+-- Dataset
|  +-- (Raw) Data Values (eg: a 4 x 5 x 6 matrix)
|  +-- Metadata
|  |  +-- Dataspace (eg: Rank = 3, Dimensions = {4, 5, 6})
|  |  +-- Datatype (eg: Integer)
|  |  +-- Properties (eg: Chuncked, Compressed)
|  |  +-- Attributes (eg: attr1 = 32.4, attr2 = "hello", ...)
|

+-- /
|  +-- group_1
|  |  +-- dataset_1_1
|  |  |  +-- attribute_1_1_1
|  |  |  +-- attribute_1_1_2
|  |  |  +-- ...
|  |  |
|  |  +-- dataset_1_2
|  |  |  +-- attribute_1_2_1
|  |  |  +-- attribute_1_2_2
|  |  |  +-- ...
|  |  |
|  |  +-- ...
|  |
|  +-- group_2
|  |  +-- dataset_2_1
|  |  |  +-- attribute_2_1_1
|  |  |  +-- attribute_2_1_2
|  |  |  +-- ...
|  |  |
|  |  +-- dataset_2_2
|  |  |  +-- attribute_2_2_1
|  |  |  +-- attribute_2_2_2
|  |  |  +-- ...
|  |  |
|  |  +-- ...
|  |
|  +-- ...
|

#!/usr/bin/python
# -*- coding: UTF-8 -*-
#
# Created by WW on Jan. 26, 2020
# All rights reserved.
#

import h5py
import numpy as np

def main():
  #===========================================================================
  # Create a HDF5 file.
  f = h5py.File("h5py_example.hdf5", "w")  # mode = {'w', 'r', 'a'}

  # Create two groups under root '/'.
  g1 = f.create_group("bar1")
  g2 = f.create_group("bar2")

  # Create a dataset under root '/'.
  d = f.create_dataset("dset", data=np.arange(16).reshape([4, 4]))

  # Add two attributes to dataset 'dset'
  d.attrs["myAttr1"] = [100, 200]
  d.attrs["myAttr2"] = "Hello, world!"

  # Create a group and a dataset under group "bar1".
  c1 = g1.create_group("car1")
  d1 = g1.create_dataset("dset1", data=np.arange(10))

  # Create a group and a dataset under group "bar2".
  c2 = g2.create_group("car2")
  d2 = g2.create_dataset("dset2", data=np.arange(10))

  # Save and exit the file.
  f.close()

  ''' h5py_example.hdf5 file structure
  +-- '/'
  |  +--  group "bar1"
  |  |  +-- group "car1"
  |  |  |  +-- None
  |  |  |  
  |  |  +-- dataset "dset1"
  |  |
  |  +-- group "bar2"
  |  |  +-- group "car2"
  |  |  |  +-- None
  |  |  |
  |  |  +-- dataset "dset2"
  |  |  
  |  +-- dataset "dset"
  |  |  +-- attribute "myAttr1"
  |  |  +-- attribute "myAttr2"
  |  |  
  |  
  '''

  #===========================================================================
  # Read HDF5 file.
  f = h5py.File("h5py_example.hdf5", "r")  # mode = {'w', 'r', 'a'}

  # Print the keys of groups and datasets under '/'.
  print(f.filename, ":")
  print([key for key in f.keys()], "\n") 

  #===================================================
  # Read dataset 'dset' under '/'.
  d = f["dset"]

  # Print the data of 'dset'.
  print(d.name, ":")
  print(d[:])

  # Print the attributes of dataset 'dset'.
  for key in d.attrs.keys():
    print(key, ":", d.attrs[key])

  print()

  #===================================================
  # Read group 'bar1'.
  g = f["bar1"]

  # Print the keys of groups and datasets under group 'bar1'.
  print([key for key in g.keys()])

  # Three methods to print the data of 'dset1'.
  print(f["/bar1/dset1"][:])    # 1. absolute path

  print(f["bar1"]["dset1"][:])  # 2. relative path: file[][]

  print(g['dset1'][:])    # 3. relative path: group[]
  # Delete a database.
  # Notice: the mode should be 'a' when you read a file.
  '''
  del g["dset1"]
  '''

  # Save and exit the file
  f.close()

if __name__ == "__main__":
  main()

import h5py
f=h5py.File("myh5py.hdf5","w")
#deset1是数据集的name，（20,）代表数据集的shape，i代表的是数据集的元素类型
d1=f.create_dataset("dset1", (20,), 'i')
for key in f.keys():
  print(key)
  print(f[key].name)
  print(f[key].shape)
  print(f[key].value)

import h5py
import numpy as np
f=h5py.File("myh5py.hdf5","w")

d1=f.create_dataset("dset1",(20,),'i')
#赋值
d1[...]=np.arange(20)
#或者我们可以直接按照下面的方式创建数据集并赋值
f["dset2"]=np.arange(15)

for key in f.keys():
  print(f[key].name)
  print(f[key].value)

import h5py
import numpy as np
f=h5py.File("myh5py.hdf5","w")

#创建一个名字为bar的组
g1=f.create_group("bar")

#在bar这个组里面分别创建name为dset1,dset2的数据集并赋值。
g1["dset1"]=np.arange(10)
g1["dset2"]=np.arange(12).reshape((3,4))

for key in g1.keys():
  print(g1[key].name)
  print(g1[key].value)

import pandas as pd
import numpy as np

# 将mode改成r即可
hdf5 = pd.HDFStore("hello.h5", mode="r")
# 或者
"""
hdfs = pd.read_hdf("hello.h5", key="xxx")
"""