docs: change city names in docs-examples

docs-examples/c/async_query_example.c

@@ -182,14 +182,14 @@ int main() {
 // query callback ...
 // ts current voltage phase location groupid
 // numOfRow = 8
-// 1538548685000 10.300000 219 0.310000 beijing.chaoyang 2
-// 1538548695000 12.600000 218 0.330000 beijing.chaoyang 2
-// 1538548696800 12.300000 221 0.310000 beijing.chaoyang 2
-// 1538548696650 10.300000 218 0.250000 beijing.chaoyang 3
-// 1538548685500 11.800000 221 0.280000 beijing.haidian 2
-// 1538548696600 13.400000 223 0.290000 beijing.haidian 2
-// 1538548685000 10.800000 223 0.290000 beijing.haidian 3
-// 1538548686500 11.500000 221 0.350000 beijing.haidian 3
+// 1538548685500 11.800000 221 0.280000 california.losangeles 2
+// 1538548696600 13.400000 223 0.290000 california.losangeles 2
+// 1538548685000 10.800000 223 0.290000 california.losangeles 3
+// 1538548686500 11.500000 221 0.350000 california.losangeles 3
+// 1538548685000 10.300000 219 0.310000 california.sanfrancisco 2
+// 1538548695000 12.600000 218 0.330000 california.sanfrancisco 2
+// 1538548696800 12.300000 221 0.310000 california.sanfrancisco 2
+// 1538548696650 10.300000 218 0.250000 california.sanfrancisco 3
 // numOfRow = 0
 // no more data, close the connection.
 // ANCHOR_END: demo
\ No newline at end of file

docs-examples/python/conn_native_pandas.py

@@ -13,7 +13,7 @@ print(df.head(3))
 # output:
 # RangeIndex(start=0, stop=8, step=1)
 # <class 'pandas._libs.tslibs.timestamps.Timestamp'>
-#                        ts  current  voltage  phase          location  groupid
-# 0 2018-10-03 14:38:05.000     10.3      219   0.31  beijing.chaoyang        2
-# 1 2018-10-03 14:38:15.000     12.6      218   0.33  beijing.chaoyang        2
-# 2 2018-10-03 14:38:16.800     12.3      221   0.31  beijing.chaoyang        2
+#                        ts  current  ...               location  groupid
+# 0 2018-10-03 14:38:05.500     11.8  ...  california.losangeles        2
+# 1 2018-10-03 14:38:16.600     13.4  ...  california.losangeles        2
+# 2 2018-10-03 14:38:05.000     10.8  ...  california.losangeles        3

docs-examples/python/conn_rest_pandas.py

@@ -11,9 +11,9 @@ print(type(df.ts[0]))
 print(df.head(3))
 
 # output:
-# <class 'datetime.datetime'>
 # RangeIndex(start=0, stop=8, step=1)
-#                                  ts  current  ...          location  groupid
-# 0         2018-10-03 14:38:05+08:00     10.3  ...  beijing.chaoyang        2
-# 1         2018-10-03 14:38:15+08:00     12.6  ...  beijing.chaoyang        2
-# 2  2018-10-03 14:38:16.800000+08:00     12.3  ...  beijing.chaoyang        2
+# <class 'pandas._libs.tslibs.timestamps.Timestamp'>
+#                                 ts  current  ...               location  groupid
+# 0 2018-10-03 06:38:05.500000+00:00     11.8  ...  california.losangeles        2
+# 1 2018-10-03 06:38:16.600000+00:00     13.4  ...  california.losangeles        2
+# 2        2018-10-03 06:38:05+00:00     10.8  ...  california.losangeles        3

