Fix: Use iteritems from six for Python3 compatability

psamm/command.py

@@ -48,7 +48,7 @@
 from . import fluxanalysis, massconsistency, fastcore
 from .lpsolver import generic
 
-from six import add_metaclass
+from six import add_metaclass, iteritems
 
 # Module-level logging
 logger = logging.getLogger(__name__)
@@ -430,7 +430,7 @@ def run_fba_minimized(self, reaction):
         fmin_fluxes = dict(fluxanalysis.flux_minimization(
             self._mm, {reaction: optimum}, solver=solver))
         count = 0
-        for reaction_id, flux in fmin_fluxes.iteritems():
+        for reaction_id, flux in iteritems(fmin_fluxes):
             if fba_fluxes[reaction_id] - epsilon > flux:
                 count += 1
             yield reaction_id, fba_fluxes[reaction_id], flux
@@ -446,7 +446,7 @@ def run_tfba(self, reaction):
         fluxes = dict(fluxanalysis.flux_balance(
             self._mm, reaction, tfba=True, solver=solver))
 
-        for reaction_id, flux in fluxes.iteritems():
+        for reaction_id, flux in iteritems(fluxes):
             yield reaction_id, fba_fluxes[reaction_id], flux
 
 
@@ -1237,7 +1237,7 @@ def main(command_class=None):
 
         # Create parsers for subcommands
         subparsers = parser.add_subparsers(title='Command')
-        for name, values in sorted(commands.iteritems()):
+        for name, values in sorted(iteritems(commands)):
             title, command_class = values
             subparser = subparsers.add_parser(name, help=title)
             subparser.set_defaults(command=command_class)

psamm/datasource/native.py

@@ -31,7 +31,7 @@
 import csv
 
 import yaml
-from six import string_types
+from six import string_types, iteritems
 
 from ..reaction import Reaction, Compound
 from . import modelseed
@@ -303,7 +303,7 @@ def parse_compound_table_file(path, f):
         if 'id' not in row or row['id'].strip() == '':
             raise ParseError('Expected `id` column in table')
 
-        props = {key: value for key, value in row.iteritems() if value != ''}
+        props = {key: value for key, value in iteritems(row) if value != ''}
         yield CompoundEntry(row['id'], props)
 
 
@@ -446,7 +446,7 @@ def parse_reaction_table_file(f):
         if 'id' not in row or row['id'].strip() == '':
             raise ParseError('Expected `id` column in table')
 
-        props = {key: value for key, value in row.iteritems() if value != ''}
+        props = {key: value for key, value in iteritems(row) if value != ''}
 
         if 'equation' in props:
             props['equation'] = modelseed.parse_reaction(props['equation'])

psamm/datasource/sbml.py

@@ -23,7 +23,7 @@
 from functools import partial
 from itertools import count
 
-from six import itervalues
+from six import itervalues, iteritems
 
 from ..reaction import Reaction, Compound
 
@@ -422,7 +422,7 @@ def write_model(self, file, model, compounds):
         # Create list of compartments
         compartments = ET.SubElement(
             model_tag, self._sbml_tag('listOfCompartments'))
-        for compartment, compartment_id in model_compartments.iteritems():
+        for compartment, compartment_id in iteritems(model_compartments):
             compartment_tag = ET.SubElement(
                 compartments, self._sbml_tag('compartment'))
             compartment_tag.set(self._sbml_tag('id'), compartment_id)
@@ -431,7 +431,7 @@ def write_model(self, file, model, compounds):
         # Create list of species
         species_list = ET.SubElement(
             model_tag, self._sbml_tag('listOfSpecies'))
-        for species, species_id in model_species.iteritems():
+        for species, species_id in iteritems(model_species):
             species_tag = ET.SubElement(species_list,
                                         self._sbml_tag('species'))
             species_tag.set(self._sbml_tag('id'), species_id)

psamm/gapfill.py

@@ -20,6 +20,8 @@
 This implements a variant of the algorithms described in [Kumar07]_.
 """
 
