### Create HDF5 Dataset with ZFP Compression

Source: https://hdf5plugin.readthedocs.io/en/latest/usage.html

Example of creating an HDF5 file and a dataset using the ZFP compression filter. This is a basic setup before applying specific ZFP modes.

```python
f = h5py.File('test.h5', 'w')
f.create_dataset(
    'zfp',
    data=numpy.random.random(100),
    compression=hdf5plugin.Zfp())
f.close()

```

--------------------------------

### Install hdf5plugin from source directory

Source: https://hdf5plugin.readthedocs.io/en/latest/_sources/install.rst.txt

Install hdf5plugin from the source directory, allowing for custom build options.

```bash
pip install . --no-binary hdf5plugin
```

--------------------------------

### Install hdf5plugin from source

Source: https://hdf5plugin.readthedocs.io/en/latest/_sources/install.rst.txt

Install hdf5plugin from source to enable compilation optimizations specific to your host machine. The [--user] flag is optional.

```bash
pip install hdf5plugin --no-binary hdf5plugin [--user]
```

--------------------------------

### Install hdf5plugin using pip

Source: https://hdf5plugin.readthedocs.io/en/latest/_sources/install.rst.txt

Use this command to install the pre-built hdf5plugin package from PyPI. The [--user] flag is optional.

```bash
pip install hdf5plugin [--user]
```

--------------------------------

### Example of creating a Blosc compressed dataset with byte shuffle

Source: https://hdf5plugin.readthedocs.io/en/latest/hdf5plugin_EuropeanHUG2022.html

This example, found within the help documentation for hdf5plugin.Blosc, shows how to create an HDF5 dataset compressed with Blosc using 'blosclz' codec, level 9, and byte-wise shuffle.

```python
f = h5py.File('test.h5', 'w')
f.create_dataset(
    'blosc_byte_shuffle_blosclz',
    data=numpy.arange(100),
    **hdf5plugin.Blosc(cname='blosclz', clevel=9, shuffle=hdf5plugin.Blosc.SHUFFLE))
f.close()
```

--------------------------------

### Read and display compressed data

Source: https://hdf5plugin.readthedocs.io/en/latest/hdf5plugin_EuropeanHUG2022.html

This example demonstrates how to read data from a compressed HDF5 dataset and display it.

```APIDOC
## Read and display compressed data
h5file = h5py.File("new_file_blosc_bitshuffle_lz4.h5", mode="r")
imshow(h5file["/compressed_data"][()])
h5file.close()
```

--------------------------------

### Compare file sizes

Source: https://hdf5plugin.readthedocs.io/en/latest/hdf5plugin_EuropeanHUG2022.html

This command-line example shows how to compare the file sizes of a compressed HDF5 file created with hdf5plugin and an uncompressed version.

```APIDOC
## Compare file sizes
!ls -sh new_file*.h5
```

--------------------------------

### Install hdf5plugin

Source: https://hdf5plugin.readthedocs.io/en/latest/hdf5plugin_EuropeanHUG2023/presentation.html

Install the hdf5plugin package using pip or conda. For Debian/Ubuntu, use the system package manager.

```bash
pip3 install hdf5plugin
# Or:
conda install -c conda-forge hdf5plugin
```

```bash
apt-get install python3-hdf5plugin
```

--------------------------------

### Build Documentation with Sphinx

Source: https://hdf5plugin.readthedocs.io/en/latest/contribute.html

Build the project's documentation using Sphinx. This involves running a setup script and then invoking Sphinx to generate HTML output. Ensure you are in the project root directory.

```bash
python setup.py build
PYTHONPATH=build/lib.<os>-<machine>-<pyver>/ sphinx-build -b html doc/ build/html
```

--------------------------------

### Write and Read Compressed Dataset with LZ4

Source: https://hdf5plugin.readthedocs.io/en/latest/usage.html

This example demonstrates writing a dataset compressed with LZ4 and then reading it back. Ensure hdf5plugin is imported to enable the LZ4 filter.

```python
import numpy
import h5py
import hdf5plugin

# Compression
f = h5py.File('test.h5', 'w')
f.create_dataset('data', data=numpy.arange(100), compression=hdf5plugin.LZ4())
f.close()

# Decompression
f = h5py.File('test.h5', 'r')
data = f['data'][()]
f.close()

