cs.timeseries 20220606

Efficient portable machine native columnar storage of time series data for double float and signed 64-bit integers.

Efficient portable machine native columnar storage of time series data for double float and signed 64-bit integers.

Latest release 20220606: Initial PyPI release.

The core purpose is to provide time series data storage; there are assorted convenience methods to export arbitrary subsets of the data for use by other libraries in common forms, such as dataframes or series, numpy arrays and simple lists. There are also some simple plot methods for plotting graphs.

Three levels of storage are defined here:

• TimeSeriesFile: a single file containing a binary list of float64 or signed int64 values
• TimeSeriesPartitioned: a directory containing multiple TimeSeriesFile files, each covering a separate time span according to a supplied policy, for example a calendar month
• TimeSeriesDataDir: a directory containing multiple TimeSeriesPartitioned subdirectories, each for a different time series, for example one subdirectory for grid voltage and another for grid power

Together these provide a hierarchy for finite sized files storing unbounded time series data for multiple parameters.

On a personal basis, I use this as efficient storage of time series data from my solar inverter, which reports in a slightly clunky time limited CSV format; I import those CSVs into time series data directories which contain the overall accrued data; see my cs.splink module which is built on this module.

Function array_byteswapped(ary)

Context manager to byteswap the array.array ary temporarily.

Class ArrowBasedTimespanPolicy(TimespanPolicy, icontract._metaclass.DBC, HasEpochMixin, TimeStepsMixin)

A TimespanPolicy based on an Arrow format string.

See the raw_edges method for the specifics of how these are defined.

Function deduce_type_bigendianness(typecode: str) -> bool

Deduce the native endianness for typecode, an array/struct typecode character.

Class Epoch(Epoch, builtins.tuple, TimeStepsMixin)

The basis of time references with a starting UNIX time, the epoch and the step defining the width of a time slot.

Function get_default_timezone_name()

Return the default timezone name.

Class HasEpochMixin(TimeStepsMixin)

A TimeStepsMixin with .start and .step derive from self.epoch.

Function main(argv=None)

Run the command line tool for TimeSeries data.

Function plot_events(ax, events, value_func, *, start=None, stop=None, **scatter_kw)

Plot events, an iterable of objects with .unixtime attributes such as an SQLTagSet, on an existing set of axes ax.

Parameters:

• ax: axes on which to plot
• events: an iterable of objects with .unixtime attributes
• value_func: a callable to compute the y-axis value from an event
• start: optional start UNIX time, used to crop the events plotted
• stop: optional stop UNIX time, used to crop the events plotted Other keyword parameters are passed to Axes.scatter.

Function plotrange(*da, **dkw)

A decorator for plotting methods with optional start and stop leading positional parameters and an optional figure keyword parameter.

The decorator parameters needs_start and needs_stop may be set to require non-None values for start and stop.

If start is None its value is set to self.start. If stop is None its value is set to self.stop.

The decorated method is then called as:

func(self, start, stop, *a, **kw)

where *a and **kw are the additional positional and keyword parameters respectively, if any.

Function print_figure(figure_or_ax, imgformat=None, file=None)

Print figure_or_ax to a file.

Parameters:

• figure_or_ax: a matplotlib.figure.Figure or an object with a .figure attribute such as a set of Axes
• imgformat: optional output format; if omitted use 'sixel' if file is a terminal, otherwise 'png'
• file: the output file, default sys.stdout

Function save_figure(figure_or_ax, imgpath: str, force=False)

Save a Figure to the file imgpath.

Parameters:

• figure_or_ax: a matplotlib.figure.Figure or an object with a .figure attribute such as a set of Axes
• imgpath: the filesystem path to which to save the image
• force: optional flag, default False: if true the imgpath will be written to even if it exists

Function saved_figure(figure_or_ax, dir=None, ext=None)

Context manager to save a Figure to a file and yield the file path.

