(core) Improve suggestions for formula autocomplete

Summary:
- Make suggestions less case-sensitive (not entirely case-insensitive, but
  allow top-level suggestions to match in all-lowercase)
- Add function signatures to suggestions for Grist functions.
- Excel-like functions that are present but not implemented are no longer
  offered as suggestions.

Test Plan:
Added a test case on python side, and a browser test case for how suggestions
are rendered and inserted.

Reviewers: paulfitz

Reviewed By: paulfitz

Differential Revision: https://phab.getgrist.com/D2608

sandbox/grist/autocomplete_context.py

@@ -0,0 +1,87 @@
+"""
+Helper class for handling formula autocomplete.
+
+It's intended to use with rlcompleter.Completer. It allows finding global names using
+lowercase searches, and adds function usage information to some results.
+"""
+import __builtin__
+import inspect
+from collections import namedtuple
+
+# funcname is the function name, e.g. "MAX"
+# argspec is the signature, e.g. "(arg, *more_args)"
+# isgrist is a boolean for whether this function should be in Grist documentation.
+Completion = namedtuple('Completion', ['funcname', 'argspec', 'isgrist'])
+
+def is_grist_func(func):
+  try:
+    return inspect.getmodule(func).__name__.startswith('functions.')
+  except Exception, e:
+    return e
+
+class AutocompleteContext(object):
+  def __init__(self, usercode_context):
+    # rlcompleter is case-sensitive. This is hard to work around while maintaining attribute
+    # lookups. As a middle ground, we only introduce lowercase versions of all global names.
+    self._context = {
+      key: value for key, value in usercode_context.iteritems()
+      # Don't propose unimplemented functions in autocomplete
+      if not (value and callable(value) and getattr(value, 'unimplemented', None))
+    }
+
+    # Prepare detailed Completion objects for functions where we can supply more info.
+    # TODO It would be nice to include builtin functions too, but getargspec doesn't work there.
+    self._functions = {}
+    for key, value in self._context.iteritems():
+      if value and callable(value):
+        argspec = inspect.formatargspec(*inspect.getargspec(value))
+        self._functions[key] = Completion(key, argspec, is_grist_func(value))
+
+    # Add in the important UserTable methods, with custom friendlier descriptions.
+    self._functions['.lookupOne'] = Completion('.lookupOne', '(colName=<value>, ...)', True)
+    self._functions['.lookupRecords'] = Completion('.lookupRecords', '(colName=<value>, ...)', True)
+
+    # Remember the original name for each lowercase one.
+    self._lowercase = {}
+    for key in self._context:
+      lower = key.lower()
+      if lower == key:
+        continue
+      if lower not in self._context and lower not in __builtin__.__dict__:
+        self._lowercase[lower] = key
+      else:
+        # This is still good enough to find a match for, and translate back to the original.
+        # It allows rlcompleter to match e.g. 'max' against 'max', 'Max', and 'MAX' (using keys
+        # 'max', 'max*', and 'max**', respectively).
+        lower += '*'
+        if lower in self._lowercase:
+          lower += '*'
+        self._lowercase[lower] = key
+
+    # Add the lowercase names to the context, and to the detailed completions in _functions.
+    for lower, key in self._lowercase.iteritems():
+      self._context[lower] = self._context[key]
+      if key in self._functions:
+        self._functions[lower] = self._functions[key]
+
+  def get_context(self):
+    return self._context
+
+  def process_result(self, result):
+    # Callables are returned by rlcompleter with a trailing "(".
+    if result.endswith('('):
+      funcname = result[0:-1]
+      dot = funcname.rfind(".")
+      key = funcname[dot:] if dot >= 0 else funcname
+      completion = self._functions.get(key)
+      # Return the detailed completion if we have it, or the result string otherwise.
+      if completion:
+        # For methods (eg ".lookupOne"), use the original result as funcname (eg "Foo.lookupOne").
+        if dot >= 0:
+          completion = completion._replace(funcname=funcname)
+        return tuple(completion)
+
+      return result
+
+    # Return translation from lowercase if there is one, or the result string otherwise.
+    return self._lowercase.get(result, result)

sandbox/grist/engine.py

@@ -1,3 +1,4 @@
+# pylint:disable=too-many-lines
 """
 The data engine ties the code generated from the schema with the document data, and with
 dependency tracking.
@@ -5,16 +6,17 @@ dependency tracking.
 import contextlib
 import itertools
 import re
+import rlcompleter
 import sys
+import time
 import traceback
 from collections import namedtuple, OrderedDict, Hashable
 from sortedcontainers import SortedSet
 