```

--------------------------------

### Install hdf5plugin

Source: https://hdf5plugin.readthedocs.io/en/latest/hdf5plugin_EuropeanHUG2022.html

Install the hdf5plugin package using pip or conda. This is required to enable support for HDF5 compression filters not natively supported by libHDF5.

```bash
%%bash
pip3 install hdf5plugin
```

--------------------------------

### Create a compressed dataset using Blosc

Source: https://hdf5plugin.readthedocs.io/en/latest/hdf5plugin_EuropeanHUG2022.html

This example demonstrates how to create a compressed HDF5 dataset using the hdf5plugin library with Blosc compression, specifying the compression codec, level, and shuffle option.

```APIDOC
## Create a compressed dataset
h5file = h5py.File("new_file_blosc_bitshuffle_lz4.h5", mode="w")
h5file.create_dataset(
    "/compressed_data",
    data=data,
    **hdf5plugin.Blosc(
        cname='lz4',
        clevel=5,
        shuffle=hdf5plugin.Blosc.BITSHUFFLE),
)
h5file.close()
```

--------------------------------

### Browse HDF5 files with H5Glance

Source: https://hdf5plugin.readthedocs.io/en/latest/hdf5plugin_EuropeanHUG2021.html

Use H5Glance to browse HDF5 files. Ensure H5Glance is installed.

```python
from h5glance import H5Glance  # Browsing HDF5 files
H5Glance("data.h5")
```

--------------------------------

### Create HDF5 Dataset with Zstd Compression

Source: https://hdf5plugin.readthedocs.io/en/latest/usage.html

Example of creating an HDF5 file and a dataset using the Zstd compression filter with a specified compression level. Ensure the file is closed after creation.

```python
f = h5py.File('test.h5', 'w')
f.create_dataset(
    'zstd',
    data=numpy.arange(100),
    compression=hdf5plugin.Zstd(clevel=22))
f.close()

```

--------------------------------

### Write Compressed Dataset with LZ4

Source: https://hdf5plugin.readthedocs.io/en/latest/usage.html

Example of writing a compressed dataset using h5py.Group.create_dataset with the hdf5plugin.LZ4 filter.

```APIDOC
import numpy
import h5py
import hdf5plugin

f = h5py.File('test.h5', 'w')
f.create_dataset('data', data=numpy.arange(100), compression=hdf5plugin.LZ4())
f.close()

f = h5py.File('test.h5', 'r')
data = f['data'][()]
f.close()
```

--------------------------------

### Inspect HDF5 file content

Source: https://hdf5plugin.readthedocs.io/en/latest/hdf5plugin_EuropeanHUG2022.html

This example shows how to use H5Glance to inspect the contents of an HDF5 file, including dataset information.

```APIDOC
## Inspect HDF5 file content
H5Glance("new_file_blosc_bitshuffle_lz4.h5")
```

--------------------------------

### Display hdf5plugin Build Configuration

Source: https://hdf5plugin.readthedocs.io/en/latest/_downloads/594fcc4a4f6d40f9213ff2f85f815f91/benchmark.ipynb

Prints the Python version and detailed build configuration of the hdf5plugin library. This is useful for verifying the installed version and its features.

```python
import os
import sys

print('Python:', sys.version)

config = hdf5plugin.get_config()
print(f"""hdf5plugin:
* Version: {hdf5plugin.version}
* Build config:
{'''
'''.join(f'  - {k}: {v}' for k, v in config.build_config._asdict().items())}
""")
```

--------------------------------

### Get HDF5 Plugin Build Configuration

Source: https://hdf5plugin.readthedocs.io/en/latest/usage.html

Provides information about the build configuration and filters registered by the hdf5plugin library.

```python
import hdf5plugin

config = hdf5plugin.get_config()
print(config)

```

--------------------------------

### Display HDF5Plugin Information

Source: https://hdf5plugin.readthedocs.io/en/latest/hdf5plugin_EuropeanHUG2023/benchmark.html

Use this snippet to print the Python version, HDF5Plugin version, and its build configuration details. Ensure hdf5plugin is installed.

```python
import os
import sys

print('Python:', sys.version)

config = hdf5plugin.get_config()
print(f"""hdf5plugin:
* Version: {hdf5plugin.version}
* Build config:
{'''
'''.join(f'  - {k}: {v}' for k, v in config.build_config._asdict().items())}
""")

