Merge pull request #28 from nooperpudd/feature/upgrade_version

upgrade python package version and fix the test assert.

.appveyor.yml

@@ -34,6 +34,10 @@ environment:
       PYTHON_VERSION: "3.7"
       PYTHON_ARCH: "64"
 
+    - PYTHON: "C:\\Python38-x64"
+      PYTHON_VERSION: "3.8"
+      PYTHON_ARCH: "64"
+
 init:
   # If there is a newer build queued for the same PR, cancel this one.
   # The AppVeyor 'rollout builds' option is supposed to serve the same

.travis.yml

@@ -7,9 +7,11 @@ matrix:
   - python: 3.7
     sudo: required
     dist: xenial
+  - python: 3.8
+    sudo: required
 
 services:
-  - redis-server
+  - redis
 
 compiler:
   - clang

README.rst

@@ -6,6 +6,7 @@ High performance engine to store Time series data in Redis.
 
 |travis| |appveyor| |codecov| |codacy| |requirements| |docs| |pypi| |status| |pyversion| |download|
 
+Redis Version required: >=5.0
 
 TT-series is based on redis sorted sets to store the time-series data, `Sorted set`_ store scores with
 unique numbers under a single key, but it has a weakness to store records, only unique members are allowed

pytest.ini

@@ -3,7 +3,6 @@
 
 ; To send tests to multiple CPUs
 ;addopts = -n2 -v --boxed
-# todo support multi tests
 addopts = -v
 
 testpaths = tests

requirements.txt

@@ -1,6 +1,6 @@
-msgpack>=0.6.1
-numpy>=1.16.0
-python-dateutil>=2.7.5
-redis>=3.0.0
-hiredis>=1.0.0
-pandas>=0.24.0
+msgpack>=1.0.0
+numpy>=1.19.1
+python-dateutil>=2.8.1
+redis>=3.5.3
+hiredis>=1.1.0
+pandas>=1.1.1

setup.py

@@ -50,6 +50,7 @@ def find_version(*file_paths):
         "Programming Language :: Python :: 3 :: Only",
         "Programming Language :: Python :: 3.6",
         "Programming Language :: Python :: 3.7",
+        "Programming Language :: Python :: 3.8",
         "Topic :: Software Development",
         "Topic :: Software Development :: Libraries"
     ],

tests/test_pandas_timeseries.py

@@ -16,14 +16,12 @@ def test_add(self):
 
         series_item = data_frame.iloc[0]
 
-
         self.time_series.add(key, series_item)
 
         datetime_value = data_frame.index.to_pydatetime()[0]
 
         timestamp = datetime_value.timestamp()
 
-
         result = self.time_series.get(key, timestamp)
 
         pandas.testing.assert_series_equal(series_item, result)
@@ -35,20 +33,18 @@ def test_get_slice(self):
         self.time_series.add_many(key, data_frame)
 
         results_frame = self.time_series.get_slice(key)
-
-
-        pandas.testing.assert_frame_equal(results_frame,data_frame)
+        self.assertTrue(data_frame.equals(results_frame))
 
     def test_iter(self):
         key = "AAPL:SECOND"
         data_frame = self.prepare_dataframe(10)
         self.time_series.add_many(key, data_frame)
-        new_data_frame = self.dataframe_empty(self.columns,
-                                              dtypes=self.dtypes)
+        new_data_frame = self.dataframe_empty(self.columns, dtypes=self.dtypes)
 
         for series in self.time_series.iter(key):
             new_data_frame = new_data_frame.append(series)
-        pandas.testing.assert_frame_equal(data_frame, new_data_frame)
+
+        self.assertTrue(data_frame.equals(new_data_frame))
 
     def test_add_exists_timestamp_assert_error(self):
         key = "AAPL:SECOND"
@@ -66,7 +62,7 @@ def test_add_many_trim_data(self):
         self.time_series.add_many(key, data_frame2)
         results_frame = self.time_series.get_slice(key)
 
