refactor: vals -> keys

Author: trichter

sugar/_io/tab/xsv.py

@@ -89,9 +89,9 @@ def _read_fts_xsv(f, ftype=None, **kw):
     return FeatureList.frompandas(df, ftype=ftype)
 
 
-def _write_fts_xsv(fts: FeatureList, f, vals='type start stop strand', dtype=None, index=False, **kw):
+def _write_fts_xsv(fts: FeatureList, f, keys='type start stop strand', dtype=None, index=False, **kw):
     try:
-        df = fts.topandas(vals, dtype=dtype)
+        df = fts.topandas(keys, dtype=dtype)
     except ImportError:
         raise ImportError('TSV/CSV writer depends on pandas module')
     return df.to_csv(f, index=index, **kw)

sugar/core/fts.py

@@ -567,11 +567,11 @@ def tofmtstr(self, fmt, **kw):
         """
         return self.write(None, fmt)
 
-    def tolists(self, vals='type start stop strand'):
+    def tolists(self, keys='type start stop strand'):
         """
         Return a generator yielding a list for each feature
 
-        :param vals: Parameters from the metadata or location to return,
+        :param keys: Parameters from the metadata or location to return,
             ``'len'`` is also allowed,
             might be a string or tuple, defaults to ``'type start stop strand'``
 
@@ -586,24 +586,24 @@ def tolists(self, vals='type start stop strand'):
         cDNA_match 103944892 - 7136
         cDNA_match 107859806 - 2392
         """
-        if isinstance(vals, str):
-            vals = vals.split()
+        if isinstance(keys, str):
+            keys = keys.split()
         for ft in self:
             yield [
-                ft.loc.strand if v == 'strand' else
-                ft.loc.defect if v == 'defect' else
-                ft.locs.range[0] if v == 'start' else
-                ft.locs.range[1] if v == 'stop' else
-                len(ft) if v == 'len' else
-                ft.meta.get(v)
-                for v in vals
+                ft.loc.strand if k == 'strand' else
+                ft.loc.defect if k == 'defect' else
+                ft.locs.range[0] if k == 'start' else
+                ft.locs.range[1] if k == 'stop' else
+                len(ft) if k == 'len' else
+                ft.meta.get(k)
+                for k in keys
             ]
 
-    def topandas(self, vals='type start stop strand', **kw):
+    def topandas(self, keys='type start stop strand', **kw):
         """
         Return a `pandas.DataFrame` of the features
 
-        :param vals: Parameters from the metadata or location to return,
+        :param keys: Parameters from the metadata or location to return,
             ``'len'`` is also allowed,
             might be a string or tuple, defaults to ``'type start stop strand'``
 
@@ -620,10 +620,10 @@ def topandas(self, vals='type start stop strand', **kw):
         3  cDNA_match  107859806  107862198      -
         """
         import pandas
-        if isinstance(vals, str):
-            vals = vals.split()
-        kw.setdefault('columns', vals)
-        return pandas.DataFrame(self.tolists(vals=vals), **kw)
+        if isinstance(keys, str):
+            keys = keys.split()
+        kw.setdefault('columns', keys)
+        return pandas.DataFrame(self.tolists(keys=keys), **kw)
 
 
     def get(self, type):

sugar/tests/test_io_tab_xsv.py

@@ -25,10 +25,10 @@ def test_csv():
 def test_xsv_edgecases():
     pytest.importorskip('pandas')
     fts = read_fts()
-    out = fts.write(None, 'csv', sep=' ', vals='type start len strand defect')
+    out = fts.write(None, 'csv', sep=' ', keys='type start len strand defect')
     fts2 = read_fts(io.StringIO(out), sep=None, engine='python')
     fts3 = read_fts('!data/fts_example.tsv')
     assert fts2 == fts3
-    out = fts.write(None, 'csv', sep='|', vals='type stop len strand defect')
+    out = fts.write(None, 'csv', sep='|', keys='type stop len strand defect')
     fts2 = read_fts(io.StringIO(out), sep='|')
     assert fts2 == fts3