Python influxdb08.DataFrameClient类代码示例

    def test_write_points_from_dataframe_with_numeric_column_names(self):
        """Test write points from dataframe with numeric columns."""
        now = pd.Timestamp('1970-01-01 00:00+00:00')
        # df with numeric column names
        dataframe = pd.DataFrame(data=[["1", 1, 1.0], ["2", 2, 2.0]],
                                 index=[now, now + timedelta(hours=1)])
        points = [
            {
                "points": [
                    ["1", 1, 1.0, 0],
                    ["2", 2, 2.0, 3600]
                ],
                "name": "foo",
                "columns": ['0', '1', '2', "time"]
            }
        ]

        with requests_mock.Mocker() as m:
            m.register_uri(requests_mock.POST,
                           "http://localhost:8086/db/db/series")

            cli = DataFrameClient(database='db')
            cli.write_points({"foo": dataframe})

            self.assertListEqual(json.loads(m.last_request.body), points)

    def test_write_points_from_dataframe_with_float_nan(self):
        now = pd.Timestamp('1970-01-01 00:00+00:00')
        dataframe = pd.DataFrame(data=[[1, float("NaN"), 1.0], [2, 2, 2.0]],
                                 index=[now, now + timedelta(hours=1)],
                                 columns=["column_one", "column_two",
                                          "column_three"])
        points = [
            {
                "points": [
                    [1, None, 1.0, 0],
                    [2, 2, 2.0, 3600]
                ],
                "name": "foo",
                "columns": ["column_one", "column_two", "column_three", "time"]
            }
        ]

        with requests_mock.Mocker() as m:
            m.register_uri(requests_mock.POST,
                           "http://localhost:8086/db/db/series")

            cli = DataFrameClient(database='db')
            cli.write_points({"foo": dataframe})

            self.assertListEqual(json.loads(m.last_request.body), points)

    def test_write_points_from_dataframe_with_period_index(self):
        dataframe = pd.DataFrame(data=[["1", 1, 1.0], ["2", 2, 2.0]],
                                 index=[pd.Period('1970-01-01'),
                                        pd.Period('1970-01-02')],
                                 columns=["column_one", "column_two",
                                          "column_three"])
        points = [
            {
                "points": [
                    ["1", 1, 1.0, 0],
                    ["2", 2, 2.0, 86400]
                ],
                "name": "foo",
                "columns": ["column_one", "column_two", "column_three", "time"]
            }
        ]

        with requests_mock.Mocker() as m:
            m.register_uri(requests_mock.POST,
                           "http://localhost:8086/db/db/series")

            cli = DataFrameClient(database='db')
            cli.write_points({"foo": dataframe})

            self.assertListEqual(json.loads(m.last_request.body), points)

 def _search_db(self,series_name):
     '''
     Search the db name for a series name
     '''
     for db in self.db_list:
         temp_db = DataFrameClient(self.url, self.port, self.user, self.password, db)
         if series_name in temp_db.get_list_series():
             return db
     
     return None

    def test_write_points_from_dataframe_fails_with_series(self):
        now = pd.Timestamp('1970-01-01 00:00+00:00')
        dataframe = pd.Series(data=[1.0, 2.0],
                              index=[now, now + timedelta(hours=1)])

        with requests_mock.Mocker() as m:
            m.register_uri(requests_mock.POST,
                           "http://localhost:8086/db/db/series")

            cli = DataFrameClient(database='db')
            cli.write_points({"foo": dataframe})

    def test_write_points_from_dataframe_fails_without_time_index(self):
        dataframe = pd.DataFrame(data=[["1", 1, 1.0], ["2", 2, 2.0]],
                                 columns=["column_one", "column_two",
                                          "column_three"])

        with requests_mock.Mocker() as m:
            m.register_uri(requests_mock.POST,
                           "http://localhost:8086/db/db/series")

            cli = DataFrameClient(database='db')
            cli.write_points({"foo": dataframe})

    def test_write_points_from_dataframe_in_batches(self):
        now = pd.Timestamp('1970-01-01 00:00+00:00')
        dataframe = pd.DataFrame(data=[["1", 1, 1.0], ["2", 2, 2.0]],
                                 index=[now, now + timedelta(hours=1)],
                                 columns=["column_one", "column_two",
                                          "column_three"])
        with requests_mock.Mocker() as m:
            m.register_uri(requests_mock.POST,
                           "http://localhost:8086/db/db/series")