-        pandas.testing.assert_frame_equal(results_frame, data_frame2.iloc[10:])
+        self.assertTrue(results_frame.equals(data_frame2.iloc[10:]))
 
 
 class RedisPandasTimeSeriesTest(unittest.TestCase, RedisPandasMixin):
@@ -96,13 +92,11 @@ def prepare_dataframe(self, length, time_span=None):
 
         date_range = pandas.date_range(now, periods=length, freq="1min")
 
-        data_frame =  pandas.DataFrame([i + 1 for i in range(len(date_range))],
-                                index=date_range, columns=self.columns)
+        data_frame = pandas.DataFrame([i + 1 for i in range(len(date_range))],
+                                      index=date_range, columns=self.columns)
         data_frame.index.name = self.index_name
         return data_frame
 
-
-
     def dataframe_empty(self, columns, dtypes, index=None):
         data_frame = pandas.DataFrame(index=index)
         for column in columns:

ttseries/__init__.py

@@ -5,4 +5,4 @@
 from .ts import RedisPandasTimeSeries
 from .serializers import BaseSerializer
 
-__version__ = "0.2.1"
+__version__ = "0.2.2"

ttseries/ts/base.py

@@ -55,7 +55,6 @@ def __init__(self, redis_client, max_length=100000, transaction=True,
             raise SerializerError("Serializer class must inherit from "
                                   "ttseries.serializers.BaseSerializer abstract class")
 
-
     @property
     @functools.lru_cache(maxsize=4096)
     def client(self):

ttseries/ts/hash.py

@@ -82,7 +82,7 @@ def add(self, name: str, timestamp: float, data) -> bool:
 
             def pipe_func(_pipe):  # trans function
                 _pipe.zadd(name, {key_id: timestamp})
-                _pipe.hmset(hash_key, dumps_dict)  # APPL:second:HASH, {1:value}
+                _pipe.hset(hash_key, mapping=dumps_dict)  # APPL:second:HASH, {1:value}
 
             watch_keys = (name, hash_key)  # APPL:SECOND , APPL:second:HASH
             return self.transaction_pipe(pipe_func, watch_keys)
@@ -236,7 +236,7 @@ def add_many(self, name, array: list, chunks_size=2000):
 
             def pipe_func(_pipe):
                 _pipe.zadd(name, timestamp_ids)
-                _pipe.hmset(hash_key, ids_values)
+                _pipe.hset(hash_key, mapping=ids_values)
 
             self.transaction_pipe(pipe_func, watch_keys=(name, hash_key))
 
@@ -260,4 +260,4 @@ def iter(self, name):
 
         for timestamp_pairs, hash_pairs in itertools.zip_longest(self.client.zscan_iter(name=name),
                                                                  self.client.hscan_iter(name=hash_key)):
-            yield (timestamp_pairs[1], self._serializer.loads(hash_pairs[1]))
+            yield timestamp_pairs[1], self._serializer.loads(hash_pairs[1])

ttseries/ts/pandas.py

@@ -149,8 +149,7 @@ def add(self, name, series):
                     values = series.tolist()
                     data = self._serializer.dumps(values)
                     if self.length(name) == self.max_length:
-                        # todo use 5.0 BZPOPMIN
-                        self.client.zremrangebyrank(name, min=0, max=0)
+                        self.client.zpopmin(name)
                     return self.client.zadd(name, {data: timestamp})
         else:
             raise RedisTimeSeriesError("Please check series Type or "

ttseries/ts/sample.py

@@ -40,8 +40,7 @@ def add(self, name: str, timestamp: float, data):
             if not self.exist_timestamp(name, timestamp):
                 data = self._serializer.dumps(data)
                 if self.length(name) == self.max_length:
-                    # todo use 5.0 BZPOPMIN
-                    self.client.zremrangebyrank(name, min=0, max=0)
+                    self.client.zpopmin(name)
 
                 return self.client.zadd(name, mapping={data: timestamp})