H5py

The kinds of cosmological simulations that I run generate huge amounts h5py data, h5py, and to analyse them I need to be able access the exact data that I want quickly and painlessly. HDF5 is one answer. It provides parallel IO, and carries out a bunch h5py low level optimisations under the hood to make queries faster and storage requirements smaller, h5py. Getting h5py is relatively painless in comparison, just use your favourite package manager.

Released: Apr 8, View statistics for this project via Libraries. The h5py package provides both a high- and low-level interface to the HDF5 library from Python. A strong emphasis on automatic conversion between Python Numpy datatypes and data structures and their HDF5 equivalents vastly simplifies the process of reading and writing data from Python. Oct 9, Jun 20, Jan 23,

H5py

The h5py package is a Pythonic interface to the HDF5 binary data format. It lets you store huge amounts of numerical data, and easily manipulate that data from NumPy. For example, you can slice into multi-terabyte datasets stored on disk, as if they were real NumPy arrays. Thousands of datasets can be stored in a single file, categorized and tagged however you want. For example, you can iterate over datasets in a file, or check out the. You don't need to know anything special about HDF5 to get started. Almost anything you can do from C in HDF5, you can do from h5py. Best of all, the files you create are in a widely-used standard binary format, which you can exchange with other people , including those who use programs like IDL and MATLAB. Check out the install guide. All development for h5py takes place on GitHub. Before sending a pull request, please ping the mailing list at Google Groups.

Dec 20, The h5py h5py provides both a high- and low-level interface to the HDF5 library from Python. Oct 9,

Released: Oct 9, View statistics for this project via Libraries. The h5py package provides both a high- and low-level interface to the HDF5 library from Python. A strong emphasis on automatic conversion between Python Numpy datatypes and data structures and their HDF5 equivalents vastly simplifies the process of reading and writing data from Python. Wheels are provided for several popular platforms, with an included copy of the HDF5 library usually the latest version when h5py is released. You can also build h5py from source with any HDF5 stable release from version 1.

The kinds of cosmological simulations that I run generate huge amounts of data, and to analyse them I need to be able access the exact data that I want quickly and painlessly. HDF5 is one answer. It provides parallel IO, and carries out a bunch of low level optimisations under the hood to make queries faster and storage requirements smaller. Getting h5py is relatively painless in comparison, just use your favourite package manager. We first load the numpy and h5py modules. The first step to creating a HDF5 file is to initialise it. It uses a very similar syntax to initialising a typical text file in numpy. The first argument provides the filename and location, the second the mode. This creates a file object, hf , which has a bunch of associated methods.

H5py

The h5py package is a Pythonic interface to the HDF5 binary data format. It lets you store huge amounts of numerical data, and easily manipulate that data from NumPy. For example, you can slice into multi-terabyte datasets stored on disk, as if they were real NumPy arrays. Thousands of datasets can be stored in a single file, categorized and tagged however you want. For example, you can iterate over datasets in a file, or check out the. You don't need to know anything special about HDF5 to get started. Almost anything you can do from C in HDF5, you can do from h5py. Best of all, the files you create are in a widely-used standard binary format, which you can exchange with other people , including those who use programs like IDL and MATLAB. Check out the install guide. All development for h5py takes place on GitHub.

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A strong emphasis on automatic conversion between Python Numpy datatypes and data structures and their HDF5 equivalents vastly simplifies the process of reading and writing data from Python. Getting h5py is relatively painless in comparison, just use your favourite package manager. The default is 4, but it can be an integer between 0 and 9. Groups are the basic container mechanism in a HDF5 file, allowing hierarchical organisation of the data. To save on disk space, while sacrificing read speed, you can compress the data. Download the file for your platform. Documentation The h5py user manual is a great place to start; you may also want to check out the FAQ. Search PyPI Search. Best of all, the files you create are in a widely-used standard binary format, which you can exchange with other people , including those who use programs like IDL and MATLAB. Mar 5,

Released: Feb 8,

Uploaded Jun 11, cp Download files Download the file for your platform. Project description Project details Release history Download files Project description The h5py package provides both a high- and low-level interface to the HDF5 library from Python. Nov 3, The h5py user manual is a great place to start; you may also want to check out the FAQ. This post took inspiration from a DataJoy tutorial. Groups are the basic container mechanism in a HDF5 file, allowing hierarchical organisation of the data. General questions are always welcome on the mailing list. It provides parallel IO, and carries out a bunch of low level optimisations under the hood to make queries faster and storage requirements smaller. May 24, This creates a file object, hf , which has a bunch of associated methods. Jan 7,