ENH: option to change the number in _dir_additions_for_owner

doc/source/user_guide/options.rst

@@ -430,6 +430,10 @@ display.html.use_mathjax                True         When True, Jupyter notebook
                                                      table contents using MathJax, rendering
                                                      mathematical expressions enclosed by the
                                                      dollar symbol.
+display.max_dir_items                   100          The number of columns from a dataframe that
+                                                     are added to dir. These columns can then be
+                                                     suggested by tab completion. 'None' value means
+                                                     unlimited.
 io.excel.xls.writer                     xlwt         The default Excel writer engine for
                                                      'xls' files.
 

doc/source/whatsnew/v1.4.0.rst

@@ -213,7 +213,7 @@ Other enhancements
 - :meth:`.GroupBy.mean` now supports `Numba <http://numba.pydata.org/>`_ execution with the ``engine`` keyword (:issue:`43731`)
 - :meth:`Timestamp.isoformat`, now handles the ``timespec`` argument from the base :class:``datetime`` class (:issue:`26131`)
 - :meth:`NaT.to_numpy` ``dtype`` argument is now respected, so ``np.timedelta64`` can be returned (:issue:`44460`)
--
+- New option ``display.max_dir_items`` customizes the number of columns added to :meth:`Dataframe.__dir__` and suggested for tab completion (:issue:`37996`)
 
 
 .. ---------------------------------------------------------------------------

pandas/core/config_init.py

@@ -238,6 +238,16 @@ def use_numba_cb(key):
     (default: True)
 """
 
+pc_max_dir_items = """\
+: int
+    The number of items that will be added to `dir(...)`. 'None' value means
+    unlimited. Because dir is cached, changing this option will not immediately
+    affect already existing dataframes until a column is deleted or added.
+
+    This is for instance used to suggest columns from a dataframe to tab
+    completion.
+"""
+
 pc_width_doc = """
 : int
     Width of the display in characters. In case python/IPython is running in
@@ -451,6 +461,9 @@ def _deprecate_negative_int_max_colwidth(key):
     cf.register_option(
         "html.use_mathjax", True, pc_html_use_mathjax_doc, validator=is_bool
     )
+    cf.register_option(
+        "max_dir_items", 100, pc_max_dir_items, validator=is_nonnegative_int
+    )
 
 tc_sim_interactive_doc = """
 : boolean

pandas/core/indexes/base.py

@@ -846,7 +846,7 @@ def _dir_additions_for_owner(self) -> set[str_t]:
         """
         return {
             c
-            for c in self.unique(level=0)[:100]
+            for c in self.unique(level=0)[: get_option("display.max_dir_items")]
             if isinstance(c, str) and c.isidentifier()
         }
 

pandas/tests/frame/test_api.py

@@ -5,6 +5,8 @@
 import numpy as np
 import pytest
 
+from pandas._config.config import option_context
+
 import pandas.util._test_decorators as td
 from pandas.util._test_decorators import (
     async_mark,
@@ -87,6 +89,25 @@ def test_tab_completion(self):
             assert key not in dir(df)
         assert isinstance(df.__getitem__("A"), DataFrame)
 
+    def test_display_max_dir_items(self):
+        # display.max_dir_items increaes the number of columns that are in __dir__.
+        columns = ["a" + str(i) for i in range(420)]
+        values = [range(420), range(420)]
+        df = DataFrame(values, columns=columns)
+
+        # The default value for display.max_dir_items is 100
+        assert "a99" in dir(df)
+        assert "a100" not in dir(df)
+
+        with option_context("display.max_dir_items", 300):
+            df = DataFrame(values, columns=columns)
+            assert "a299" in dir(df)
+            assert "a300" not in dir(df)
+
+        with option_context("display.max_dir_items", None):
+            df = DataFrame(values, columns=columns)
+            assert "a419" in dir(df)
+
     def test_not_hashable(self):
         empty_frame = DataFrame()