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Constants

pingthings.timeseries.constants

This module contains various static constants and schemas used by the Predictive Grid Platform

pingthings.timeseries.constants.PW module-attribute 

PW: tuple[_PW, ...] = tuple(_PW(i) for i in range(61))

Durations that naturally align with the platform timeseries data structure. Utilizing windowed value queries where the start, end and averaging windows align with these point-widths ensures optimal query performance.

These point-width durations are as follows:

point-width number of nanoseconds duration
PW[0] 1 1 ns
PW[1] 2 2 ns
PW[2] 4 4 ns
PW[3] 8 8 ns
PW[4] 16 16 ns
PW[5] 32 32 ns
PW[6] 64 64 ns
PW[7] 128 128 ns
PW[8] 256 256 ns
PW[9] 512 512 ns
PW[10] 1024 1 μs 24 ns
PW[11] 2048 2 μs 48 ns
PW[12] 4096 4 μs 96 ns
PW[13] 8192 8 μs 192 ns
PW[14] 16384 16 μs 384 ns
PW[15] 32768 32 μs 768 ns
PW[16] 65536 65 μs 536 ns
PW[17] 131072 131 μs 72 ns
PW[18] 262144 262 μs 144 ns
PW[19] 524288 524 μs 288 ns
PW[20] 1.04858e+06 1 ms 48 μs 576 ns
PW[21] 2.09715e+06 2 ms 97 μs 152 ns
PW[22] 4.1943e+06 4 ms 194 μs 304 ns
PW[23] 8.38861e+06 8 ms 388 μs 608 ns
PW[24] 1.67772e+07 16 ms 777 μs 216 ns
PW[25] 3.35544e+07 33 ms 554 μs 432 ns
PW[26] 6.71089e+07 67 ms 108 μs 864 ns
PW[27] 1.34218e+08 134 ms 217 μs 728 ns
PW[28] 2.68435e+08 268 ms 435 μs 456 ns
PW[29] 5.36871e+08 536 ms 870 μs 912 ns
PW[30] 1.07374e+09 1 sec 73 ms 741 μs
PW[31] 2.14748e+09 2 sec 147 ms 483 μs
PW[32] 4.29497e+09 4 sec 294 ms 967 μs
PW[33] 8.58993e+09 8 sec 589 ms 934 μs
PW[34] 1.71799e+10 17 sec 179 ms 869 μs
PW[35] 3.43597e+10 34 sec 359 ms 738 μs
PW[36] 6.87195e+10 1 min 8 sec 719 ms
PW[37] 1.37439e+11 2 mins 17 sec 438 ms
PW[38] 2.74878e+11 4 mins 34 sec 877 ms
PW[39] 5.49756e+11 9 mins 9 sec 755 ms
PW[40] 1.09951e+12 18 mins 19 sec 511 ms
PW[41] 2.19902e+12 36 mins 39 sec 23 ms
PW[42] 4.39805e+12 1 hour 13 mins 18 sec
PW[43] 8.79609e+12 2 hours 26 mins 36 sec
PW[44] 1.75922e+13 4 hours 53 mins 12 sec
PW[45] 3.51844e+13 9 hours 46 mins 24 sec
PW[46] 7.03687e+13 19 hours 32 mins 48 sec
PW[47] 1.40737e+14 1 day 15 hours 5 mins
PW[48] 2.81475e+14 3 days 6 hours 11 mins
PW[49] 5.6295e+14 6 days 12 hours 22 mins
PW[50] 1.1259e+15 13 days 44 mins 59 sec
PW[51] 2.2518e+15 26 days 1 hour 29 mins
PW[52] 4.5036e+15 52 days 2 hours 59 mins
PW[53] 9.0072e+15 104 days 5 hours 59 mins
PW[54] 1.80144e+16 208 days 11 hours 59 mins
PW[55] 3.60288e+16 1 year 51 days 23 hours
PW[56] 7.20576e+16 2 years 103 days 23 hours
PW[57] 1.44115e+17 4 years 207 days 23 hours
PW[58] 2.8823e+17 9 years 50 days 23 hours
PW[59] 5.76461e+17 18 years 101 days 23 hours
PW[60] 1.15292e+18 36 years 203 days 23 hours

pingthings.timeseries.constants.MINIMUM_TIME module-attribute 

MINIMUM_TIME: Final[int] = -16 << 56

Minimum time the timeseries platform supports.

pingthings.timeseries.constants.MAXIMUM_TIME module-attribute 

MAXIMUM_TIME: Final[int] = 48 << 56 - 1

Maximum time the timeseries platform supports.

pingthings.timeseries.constants.TIME_VALUE_F64_SCHEMA module-attribute 

TIME_VALUE_F64_SCHEMA: Final[Schema] = schema(
    [
        field(
            "time",
            timestamp(unit="ns", tz="UTC"),
            nullable=False,
        ),
        field("value", float64(), nullable=False),
    ]
)

The pyarrow schema that all timeseries inserts are coerced to.

pingthings.timeseries.constants.TIME_VALUE_F32_SCHEMA module-attribute 

TIME_VALUE_F32_SCHEMA: Final[Schema] = schema(
    [
        field(
            "time",
            timestamp(unit="ns", tz="UTC"),
            nullable=False,
        ),
        field("value", float32(), nullable=False),
    ]
)

32-bit floating point value column, null values will be represented as NaNs, the default return schema from the platform for raw data queries.

pingthings.timeseries.constants.TIME_VALUE_F32_NULLABLE_VALUE_SCHEMA module-attribute 

TIME_VALUE_F32_NULLABLE_VALUE_SCHEMA: Final[Schema] = (
    schema(
        [
            field(
                "time",
                timestamp(unit="ns", tz="UTC"),
                nullable=False,
            ),
            field("value", float32(), nullable=True),
        ]
    )
)

32-bit floating point value column, where the value column can be nullable instead of NaNs.

pingthings.timeseries.constants.STAT_F32_SCHEMA module-attribute 

STAT_F32_SCHEMA: Final[Schema] = schema(
    [
        field(
            "time",
            timestamp("ns", tz="UTC"),
            nullable=False,
        ),
        field("min", float32(), nullable=False),
        field("mean", float32(), nullable=False),
        field("max", float32(), nullable=False),
        field("count", uint64(), nullable=False),
        field("stddev", float32(), nullable=False),
    ]
)

32-bit floating point schema for min, mean, max and stddev.

pingthings.timeseries.constants.STAT_F64_SCHEMA module-attribute 

STAT_F64_SCHEMA: Final[Schema] = schema(
    [
        field(
            "time",
            timestamp("ns", tz="UTC"),
            nullable=False,
        ),
        field("min", float64(), nullable=False),
        field("mean", float64(), nullable=False),
        field("max", float64(), nullable=False),
        field("count", uint64(), nullable=False),
        field("stddev", float64(), nullable=False),
    ]
)

Statistical point data returned by windows and aligned_window queries.

pingthings.timeseries.constants.DEFAULT_CONCURRENCY_LIMIT module-attribute 

DEFAULT_CONCURRENCY_LIMIT: Final[int] = 64

Limit on amount of tasks to be scheduled at once.

pingthings.timeseries.constants.CONCURRENCY_ENV_VAR module-attribute 

CONCURRENCY_ENV_VAR: Final[str] = (
    "PINGTHINGS_CONCURRENCY_LIMIT"
)

Control the asynchronous concurrency limit using this environment variable.