```

--------------------------------

### Install hdf5plugin with OpenMP disabled

Source: https://hdf5plugin.readthedocs.io/en/latest/_sources/install.rst.txt

Disable OpenMP compilation when installing hdf5plugin by setting the HDF5PLUGIN_OPENMP environment variable to False. This can be done either globally before the pip install command or when installing from the source directory.

```bash
HDF5PLUGIN_OPENMP=False pip install hdf5plugin --no-binary hdf5plugin
```

```bash
HDF5PLUGIN_OPENMP=False pip install .
```

--------------------------------

### Install hdf5plugin using pip

Source: https://hdf5plugin.readthedocs.io/en/latest/hdf5plugin_EuropeanHUG2021.html

Install the hdf5plugin package using pip. Alternatively, use 'conda install -c conda-forge hdf5plugin'.

```bash
pip3 install hdf5plugin
```

--------------------------------

### Install hdf5plugin using conda

Source: https://hdf5plugin.readthedocs.io/en/latest/_sources/install.rst.txt

Use this command to install the hdf5plugin package from the conda-forge channel.

```bash
conda install -c conda-forge hdf5plugin
```

--------------------------------

### Get Filter Information

Source: https://hdf5plugin.readthedocs.io/en/latest/usage.html

Retrieve information about available HDF5 filters. You can get all filters by default or specify a subset by name or ID.

```APIDOC
## Get information about hdf5plugin

### Constants

`hdf5plugin.PLUGIN_PATH`
    Directory where the provided HDF5 filter plugins are stored.

### Functions

`hdf5plugin.get_filters(_filters =('bshuf', 'blosc', 'blosc2', 'bzip2', 'fcidecomp', 'lz4', 'sperr', 'sz', 'sz3', 'zfp', 'zstd')_)`
    Returns selected filter classes.
    By default it returns all filter classes.

    Parameters:
        **filters** (`int` | `str` | `tuple`[`int` | `str`, `...`]) – Filter name or ID or sequence of filter names or IDs (default: all filters). It also supports the value “registered” which selects currently available filters.

    Return type:
        `tuple`[`type`[`FilterRefBase`], `...`]

    Returns:
        Tuple of filter classes

`hdf5plugin.get_config()`
    Provides information about build configuration and filters registered by hdf5plugin.

    Return type:
        `HDF5PluginConfig`
```

--------------------------------

### Create Compressed Dataset with Shuffle and Gzip

Source: https://hdf5plugin.readthedocs.io/en/latest/hdf5plugin_EuropeanHUG2021.html

Demonstrates creating an HDF5 dataset with both byte-shuffling enabled and gzip compression. This uses standard h5py arguments.

```python
h5file = h5py.File("new_file_shuffle_gzip.h5", mode="w")
h5file.create_dataset(
    "/compressed_data_shuffle_gzip", data=data, shuffle=True, compression="gzip")
h5file.close()
```

--------------------------------

### Create HDF5 dataset with Bitshuffle and LZ4 compression using hdf5plugin

Source: https://hdf5plugin.readthedocs.io/en/latest/hdf5plugin_EuropeanHUG2022.html

Shows how to create an HDF5 file and write a dataset using Bitshuffle and LZ4 compression by passing an hdf5plugin.Bitshuffle() object to the compression argument.

```python
h5file = h5py.File("new_file_bitshuffle_lz4.h5", mode="w")
h5file.create_dataset(
    "/compressed_data_bitshuffle_lz4",
    data=data,
    **hdf5plugin.Bitshuffle()
)
h5file.close()

```

--------------------------------

### Install hdf5plugin from source with pip and disable OpenMP

Source: https://hdf5plugin.readthedocs.io/en/latest/install.html

Install hdf5plugin from source using pip, disabling OpenMP compilation by setting the HDF5PLUGIN_OPENMP environment variable to False.

```bash
HDF5PLUGIN_OPENMP=False pip install hdf5plugin --no-binary hdf5plugin
```

--------------------------------

### Install hdf5plugin from local source directory with pip and disable OpenMP

Source: https://hdf5plugin.readthedocs.io/en/latest/install.html

Install hdf5plugin from the local source directory using pip, disabling OpenMP compilation by setting the HDF5PLUGIN_OPENMP environment variable to False.

```bash
HDF5PLUGIN_OPENMP=False pip install .
```

