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diff --git a/cython/cython/reader_utils.pyx b/cython/cython/reader_utils.pyx
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+++ b/cython/cython/reader_utils.pyx
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+from cython cimport numeric
+from libcpp.vector cimport vector
+from libcpp.string cimport string
+from libcpp.map cimport map
+from libcpp.pair cimport pair
+import os
+
+"""This file is part of the Gudhi Library. The Gudhi library
+   (Geometric Understanding in Higher Dimensions) is a generic C++
+   library for computational topology.
+
+   Author(s):       Vincent Rouvreau
+
+   Copyright (C) 2017 INRIA
+
+   This program is free software: you can redistribute it and/or modify
+   it under the terms of the GNU General Public License as published by
+   the Free Software Foundation, either version 3 of the License, or
+   (at your option) any later version.
+
+   This program is distributed in the hope that it will be useful,
+   but WITHOUT ANY WARRANTY; without even the implied warranty of
+   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+   GNU General Public License for more details.
+
+   You should have received a copy of the GNU General Public License
+   along with this program.  If not, see <http://www.gnu.org/licenses/>.
+"""
+
+__author__ = "Vincent Rouvreau"
+__copyright__ = "Copyright (C) 2017 INRIA"
+__license__ = "GPL v3"
+
+cdef extern from "Reader_utils_interface.h" namespace "Gudhi":
+    vector[vector[double]] read_matrix_from_csv_file(string off_file, char separator)
+    map[int, vector[pair[double, double]]] read_pers_intervals_grouped_by_dimension(string filename)
+    vector[pair[double, double]] read_pers_intervals_in_dimension(string filename, int only_this_dim)
+
+def read_lower_triangular_matrix_from_csv_file(csv_file='', separator=';'):
+    """Read lower triangular matrix from a CSV style file.
+
+    :param csv_file: A CSV file style name.
+    :type csv_file: string
+    :param separator: The value separator in the CSV file. Default value is ';'
+    :type separator: char
+
+    :returns:  The lower triangular matrix.
+    :rtype: vector[vector[double]]
+    """
+    if csv_file is not '':
+        if os.path.isfile(csv_file):
+            return read_matrix_from_csv_file(str.encode(csv_file), ord(separator[0]))
+    print("file " + csv_file + " not set or not found.")
+    return []
+
+def read_persistence_intervals_grouped_by_dimension(persistence_file=''):
+    """Reads a file containing persistence intervals.
+    Each line might contain 2, 3 or 4 values: [[field] dimension] birth death
+    The return value is an `map[dim, vector[pair[birth, death]]]`
+    where `dim` is an `int`, `birth` a `double`, and `death` a `double`.
+    Note: the function does not check that birth <= death.
+
+    :param persistence_file: A persistence file style name.
+    :type persistence_file: string
+
+    :returns:  The persistence pairs grouped by dimension.
+    :rtype: map[int, vector[pair[double, double]]]
+    """
+    if persistence_file is not '':
+        if os.path.isfile(persistence_file):
+            return read_pers_intervals_grouped_by_dimension(str.encode(persistence_file))
+    print("file " + persistence_file + " not set or not found.")
+    return []
+
+def read_persistence_intervals_in_dimension(persistence_file='', only_this_dim=-1):
+    """Reads a file containing persistence intervals.
+    Each line might contain 2, 3 or 4 values: [[field] dimension] birth death
+    If `only_this_dim` = -1, dimension is ignored and all lines are returned.
+    If `only_this_dim` is >= 0, only the lines where dimension = `only_this_dim`
+    (or where dimension is not specified) are returned.
+    The return value is an `vector[pair[birth, death]]`
+    where `birth` a `double`, and `death` a `double`.
+    Note: the function does not check that birth <= death.
+
+    :param persistence_file: A persistence file style name.
+    :type persistence_file: string
+
+    :returns:  The persistence pairs grouped by dimension.
+    :rtype: map[int, vector[pair[double, double]]]
+    """
+    if persistence_file is not '':
+        if os.path.isfile(persistence_file):
+            return read_pers_intervals_in_dimension(str.encode(persistence_file), only_this_dim)
+    print("file " + persistence_file + " not set or not found.")
+    return []