-import time
-import rlcompleter
 import acl
 import actions
 import action_obj
+from autocomplete_context import AutocompleteContext
 from codebuilder import DOLLAR_REGEX
 import depend
 import docactions
@@ -232,6 +234,9 @@ class Engine(object):
     # current cell.
     self._cell_required_error = None
 
+    # Initial empty context for autocompletions; we update it when we generate the usercode module.
+    self._autocomplete_context = AutocompleteContext({})
+
   def load_empty(self):
     """
     Initialize an empty document, e.g. a newly-created one.
@@ -1016,6 +1021,9 @@ class Engine(object):
     self._repl.locals.update(self.gencode.usercode.__dict__)
     self.gencode.usercode.__dict__.update(self._repl.locals)
 
+    # Update the context used for autocompletions.
+    self._autocomplete_context = AutocompleteContext(self.gencode.usercode.__dict__)
+
     # TODO: Whenever schema changes, we need to adjust the ACL resources to remove or rename
     # tableIds and colIds.
 
@@ -1205,8 +1213,9 @@ class Engine(object):
     if txt == '$':
       tweaked_txt = 'rec.'
     table = self.tables[table_id]
-    context = {'rec': table.sample_record}
+
-    context.update(self.gencode.usercode.__dict__)
+    context = self._autocomplete_context.get_context()
+    context['rec'] = table.sample_record
 
     completer = rlcompleter.Completer(context)
     results = []
@@ -1219,11 +1228,12 @@ class Engine(object):
         break
       if skipped_completions.search(result):
         continue
-      results.append(result)
+      results.append(self._autocomplete_context.process_result(result))
+
     # If we changed the prefix (expanding the $ symbol) we now need to change it back.
     if tweaked_txt != txt:
       results = [txt + result[len(tweaked_txt):] for result in results]
-    results.sort()
+    results.sort(key=lambda r: r[0] if type(r) == tuple else r)
     return results
 
   def _get_undo_checkpoint(self):

sandbox/grist/functions/info.py

@@ -9,9 +9,11 @@ import re
 
 import column
 from functions import date      # pylint: disable=import-error
+from functions.unimplemented import unimplemented
 from usertypes import AltText   # pylint: disable=import-error
 from records import Record, RecordSet
 
+@unimplemented
 def ISBLANK(value):
   """
   Returns whether a value refers to an empty cell. It isn't implemented in Grist. To check for an
@@ -486,6 +488,7 @@ def NA():
   return float('nan')
 
 
+@unimplemented
 def TYPE(value):
   """
   Returns a number associated with the type of data passed into the function. This is not
@@ -493,6 +496,7 @@ def TYPE(value):
   """
   raise NotImplementedError()
 
+@unimplemented
 def CELL(info_type, reference):
   """
   Returns the requested information about the specified cell. This is not implemented in Grist

sandbox/grist/functions/lookup.py

@@ -1,57 +1,72 @@
 # pylint: disable=redefined-builtin, line-too-long
+from unimplemented import unimplemented
 
+@unimplemented
 def ADDRESS(row, column, absolute_relative_mode, use_a1_notation, sheet):
   """Returns a cell reference as a string."""
   raise NotImplementedError()
 
+@unimplemented
 def CHOOSE(index, choice1, choice2):
   """Returns an element from a list of choices based on index."""
   raise NotImplementedError()
 
+@unimplemented
 def COLUMN(cell_reference=None):
   """Returns the column number of a specified cell, with `A=1`."""
   raise NotImplementedError()
 
+@unimplemented
 def COLUMNS(range):
   """Returns the number of columns in a specified array or range."""
   raise NotImplementedError()
 
+@unimplemented
 def GETPIVOTDATA(value_name, any_pivot_table_cell, original_column_1, pivot_item_1=None, *args):
   """Extracts an aggregated value from a pivot table that corresponds to the specified row and column headings."""
   raise NotImplementedError()
 