--------------------------------

### Download Demo Data

Source: https://hdf5plugin.readthedocs.io/en/latest/hdf5plugin_EuropeanHUG2023/hdf5_compressed_chunk_direct_read.html

Downloads a sample HDF5 file containing kevlar data, which will be used for demonstrating compressed chunk reading.

```bash
# Download dataset
!wget -O /dev/shm/kevlar.h5 http://www.silx.org/pub/pyFAI/pyFAI_UM_2020/data_ID13/kevlar.h5
```

--------------------------------

### Create HDF5 dataset with shuffle and gzip compression using h5py

Source: https://hdf5plugin.readthedocs.io/en/latest/hdf5plugin_EuropeanHUG2022.html

Demonstrates creating an HDF5 file and writing a dataset with byte-shuffle and gzip compression enabled via h5py parameters.

```python
h5file = h5py.File("new_file_shuffle_gzip.h5", mode="w")
h5file.create_dataset(
    "/compressed_data_shuffle_gzip", data=data, shuffle=True, compression="gzip")
h5file.close()

```

--------------------------------

### Prepare Compressed Datasets

Source: https://hdf5plugin.readthedocs.io/en/latest/hdf5plugin_EuropeanHUG2023/hdf5_compressed_chunk_direct_read.html

Creates two new HDF5 files, one with Blosc2 compression and another with Bitshuffle compression, using a specific data slice from the downloaded file.

```python
import h5py
import hdf5plugin

with h5py.File("/dev/shm/kevlar.h5", "r") as h:
    data_ref = h["/entry/data/data"][500]

with h5py.File("/dev/shm/kevlar_blosc2.h5", "w") as h:
    h.create_dataset(
        "data",
        data=data_ref,
        chunks=data_ref.shape,
        compression=hdf5plugin.Blosc2(
            cname='lz4',
            clevel=5,
            filters=hdf5plugin.Blosc2.BITSHUFFLE,
        ),
    )
with h5py.File("/dev/shm/kevlar_bitshuffle.h5", "w") as h:
    h.create_dataset(
        "data",
        data=data_ref,
        chunks=data_ref.shape,
        compression=hdf5plugin.Bitshuffle(),
    )
```

--------------------------------

### Write Compressed Datasets

Source: https://hdf5plugin.readthedocs.io/en/latest/_sources/usage.rst.txt

Demonstrates how to create a compressed dataset using h5py and hdf5plugin, specifying compression filters and options.

```APIDOC
## Write Compressed Datasets

### Description
To write compressed datasets, `import hdf5plugin` is required to enable the supported compression filters. You can then use `h5py.Group.create_dataset` with the `compression` and `compression_opts` arguments. `hdf5plugin` provides helper classes for preparing these options.

### Example
```python
import numpy
import h5py
import hdf5plugin

# Create a compressed dataset using LZ4 compression
f = h5py.File('test.h5', 'w')
f.create_dataset('data', data=numpy.arange(100), compression=hdf5plugin.LZ4())
f.close()

# Read the compressed dataset (decompression is handled automatically)
f = h5py.File('test.h5', 'r')
data = f['data'][()]
f.close()
```

### Compression Filters
`hdf5plugin` provides helper classes for various compression filters, including:
- `Bitshuffle`
- `Blosc`
- `Blosc2`
- `BZip2`
- `FciDecomp`
- `LZ4`
- `Sperr`
- `SZ`
- `SZ3`
- `Zfp`
- `Zstd`

Each of these can be instantiated and passed to the `compression` argument of `create_dataset`.
```

--------------------------------

### Download Benchmark Dataset

Source: https://hdf5plugin.readthedocs.io/en/latest/hdf5plugin_EuropeanHUG2023/benchmark.html

Use wget to download the benchmark dataset. The dataset is saved to /dev/shm/kevlar.h5.

```bash
!wget -O /dev/shm/kevlar.h5 http://www.silx.org/pub/pyFAI/pyFAI_UM_2020/data_ID13/kevlar.h5
```

