fixup features

Author: MarcoGorelli

README.md

@@ -13,7 +13,7 @@ Seamlessly support both, without depending on either!
 
 - ✅ **Just use** a subset of **the Polars API**, no need to learn anything new
 - ✅ **No dependencies** (not even Polars), keep your library lightweight
-- ✅ Be **lazy**
+- ✅ Support both **lazy** and eager execution
 - ✅ Use Polars **Expressions**
 
 **Note: this is work-in-progress, and a bit of an experiment, don't take it too seriously**.

f.py

@@ -44,8 +44,6 @@ def my_agnostic_function(
     "city": ["London", "Paris", "Oslo", "London", "Paris", "London"],
 }
 
-reveal_type(parts)
-
 print("pandas output:")
 print(
     my_agnostic_function(
@@ -60,7 +58,7 @@ def my_agnostic_function(
         pl.DataFrame(parts),
     )
 )
-reveal_type(
+print(
     my_agnostic_function(
         pl.DataFrame(suppliers),
         pl.DataFrame(parts),

t.py

@@ -6,7 +6,7 @@
 import narwhals as nw
 
 df_raw = pd.DataFrame({"a": [1, 3, 2], "b": [4, 4, 6], "z": [7.0, 8, 9]})
-df = nw.DataFrame(df_raw, features=["lazy"])
+df = nw.DataFrame(df_raw)
 df_raw_2 = pd.DataFrame({"a": [1, 3], "c": [7, 9]})
 df2 = nw.DataFrame(df_raw_2, features=["lazy"])