+@unimplemented
 def HLOOKUP(search_key, range, index, is_sorted):
   """Horizontal lookup. Searches across the first row of a range for a key and returns the value of a specified cell in the column found."""
   raise NotImplementedError()
 
+@unimplemented
 def HYPERLINK(url, link_label):
   """Creates a hyperlink inside a cell."""
   raise NotImplementedError()
 
+@unimplemented
 def INDEX(reference, row, column):
   """Returns the content of a cell, specified by row and column offset."""
   raise NotImplementedError()
 
+@unimplemented
 def INDIRECT(cell_reference_as_string):
   """Returns a cell reference specified by a string."""
   raise NotImplementedError()
 
+@unimplemented
 def LOOKUP(search_key, search_range_or_search_result_array, result_range=None):
   """Looks through a row or column for a key and returns the value of the cell in a result range located in the same position as the search row or column."""
   raise NotImplementedError()
 
+@unimplemented
 def MATCH(search_key, range, search_type):
   """Returns the relative position of an item in a range that matches a specified value."""
   raise NotImplementedError()
 
+@unimplemented
 def OFFSET(cell_reference, offset_rows, offset_columns, height, width):
   """Returns a range reference shifted a specified number of rows and columns from a starting cell reference."""
   raise NotImplementedError()
 
+@unimplemented
 def ROW(cell_reference):
   """Returns the row number of a specified cell."""
   raise NotImplementedError()
 
+@unimplemented
 def ROWS(range):
   """Returns the number of rows in a specified array or range."""
   raise NotImplementedError()

sandbox/grist/functions/math.py

@@ -7,6 +7,7 @@ import operator
 import random
 
 from functions.info import ISNUMBER, ISLOGICAL
+from functions.unimplemented import unimplemented
 import roman
 
 # Iterates through elements of iterable arguments, or through individual args when not iterable.
@@ -727,6 +728,7 @@ def SQRTPI(value):
   """
   return _math.sqrt(_math.pi * value)
 
+@unimplemented
 def SUBTOTAL(function_code, range1, range2):
   """
   Returns a subtotal for a vertical range of cells using a specified aggregation function.
@@ -755,12 +757,14 @@ def SUM(value1, *more_values):
   return sum(_chain_numeric_a(value1, *more_values))
 
 
+@unimplemented
 def SUMIF(records, criterion, sum_range):
   """
   Returns a conditional sum across a range.
   """
   raise NotImplementedError()
 
+@unimplemented
 def SUMIFS(sum_range, criteria_range1, criterion1, *args):
   """
   Returns the sum of a range depending on multiple criteria.
@@ -782,6 +786,7 @@ def SUMPRODUCT(array1, *more_arrays):
   """
   return sum(reduce(operator.mul, values) for values in itertools.izip(array1, *more_arrays))
 
+@unimplemented
 def SUMSQ(value1, value2):
   """
   Returns the sum of the squares of a series of numbers and/or cells.

sandbox/grist/functions/stats.py

@@ -3,7 +3,7 @@
 from math import _chain, _chain_numeric, _chain_numeric_a
 from info import ISNUMBER, ISLOGICAL
 from date import DATE       # pylint: disable=unused-import
-
+from unimplemented import unimplemented
 
 def _average(iterable):
   total, count = 0.0, 0
@@ -24,6 +24,7 @@ def _default_if_empty(iterable, default):
     yield default
 
 
+@unimplemented
 def AVEDEV(value1, value2):
   """Calculates the average of the magnitudes of deviations of data from a dataset's mean."""
   raise NotImplementedError()
@@ -95,14 +96,17 @@ def AVERAGE_WEIGHTED(pairs):
   return sum_value / sum_weight
 
 
+@unimplemented
 def AVERAGEIF(criteria_range, criterion, average_range=None):
   """Returns the average of a range depending on criteria."""
   raise NotImplementedError()
 
+@unimplemented
 def AVERAGEIFS(average_range, criteria_range1, criterion1, *args):
   """Returns the average of a range depending on multiple criteria."""
   raise NotImplementedError()
 
+@unimplemented
 def BINOMDIST(num_successes, num_trials, prob_success, cumulative):
   """
   Calculates the probability of drawing a certain number of successes (or a maximum number of
@@ -111,10 +115,12 @@ def BINOMDIST(num_successes, num_trials, prob_success, cumulative):
   """
   raise NotImplementedError()
 