--------------------------------

### Get Information about hdf5plugin

Source: https://hdf5plugin.readthedocs.io/en/latest/_sources/usage.rst.txt

Provides information on accessing constants and functions related to hdf5plugin's configuration and filters.

```APIDOC
## Get Information about hdf5plugin

### Description
`hdf5plugin` provides access to constants and functions that can help you understand its configuration and available filters.

### Constants
- `hdf5plugin.PLUGIN_PATH`: Directory where the provided HDF5 filter plugins are stored.

### Functions
- `hdf5plugin.get_filters()`: Retrieves information about the available filters.
- `hdf5plugin.get_config()`: Gets the current configuration of the plugin.

### Usage
These can be imported and called to inspect the plugin's state and capabilities.
```

--------------------------------

### Instantiate Compression Filter Configuration

Source: https://hdf5plugin.readthedocs.io/en/latest/usage.html

Creates a compression filter configuration instance from an HDF5 filter ID and its options. Raises ValueError or NotImplementedError for unsupported combinations.

```python
import h5py
import hdf5plugin

create_plist = dataset.id.get_create_plist()
compression_filters = []

for index in range(create_plist.get_nfilters()):
    filter_id, _, filter_options, _ = create_plist.get_filter(index)
    if filter_id in hdf5plugin.FILTERS.values():
        compression_filters.append(hdf5plugin.from_filter_options(filter_id, filter_options))

```

--------------------------------

### Read and Display Compressed Data

Source: https://hdf5plugin.readthedocs.io/en/latest/hdf5plugin_EuropeanHUG2023/presentation.html

Read a compressed dataset and display it using Matplotlib. This step requires hdf5plugin to be installed and imported.

```python
data = h5file["/compressed_data"][()]  # Access datset
plt.imshow(data, cmap="gray")          # Display data
```

--------------------------------

### Configure HDF5 Plugin and Environment

Source: https://hdf5plugin.readthedocs.io/en/latest/hdf5plugin_EuropeanHUG2023/hdf5_compressed_chunk_direct_read.html

Sets CPU affinity and environment variables for multithreading before importing libraries. Displays hdf5plugin version and build configuration details.

```python
import os

os.sched_setaffinity(0, [0])

AFFINITY = os.sched_getaffinity(0)
NCPU = len(AFFINITY)

print(f"Number of CPU: {NCPU}; Affinity: {AFFINITY}")

os.environ["OPENMP_NUM_THREADS"] = str(NCPU)
os.environ["BLOSC_NTHREADS"] = str(NCPU)
print(f"""env:
  OPENMP_NUM_THREADS: {os.environ.get("OPENMP_NUM_THREADS", "unset")}
  BLOSC_NTHREADS: {os.environ.get("BLOSC_NTHREADS", "unset")}
""")

import h5py
import hdf5plugin

config = hdf5plugin.get_config()

print(f"""hdf5plugin:
  Version: {hdf5plugin.version}
  Build config:
{'''
'''.join(f'  {k}: {v}' for k, v in config.build_config._asdict().items())}
""")
```

--------------------------------

### List available compression libraries

Source: https://hdf5plugin.readthedocs.io/en/latest/hdf5plugin_EuropeanHUG2021.html

Lists the dynamic libraries for compression filters found at the hdf5plugin.PLUGINS_PATH.

```bash
ls `python3 -c "import hdf5plugin; print(hdf5plugin.PLUGINS_PATH)"`
```

--------------------------------

### Use ZFP Compression in Expert Mode

Source: https://hdf5plugin.readthedocs.io/en/latest/usage.html

Utilize ZFP compression in expert mode for fine-grained control over compression parameters like minbits, maxbits, maxprec, and minexp.

```python
f.create_dataset(
    'zfp_expert',
    data=numpy.random.random(100),
    compression=hdf5plugin.Zfp(minbits=1, maxbits=16657, maxprec=64, minexp=-1074))

```

--------------------------------

### Use SZ Compression with h5py

Source: https://hdf5plugin.readthedocs.io/en/latest/usage.html

Demonstrates creating an HDF5 dataset with SZ2 compression. This is the default configuration.

```python
f = h5py.File('test.h5', 'w')
f.create_dataset(
    'sz',
    data=numpy.random.random(100),
    compression=hdf5plugin.SZ())
f.close()
```

--------------------------------

### Run Self-Contained Tests in Python

Source: https://hdf5plugin.readthedocs.io/en/latest/contribute.html

Execute the project's self-contained tests directly from a Python interpreter. Ensure the 'hdf5plugin' library is installed.

```python
import hdf5plugin.test
hdf5plugin.test.run_tests()
```

