visualization Control System]]
-    * [[https://github.com/CDAT/vcs/issues/238|Colormaps in vcs examples]]
-  * [[https://github.com/CDAT/cdat-site/blob/master/eztemplate.md|EzTemplate Documentation]]
 ===== Matplotlib =====
@@ Line 462: / Line 461: @@
   * [[https://github.com/LibraryOfCongress/bagger|Bagger]] (BagIt GUI)
   * [[https://github.com/LibraryOfCongress/bagit-python|bagit-python]]
+==== Protocol Buffers ====
+//Protocol Buffers are (Google's) language-neutral, platform-neutral extensible mechanisms for serializing structured data//
+  * https://protobuf.dev/
+  * [[https://protobuf.dev/getting-started/pythontutorial/|Protocol Buffer Basics: Python]]
+    * ''mamba install protobuf''
 ===== Quick Reference and cheat sheets =====
@@ Line 569: / Line 576: @@
 You can do a lot more with python! But if you have read at least a part of this page, you should be able to find and use the modules you need. Make sure you do not reinvent the wheel! Use existing packages when possible, and make sure to report bugs or errors in the documentations when you find some
+===== Out-of-date stuff =====
+==== CDAT-related resources ====
+Some links, in case they can't be found easily on the [[https://cdat.llnl.gov|CDAT]] web site...
+  * [[https://cdat.llnl.gov/tutorials.html|Tutorials in ipython notebooks]]
+  * [[http://cdat-vcs.readthedocs.io/en/latest/|VCS: Visualization Control System]]
+    * [[https://github.com/CDAT/vcs/issues/238|Colormaps in vcs examples]]
+  * [[https://github.com/CDAT/cdat-site/blob/master/eztemplate.md|EzTemplate Documentation]]
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