+@unimplemented
 def CONFIDENCE(alpha, standard_deviation, pop_size):
   """Calculates the width of half the confidence interval for a normal distribution."""
   raise NotImplementedError()
 
+@unimplemented
 def CORREL(data_y, data_x):
   """Calculates r, the Pearson product-moment correlation coefficient of a dataset."""
   raise NotImplementedError()
@@ -156,22 +162,27 @@ def COUNTA(value, *more_values):
   return sum(1 for v in _chain(value, *more_values))
 
 
+@unimplemented
 def COVAR(data_y, data_x):
   """Calculates the covariance of a dataset."""
   raise NotImplementedError()
 
+@unimplemented
 def CRITBINOM(num_trials, prob_success, target_prob):
   """Calculates the smallest value for which the cumulative binomial distribution is greater than or equal to a specified criteria."""
   raise NotImplementedError()
 
+@unimplemented
 def DEVSQ(value1, value2):
   """Calculates the sum of squares of deviations based on a sample."""
   raise NotImplementedError()
 
+@unimplemented
 def EXPONDIST(x, lambda_, cumulative):
   """Returns the value of the exponential distribution function with a specified lambda at a specified value."""
   raise NotImplementedError()
 
+@unimplemented
 def F_DIST(x, degrees_freedom1, degrees_freedom2, cumulative):
   """
   Calculates the left-tailed F probability distribution (degree of diversity) for two data sets
@@ -180,6 +191,7 @@ def F_DIST(x, degrees_freedom1, degrees_freedom2, cumulative):
   """
   raise NotImplementedError()
 
+@unimplemented
 def F_DIST_RT(x, degrees_freedom1, degrees_freedom2):
   """
   Calculates the right-tailed F probability distribution (degree of diversity) for two data sets
@@ -188,6 +200,7 @@ def F_DIST_RT(x, degrees_freedom1, degrees_freedom2):
   """
   raise NotImplementedError()
 
+@unimplemented
 def FDIST(x, degrees_freedom1, degrees_freedom2):
   """
   Calculates the right-tailed F probability distribution (degree of diversity) for two data sets
@@ -196,46 +209,57 @@ def FDIST(x, degrees_freedom1, degrees_freedom2):
   """
   raise NotImplementedError()
 
+@unimplemented
 def FISHER(value):
   """Returns the Fisher transformation of a specified value."""
   raise NotImplementedError()
 
+@unimplemented
 def FISHERINV(value):
   """Returns the inverse Fisher transformation of a specified value."""
   raise NotImplementedError()
 
+@unimplemented
 def FORECAST(x, data_y, data_x):
   """Calculates the expected y-value for a specified x based on a linear regression of a dataset."""
   raise NotImplementedError()
 
+@unimplemented
 def GEOMEAN(value1, value2):
   """Calculates the geometric mean of a dataset."""
   raise NotImplementedError()
 
+@unimplemented
 def HARMEAN(value1, value2):
   """Calculates the harmonic mean of a dataset."""
   raise NotImplementedError()
 
+@unimplemented
 def HYPGEOMDIST(num_successes, num_draws, successes_in_pop, pop_size):
   """Calculates the probability of drawing a certain number of successes in a certain number of tries given a population of a certain size containing a certain number of successes, without replacement of draws."""
   raise NotImplementedError()
 
+@unimplemented
 def INTERCEPT(data_y, data_x):
   """Calculates the y-value at which the line resulting from linear regression of a dataset will intersect the y-axis (x=0)."""
   raise NotImplementedError()
 
+@unimplemented
 def KURT(value1, value2):
   """Calculates the kurtosis of a dataset, which describes the shape, and in particular the "peakedness" of that dataset."""
   raise NotImplementedError()
 
+@unimplemented
 def LARGE(data, n):
   """Returns the nth largest element from a data set, where n is user-defined."""
   raise NotImplementedError()
 
+@unimplemented
 def LOGINV(x, mean, standard_deviation):
   """Returns the value of the inverse log-normal cumulative distribution with given mean and standard deviation at a specified value."""
   raise NotImplementedError()
 