--------------------------------

### Get HDF5 Filter Classes

Source: https://hdf5plugin.readthedocs.io/en/latest/usage.html

Retrieves specific HDF5 filter classes by name or ID. Defaults to all available filters if no arguments are provided.

```python
import hdf5plugin

# Get all filter classes
all_filters = hdf5plugin.get_filters()

# Get specific filter classes
blosc_filters = hdf5plugin.get_filters(['blosc', 'blosc2'])

```

--------------------------------

### Get hdf5plugin Path in Python

Source: https://hdf5plugin.readthedocs.io/en/latest/_sources/usage.rst.txt

Retrieve the plugin path for hdf5plugin. This path is used to set the HDF5_PLUGIN_PATH environment variable for non-Python applications.

```python
import hdf5plugin; print(hdf5plugin.PLUGIN_PATH)
```

--------------------------------

### Create Compressed Dataset with Blosc2 Filter (Raw)

Source: https://hdf5plugin.readthedocs.io/en/latest/hdf5plugin_EuropeanHUG2023/presentation.html

Demonstrates creating a compressed dataset using the Blosc2 filter with its raw HDF5 filter identifier and options tuple.

```python
h5file = h5py.File("new_file_blosc2_bitshuffle_lz4.h5", mode="w")
h5file.create_dataset(
    "/compressed_data",
    data=data,
    compression=32026,  # Blosc2 HDF5 filter identifier
    # options: 0, 0, 0, 0, level, filter, compression
    compression_opts=(0, 0, 0, 0, 5, 2, 1)
)
h5file.close()
```

--------------------------------

### Blosc Class Documentation

Source: https://hdf5plugin.readthedocs.io/en/latest/hdf5plugin_EuropeanHUG2022.html

This section provides the help documentation for the hdf5plugin.Blosc class, detailing its constructor parameters and available options for Blosc compression.

```APIDOC
## Blosc Class Help
help(hdf5plugin.Blosc)
```

--------------------------------

### Get HDF5 Plugin Path

Source: https://hdf5plugin.readthedocs.io/en/latest/hdf5plugin_EuropeanHUG2021.html

Retrieves the path where HDF5 compression filter plugins are stored by hdf5plugin. This path can be set as the HDF5_PLUGIN_PATH environment variable.

```python
# Directory where HDF5 compression filters are stored
hdf5plugin.PLUGINS_PATH
```

--------------------------------

### Create Compressed Dataset with hdf5plugin.Bitshuffle

Source: https://hdf5plugin.readthedocs.io/en/latest/hdf5plugin_EuropeanHUG2021.html

Shows how to create a compressed HDF5 dataset using the hdf5plugin.Bitshuffle helper. This is a more Pythonic way to apply the filter.

```python
h5file = h5py.File("new_file_bitshuffle_lz4.h5", mode="w")
h5file.create_dataset(
    "/compressed_data_bitshuffle_lz4",
    data=data,
    **hdf5plugin.Bitshuffle()  # Or: **hdf5plugin.BitShuffle(lz4=True)
)
h5file.close()
```

--------------------------------

### Set HDF5 Plugin Path (Command Line)

Source: https://hdf5plugin.readthedocs.io/en/latest/usage.html

Prints the HDF5 plugin path to the console, which can be used to set the HDF5_PLUGIN_PATH environment variable for non-Python applications.

```bash
python -c "import hdf5plugin; print(hdf5plugin.PLUGIN_PATH)"

```

--------------------------------

### Get Dataset Compression Configuration

Source: https://hdf5plugin.readthedocs.io/en/latest/usage.html

Retrieve compression filter configuration from HDF5 dataset's low-level API and instantiate filter configurations using hdf5plugin.

```APIDOC
## Get dataset compression

For **built-in** compression filters (i.e., GZIP, LZF, SZIP), dataset compression configuration can be retrieved with h5py.Dataset’s compression and compression_opts properties.
For **third-party** compression filters such as the one supported by hdf5plugin, the dataset compression configuration is stored in HDF5 filter pipeline. This filter pipeline configuration can be retrieved with h5py.Dataset “low level” API. For a given h5py.Dataset, `dataset`:
```python
create_plist = dataset.id.get_create_plist()

