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The fastest way to obtain conda is to install Miniconda, a mini version of Anaconda that includes only conda and its dependencies. If you prefer to have conda plus over 7,500 open-source packages, install Anaconda. Conda install linux-64 v1.06; noarch v1.06; osx-64 v1.06; win-64 v1.06; To install this package with conda run one of the following: conda install -c conda-forge r-brew.

Python interface to the ecCodes GRIB and BUFR decoder/encoder

Project description

Python 3 interface to decode and encode GRIB and BUFR files via theECMWF ecCodes library.

Brew install saulpw/vd/visidata: Base, http, html, xls(x). If these packages are included in the conda environment, they can be installed with. Apr 02, 2021 The Jupyter Notebook is a web-based interactive computing platform. The notebook combines live code, equations, narrative text, visualizations, interactive dashboards and other media. Cask anaconda installs files under $(brew -prefix). The presence of such files can cause warnings when running `brew doctor`, which is considered.

Features:

  • reads and writes GRIB 1 and 2 files,
  • reads and writes BUFR 3 and 4 files,
  • supports all modern versions of Python 3.8, 3.7, 3.6, 3.5 and PyPy3,
  • works on most Linux distributions and MacOS, the ecCodes C-library
  • is the only system dependency,
  • PyPI package can be installed without compiling,at the cost of being twice as slow as the original ecCodes module,
  • an optional compile step makes the code as fast as the original modulebut it needs the recommended (the most up-to-date) version of ecCodes.

Limitations:

  • Microsoft Windows support is untested.

Installation

The package is installed from PyPI with:

System dependencies

The Python module depends on the ECMWF ecCodes librarythat must be installed on the system and accessible as a shared library.

On a MacOS with HomeBrew use:

Or if you manage binary packages with Conda use:

As an alternative you may install the official source distributionby following the instructions athttps://software.ecmwf.int/wiki/display/ECC/ecCodes+installation

You may run a simple selfcheck command to ensure that your system is set up correctly:

Usage

Refer to the ecCodesdocumentation pagesfor usage.

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Experimental features

Fast bindings

To test the much faster CFFI API level, out-of-line mode you need theecCodes header files.Then you need to clone the repo in the same folder as your ecCodessource tree, make a pip development install and custom compilethe binary bindings:

To revert back to ABI level, in-line more just remove the compiled bindings:

Project resources

Developmenthttps://github.com/ecmwf/eccodes-python
Downloadhttps://pypi.org/project/eccodes

Contributing

The main repository is hosted on GitHub,testing, bug reports and contributions are highly welcomed and appreciated:

Please see the CONTRIBUTING.rst document for the best way to help.

Maintainer:

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  • Shahram Najm - ECMWF

Brew Install Conda

Contributors:

  • Alessandro Amici - B-Open

See also the list of contributorswho participated in this project.

License

© Copyright 2017- ECMWF.

This software is licensed under the terms of the Apache Licence Version 2.0which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.

In applying this licence, ECMWF does not waive the privileges and immunitiesgranted to it by virtue of its status as an intergovernmental organisation nordoes it submit to any jurisdiction.

Changelog for eccodes-python

1.3.2 (2021-04-16)

  • Restore the experimental high-level interface

1.3.0 (2021-04-09)

  • ECC-1231: Remove the experimental high-level interface
  • Added the “findlibs” module
  • Fix tests/test_high_level_api.py when MEMFS enabled
  • ECC-1226: Python3 bindings: Typo causes AttributeError when calling codes_index_get_double

1.2.0 (2021-03-23)

  • Added test for multi-field GRIBs
  • Fix deprecation warning: np.float is a deprecated alias for the builtin float
  • Experimental feature: grib_nearest_find

1.1.0 (2021-01-20)

  • ECC-1171: Performance: Python bindings: remove assert statements
  • ECC-1161: Python3 bindings: Do not raise exception on first failed attempt
  • ECC-1176: Python3 bindings: float32 recognised as int instead of float
  • GitHub pull request #41: Remove the apparent support for Python 2
  • GitHub pull request #44: Fix CFFI crash on windows
  • GitHub pull request #42: Add unit testing with GitHub actions (linux, macos and windows)

1.0.0 (2020-10-14)

  • ECC-1143: CMake: Migration to ecbuild v3.4
  • ECC-1133: C API: Propagate const char* for codes_index_new_from_file and codes_index_select_string

0.9.9 (2020-08-04)

  • Support for ecmwflibs. An additional way to find ECMWF libraries (if available)
  • ECC-1140: Segfault from invalid pointer reference in grib_set_double_array()

0.9.8 (2020-06-26)

  • ECC-1110: Removed obsolete function codes_close_file()
  • Provide missing argument to exceptions
  • Fix codes_set_definitions_path() typo
  • Fix grib_get_double_element(). Missing last argument
  • Add more tests to increase coverage
  • GitHub pull request #15: Add .__next__() method to eccodes.CodesFile class
  • ECC-1113: Python3 bindings under Windows: codes_get_long_array returns incorrect values
  • ECC-1108: Python3 bindings under Windows: use of handle causes crash
  • ECC-1121: Segfault when closing GribFile if messages are closed manually

