from python2 to python3 > ok from command line

src/jflow/featureiolib/abstractfeaturereader.py

@@ -51,7 +51,7 @@ class Entry(object):
         return self.attrib[key]
 
     def has(self,attr):
-        return self.attrib.has_key(attr)
+        return attr in self.attrib
         
 class _AbstractFeatureReader(object):
     '''
@@ -63,7 +63,7 @@ class _AbstractFeatureReader(object):
             @param wholefile: If True, then it is ok to read the entire file  into memory. This is faster when there are 
                 many newlines in the file, but may obviously need a lot of memory.
         """
-        if isinstance(file, basestring):
+        if isinstance(file, str):
             file = xopen(file, "r")
         self.fp = file
         self.wholefile = wholefile

src/jflow/featureiolib/bed.py

@@ -21,7 +21,7 @@ import re
 from jflow.seqio import FormatError
 from jflow.seqio import UnknownFileType
 
-from abstractfeaturereader import _AbstractFeatureReader, Entry, boolify, autocast
+from .abstractfeaturereader import _AbstractFeatureReader, Entry, boolify, autocast
 
 
 class BEDReader(_AbstractFeatureReader):
@@ -30,7 +30,7 @@ class BEDReader(_AbstractFeatureReader):
     '''
     def _process_line(self,line):
         row = line.rstrip().split('\t')
-        if len(row) not in range(3,13) : raise FormatError('Invalid number of columns in your BED file {0}'.format( len(row)))
+        if len(row) not in list(range(3,13)) : raise FormatError('Invalid number of columns in your BED file {0}'.format( len(row)))
         return Entry(**{ 'chrom' : row[0], 'chromStart' : row[1], 'chromEnd' : row[2] })
         
     def _streaming_iter(self):

src/jflow/featureiolib/biom.py

@@ -74,7 +74,7 @@ def _bootstrap_selection( OTU_count, nb_total_elts, nb_selected_elts ):
             if elt_index <= (OTU_count[OTU_idx]["nb"] + previous_elt):
                 find = True
                 OTU_id = OTU_count[OTU_idx]["id"]
-                if selected_OTU.has_key( OTU_id ):
+                if OTU_id in selected_OTU:
                     selected_OTU[OTU_id] += 1
                 else:
                     selected_OTU[OTU_id] = 1
@@ -141,7 +141,7 @@ class SparseData( dict ):
     def __init__( self, list=None ):
         ini_list = list if list is not None else list()
         for data in ini_list:
-            if not self.has_key( data[0] ):
+            if not data[0] in self:
                 self[data[0]] = dict()
             self[data[0]][data[1]] = data[2]
 
@@ -154,7 +154,7 @@ class SparseData( dict ):
                      [ 9, 1, 521 ]]  # The column 1 of the row 9 has a count of 521.
         """
         sparse = list()
-        for rows_idx in sorted(self.keys(), key=int):
+        for rows_idx in sorted(list(self.keys()), key=int):
             for columns_idx in sorted(self[rows_idx].keys()):
                 sparse.append([ rows_idx, columns_idx, self[rows_idx][columns_idx] ])
         return sparse
@@ -171,12 +171,12 @@ class SparseData( dict ):
         @summary : Remove all the count for the column provided.
          @param remove_idx : [int] The real index of the column to remove.
         """
-        for rows_idx in self.keys():
+        for rows_idx in list(self.keys()):
             # Remove data
-            if self[rows_idx].has_key( remove_idx ):
+            if remove_idx in self[rows_idx]:
                 del self[rows_idx][remove_idx]
             # Change index
-            row_columns_idx = sorted( self[rows_idx].keys(), key=int )
+            row_columns_idx = sorted( list(self[rows_idx].keys()), key=int )
             for column_idx in row_columns_idx:
                 if column_idx > remove_idx:
                     self[rows_idx][column_idx -1] = self[rows_idx][column_idx]
@@ -188,10 +188,10 @@ class SparseData( dict ):
          @param remove_idx : [int] The real index of the row to remove.
         """
         # Remove data
-        if self.has_key( remove_idx ):
+        if remove_idx in self:
             del self[remove_idx]
         # Change indexes
-        all_rows_idx = sorted( self.keys(), key=int )
+        all_rows_idx = sorted( list(self.keys()), key=int )
         for row_idx in all_rows_idx:
             if row_idx > remove_idx:
                 self[row_idx - 1] = self[row_idx]
@@ -205,8 +205,8 @@ class SparseData( dict ):
         """
         # Merge counts
         added_values = dict()
-        for row_idx in self.keys():
-            if self[row_idx].has_key( added_idx ):
+        for row_idx in list(self.keys()):
+            if added_idx in self[row_idx]:
                 self.add( row_idx, sum_idx, self[row_idx][added_idx] )
         # Remove column
         self.remove_col( added_idx )
@@ -218,7 +218,7 @@ class SparseData( dict ):
          @param col_idx : [int] The index of the column.
         """
         nb = 0
-        if self.has_key(row_idx) and self[row_idx].has_key(col_idx):
+        if row_idx in self and col_idx in self[row_idx]:
             nb = self[row_idx][col_idx]
         return nb
 
