How to Install and Uninstall python-h5py Package on Ubuntu 16.04 LTS (Xenial Xerus)

Last updated: December 25,2024

1. Install "python-h5py" package

Please follow the guidance below to install python-h5py on Ubuntu 16.04 LTS (Xenial Xerus)


    
        
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                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                python-h5py
            
                    
    
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2. Uninstall "python-h5py" package

Please follow the steps below to uninstall python-h5py on Ubuntu 16.04 LTS (Xenial Xerus):


    
        
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                sudo apt remove
            
                        
                python-h5py
            
                    
    
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            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the python-h5py package on Ubuntu 16.04 LTS (Xenial Xerus)

Package: python-h5py
Priority: optional
Section: universe/python
Installed-Size: 2262
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Science Maintainers
Architecture: amd64
Source: h5py
Version: 2.6.0-1
Depends: python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python (<< 2.8), python (>= 2.7~), python-six, python:any (>= 2.7.5-5~), libc6 (>= 2.14), libhdf5-10
Filename: pool/universe/h/h5py/python-h5py_2.6.0-1_amd64.deb
Size: 493376
MD5sum: 9b6aa316a4d0959140fad20d6c9bc1af
SHA1: 488967615fcef210f1e3bd872acabd86cc5649eb
SHA256: c82da04f04f598039d654868fbc2b3fd93a1e75150db45f06faee89077583b64
Description-en: general-purpose Python interface to hdf5 (Python 2)
HDF5 for Python (h5py) is a general-purpose Python interface to the
Hierarchical Data Format library, version 5. HDF5 is a versatile, mature
scientific software library designed for the fast, flexible storage of
enormous amounts of data.
.
From a Python programmer's perspective, HDF5 provides a robust way to
store data, organized by name in a tree-like fashion. You can create
datasets (arrays on disk) hundreds of gigabytes in size, and perform
random-access I/O on desired sections. Datasets are organized in a
filesystem-like hierarchy using containers called "groups", and accessed
using the tradional POSIX /path/to/resource syntax.
.
H5py provides a simple, robust read/write interface to HDF5 data from
Python. Existing Python and Numpy concepts are used for the interface;
for example, datasets on disk are represented by a proxy class that
supports slicing, and has dtype and shape attributes. HDF5 groups are
presented using a dictionary metaphor, indexed by name.
.
This package provides h5py for the Python 2 interpreter.
Description-md5: c10280e081c685f94c2ceca600491020
Homepage: http://www.h5py.org/
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Origin: Ubuntu