How to Install and Uninstall python3-tables Package on Kali Linux

Last updated: May 18,2024

1. Install "python3-tables" package

Here is a brief guide to show you how to install python3-tables on Kali Linux


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                python3-tables
            
                    
    
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2. Uninstall "python3-tables" package

This tutorial shows how to uninstall python3-tables on Kali Linux:


    
        
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                sudo apt remove
            
                        
                python3-tables
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the python3-tables package on Kali Linux

Package: python3-tables
Source: pytables
Version: 3.7.0-10
Installed-Size: 2834
Maintainer: Debian Science Maintainers
Architecture: all
Depends: python3-numexpr, python3-numpy, python3-packaging, python3:any, python-tables-data (= 3.7.0-10), python3-tables-lib (>= 3.7.0-10), python3-tables-lib (<< 3.7.0-10.1~)
Suggests: python3-netcdf4, python-tables-doc, vitables
Size: 337944
SHA256: 5288136b8c97f53da70738d2540c54a4b4fa54a210974d01b80af48fdda11534
SHA1: 6b1f15239e74c116ef40f3cfcc6e7742b7438c4a
MD5sum: a921e69a4a5eb9c1ea4776d83fb12876
Description: Hierarchical database for Python3 based on HDF5
PyTables is a package for managing hierarchical datasets and designed
to efficiently cope with extremely large amounts of data.
.
It is built on top of the HDF5 library and the NumPy package. It
features an object-oriented interface that, combined with C extensions
for the performance-critical parts of the code (generated using
Cython), makes it a fast, yet extremely easy to use tool for
interactively save and retrieve very large amounts of data. One
important feature of PyTables is that it optimizes memory and disk
resources so that they take much less space (between a factor 3 to 5,
and more if the data is compressible) than other solutions, like for
example, relational or object oriented databases.
.
- Compound types (records) can be used entirely from Python (i.e. it
is not necessary to use C for taking advantage of them).
- The tables are both enlargeable and compressible.
- I/O is buffered, so you can get very fast I/O, specially with
large tables.
- Very easy to select data through the use of iterators over the
rows in tables. Extended slicing is supported as well.
- It supports the complete set of NumPy objects.
Description-md5:
Homepage: https://www.pytables.org
Section: python
Priority: optional
Filename: pool/main/p/pytables/python3-tables_3.7.0-10_all.deb