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from collections import defaultdict
from typing import Union
from dataclasses import dataclass
import argparse
from functools import partial, reduce
import operator
import math
import h5py

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import argparse
from warnings import warn
import h5py


WARN_UBLOCK_SIZE = 10 * 1024 * 1024
COPY_BLOCK_SIZE = 10 * 1024 * 1024

parser = argparse.ArgumentParser(
    description='Add empty user block to an HDF5 file.',

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@startmindmap HDF5 Ecosystem

<style>
node {
    RoundCorner 40
    MaximumWidth 300
    FontName Helvetica
    FontSize 18
}
rootNode {

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import sys
import h5py


def comp_ratio(name, obj):
    if isinstance(obj, h5py.Dataset) and obj.chunks is not None:
        if obj.id.get_create_plist().get_nfilters():
            stor_size = obj.id.get_storage_size()
            if stor_size != 0:
                ratio = float(obj.nbytes) / float(stor_size)

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@startuml HDF5 Universe

title HDF5 Universe

together {
    folder "Abstract\nData Model" as ADM
    folder "Programming\nModel" as PM
    folder Library as L
}

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# Requirements:
# HDF5 library version 1.10.5 or later
# h5py version 3.0 or later
# pip install git+https://github.com/HDFGroup/zarr-python.git@hdf5

import logging
from urllib.parse import urlparse, urlunparse
import numpy as np
import h5py
import zarr

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{
    "metadata": {
        ".zattrs": {
            "Conventions": "UGRID-0.9.0",
            "_FillValue": -99999.0,
            "_NCProperties": "version=1|h5netcdfversion=0.6.1|hdf5libversion=1.10.2",
            "a00": 0.35,
            "agrid": "grid",
            "b00": 0.3,
            "c00": 0.35,

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#!/usr/bin/env python3
"""
Print storage information for every HDF5 dataset in a file.

Run "store_info.py --help" for information.
"""
from os import SEEK_SET
import argparse
import json
from functools import partial

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