            cli = DataFrameClient(database='db')
            self.assertTrue(cli.write_points({"foo": dataframe}, batch_size=1))

 def test_list_series(self):
     response = [
         {
             'columns': ['time', 'name'],
             'name': 'list_series_result',
             'points': [[0, 'seriesA'], [0, 'seriesB']]
         }
     ]
     with _mocked_session('get', 200, response):
         cli = DataFrameClient('host', 8086, 'username', 'password', 'db')
         series_list = cli.get_list_series()
         self.assertEqual(series_list, ['seriesA', 'seriesB'])

 def __init__(self, db_name=None):
     self.url = 'localhost'
     self.port = 8086
     self.user = 'root'
     self.password = 'root'
     self.db_list = [ 'FRED', 'Quandl', 'Econ', 'ChinaData' ]
     
     self.db = DataFrameClient(self.url, self.port, self.user, self.password)
     if(db_name != None):
         self.db_name = db_name
     self.db.switch_database(db_name)

 def test_query_into_dataframe(self):
     data = [
         {
             "name": "foo",
             "columns": ["time", "sequence_number", "column_one"],
             "points": [
                 [3600, 16, 2], [3600, 15, 1],
                 [0, 14, 2], [0, 13, 1]
             ]
         }
     ]
     # dataframe sorted ascending by time first, then sequence_number
     dataframe = pd.DataFrame(data=[[13, 1], [14, 2], [15, 1], [16, 2]],
                              index=pd.to_datetime([0, 0,
                                                   3600, 3600],
                                                   unit='s', utc=True),
                              columns=['sequence_number', 'column_one'])
     with _mocked_session('get', 200, data):
         cli = DataFrameClient('host', 8086, 'username', 'password', 'db')
         result = cli.query('select column_one from foo;')
         assert_frame_equal(dataframe, result)

    def test_datetime_to_epoch(self):
        """Test convert datetime to epoch."""
        timestamp = pd.Timestamp('2013-01-01 00:00:00.000+00:00')
        cli = DataFrameClient('host', 8086, 'username', 'password', 'db')

        self.assertEqual(
            cli._datetime_to_epoch(timestamp),
            1356998400.0
        )
        self.assertEqual(
            cli._datetime_to_epoch(timestamp, time_precision='s'),
            1356998400.0
        )
        self.assertEqual(
            cli._datetime_to_epoch(timestamp, time_precision='m'),
            1356998400000.0
        )
        self.assertEqual(
            cli._datetime_to_epoch(timestamp, time_precision='ms'),
            1356998400000.0
        )
        self.assertEqual(
            cli._datetime_to_epoch(timestamp, time_precision='u'),
            1356998400000000.0
        )

 def test_query_multiple_time_series(self):
     """Test query for multiple time series."""
     data = [
         {
             "name": "series1",
             "columns": ["time", "mean", "min", "max", "stddev"],
             "points": [[0, 323048, 323048, 323048, 0]]
         },
         {
             "name": "series2",
             "columns": ["time", "mean", "min", "max", "stddev"],
             "points": [[0, -2.8233, -2.8503, -2.7832, 0.0173]]
         },
         {
             "name": "series3",
             "columns": ["time", "mean", "min", "max", "stddev"],
             "points": [[0, -0.01220, -0.01220, -0.01220, 0]]
         }
     ]
     dataframes = {
         'series1': pd.DataFrame(data=[[323048, 323048, 323048, 0]],
                                 index=pd.to_datetime([0], unit='s',
                                                      utc=True),
                                 columns=['mean', 'min', 'max', 'stddev']),
         'series2': pd.DataFrame(data=[[-2.8233, -2.8503, -2.7832, 0.0173]],
                                 index=pd.to_datetime([0], unit='s',
                                                      utc=True),
                                 columns=['mean', 'min', 'max', 'stddev']),
         'series3': pd.DataFrame(data=[[-0.01220, -0.01220, -0.01220, 0]],
                                 index=pd.to_datetime([0], unit='s',
                                                      utc=True),
                                 columns=['mean', 'min', 'max', 'stddev'])
     }
     with _mocked_session('get', 200, data):
         cli = DataFrameClient('host', 8086, 'username', 'password', 'db')
         result = cli.query("""select mean(value), min(value), max(value),
             stddev(value) from series1, series2, series3""")
         self.assertEqual(dataframes.keys(), result.keys())
         for key in dataframes.keys():
             assert_frame_equal(dataframes[key], result[key])

