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Version: Python

Replay data from static tables

This guide will show you how to replay historical data as if it was live data in Deephaven.

Deephaven excels at handling live data. Integrating historical data into real-time analysis is common in a multitude of fields including machine learning, validation, modeling, simulation, and forecasting.

For learning, testing, and other purposes, it can be useful to replay pre-recorded data as if it were live.

In this guide, we will take historical data and play it back as real-time data based on timestamps in a table. This example could be easily extended towards a variety of real-world applications.

Get a historical data table​

To replay historical data, we need a table with timestamps in DateTime format. Let's grab one from Deephaven's examples repository. We'll use data from a 100 km bike ride in a file called metriccentury.csv.

from deephaven import read_csv

metric_century = read_csv(
    "https://media.githubusercontent.com/media/deephaven/examples/main/MetricCentury/csv/metriccentury.csv"
)

Replay the data​

The data is in memory. We can replay it with the following steps:

  • Import TableReplayer.
  • Set a start and end time for data replay.
    • These times correspond to those in the table itself.
  • Create the replayer using the start and end time.
  • Call add_table to prepare the replayed table.
    • This takes two inputs: the table and the DateTime column name.
  • Call start to start replaying data.
from deephaven.replay import TableReplayer
from deephaven.time import to_j_instant

start_time = to_j_instant("2019-08-25T15:34:55Z")
end_time = to_j_instant("2019-08-25T17:10:22Z")

replayer = TableReplayer(start_time, end_time)
replayed_table = replayer.add_table(metric_century, "Time")
replayer.start()

Replay a table with no date-time column​

Some historical data tables don't have a date-time column.

from deephaven import read_csv

iris = read_csv(
    "https://media.githubusercontent.com/media/deephaven/examples/main/Iris/csv/iris.csv"
)

In such a case, a date-time column can be added.

from deephaven.time import to_j_instant

start_time = to_j_instant("2022-01-01T00:00:00 ET")

iris_with_datetimes = iris.update(["Timestamp = start_time + i * SECOND"])

Then, the data can be replayed just as before.

from deephaven.replay import TableReplayer
from deephaven.time import to_j_instant

start_time = to_j_instant("2022-01-01T00:00:00 ET")
end_time = to_j_instant("2022-01-01T00:02:30 ET")

replayer = TableReplayer(start_time, end_time)
replayed_iris = replayer.add_table(iris_with_datetimes, "Timestamp")
replayer.start()

Replay multiple tables​

Real-time applications in Deephaven commonly involve more than a single ticking table. These tables tick simultaneously. A table replayer can be used to replay multiple tables at the same time, provided that the timestamps overlap.

The following code creates two tables with timestamps that overlap.

from deephaven import empty_table

source_1 = empty_table(20).update(["Timestamp = '2024-01-01T08:00:00 ET' + i * SECOND"])
source_2 = empty_table(25).update(
    ["Timestamp = '2024-01-01T08:00:00 ET' + i * (int)(0.8 * SECOND)"]
)

To replay multiple tables with the same replayer, simply call add_table twice before start.

from deephaven.replay import TableReplayer

replayer = TableReplayer(
    start_time="2024-01-01T08:00:00 ET", end_time="2024-01-01T08:00:20 ET"
)

replayed_source_1 = replayer.add_table(table=source_1, col="Timestamp")
replayed_source_2 = replayer.add_table(table=source_2, col="Timestamp")
replayer.start()