+from six import iteritems
+
 from .lpsolver import lp
 
 
@@ -51,7 +53,7 @@ def gapfind(model, solver, epsilon=1e-5, v_max=1000):
 
     # Define constraints on production of metabolites in reaction
     binary_cons_lhs = {compound: 0 for compound in model.compounds}
-    for spec, value in model.matrix.iteritems():
+    for spec, value in iteritems(model.matrix):
         compound, reaction_id = spec
         if value != 0 and (reaction_id in model.reversible or value > 0):
             prob.define(('w', reaction_id, compound),
@@ -74,15 +76,15 @@ def gapfind(model, solver, epsilon=1e-5, v_max=1000):
     objective = sum(prob.var(('xp', compound)) for compound in model.compounds)
     prob.set_linear_objective(objective)
 
-    for compound, lhs in binary_cons_lhs.iteritems():
+    for compound, lhs in iteritems(binary_cons_lhs):
         prob.add_linear_constraints(lhs >= prob.var(('xp', compound)))
 
     # Define mass balance constraints
     massbalance_lhs = {compound: 0 for compound in model.compounds}
-    for spec, value in model.matrix.iteritems():
+    for spec, value in iteritems(model.matrix):
         compound, reaction_id = spec
         massbalance_lhs[compound] += prob.var(('v', reaction_id)) * value
-    for compound, lhs in massbalance_lhs.iteritems():
+    for compound, lhs in iteritems(massbalance_lhs):
         # The constraint is merely >0 meaning that we have implicit sinks
         # for all compounds.
         prob.add_linear_constraints(lhs >= 0)
@@ -156,7 +158,7 @@ def gapfill(model, core, blocked, solver, epsilon=1e-5, v_max=1000):
 
     # Define constraints on production of blocked metabolites in reaction
     binary_cons_lhs = {compound: 0 for compound in blocked}
-    for spec, value in model.matrix.iteritems():
+    for spec, value in iteritems(model.matrix):
         compound, reaction_id = spec
         if compound in blocked and value != 0:
             prob.define(('w', reaction_id, compound),
@@ -171,16 +173,16 @@ def gapfill(model, core, blocked, solver, epsilon=1e-5, v_max=1000):
             if reaction_id in model.reversible or value > 0:
                 binary_cons_lhs[compound] += w
 
-    for compound, lhs in binary_cons_lhs.iteritems():
+    for compound, lhs in iteritems(binary_cons_lhs):
         if compound in blocked:
             prob.add_linear_constraints(lhs >= 1)
 
     # Define mass balance constraints
     massbalance_lhs = {compound: 0 for compound in model.compounds}
-    for spec, value in model.matrix.iteritems():
+    for spec, value in iteritems(model.matrix):
         compound, reaction_id = spec
         massbalance_lhs[compound] += prob.var(('v', reaction_id)) * value
-    for compound, lhs in massbalance_lhs.iteritems():
+    for compound, lhs in iteritems(massbalance_lhs):
         # The constraint is merely >0 meaning that we have implicit sinks
         # for all compounds.
         prob.add_linear_constraints(lhs >= 0)

psamm/util.py

@@ -20,6 +20,8 @@
 import re
 import math
 
+from six import iteritems
+
 
 class LoggerFile(object):
     """File-like object that forwards to a logger.
@@ -80,20 +82,20 @@ def update_weight(value):
         # the next is less than epsilon.
         while True:
             weights = {identifier: update_weight(value)
-                       for identifier, value in result.iteritems()}
+                       for identifier, value in iteritems(result)}
             kwargs['weights'] = weights
 
             last_result = result
             full_result = f(*args, **kwargs)
             result = dict_result(full_result)
 
             delta = math.sqrt(sum(pow(value - last_result[identifier], 2)
-                                  for identifier, value in result.iteritems()))
+                                  for identifier, value in iteritems(result)))
             if delta < epsilon:
                 break
 
         if isinstance(full_result, tuple):
-            return (result.iteritems(),) + full_result[1:]
-        return result.iteritems()
+            return (iteritems(result),) + full_result[1:]
+        return iteritems(result)
 
     return convex_cardinality_wrapper