--- modeller-9.25/modlib/modeller/__init__.py	(original)
+++ modeller-9.25/modlib/modeller/__init__.py	(refactored)
@@ -48,7 +48,7 @@
         return sys.maxsize > 2**32
     # This works on older Pythons, but not in Python 3
     else:
-        return type(sys.dllhandle) == long
+        return type(sys.dllhandle) == int
 
 # Special processing on Windows to find _modeller.pyd and Modeller DLLs:
 if hasattr(config, 'install_dir') and hasattr(sys, 'dllhandle'):
--- modeller-9.25/modlib/modeller/coordinates.py	(original)
+++ modeller-9.25/modlib/modeller/coordinates.py	(refactored)
@@ -147,7 +147,7 @@
         (startres, endres) = self._get_resind()
         (startatm, endatm) = get_residue_atom_indices(self.seq, startres,
                                                       endres)
-        return (range(startatm+1, endatm+1), self.seq)
+        return (list(range(startatm+1, endatm+1)), self.seq)
 
     atoms = property(__get_atoms, doc="List of all atoms in this chain")
 
@@ -158,7 +158,7 @@
     def get_atom_indices(self):
         (startind, endind) = get_residue_atom_indices(self.mdl, self._num,
                                                       self._num + 1)
-        return range(startind + 1, endind + 1), self.mdl
+        return list(range(startind + 1, endind + 1)), self.mdl
 
     def __repr__(self):
         # Get residue number before we do anything else. For alignment
@@ -252,7 +252,7 @@
     def get_atom_indices(self):
         (startind, endind) = get_residue_atom_indices(self.mdl, self.offset,
                                                       self.offset + len(self))
-        return range(startind + 1, endind + 1), self.mdl
+        return list(range(startind + 1, endind + 1)), self.mdl
 
     def __getitem__(self, indx):
         ret = modutil.handle_seq_indx(self, indx, self.mdl._indxres,
@@ -398,7 +398,7 @@
             return self.mdl.natm
 
     def get_atom_indices(self):
-        return range(self.offset + 1, self.offset + len(self) + 1), self.mdl
+        return list(range(self.offset + 1, self.offset + len(self) + 1)), self.mdl
 
     def __getitem__(self, indx):
         ret = modutil.handle_seq_indx(self, indx, self.mdl._indxatm,
--- modeller-9.25/modlib/modeller/id_table.py	(original)
+++ modeller-9.25/modlib/modeller/id_table.py	(refactored)
@@ -40,7 +40,7 @@
 def write_seqid_matrix(fh, coder, mat):
     """Write a sequence identity matrix to a file"""
     nseq = len(mat)
-    print(" " * 9 + "".join([ s[:8] for s in coder ]))
+    print((" " * 9 + "".join([ s[:8] for s in coder ])))
     for n1 in range(nseq):
         fh.write(coder[n1][:8] + " " + \
                  "".join(["%8d" % (mat[n1][n2]+0.5) for n2 in range(nseq)]))
--- modeller-9.25/modlib/modeller/libraries.py	(original)
+++ modeller-9.25/modlib/modeller/libraries.py	(refactored)
@@ -32,7 +32,7 @@
             return BytesIO(*args)
     else:
         def _make_bytes_io(self, *args):
-            from cStringIO import StringIO
+            from io import StringIO
             return StringIO(*args)
 
     def __getstate__(self):
--- modeller-9.25/modlib/modeller/model.py	(original)
+++ modeller-9.25/modlib/modeller/model.py	(refactored)
@@ -121,7 +121,7 @@
 
     def get_atom_indices(self):
         """Get the indices of all atoms in this model"""
-        return (range(1, self.natm+1), self)
+        return (list(range(1, self.natm+1)), self)
 
     def read(self, file, model_format='PDB',
              model_segment=('FIRST:@', 'LAST:'), io=None,
@@ -340,7 +340,7 @@
         dope_score = sel.assess_dope()
         scorer = normalized_dope.DOPEScorer(self)
         z_score = scorer.get_z_score(dope_score)
-        print(">> Normalized DOPE z score: %.3f" % z_score)
+        print((">> Normalized DOPE z score: %.3f" % z_score))
         return z_score
 
     def assess_normalized_dopehr(self):
@@ -351,7 +351,7 @@
         dope_score = sel.assess_dopehr()
         scorer = normalized_dope.DOPEHRScorer(self)
         z_score = scorer.get_z_score(dope_score)
-        print(">> Normalized DOPE-HR z score: %.3f" % z_score)
+        print((">> Normalized DOPE-HR z score: %.3f" % z_score))
         return z_score
 
     def get_normalized_dope_profile(self):
--- modeller-9.25/modlib/modeller/model_topology.py	(original)
+++ modeller-9.25/modlib/modeller/model_topology.py	(refactored)
@@ -50,7 +50,7 @@
         self.check_args = args
     def __iter__(self):
         return self
-    def next(self):
+    def __next__(self):
         while True:
             atoms = self.__int_next()
             if self.check_func is None \
@@ -82,7 +82,7 @@
         self.check_args = args
     def __iter__(self):
         return self
-    def next(self):
+    def __next__(self):
         while True:
             atoms = self.__int_next()
             if self.check_func is None \
--- modeller-9.25/modlib/modeller/physical.py	(original)
+++ modeller-9.25/modlib/modeller/physical.py	(refactored)
@@ -31,7 +31,7 @@
     def __init__(self, default=1.0, **keys):
         self._default = default
         self._dict = {}
-        for (term,val) in keys.items():
+        for (term,val) in list(keys.items()):
             term = eval("%s" % term)
             self[term] = val
 