@@ -228,8 +228,8 @@ class SparseData( dict ):
          @param col_idx : [int] The index of the column.
         """
         total = 0
-        for row_idx in self.keys():
-            if self[row_idx].has_key( col_idx ):
+        for row_idx in list(self.keys()):
+            if col_idx in self[row_idx]:
                 total += self[row_idx][col_idx]
         return total
 
@@ -239,8 +239,8 @@ class SparseData( dict ):
          @param row_idx : [int] The index of the row.
         """
         total = 0
-        if self.has_key( row_idx ):
-            for column_idx in self[row_idx].keys():
+        if row_idx in self:
+            for column_idx in list(self[row_idx].keys()):
                 total += self[row_idx][column_idx]
         return total
 
@@ -252,7 +252,7 @@ class SparseData( dict ):
          @param nb_col : [int] The expected number of columns.
         """
         array = [0 for current in range(nb_col)]
-        if self.has_key( row_idx ):
+        if row_idx in self:
             for column_idx in sorted( self[row_idx].keys() ):
                 array[column_idx] = self[row_idx][column_idx]
         return array
@@ -264,9 +264,9 @@ class SparseData( dict ):
          @param col_idx : [int] The index of the column.
          @param value : [int] The value to add.
         """
-        if not self.has_key( row_idx ):
+        if not row_idx in self:
             self[row_idx] = { col_idx : 0 }
-        elif not self[row_idx].has_key( col_idx ):
+        elif not col_idx in self[row_idx]:
             self[row_idx][col_idx] = 0
         self[row_idx][col_idx] += value
         
@@ -277,7 +277,7 @@ class SparseData( dict ):
          @param col_idx : [int] The index of the column.
          @param value : [int] The value to subtract.
         """
-        if self.has_key( row_idx ) and self[row_idx].has_key( col_idx ) and self[row_idx][col_idx] >= value:
+        if row_idx in self and col_idx in self[row_idx] and self[row_idx][col_idx] >= value:
             self[row_idx][col_idx] -= value
         else:
             raise Exception( "'" + str(value) + "' cannot be subtract from row " + str(row_idx) + " column " + str(col_idx) + "." ) 
@@ -290,12 +290,12 @@ class SparseData( dict ):
          @param value : [int] The new value.
         """
         if value != 0:
-            if not self.has_key( row_idx ):
+            if not row_idx in self:
                 self[row_idx] = { col_idx : value }
             else:
                 self[row_idx][col_idx] = value
         else:
-            if self.has_key( row_idx ) and self[row_idx].has_key( col_idx ) :
+            if row_idx in self and col_idx in self[row_idx]:
                 del self[row_idx][col_idx]
     