+@unimplemented
 def LOGNORMDIST(x, mean, standard_deviation):
   """Returns the value of the log-normal cumulative distribution with given mean and standard deviation at a specified value."""
   raise NotImplementedError()
@@ -364,14 +388,17 @@ def MINA(value, *more_values):
   return min(_default_if_empty(_chain_numeric_a(value, *more_values), 0))
 
 
+@unimplemented
 def MODE(value1, value2):
   """Returns the most commonly occurring value in a dataset."""
   raise NotImplementedError()
 
+@unimplemented
 def NEGBINOMDIST(num_failures, num_successes, prob_success):
   """Calculates the probability of drawing a certain number of failures before a certain number of successes given a probability of success in independent trials."""
   raise NotImplementedError()
 
+@unimplemented
 def NORMDIST(x, mean, standard_deviation, cumulative):
   """
   Returns the value of the normal distribution function (or normal cumulative distribution
@@ -379,42 +406,52 @@ def NORMDIST(x, mean, standard_deviation, cumulative):
   """
   raise NotImplementedError()
 
+@unimplemented
 def NORMINV(x, mean, standard_deviation):
   """Returns the value of the inverse normal distribution function for a specified value, mean, and standard deviation."""
   raise NotImplementedError()
 
+@unimplemented
 def NORMSDIST(x):
   """Returns the value of the standard normal cumulative distribution function for a specified value."""
   raise NotImplementedError()
 
+@unimplemented
 def NORMSINV(x):
   """Returns the value of the inverse standard normal distribution function for a specified value."""
   raise NotImplementedError()
 
+@unimplemented
 def PEARSON(data_y, data_x):
   """Calculates r, the Pearson product-moment correlation coefficient of a dataset."""
   raise NotImplementedError()
 
+@unimplemented
 def PERCENTILE(data, percentile):
   """Returns the value at a given percentile of a dataset."""
   raise NotImplementedError()
 
+@unimplemented
 def PERCENTRANK(data, value, significant_digits=None):
   """Returns the percentage rank (percentile) of a specified value in a dataset."""
   raise NotImplementedError()
 
+@unimplemented
 def PERCENTRANK_EXC(data, value, significant_digits=None):
   """Returns the percentage rank (percentile) from 0 to 1 exclusive of a specified value in a dataset."""
   raise NotImplementedError()
 
+@unimplemented
 def PERCENTRANK_INC(data, value, significant_digits=None):
   """Returns the percentage rank (percentile) from 0 to 1 inclusive of a specified value in a dataset."""
   raise NotImplementedError()
 
+@unimplemented
 def PERMUT(n, k):
   """Returns the number of ways to choose some number of objects from a pool of a given size of objects, considering order."""
   raise NotImplementedError()
 
+@unimplemented
 def POISSON(x, mean, cumulative):
   """
   Returns the value of the Poisson distribution function (or Poisson cumulative distribution
@@ -422,42 +459,52 @@ def POISSON(x, mean, cumulative):
   """
   raise NotImplementedError()
 
+@unimplemented
 def PROB(data, probabilities, low_limit, high_limit=None):
   """Given a set of values and corresponding probabilities, calculates the probability that a value chosen at random falls between two limits."""
   raise NotImplementedError()
 
+@unimplemented
 def QUARTILE(data, quartile_number):
   """Returns a value nearest to a specified quartile of a dataset."""
   raise NotImplementedError()
 
+@unimplemented
 def RANK(value, data, is_ascending=None):
   """Returns the rank of a specified value in a dataset."""
   raise NotImplementedError()
 
+@unimplemented
 def RANK_AVG(value, data, is_ascending=None):
   """Returns the rank of a specified value in a dataset. If there is more than one entry of the same value in the dataset, the average rank of the entries will be returned."""
   raise NotImplementedError()
 
+@unimplemented
 def RANK_EQ(value, data, is_ascending=None):
   """Returns the rank of a specified value in a dataset. If there is more than one entry of the same value in the dataset, the top rank of the entries will be returned."""
   raise NotImplementedError()
 
+@unimplemented
 def RSQ(data_y, data_x):
   """Calculates the square of r, the Pearson product-moment correlation coefficient of a dataset."""
   raise NotImplementedError()
 