Parameters:

• figure_or_ax: a matplotlib.figure.Figure or an object with a .figure attribute such as a set of Axes
• dir: passed to tempfile.TemporaryDirectory
• ext: optional file extension, default 'png'

Function struct_format(typecode, bigendian)

Return a struct format string for the supplied typecode and big endianness.

Class TimePartition(TimePartition, builtins.tuple, TimeStepsMixin)

A namedtuple for a slice of time with the following attributes:

• epoch: the reference Epoch
• name: the name for this slice
• offset0: the epoch offset of the start time (self.start)
• steps: the number of time slots in this partition

These are used by TimespanPolicy instances to express the partitions into which they divide time.

Class TimeSeries(cs.resources.MultiOpenMixin, cs.context.ContextManagerMixin, HasEpochMixin, TimeStepsMixin)

Common base class of any time series.

Function timeseries_from_path(tspath: str, epoch: Union[cs.timeseries.Epoch, Tuple[Union[int, float], Union[int, float]], int, float, NoneType] = None, typecode=None)

Turn a time series filesystem path into a time series:

• a file: a TimeSeriesFile
• a directory holding .csts files: a TimeSeriesPartitioned
• a directory: a TimeSeriesDataDir

Class TimeSeriesBaseCommand(cs.cmdutils.BaseCommand)

Abstract base class for command line interfaces to TimeSeries data files.

Command line usage:

Usage: timeseriesbase subcommand [...]
  Subcommands:
    fetch ...
      Fetch raw data files from the primary source to a local spool.
      To be implemented in subclasses.
    help [-l] [subcommand-names...]
      Print the full help for the named subcommands,
      or for all subcommands if no names are specified.
      -l  Long help even if no subcommand-names provided.
    import ...
      Import data into the time series.
      To be implemented in subclasses.
    info
      Report information.
    plot [-f] [-o imgpath.png] [--show] days [{glob|fields}...]
      Plot the most recent days of data from the time series at tspath.
      Options:
      -f              Force. -o will overwrite an existing image file.
      -o imgpath.png  File system path to which to save the plot.
      --show          Show the image in the GUI.
      --stacked       Stack the plot lines/areas.
      glob|fields     If glob is supplied, constrain the keys of
                      a TimeSeriesDataDir by the glob.

Class TimeSeriesCommand(TimeSeriesBaseCommand, cs.cmdutils.BaseCommand)

Command line interface to TimeSeries data files.

Command line usage:

Usage: timeseries [-s ts-step] tspath subcommand...
    -s ts-step  Specify the UNIX time step for the time series,
                used if the time series is new and checked otherwise.
    tspath      The filesystem path to the time series;
                this may refer to a single .csts TimeSeriesFile, a
                TimeSeriesPartitioned directory of such files, or
                a TimeSeriesDataDir containing partitions for
                multiple keys.
  Subcommands:
    dump
      Dump the contents of tspath.
    fetch ...
      Fetch raw data files from the primary source to a local spool.
      To be implemented in subclasses.
    help [-l] [subcommand-names...]
      Print the full help for the named subcommands,
      or for all subcommands if no names are specified.
      -l  Long help even if no subcommand-names provided.
    import csvpath datecol[:conv] [import_columns...]
      Import data into the time series.
      csvpath   The CSV file to import.
      datecol[:conv]
                Specify the timestamp column and optional
                conversion function.
                "datecol" can be either the column header name
                or a numeric column index counting from 0.
                If "conv" is omitted, the column should contain
                a UNIX seconds timestamp.  Otherwise "conv"
                should be either an identifier naming one of
                the known conversion functions or an "arrow.get"
                compatible time format string.
      import_columns
                An optional list of column names or their derived
                attribute names. The default is to import every
                numeric column except for the datecol.
    info
      Report infomation about the time series stored at tspath.
    plot [-f] [-o imgpath.png] [--show] days [{glob|fields}...]
      Plot the most recent days of data from the time series at tspath.
      Options:
      -f              Force. -o will overwrite an existing image file.
      -o imgpath.png  File system path to which to save the plot.
      --show          Show the image in the GUI.
      --stacked       Stack the plot lines/areas.
      glob|fields     If glob is supplied, constrain the keys of
                      a TimeSeriesDataDir by the glob.
    test [testnames...]
      Run some tests of functionality.

