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diff --git a/ml_exp/qm7db.py b/ml_exp/qm7db.py
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+"""MIT License
+
+Copyright (c) 2019 David Luevano Alvarado
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+"""
+import os
+import numpy as np
+import random
+
+
+# 'hof_qm7.txt.txt' retrieved from
+# https://github.com/qmlcode/tutorial
+def qm7db(zi_data,
+          data_path,
+          r_seed=111,
+          return_atoms=False):
+    """
+    Reads molecule database and extracts
+    its contents as usable variables.
+    zi_data: dictionary containing nuclear charge data.
+    data_path: path to the data directory.
+    r_seed: random seed to use for the shuffling.
+    return_atoms: if atom list should be returned.
+    """
+    os.chdir(data_path)
+
+    fname = 'hof_qm7.txt'
+    with open(fname, 'r') as infile:
+        lines = infile.readlines()
+
+    # Temporary energy dictionary.
+    energy_temp = dict()
+
+    for line in lines:
+        xyz_data = line.split()
+
+        xyz_name = xyz_data[0]
+        hof = float(xyz_data[1])
+        dftb = float(xyz_data[2])
+        # print(xyz_name, hof, dftb)
+
+        energy_temp[xyz_name] = np.array([hof, hof - dftb])
+
+    # Use a random seed.
+    random.seed(r_seed)
+
+    et_keys = list(energy_temp.keys())
+    random.shuffle(et_keys)
+
+    # Temporary energy dictionary, shuffled.
+    energy_temp_shuffled = dict()
+    for key in et_keys:
+        energy_temp_shuffled.update({key: energy_temp[key]})
+
+    mol_data = []
+    mol_nc_data = []
+    atoms = []
+    # Actual reading of the xyz files.
+    for i, k in enumerate(energy_temp_shuffled.keys()):
+        with open(k, 'r') as xyz_file:
+            lines = xyz_file.readlines()
+
+        len_lines = len(lines)
+        mol_temp_data = []
+        mol_nc_temp_data = np.array(np.zeros(len_lines-2))
+        atoms_temp = []
+        for j, line in enumerate(lines[2:len_lines]):
+            line_list = line.split()
+
+            atoms_temp.append(line_list[0])
+            mol_nc_temp_data[j] = float(zi_data[line_list[0]])
+            line_data = np.array(np.asarray(line_list[1:4], dtype=float))
+            mol_temp_data.append(line_data)
+
+        mol_data.append(mol_temp_data)
+        mol_nc_data.append(mol_nc_temp_data)
+        atoms.append(atoms_temp)
+
+    # Convert everything to a numpy array.
+    molecules = np.array([np.array(mol) for mol in mol_data])
+    nuclear_charge = np.array([nc_d for nc_d in mol_nc_data])
+    energy_pbe0 = np.array([energy_temp_shuffled[k][0]
+                            for k in energy_temp_shuffled.keys()])
+    energy_delta = np.array([energy_temp_shuffled[k][1]
+                             for k in energy_temp_shuffled.keys()])
+
+    if return_atoms:
+        return molecules, nuclear_charge, energy_pbe0, energy_delta, atoms
+    return molecules, nuclear_charge, energy_pbe0, energy_delta