+@unimplemented
 def SKEW(value1, value2):
   """Calculates the skewness of a dataset, which describes the symmetry of that dataset about the mean."""
   raise NotImplementedError()
 
+@unimplemented
 def SLOPE(data_y, data_x):
   """Calculates the slope of the line resulting from linear regression of a dataset."""
   raise NotImplementedError()
 
+@unimplemented
 def SMALL(data, n):
   """Returns the nth smallest element from a data set, where n is user-defined."""
   raise NotImplementedError()
 
+@unimplemented
 def STANDARDIZE(value, mean, standard_deviation):
   """Calculates the normalized equivalent of a random variable given mean and standard deviation of the distribution."""
   raise NotImplementedError()
@@ -559,50 +606,62 @@ def STDEVPA(value, *more_values):
   """
   return _stddev(list(_chain_numeric_a(value, *more_values)), 0)
 
+@unimplemented
 def STEYX(data_y, data_x):
   """Calculates the standard error of the predicted y-value for each x in the regression of a dataset."""
   raise NotImplementedError()
 
+@unimplemented
 def T_INV(probability, degrees_freedom):
   """Calculates the negative inverse of the one-tailed TDIST function."""
   raise NotImplementedError()
 
+@unimplemented
 def T_INV_2T(probability, degrees_freedom):
   """Calculates the inverse of the two-tailed TDIST function."""
   raise NotImplementedError()
 
+@unimplemented
 def TDIST(x, degrees_freedom, tails):
   """Calculates the probability for Student's t-distribution with a given input (x)."""
   raise NotImplementedError()
 
+@unimplemented
 def TINV(probability, degrees_freedom):
   """Calculates the inverse of the two-tailed TDIST function."""
   raise NotImplementedError()
 
+@unimplemented
 def TRIMMEAN(data, exclude_proportion):
   """Calculates the mean of a dataset excluding some proportion of data from the high and low ends of the dataset."""
   raise NotImplementedError()
 
+@unimplemented
 def TTEST(range1, range2, tails, type):
   """Returns the probability associated with t-test. Determines whether two samples are likely to have come from the same two underlying populations that have the same mean."""
   raise NotImplementedError()
 
+@unimplemented
 def VAR(value1, value2):
   """Calculates the variance based on a sample."""
   raise NotImplementedError()
 
+@unimplemented
 def VARA(value1, value2):
   """Calculates an estimate of variance based on a sample, setting text to the value `0`."""
   raise NotImplementedError()
 
+@unimplemented
 def VARP(value1, value2):
   """Calculates the variance based on an entire population."""
   raise NotImplementedError()
 
+@unimplemented
 def VARPA(value1, value2):
   """Calculates the variance based on an entire population, setting text to the value `0`."""
   raise NotImplementedError()
 
+@unimplemented
 def WEIBULL(x, shape, scale, cumulative):
   """
   Returns the value of the Weibull distribution function (or Weibull cumulative distribution
@@ -610,6 +669,7 @@ def WEIBULL(x, shape, scale, cumulative):
   """
   raise NotImplementedError()
 
+@unimplemented
 def ZTEST(data, value, standard_deviation):
   """Returns the two-tailed P-value of a Z-test with standard distribution."""
   raise NotImplementedError()

sandbox/grist/functions/text.py

@@ -5,6 +5,7 @@ import dateutil.parser
 import numbers
 import re
 
+from unimplemented import unimplemented
 from usertypes import AltText   # pylint: disable=import-error
 
 def CHAR(table_number):
@@ -499,6 +500,7 @@ def T(value):
           str(value) if isinstance(value, AltText) else "")
 
 
+@unimplemented
 def TEXT(number, format_type):
   """
   Converts a number into text according to a specified format. It is not yet implemented in

sandbox/grist/functions/unimplemented.py

@@ -0,0 +1,11 @@
+"""
+Decorator that marks functions as not implemented. It sets func.unimplemented=True.
+Usage:
+
+@unimplemented
+def func(...):
+  raise NotImplemented
+"""
+def unimplemented(func):
+  func.unimplemented = True
+  return func

sandbox/grist/test_completion.py

@@ -1,5 +1,4 @@
 import testsamples
-import testutil
 import test_engine
 
 class TestCompletion(test_engine.EngineTestCase):
@@ -24,18 +23,63 @@ class TestCompletion(test_engine.EngineTestCase):
 
