Avoid loading file into memory in read_csv

agate/table/__init__.py

@@ -79,7 +79,13 @@ def __init__(self, rows, column_names=None, column_types=None, row_names=None, _
         if column_names:
             self._column_names = utils.deduplicate(column_names, column_names=True)
         elif rows:
-            self._column_names = tuple(utils.letter_name(i) for i in range(len(rows[0])))
+            try:
+                first_row = rows[0]
+            except TypeError:
+                # it's an iterator
+                first_row = next(rows)
+                rows = chain([first_row], rows)
+            self._column_names = tuple(utils.letter_name(i) for i in range(len(first_row)))
             warnings.warn('Column names not specified. "%s" will be used as names.' % str(self._column_names),
                           RuntimeWarning, stacklevel=2)
         else:
@@ -102,6 +108,9 @@ def __init__(self, rows, column_names=None, column_types=None, row_names=None, _
                     raise ValueError('Column types must be instances of DataType.')
 
         if isinstance(column_types, TypeTester):
+            # if rows is streaming, we must bring it in-memory
+            # note: we could do better here.
+            rows = tuple(rows)
             self._column_types = column_types.run(rows, self._column_names)
         else:
             self._column_types = tuple(column_types)

agate/table/from_csv.py

@@ -59,14 +59,18 @@ def from_csv(cls, path, column_names=None, column_types=None, row_names=None, sk
         else:
             raise ValueError('skip_lines argument must be an int')
 
-        contents = StringIO(f.read())
+        handle = f
 
         if sniff_limit is None:
-            kwargs['dialect'] = csv.Sniffer().sniff(contents.getvalue())
+            # avoid reading the file twice
+            handle = StringIO(f.read())
+            kwargs['dialect'] = csv.Sniffer().sniff(handle.getvalue())
         elif sniff_limit > 0:
-            kwargs['dialect'] = csv.Sniffer().sniff(contents.getvalue()[:sniff_limit])
+            kwargs['dialect'] = csv.Sniffer().sniff(f.read(sniff_limit))
+            # return to the start of the file
+            f.seek(0)
 
-        reader = csv.reader(contents, header=header, **kwargs)
+        reader = csv.reader(handle, header=header, **kwargs)
 
         if header:
             if column_names is None:
@@ -75,12 +79,12 @@ def from_csv(cls, path, column_names=None, column_types=None, row_names=None, sk
                 next(reader)
 
         if row_limit is None:
-            rows = tuple(reader)
+            rows = reader
         else:
-            rows = tuple(itertools.islice(reader, row_limit))
+            rows = itertools.islice(reader, row_limit)
+
+        return Table(rows, column_names, column_types, row_names=row_names)
 
     finally:
         if close:
             f.close()
-
-    return Table(rows, column_names, column_types, row_names=row_names)