Removed block context from objToJSON

asv_bench/benchmarks/io/json.py

@@ -63,10 +63,10 @@ def peakmem_read_json_lines_concat(self, index):
 class ToJSON(BaseIO):
 
     fname = "__test__.json"
-    params = ["split", "columns", "index"]
+    params = ["split", "columns", "index", "records", "values"]
     param_names = ["orient"]
 
-    def setup(self, lines_orient):
+    def setup(self, orient):
         N = 10 ** 5
         ncols = 5
         index = date_range("20000101", periods=N, freq="H")
@@ -126,29 +126,84 @@ def time_float_int(self, orient):
     def time_float_int_str(self, orient):
         self.df_int_float_str.to_json(self.fname, orient=orient)
 
-    def time_floats_with_int_idex_lines(self, orient):
+
+class ToJSONLines(BaseIO):
+
+    fname = "__test__.json"
+
+    def setup(self):
+        N = 10 ** 5
+        ncols = 5
+        index = date_range("20000101", periods=N, freq="H")
+        timedeltas = timedelta_range(start=1, periods=N, freq="s")
+        datetimes = date_range(start=1, periods=N, freq="s")
+        ints = np.random.randint(100000000, size=N)
+        floats = np.random.randn(N)
+        strings = tm.makeStringIndex(N)
+        self.df = DataFrame(np.random.randn(N, ncols), index=np.arange(N))
+        self.df_date_idx = DataFrame(np.random.randn(N, ncols), index=index)
+        self.df_td_int_ts = DataFrame(
+            {
+                "td_1": timedeltas,
+                "td_2": timedeltas,
+                "int_1": ints,
+                "int_2": ints,
+                "ts_1": datetimes,
+                "ts_2": datetimes,
+            },
+            index=index,
+        )
+        self.df_int_floats = DataFrame(
+            {
+                "int_1": ints,
+                "int_2": ints,
+                "int_3": ints,
+                "float_1": floats,
+                "float_2": floats,
+                "float_3": floats,
+            },
+            index=index,
+        )
+        self.df_int_float_str = DataFrame(
+            {
+                "int_1": ints,
+                "int_2": ints,
+                "float_1": floats,
+                "float_2": floats,
+                "str_1": strings,
+                "str_2": strings,
+            },
+            index=index,
+        )
+
+    def time_floats_with_int_index_lines(self):
         self.df.to_json(self.fname, orient="records", lines=True)
 
-    def time_floats_with_dt_index_lines(self, orient):
+    def time_floats_with_dt_index_lines(self):
         self.df_date_idx.to_json(self.fname, orient="records", lines=True)
 
-    def time_delta_int_tstamp_lines(self, orient):
+    def time_delta_int_tstamp_lines(self):
         self.df_td_int_ts.to_json(self.fname, orient="records", lines=True)
 
-    def time_float_int_lines(self, orient):
+    def time_float_int_lines(self):
         self.df_int_floats.to_json(self.fname, orient="records", lines=True)
 
-    def time_float_int_str_lines(self, orient):
+    def time_float_int_str_lines(self):
         self.df_int_float_str.to_json(self.fname, orient="records", lines=True)
 
 
 class ToJSONMem:
     def setup_cache(self):
         df = DataFrame([[1]])
-        frames = {"int": df, "float": df.astype(float)}
+        wide = DataFrame(np.ones((10_000, 10_000)))
+        frames = {"int": df, "float": df.astype(float), "wide": wide}
 
         return frames
 
+    def mem_int(self, frames):
+        df = frames["wide"]
+        df.to_json()
+
     def peakmem_int(self, frames):
         df = frames["int"]
         for _ in range(100_000):