0.9.6 (2020-03-10)

  • Update Copyright notices
  • Function-argument type checks: Improve error message
  • Fix C function calls for codes_gribex_mode_on/codes_gribex_mode_off

0.9.5 (2020-01-15)

  • ECC-1029: Function-argument type-checking should be disabled by default.
    To enable these checks, export ECCODES_PYTHON_ENABLE_TYPE_CHECKS=1
  • ECC-1032: Added codes_samples_path() and codes_definition_path()
  • ECC-1042: Python3 interface writes integer arrays incorrectly
  • ECC-794: Python3 interface: Expose the grib_get_data function

0.9.4 (2019-11-27)

  • Added new function: codes_get_version_info
  • ECC-753: Expose the codes_grib_nearest_find_multiple function in Python
  • ECC-1007: Python3 interface for eccodes cannot write large arrays

0.9.3 (2019-10-04)

  • New exception added: FunctionalityNotEnabledError
  • BUFR decoding: support for multi-element constant arrays (ECC-428)

0.9.2 (2019-07-09)

  • All ecCodes tests now pass
  • Simplify the xx_new_from_file calls
  • Fix for grib_set_string_array
  • Use ECCODES_DIR to locate the library
  • Remove the new-style high-level interface. It is still available incfgrib.

0.9.1 (2019-06-06)

  • codes_get_long_array and codes_get_double_array now return a np.ndarray.See: #3.

0.8.0 (2019-04-08)

  • First public release.

Release historyRelease notifications RSS feed

1.3.2

1.3.1

1.3.0

1.2.0

1.1.0

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1.0.0

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This post shows how to build and install OpenCV 4.5.0 on a MacBook Pro that comes with an M1 chip. Yes, you guessed it right - as of January 01, 2021, there’s no pre-compiled OpenCV binary compatible with this MacBook Pro variant. So, open up a terminal and get started!

Here's a brief summary of the configuration of my MacBook -

Note: The following steps should run well on an M1 MacBook Air too.

Install Xcode and Homebrew

We start by executing sudo xcodebuild -license from a terminal.

When you execute the above command, you would need to accept the Xcode license. Then, in order to make use of Apple command line tools, we need to install it - sudo xcode-select --install.

Homebrew manages packages on a Mac. In order to install it execute the following - /usr/bin/ruby -e '%(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)'.

You would want to add the command brew after the installation is complete. To do so, execute the following - nano ~/.zshrc

Then insert export PATH=$PATH:/opt/homebrew/bin into it and press Ctrl + X from your keyboard. Then execute source ~/.zshrc from the terminal.

Note that the exact path to Homebrew might be different for your system, so please double check that.

Mac Install Miniconda

Next up, we install a few system-level utilities required by OpenCV on a Mac.

Install conda

My favorite Python virtual environment manager is virtualenv. Unfortunately, it does not play out that well with the new M1 chip. This is mostly because the pip-installable packages often break during their installations on the chip. This is why conda, specifically its miniforge distribution is the recommended package manager for a Mac shipped with M1. You can install it from here. This installs Python 3.8.

After the installation is complete, please create a new Python virtual environment by executing conda create --name <environment_name>. Then activate it by running conda activate <environment_name>.

Running conda install -y python3.8.6 will install a few common Python packages for you. I highly recommend running this.

Install NumPy

NumPy is needed by OpenCV. So, we need to install it before we build and install OpenCV. Apple provides a numpy wheel that is compatible with the M1 chip. Follow the steps below to install it -

Note: Be sure to activate your conda environment before doing the pip-install.

Compile OpenCV

First, let's download the OpenCV and OpenCV extended module files and prepare them for compilation.

Now, we are all set to fire the cmake command that would build OpenCV for us. Let’s review it briefly -

As per this issue comment, DCMAKE_SYSTEM_PROCESSOR, DCMAKE_OSX_ARCHITECTURES, DWITH_OPENJPEG, and DWITH_IPP are needed to be set during the compilation step. Also, please pay attention to the following arguments - OPENCV_EXTRA_MODULES_PATH and PYTHON3_EXECUTABLE. For these two arguments, you would want to first determine the paths and then supply them accordingly.

Now, before you run the above cmake command, activate the conda environment you created in an earlier step (conda activate <environment_name>) if you haven’t already. The compilation took ~3 minutes for me and it should produce outputs like so -

Next, we launch the make command - make -j8. With all the eight cores (j8 stands for eight cores here) chugging along, this step took ~8 minutes for me. You can adjust the j option with respect to the hardware available. After it’s done you should get an output like so -

The final step here is to execute - sudo make install. It should take just a few seconds to complete execution. Upon successful completion, you should get an output like so -

Sym-link OpenCV 4 on macOS to virtual environment site-packages

To do this, we first need to locate the .so file generated during the compilation step. We can do this with the mdfind command -

Please note that I obfuscated some parts of the outputs for privacy reasons. In the above output, we can see the absolute locations for the .so files that were generated. Now, we need to execute the following to sym-link one of the .so files in our current Python virtual environment -

Codeigniter framework. Please double-check the paths before executing the commands.

And that’s it!

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You can test the installation by executing the following -

Conda Brew Club

It should print '4.5.0'.

References