for index in range(create_plist.get_nfilters()):
    filter_id, _, filter_options, _ = create_plist.get_filter(index)
    print(filter_id, filter_options)

```

For compression filters supported by hdf5plugin, `hdf5plugin.from_filter_options()` instantiates the filter configuration from the filter id and options.

`hdf5plugin.from_filter_options(_filter_id_ , _filter_options_)`
    Returns corresponding compression filter configuration instance.
```python
create_plist = dataset.id.get_create_plist()

compression_filters = []

for index in range(create_plist.get_nfilters()):
    filter_id, _, filter_options, _ = create_plist.get_filter(index)
    if filter_id in hdf5plugin.FILTERS.values():
        compression_filters.append(hdf5plugin.from_filter_options(filter_id, filter_options))

```


    Parameters:
        * **filter_id** (`int` | `str`) – HDF5 compression filter ID
        * **filter_options** (`tuple`[`int`, `...`]) – Compression filter configuration as stored in HDF5 datasets

    Raises:
        * **ValueError** – Unsupported or invalid filter_id, filter_options combination
        * **NotImplementedError** – Given filter or version of the filter is not supported

    Return type:
        `FilterRefBase`
```

--------------------------------

### Load Benchmark Results

Source: https://hdf5plugin.readthedocs.io/en/latest/hdf5plugin_EuropeanHUG2023/benchmark.html

This code loads benchmark data from a 'benchmark.json' file and initializes Result objects. Make sure 'benchmark.json' exists in the current directory.

```python
import json

benchmarks = json.load(open("benchmark.json"))
config = benchmarks["config"]
results = {k: Result(**v) for k, v in benchmarks["results"].items()}

```

--------------------------------

### Check Code with Flake8

Source: https://hdf5plugin.readthedocs.io/en/latest/contribute.html

Perform static code analysis using 'flake8' to check for style guide violations and potential errors. Run from the source directory.

```bash
flake8
```

--------------------------------

### Initialize filter with libHDF5 symbols (C)

Source: https://hdf5plugin.readthedocs.io/en/latest/hdf5plugin_EuropeanHUG2021.html

Initializes the compression filter by loading symbols from libHDF5 dynamically. This is specific to Linux/macOS environments.

```c
typedef size_t (* DL_func_H5Tget_size)(hid_t type_id);
static struct { /* Structure storing HDF5 function pointers */
    DL_func_H5Tget_size H5Tget_size;
} DL_H5Functions = {NULL};

/* Init wrapper by loading symbols from `libHDF5` */
int init_filter(const char* libname) {
    void * handle = dlopen(libname, RTLD_LAZY | RTLD_LOCAL);  /*Load libHDF5*/
    DL_H5Functions.H5Tget_size = (DL_func_H5Tget_size)dlsym(handle, "H5Tget_size");
}
```

--------------------------------

### Get HDF5 Dataset Create Property List in Python

Source: https://hdf5plugin.readthedocs.io/en/latest/_sources/usage.rst.txt

Retrieve the create property list for an HDF5 dataset to inspect its filters. This is useful for understanding the compression settings applied to a dataset.

```python
create_plist = dataset.id.get_create_plist()

for index in range(create_plist.get_nfilters()):
    filter_id, _, filter_options, _ = create_plist.get_filter(index)
    print(filter_id, filter_options)
```

--------------------------------

### Create Compressed Dataset with Bitshuffle/LZ4

Source: https://hdf5plugin.readthedocs.io/en/latest/hdf5plugin_EuropeanHUG2021.html

Demonstrates creating an HDF5 dataset using the Bitshuffle filter with LZ4 compression. This method uses the filter identifier directly.

```python
h5file = h5py.File("new_file_bitshuffle_lz4.h5", mode="w")
h5file.create_dataset(
    "/compressed_data_bitshuffle_lz4",
    data=data,
    compression=32008,  # bitshuffle/lz4 HDF5 filter identifier
    compression_opts=(0, 2)  # options: default number of elements/block, enable LZ4
)
h5file.close()
```

--------------------------------

### Run Tests with HDF5 Files

Source: https://hdf5plugin.readthedocs.io/en/latest/contribute.html

Execute tests that require actual HDF5 files. This command should be run from the source directory of the project to ensure correct file path resolution.

```bash
python test/test.py
```