--- modeller-9.25/modlib/modeller/salign.py	(original)
+++ modeller-9.25/modlib/modeller/salign.py	(refactored)
@@ -38,8 +38,8 @@
             return aln.salign(auto_overhang=True, overhang_auto_limit=5,
                               overhang_factor=1, **keys)
         except modeller.ModellerError:
-            print("SALIGN with auto_overhang failed: %s" \
-                  % str(sys.exc_info()[1]))
+            print(("SALIGN with auto_overhang failed: %s" \
+                  % str(sys.exc_info()[1])))
             print("Retrying without auto_overhang")
             return aln.salign(**keys)
 
@@ -118,13 +118,13 @@
                 self.qscore = res.qscorepct
                 self.aln.write(file=output_aln_file, alignment_format='PIR')
                 better = True
-            print("Qlty scrs %g\t%g\t%g" % (open_penalty, extend_penalty,
-                                            res.qscorepct))
+            print(("Qlty scrs %g\t%g\t%g" % (open_penalty, extend_penalty,
+                                            res.qscorepct)))
         except modeller.ModellerError:
-            print("Set of parameters %s %g %g resulted in the "
+            print(("Set of parameters %s %g %g resulted in the "
                   "following error\t%s" % (str(weights), open_penalty,
                                            extend_penalty,
-                                           str(sys.exc_info()[1])))
+                                           str(sys.exc_info()[1]))))
         return better
 
 
@@ -181,7 +181,7 @@
                 best.try_struc_align(opfile, opfile2, fw2, ogp3d, egp3d,
                                      align_block)
 
-    print("final max quality = %g" % best.qscore)
+    print(("final max quality = %g" % best.qscore))
 
     if best.found_struc_align:
         aln.clear()
--- modeller-9.25/modlib/modeller/saxsdata.py	(original)
+++ modeller-9.25/modlib/modeller/saxsdata.py	(refactored)
@@ -206,7 +206,7 @@
         try:
             fh = open(saxsfilename,'r')
         except:
-            print("file "+saxsfilename+" not found :(")
+            print(("file "+saxsfilename+" not found :("))
             return
         fh.close()
         ns = 0
@@ -225,8 +225,8 @@
             s_low = s_min - .001
         if (not s_hi):
             s_hi = s_max + .001
-        print("s_min=%s, s_max=%s" % (str(s_min), str(s_max)))
-        print("s_low=%s, s_hi=%s" % (str(s_low), str(s_hi)))
+        print(("s_min=%s, s_max=%s" % (str(s_min), str(s_max))))
+        print(("s_low=%s, s_hi=%s" % (str(s_low), str(s_hi))))
         self.ini_saxs(atmsel,
                  filename=formfacfilename,
                  s_min=s_min, s_max=s_max, maxs=ns, nmesh=ns, natomtyp=natomtyp,
--- modeller-9.25/modlib/modeller/selection.py	(original)
+++ modeller-9.25/modlib/modeller/selection.py	(refactored)
@@ -23,7 +23,7 @@
             return self.mdl.atoms[obj - 1]
     else:
         def next(self):
-            obj = self.seliter.next()
+            obj = next(self.seliter)
             return self.mdl.atoms[obj - 1]
 
 class selection(object):
@@ -52,7 +52,7 @@
            :rtype: list of ints
         """
         if sys.version_info[:2] == (2,3):
-            keys = self.__selection.keys()
+            keys = list(self.__selection.keys())
             keys.sort()
         else:
             keys = sorted(self.__selection.keys())
@@ -722,9 +722,9 @@
     def assess(self, assessor, output='SHORT NO_REPORT', **vars):
         """Assess with the given assessor object
            (e.g. :class:`soap_loop.Scorer`)."""
-        print(">> Model assessment by %s" % assessor.name)
+        print((">> Model assessment by %s" % assessor.name))
         molpdf, terms = assessor._assess(self, output=output, **vars)
-        print("%s                     : %12.6f" % (assessor.name, molpdf))
+        print(("%s                     : %12.6f" % (assessor.name, molpdf)))
         return molpdf
 
