CompactTimeSeries is an in-memory time series library for space-efficient storing, processing, resampling and compressing of time series data.
PM> Install-Package PhilipDaubmeier.CompactTimeSeriesIf you need to deal with mostly equidistant time series with a large number of values, e.g. sensor readings that are equally spaced in time, and need to process them in memory. The main classes of this library, which implement ITimeSeries<T> allow for convenient random access read/write to a time series via time-based indexers.
If you need fast persisting/loading of such time series data, this library will not help you - just use a time series database like Influx, Graphite, CrateDB etc.
// Create a time series for today with 1 second spacing, which will result in 86400 values
var span = new TimeSeriesSpan(DateTime.Now.Date, DateTime.Now.Date.AddDays(1), TimeSeriesSpan.Spacing.Spacing1Sec);
var timeseries = new TimeSeriesStream<int>(span);
// Write to the time series via time-based indexer: the time bucket for the current second will be written
timeseries[DateTime.Now] = 42;
// Enumerate the time series values and timestamps like an IEnumerable<KeyValuePair<DateTime, T?>>
foreach (var timestampedValue in timeseries)
DoSomething(timestampedValue);For more usage examples you can also have a look at the unit tests.
CompactTimeSeries is targeted for .NET 9.0 or higher.
The MIT License (MIT)
Copyright (c) 2019-2024 Philip Daubmeier
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