    def test_write_points_from_dataframe_with_time_precision(self):
        """Test write points from dataframe with time precision."""
        now = pd.Timestamp('1970-01-01 00:00+00:00')
        dataframe = pd.DataFrame(data=[["1", 1, 1.0], ["2", 2, 2.0]],
                                 index=[now, now + timedelta(hours=1)],
                                 columns=["column_one", "column_two",
                                          "column_three"])
        points = [
            {
                "points": [
                    ["1", 1, 1.0, 0],
                    ["2", 2, 2.0, 3600]
                ],
                "name": "foo",
                "columns": ["column_one", "column_two", "column_three", "time"]
            }
        ]

        points_ms = copy.deepcopy(points)
        points_ms[0]["points"][1][-1] = 3600 * 1000

        points_us = copy.deepcopy(points)
        points_us[0]["points"][1][-1] = 3600 * 1000000

        with requests_mock.Mocker() as m:
            m.register_uri(requests_mock.POST,
                           "http://localhost:8086/db/db/series")

            cli = DataFrameClient(database='db')

            cli.write_points({"foo": dataframe}, time_precision='s')
            self.assertListEqual(json.loads(m.last_request.body), points)

            cli.write_points({"foo": dataframe}, time_precision='m')
            self.assertListEqual(json.loads(m.last_request.body), points_ms)

            cli.write_points({"foo": dataframe}, time_precision='u')
            self.assertListEqual(json.loads(m.last_request.body), points_us)

class InfluxDB(object):
    '''
    Connect to influxdb and pull/write data
    '''
    def __init__(self, db_name=None):
        self.url = 'localhost'
        self.port = 8086
        self.user = 'root'
        self.password = 'root'
        self.db_list = [ 'FRED', 'Quandl', 'Econ', 'ChinaData' ]
        
        self.db = DataFrameClient(self.url, self.port, self.user, self.password)
        if(db_name != None):
            self.db_name = db_name
        self.db.switch_database(db_name)
        
    def _search_db(self,series_name):
        '''
        Search the db name for a series name
        '''
        for db in self.db_list:
            temp_db = DataFrameClient(self.url, self.port, self.user, self.password, db)
            if series_name in temp_db.get_list_series():
                return db
        
        return None
            
    def query(self,series_name,db_name=None):
        '''
        Query a particular series
        ------
        series_name: str
            name of the series, e.g. "CPI_US"
        ------
        return a pandas DataFrame with NaN representing missing values
        ------
        '''
        if(db_name != None):
            self.db.switch_database(db_name)
            results = self.db.query('SELECT * FROM %s' % series_name)
        else:
            db_name = self._search_db(series_name)
            self.db.switch_database(db_name)
            results = self.db.query('SELECT * FROM %s' % series_name)       
        
        if(results['value'].str.contains('.').isnull().sum()!=len(results)):
            results.loc[results['value']=='.','value'] = None
        
        return results.astype(float)
    
    def _is_num(self, s):
        '''
        Determine if a string is a number
        '''
        try:
            float(s)
            return True
        except ValueError:
            return False
    
    def _include(self,expression_list,c):
        '''
        check whether expression_list include basic operator c, and give the index of first occurrence
        ------
        c: str
            the basic operator or parentheses c
        ------
        '''
        for index, item in enumerate(expression_list):
            if(type(item)==type('string')):
                if(item == c):
                    return index
        
        return -1
            
        
    def _get_index(self,expression_list, op_1, op_2):
        '''
        Get the index of first occurrence of op_1 OR op_2, assume expression_list includes op_1 OR op_2
        '''
        index_1 = self._include(expression_list, op_1)
        index_2 = self._include(expression_list, op_2)
        
        if(min(index_1,index_2)==-1):
            return(max(index_1,index_2))
        else:
            return(min(index_1,index_2))
    
    def _close_parentheses(self,expression):
        '''
        Find the closing parentheses to the first opening (
        ------
        expression: str
            str contains an opening (
        ------
        '''
        layer = 0
        for i, char in enumerate(expression):
            if(char=='('):
                layer = layer + 1
#.........这里部分代码省略.........

 def test_query_with_empty_result(self):
     with _mocked_session('get', 200, []):
         cli = DataFrameClient('host', 8086, 'username', 'password', 'db')
         result = cli.query('select column_one from foo;')
         self.assertEqual(result, [])