     def _dope_energy(self, gprsr, name, output='SHORT NO_REPORT',
@@ -733,7 +733,7 @@
                                                     nonbond_spline=1.), **vars):
         """Internal function to do DOPE or DOPE-HR assessment"""
         mdl = self.__mdl
-        print(">> Model assessment by %s potential" % name)
+        print((">> Model assessment by %s potential" % name))
         edat = self.get_dope_energy_data()
         old_gprsr = mdl.group_restraints
         mdl.group_restraints = gprsr
@@ -744,7 +744,7 @@
                             **vars)
         finally:
             mdl.group_restraints = old_gprsr
-        print("%s score               : %12.6f" % (name, molpdf))
+        print(("%s score               : %12.6f" % (name, molpdf)))
         return molpdf
 
     def debug_function(self, residue_span_range=(0, 99999),
--- modeller-9.25/modlib/modeller/test.py	(original)
+++ modeller-9.25/modlib/modeller/test.py	(refactored)
@@ -2,7 +2,7 @@
 import modeller
 import math
 try:
-    from cStringIO import StringIO
+    from io import StringIO
 except ImportError:
     from io import StringIO
 import sys
@@ -150,7 +150,7 @@
         diff = abs(num1 - num2)
         if msg is None:
             msg = "%f != %f within %g" % (num1, num2, tolerance)
-        self.assert_(diff < tolerance, msg)
+        self.assertTrue(diff < tolerance, msg)
 
     def run_capture_stdout(self, method, *args, **keys):
         """Run a method and capture its standard output. Returns both the
--- modeller-9.25/modlib/modeller/automodel/automodel.py	(original)
+++ modeller-9.25/modlib/modeller/automodel/automodel.py	(refactored)
@@ -203,13 +203,13 @@
 
     def write_ok_summary(self, all, modeltyp):
         """Print out a summary of all successfully generated models"""
-        print("\n>> Summary of successfully produced %s:" % modeltyp)
-        fields = [x for x in all[0].keys() if x.endswith(' score')]
+        print(("\n>> Summary of successfully produced %s:" % modeltyp))
+        fields = [x for x in list(all[0].keys()) if x.endswith(' score')]
         fields.sort()
         fields = ['molpdf'] + fields
         header = '%-25s ' % 'Filename' + " ".join(['%14s' % x for x in fields])
         print(header)
-        print('-' * len(header))
+        print(('-' * len(header)))
         for mdl in all:
             text = '%-25s' % mdl['name']
             for field in fields:
@@ -222,9 +222,9 @@
 
     def write_failure_summary(self, all, modeltyp):
         """Print out a summary of all failed models"""
-        print("\n>> Summary of failed %s:" % modeltyp)
+        print(("\n>> Summary of failed %s:" % modeltyp))
         for mdl in all:
-            print("%-25s %s" % (mdl['name'], mdl['failure']))
+            print(("%-25s %s" % (mdl['name'], mdl['failure'])))
         print('')
 
     def rd_restraints(self):
@@ -692,8 +692,8 @@
         elif atmsel.get_model() is not self:
             raise ModellerError("selection is defined on the wrong model")
         elif len(atmsel) < len(self.atoms):
-            print("%d (of %d total) atoms selected for optimization" \
-                  % (len(atmsel), len(self.atoms)))
+            print(("%d (of %d total) atoms selected for optimization" \
+                  % (len(atmsel), len(self.atoms))))
         return atmsel
 
     def mkhomcsr(self, atmsel, aln):
@@ -774,9 +774,9 @@
         selstd = selection(self).only_std_residues()
         selca = selstd.only_atom_types('CA')
 
-        print("%d atoms in HETATM/BLK residues constrained\n" % len(selhet) \
+        print(("%d atoms in HETATM/BLK residues constrained\n" % len(selhet) \
               + "to protein atoms within %.2f angstroms\n" % bond_distance \
-              + "and protein CA atoms within %.2f angstroms" % ca_distance)
+              + "and protein CA atoms within %.2f angstroms" % ca_distance))
         # Build the bonds first; this avoids duplicated CA-ligand bonds since
         # make_distance() will not build restraints that are already on the
         # nonbond exclusion list
@@ -823,8 +823,8 @@
         selhet = selhet.only_no_topology()
 
         # Intra-residue:
-        print("%d atoms in residues without defined topology\n" % len(selhet) \
-              + "constrained to be rigid bodies")
+        print(("%d atoms in residues without defined topology\n" % len(selhet) \
+              + "constrained to be rigid bodies"))
         rsr = self.restraints
         rsr.make_distance(selhet, selhet, aln=aln,
                           distance_rsr_model=7, maximal_distance=10.0,
@@ -898,8 +898,8 @@
             print("\nThe following CHARMM atom type assignments were made:")
             print("      Atom                 Old type        New type")
             for atom, old_type, new_type in zip(sel, old_types, new_types):
-                print("      %-20s %-15s %-15s"
-                      % (str(atom), fmt_typ(old_type), fmt_typ(new_type)))
+                print(("      %-20s %-15s %-15s"
+                      % (str(atom), fmt_typ(old_type), fmt_typ(new_type))))
 
     def select_atoms(self):
         """Select atoms to be optimized in the model building procedure. By