Class TimeSeriesDataDir(TimeSeriesMapping, builtins.dict, cs.resources.MultiOpenMixin, cs.context.ContextManagerMixin, cs.fs.HasFSPath, cs.configutils.HasConfigIni, HasEpochMixin, TimeStepsMixin)

A directory containing a collection of TimeSeriesPartitioned subdirectories.

Class TimeSeriesFile(TimeSeries, cs.resources.MultiOpenMixin, cs.context.ContextManagerMixin, HasEpochMixin, TimeStepsMixin, cs.fs.HasFSPath)

A file containing a single time series for a single data field.

This provides easy access to a time series data file. The instance can be indexed by UNIX time stamp for time based access or its .array property can be accessed for the raw data.

Read only users can just instantiate an instance. Read/write users should use the instance as a context manager, which will automatically rewrite the file with the array data on exit.

Note that the save-on-close is done with TimeSeries.flush() which ony saves if self.modified. Use of the __setitem__ or pad_to methods set this flag automatically. Direct access via the .array will not set it, so users working that way for performance should update the flag themselves.

The data file itself has a header indicating the file data big endianness, the datum type and the time type (both array.array type codes). Following these are the start and step sizes in the time type format. This is automatically honoured on load and save.

Method TimeSeriesFile.__init__(self, fspath: str, typecode: Optional[str] = None, *, epoch: Union[cs.timeseries.Epoch, Tuple[Union[int, float], Union[int, float]], int, float, NoneType] = None, fill=None, fstags=None): Prepare a new time series stored in the file at fspath containing machine data for the time series values.

Parameters:

• fspath: the filename of the data file
• typecode optional expected array.typecode value of the data; if specified and the data file exists, they must match; if not specified then the data file must exist and the typecode will be obtained from its header
• start: the UNIX epoch time for the first datum
• step: the increment between data times
• time_typecode: the type of the start and step times; inferred from the type of the start time value if unspecified
• fill: optional default fill values for pad_to; if unspecified, fill with 0 for 'q' and float('nan') for 'd'`

If start or step are omitted the file's fstags will be consulted for their values. This class does not set these tags (that would presume write access to the parent directory or its .fstags file) when a TimeSeriesFile is made by a TimeSeriesPartitioned instance it sets these flags.

Class TimeSeriesFileHeader(cs.binary.SimpleBinary, types.SimpleNamespace, cs.binary.AbstractBinary, cs.binary.BinaryMixin, HasEpochMixin, TimeStepsMixin)

The binary data structure of the TimeSeriesFile file header.

This is 24 bytes long and consists of:

• the 4 byte magic number, b'csts'
• the file bigendian marker, a struct byte order indicator with a value of b'>' for big endian data or b'<' for little endian data
• the datum typecode, b'd' for double float or b'q' for signed 64 bit integer
• the time typecode, b'd' for double float or b'q' for signed 64 bit integer
• a pad byte, value b'_'
• the start UNIX time, a double float or signed 64 bit integer according to the time typecode and bigendian flag
• the step size, a double float or signed 64 bit integer according to the time typecode and bigendian flag

In addition to the header values tnd methods this also presents:

• datum_type: a BinarySingleStruct for the binary form of a data value
• time_type: a BinarySingleStruct for the binary form of a time value

Class TimeSeriesMapping(builtins.dict, cs.resources.MultiOpenMixin, cs.context.ContextManagerMixin, HasEpochMixin, TimeStepsMixin)

A group of named TimeSeries instances, indexed by a key.

This is the basis for TimeSeriesDataDir.

Class TimeSeriesPartitioned(TimeSeries, cs.resources.MultiOpenMixin, cs.context.ContextManagerMixin, HasEpochMixin, TimeStepsMixin, cs.fs.HasFSPath)

A collection of TimeSeries files in a subdirectory. We have one of these for each TimeSeriesDataDir key.

