How to read HDF5 files in Python

Read HDF5

import h5pyfilename = "file.hdf5"with h5py.File(filename, "r") as f:    # List all groups    print("Keys: %s" % f.keys())    a_group_key = list(f.keys())[0]    # Get the data    data = list(f[a_group_key])

Write HDF5

import h5py# Create random dataimport numpy as npdata_matrix = np.random.uniform(-1, 1, size=(10, 3))# Write data to HDF5with h5py.File("file.hdf5", "w") as data_file:    data_file.create_dataset("group_name", data=data_matrix)

See h5py docs for more information.

Alternatives

• JSON: Nice for writing human-readable data; VERY commonly used (read & write)
• CSV: Super simple format (read & write)
• pickle: A Python serialization format (read & write)
• MessagePack (Python package): More compact representation (read & write)
• HDF5 (Python package): Nice for matrices (read & write)
• XML: exists too *sigh* (read & write)

For your application, the following might be important:

• Support by other programming languages
• Reading / writing performance
• Compactness (file size)

See also: Comparison of data serialization formats

In case you are rather looking for a way to make configuration files, you might want to read my short article Configuration files in Python

Reading the file

import h5pyf = h5py.File(file_name, mode)

Studying the structure of the file by printing what HDF5 groups are present

for key in f.keys():    print(key) #Names of the groups in HDF5 file.

Extracting the data

#Get the HDF5 groupgroup = f[key]#Checkout what keys are inside that group.for key in group.keys():    print(key)data = group[some_key_inside_the_group][()]#Do whatever you want with data#After you are donef.close()

you can use Pandas.

import pandas as pdpd.read_hdf(filename,key)