   def test_function(self):
     self.assertEqual(self.engine.autocomplete("MEDI", "Address"),
-                     ["MEDIAN("])
+        [('MEDIAN', '(value, *more_values)', True)])
+    self.assertEqual(self.engine.autocomplete("ma", "Address"), [
+      ('MAX', '(value, *more_values)', True),
+      ('MAXA', '(value, *more_values)', True),
+      'map(',
+      'math',
+      'max(',
+    ])
 
   def test_member(self):
     self.assertEqual(self.engine.autocomplete("datetime.tz", "Address"),
                      ["datetime.tzinfo("])
 
+  def test_case_insensitive(self):
+    self.assertEqual(self.engine.autocomplete("medi", "Address"),
+        [('MEDIAN', '(value, *more_values)', True)])
+    self.assertEqual(self.engine.autocomplete("std", "Address"), [
+      ('STDEV', '(value, *more_values)', True),
+      ('STDEVA', '(value, *more_values)', True),
+      ('STDEVP', '(value, *more_values)', True),
+      ('STDEVPA', '(value, *more_values)', True)
+    ])
+    self.assertEqual(self.engine.autocomplete("stu", "Address"),
+        ["Students"])
+
+    # Add a table name whose lowercase version conflicts with a builtin.
+    self.apply_user_action(['AddTable', 'Max', []])
+    self.assertEqual(self.engine.autocomplete("max", "Address"), [
+      ('MAX', '(value, *more_values)', True),
+      ('MAXA', '(value, *more_values)', True),
+      'Max',
+      'max(',
+    ])
+    self.assertEqual(self.engine.autocomplete("MAX", "Address"), [
+      ('MAX', '(value, *more_values)', True),
+      ('MAXA', '(value, *more_values)', True),
+    ])
+
+
   def test_suggest_globals_and_tables(self):
     # Should suggest globals and table names.
-    self.assertEqual(self.engine.autocomplete("ME", "Address"), ['MEDIAN('])
+    self.assertEqual(self.engine.autocomplete("ME", "Address"),
+        [('MEDIAN', '(value, *more_values)', True)])
     self.assertEqual(self.engine.autocomplete("Ad", "Address"), ['Address'])
-    self.assertGreaterEqual(set(self.engine.autocomplete("S", "Address")),
+    self.assertGreaterEqual(set(self.engine.autocomplete("S", "Address")), {
-                            {'Schools', 'Students', 'SUM(', 'STDEV('})
+      'Schools',
+      'Students',
+      ('SUM', '(value1, *more_values)', True),
+      ('STDEV', '(value, *more_values)', True),
+    })
+    self.assertGreaterEqual(set(self.engine.autocomplete("s", "Address")), {
+      'Schools',
+      'Students',
+      'sum(',
+      ('SUM', '(value1, *more_values)', True),
+      ('STDEV', '(value, *more_values)', True),
+    })
     self.assertEqual(self.engine.autocomplete("Addr", "Schools"), ['Address'])
 
   def test_suggest_columns(self):
@@ -56,11 +100,16 @@ class TestCompletion(test_engine.EngineTestCase):
 
   def test_suggest_lookup_methods(self):
     # Should suggest lookup formulas for tables.
-    self.assertEqual(self.engine.autocomplete("Address.", "Students"),
+    self.assertEqual(self.engine.autocomplete("Address.", "Students"), [
-        ['Address.all', 'Address.lookupOne(', 'Address.lookupRecords('])
+      'Address.all',
+      ('Address.lookupOne', '(colName=<value>, ...)', True),
+      ('Address.lookupRecords', '(colName=<value>, ...)', True),
+    ])
 
-    self.assertEqual(self.engine.autocomplete("Address.lookup", "Students"),
+    self.assertEqual(self.engine.autocomplete("Address.lookup", "Students"), [
-        ['Address.lookupOne(', 'Address.lookupRecords('])
+      ('Address.lookupOne', '(colName=<value>, ...)', True),
+      ('Address.lookupRecords', '(colName=<value>, ...)', True),
+    ])
 
   def test_suggest_column_type_methods(self):
     # Should treat columns as correct types.