This class manages a collection of files named by the partition from a TimespanPolicy, which dictates which partition holds the datum for a UNIX time.

Method TimeSeriesPartitioned.__init__(self, dirpath: str, typecode: str, *, epoch: Union[cs.timeseries.Epoch, Tuple[Union[int, float], Union[int, float]], int, float, NoneType] = None, policy, fstags: Optional[cs.fstags.FSTags] = None): Initialise the TimeSeriesPartitioned instance.

Parameters:

• dirpath: the directory filesystem path, known as .fspath within the instance
• typecode: the array type code for the data
• epoch: the time series Epoch
• policy: the partitioning TimespanPolicy

The instance requires a reference epoch because the policy start times will almost always not fall on exact multiples of epoch.step. The reference allows for reliable placement of times which fall within epoch.step of a partition boundary. For example, if epoch.start==0 and epoch.step==6 and a partition boundary came at 19 due to some calendar based policy then a time of 20 would fall in the partion left of the boundary because it belongs to the time slot commencing at 18.

If epoch or typecode are omitted the file's fstags will be consulted for their values. The start parameter will further fall back to 0. This class does not set these tags (that would presume write access to the parent directory or its .fstags file) when a TimeSeriesPartitioned is made by a TimeSeriesDataDir instance it sets these flags.

Class TimespanPolicy(icontract._metaclass.DBC, HasEpochMixin, TimeStepsMixin)

A class implementing a policy allocating times to named time spans.

The TimeSeriesPartitioned uses these policies to partition data among multiple TimeSeries data files.

Probably the most important methods are:

• span_for_time: return a TimePartition from a UNIX time
• span_for_name: return a TimePartition a partition name

Method TimespanPolicy.__init__(self, epoch: Union[cs.timeseries.Epoch, Tuple[Union[int, float], Union[int, float]], int, float]): Initialise the policy.

Class TimespanPolicyAnnual(ArrowBasedTimespanPolicy, TimespanPolicy, icontract._metaclass.DBC, HasEpochMixin, TimeStepsMixin)

A annual time policy. PARTITION_FORMAT = 'YYYY' ARROW_SHIFT_PARAMS = {'years': 1}

Class TimespanPolicyDaily(ArrowBasedTimespanPolicy, TimespanPolicy, icontract._metaclass.DBC, HasEpochMixin, TimeStepsMixin)

A daily time policy. PARTITION_FORMAT = 'YYYY-MM-DD' ARROW_SHIFT_PARAMS = {'days': 1}

Class TimespanPolicyMonthly(ArrowBasedTimespanPolicy, TimespanPolicy, icontract._metaclass.DBC, HasEpochMixin, TimeStepsMixin)

A monthly time policy. PARTITION_FORMAT = 'YYYY-MM' ARROW_SHIFT_PARAMS = {'months': 1}

Class TimespanPolicyWeekly(ArrowBasedTimespanPolicy, TimespanPolicy, icontract._metaclass.DBC, HasEpochMixin, TimeStepsMixin)

A weekly time policy. PARTITION_FORMAT = 'W' ARROW_SHIFT_PARAMS = {'weeks': 1}

Class TimespanPolicyYearly(ArrowBasedTimespanPolicy, TimespanPolicy, icontract._metaclass.DBC, HasEpochMixin, TimeStepsMixin)

A annual time policy. PARTITION_FORMAT = 'YYYY' ARROW_SHIFT_PARAMS = {'years': 1}

Class TimeStepsMixin

Methods for an object with start and step attributes.

Function type_of(typecode: str) -> type

Return the type associated with array typecode. This supports the types in SUPPORTED_TYPECODES: int and float.

Function typecode_of(type_) -> str

Return the array typecode for the type type_. This supports the types in SUPPORTED_TYPECODES: int and float.

Release Log

Release 20220606: Initial PyPI release.