     def random_by_col( self, col_idx ):
@@ -442,7 +442,7 @@ class Biom:
         final_idx = self.find_idx(self.columns, samples[0])
         final_sample = self.columns[final_idx]
         if final_sample['metadata'] is not None:
-            metadata_names = final_sample['metadata'].keys()
+            metadata_names = list(final_sample['metadata'].keys())
             for metadata_name in metadata_names:
                 final_sample['metadata'][final_sample['id'] + ":" + metadata_name] = final_sample['metadata'][metadata_name]
                 del final_sample['metadata'][metadata_name]
@@ -455,7 +455,7 @@ class Biom:
             current_idx = self.find_idx(self.columns, current_name)
             current_sample = self.columns[current_idx]
             # Update metadata history
-            if final_sample['metadata'].has_key( "merge_history" ):
+            if merge_history in final_sample['metadata']:
                 final_sample['metadata']['merge_history'] += " AND " + current_sample['id']
             else:
                 final_sample['metadata']['merge_history'] = final_sample['id'] + " AND " + current_sample['id']
@@ -514,7 +514,7 @@ class Biom:
         else:
             if subject_list[subject_idx]['metadata'] is None:
                 subject_list[subject_idx]['metadata'] = dict()
-            elif subject_list[subject_idx]['metadata'].has_key( metadata_name ):
+            elif metadata_name in subject_list[subject_idx]['metadata']:
                 sys.stderr.write("[WARNING] You erase previous value of the metadata named '" + metadata_name + "' in " + subject_name + " (OLD:'" + str(subject_list[subject_idx]['metadata'][metadata_name]) + "' => NEW:'" + str(metadata_value) + "').\n")
             subject_list[subject_idx]['metadata'][metadata_name] = metadata_value
 
@@ -583,7 +583,7 @@ class Biom:
         except ValueError:
             self.rows.append( {'id':observation_name, 'metadata':None } )
             self.data.add_row()
-            for metadata_name in ini_metadata.keys():
+            for metadata_name in list(ini_metadata.keys()):
                 self.add_metadata( observation_name, metadata_name, ini_metadata[metadata_name], "observation" )
         # Observation already exists
         else:
@@ -602,7 +602,7 @@ class Biom:
         except ValueError:
             self.columns.append( {'id':sample_name, 'metadata':None } )
             self.data.add_column()
-            for metadata_name in ini_metadata.keys():
+            for metadata_name in list(ini_metadata.keys()):
                 self.add_metadata( sample_name, metadata_name, ini_metadata[metadata_name], "sample" )
         # Sample already exists
         else:
@@ -681,7 +681,7 @@ class Biom:
                 # Random selection 
                 selected = _bootstrap_selection( remaining_OTU_count, nb_elts, nb_selected_elts )
                 # Add to new_data
-                for OTU_id in selected.keys():
+                for OTU_id in list(selected.keys()):
                     OTU_idx = self.find_idx( self.rows, OTU_id )
                     sample_idx = self.find_idx( self.columns, current_sample['id'] )
                     self.data.add( OTU_idx, sample_idx, selected[OTU_id] )
@@ -897,10 +897,10 @@ class BiomIO:
         title_fields = title_line.split()
         for metadata_name in title_fields[1:]:
             metadata_type = "str"
-            if ini_types.has_key( metadata_name ):
+            if metadata_name in ini_types:
                 metadata_type = ini_types[metadata_name]
             metadata_list_sep = None
-            if ini_list_sep.has_key( metadata_name ):
+            if metadata_name in ini_list_sep:
                 metadata_list_sep = ini_list_sep[metadata_name]
             metadata.append( {
                               'name'     : metadata_name,

src/jflow/featureiolib/gff3.py

@@ -43,7 +43,7 @@ class GFF3Record:
         if self.attributes is not None :
             self.attributes[cleaned_tag] = cleaned_value
         else:
-            raise "The attibute 'Attributes' is not initialized."
+            raise ValueError("The attibute 'Attributes' is not initialized.")
 
