From eaafdb38af52c2a138aca6ee1b1fd24d8bd3c2de Mon Sep 17 00:00:00 2001
From: Zhiyi Wu <zhiyi.wu@bioch.ox.ac.uk>
Date: Tue, 13 Jul 2021 18:45:00 +0100
Subject: [PATCH] make alchemlyb.concat behave like pd.concat (PR #152)

* fix #150
* `alchemlyb.concat([])` now raises ValueError (like pandas.concat())
* Update CHANGES
* add test
---
 CHANGES                           | 2 ++
 src/alchemlyb/__init__.py         | 6 +++++-
 src/alchemlyb/tests/test_units.py | 5 +++++
 3 files changed, 12 insertions(+), 1 deletion(-)

diff --git a/CHANGES b/CHANGES
index 8d30f716..2ada18e1 100644
--- a/CHANGES
+++ b/CHANGES
@@ -25,6 +25,8 @@ Enhancements
 Deprecations
 
 Fixes
+  - `alchemlyb.concat()` should raise ValueError when given empty list, to be compatible with
+    pandas.concat() (issue #150, PR #152).
   - Fix the support for pandas >= 1.3 (issue #147, PR #148).
   - Fix separate_dhdl not work for multiple columns (issue #149, PR #151).
 
diff --git a/src/alchemlyb/__init__.py b/src/alchemlyb/__init__.py
index 363a4f4c..061e2fe2 100644
--- a/src/alchemlyb/__init__.py
+++ b/src/alchemlyb/__init__.py
@@ -47,7 +47,11 @@ def concat(objs, *args, **kwargs):
  
     .. versionadded:: 0.5.0'''
     # Sanity check
-    attrs = objs[0].attrs
+    try:
+        attrs = objs[0].attrs
+    except IndexError: # except empty list as input
+        raise ValueError('No objects to concatenate')
+
     for obj in objs:
         if attrs != obj.attrs:
             raise ValueError('All pandas objects should have the same attrs.')
diff --git a/src/alchemlyb/tests/test_units.py b/src/alchemlyb/tests/test_units.py
index 19014656..6e9ee343 100644
--- a/src/alchemlyb/tests/test_units.py
+++ b/src/alchemlyb/tests/test_units.py
@@ -33,6 +33,11 @@ def test_concat():
     with pytest.raises(ValueError):
         alchemlyb.concat([df1, df2])
 
+def test_concat_empty():
+    '''Test if empty raise the right error.'''
+    with pytest.raises(ValueError):
+        alchemlyb.concat([])
+
 def test_setT():
     '''Test setting temperature.'''
     df = pd.DataFrame(data={'col1': [1, 2]})