docs-examples/python/connect_rest_examples.py

@@ -38,8 +38,7 @@ for row in data:
 # inserted row count: 8
 # queried row count: 3
 # ['ts', 'current', 'voltage', 'phase', 'location', 'groupid']
-# [datetime.datetime(2018, 10, 3, 14, 38, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800), '+08:00')), 10.3, 219, 0.31, 'beijing.chaoyang', 2]
-# [datetime.datetime(2018, 10, 3, 14, 38, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800), '+08:00')), 12.6, 218, 0.33, 'beijing.chaoyang', 2]
-# [datetime.datetime(2018, 10, 3, 14, 38, 16, 800000, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800), '+08:00')), 12.3, 221, 0.31, 'beijing.chaoyang', 2]
-
+# [datetime.datetime(2018, 10, 3, 14, 38, 5, 500000, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800), '+08:00')), 11.8, 221, 0.28, 'california.losangeles', 2]
+# [datetime.datetime(2018, 10, 3, 14, 38, 16, 600000, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800), '+08:00')), 13.4, 223, 0.29, 'california.losangeles', 2]
+# [datetime.datetime(2018, 10, 3, 14, 38, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800), '+08:00')), 10.8, 223, 0.29, 'california.losangeles', 3]
 # ANCHOR_END: basic

docs-examples/python/json_protocol_example.py

@@ -5,9 +5,9 @@ from taos import SmlProtocol, SmlPrecision
 
 lines = [{"metric": "meters.current", "timestamp": 1648432611249, "value": 10.3, "tags": {"location": "California.SanFrancisco", "groupid": 2}},
          {"metric": "meters.voltage", "timestamp": 1648432611249, "value": 219,
-             "tags": {"location": "California.LosAngeles", "groupid": 1}},
+          "tags": {"location": "California.LosAngeles", "groupid": 1}},
          {"metric": "meters.current", "timestamp": 1648432611250, "value": 12.6,
-             "tags": {"location": "California.SanFrancisco", "groupid": 2}},
+          "tags": {"location": "California.SanFrancisco", "groupid": 2}},
          {"metric": "meters.voltage", "timestamp": 1648432611250, "value": 221, "tags": {"location": "California.LosAngeles", "groupid": 1}}]
 
 

docs-examples/python/query_example.py

@@ -12,10 +12,10 @@ def query_api_demo(conn: taos.TaosConnection):
 
 
 # field count: 7
-# meta of files[1]: {name: ts, type: 9, bytes: 8}
+# meta of fields[1]: {name: ts, type: 9, bytes: 8}
 # ======================Iterate on result=========================
-# ('d1001', datetime.datetime(2018, 10, 3, 14, 38, 5), 10.300000190734863, 219, 0.3100000023841858, 'California.SanFrancisco', 2)
-# ('d1001', datetime.datetime(2018, 10, 3, 14, 38, 15), 12.600000381469727, 218, 0.33000001311302185, 'California.SanFrancisco', 2)
+# ('d1003', datetime.datetime(2018, 10, 3, 14, 38, 5, 500000), 11.800000190734863, 221, 0.2800000011920929, 'california.losangeles', 2)
+# ('d1003', datetime.datetime(2018, 10, 3, 14, 38, 16, 600000), 13.399999618530273, 223, 0.28999999165534973, 'california.losangeles', 2)
 # ANCHOR_END: iter
 
 # ANCHOR: fetch_all
@@ -29,8 +29,8 @@ def fetch_all_demo(conn: taos.TaosConnection):
 
 # row count: 2
 # ===============all data===================
-# [{'ts': datetime.datetime(2018, 10, 3, 14, 38, 5), 'current': 10.300000190734863},
-# {'ts': datetime.datetime(2018, 10, 3, 14, 38, 15), 'current': 12.600000381469727}]
+# [{'ts': datetime.datetime(2018, 10, 3, 14, 38, 5, 500000), 'current': 11.800000190734863},
+# {'ts': datetime.datetime(2018, 10, 3, 14, 38, 16, 600000), 'current': 13.399999618530273}]
 # ANCHOR_END: fetch_all
 
 if __name__ == '__main__':