     def addToAttribute( self, tag, value ):
         """
@@ -54,12 +54,12 @@ class GFF3Record:
         cleaned_tag = GFF3Record._getCleanedAttribute(tag)
         cleaned_value = GFF3Record._getCleanedAttribute(value)
         if self.attributes is not None :
-            if self.attributes.has_key( cleaned_tag ):
+            if cleaned_tag in self.attributes:
                 self.attributes[cleaned_tag] = self.attributes[cleaned_tag] + "%2C"  + cleaned_value
             else:
                 self.attributes[cleaned_tag] = cleaned_value
         else:
-            raise "The attibute 'Attributes' is not initialized."
+            raise ValueError("The attibute 'Attributes' is not initialized.")
 
     def _attributesToGff( self ):
         """
@@ -89,13 +89,13 @@ class GFF3Record:
          @see : RFC 3986 Percent-Encoding
         """
         cleaned_tag = GFF3Record._getCleanedAttribute(tag)
-        if self.attributes.has_key( cleaned_tag ):
+        if cleaned_tag in self.attributes:
             readable_value = self.attributes[cleaned_tag].replace('%3B', ';')
             readable_value = readable_value.replace('%2C', ',')
             redable_value = readable_value.replace('%3D', '=')
             return redable_value
         else:
-            raise "The attibute 'Attributes' is not initialized."
+            raise ValueError("The attibute 'Attributes' is not initialized.")
 
     @staticmethod
     def _getCleanedAttribute( dirty_value ):

src/jflow/featureiolib/mpileup.py

@@ -21,7 +21,7 @@ import re
 from jflow.seqio import FormatError
 from jflow.seqio import UnknownFileType
 
-from abstractfeaturereader import _AbstractFeatureReader, Entry, boolify, autocast
+from .abstractfeaturereader import _AbstractFeatureReader, Entry, boolify, autocast
 
 
 class MpileupReader(_AbstractFeatureReader):

src/jflow/featureiolib/obo.py

@@ -21,7 +21,7 @@ import re
 from jflow.seqio import FormatError
 from jflow.seqio import UnknownFileType
 
-from abstractfeaturereader import _AbstractFeatureReader, Entry, boolify, autocast
+from .abstractfeaturereader import _AbstractFeatureReader, Entry, boolify, autocast
 
 
 class OboReader(_AbstractFeatureReader):

src/jflow/featureiolib/separatedvalue.py

@@ -52,7 +52,7 @@ class SeparatedValueIO(object):
             else:
                 yield record
 
-    def next(self):
+    def __next__(self):
         """
          @summary : Returns the next line record.
          @return : [list] The line record.

src/jflow/featureiolib/vcf.py

@@ -22,7 +22,7 @@ from jflow.seqio import xopen
 from jflow.seqio import FormatError
 from jflow.seqio import UnknownFileType
 
-from abstractfeaturereader import _AbstractFeatureReader, Entry, boolify, autocast
+from .abstractfeaturereader import _AbstractFeatureReader, Entry, boolify, autocast
 
 
 class VCFReader(_AbstractFeatureReader):
@@ -49,7 +49,7 @@ class VCFReader(_AbstractFeatureReader):
             @param wholefile: If True, then it is ok to read the entire file  into memory. This is faster when there are 
                 many newlines in the file, but may obviously need a lot of memory.
         """
-        if isinstance(file, basestring):
+        if isinstance(file, str):
             file = xopen(file, "r")
         self.fp = file
         self.wholefile = wholefile

src/jflow/featureiolib/wego.py

@@ -21,7 +21,7 @@ import re
 from jflow.seqio import FormatError
 from jflow.seqio import UnknownFileType
 
-from abstractfeaturereader import _AbstractFeatureReader, Entry, boolify, autocast
+from .abstractfeaturereader import _AbstractFeatureReader, Entry, boolify, autocast
 
 
 class WEGOReader(_AbstractFeatureReader):