pyre.tabular¶
Submodules¶
pyre.tabular.Chartpyre.tabular.Columnpyre.tabular.Dimensionpyre.tabular.Inferredpyre.tabular.Intervalpyre.tabular.Measurepyre.tabular.Pivotpyre.tabular.Primarypyre.tabular.Reductionpyre.tabular.Selectorpyre.tabular.Sheetpyre.tabular.Surveyorpyre.tabular.Tabulatorpyre.tabular.Viewpyre.tabular.exceptions
Package Contents¶
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pyre.tabular.field¶
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pyre.tabular.derivation¶
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pyre.tabular.literal¶
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class
pyre.tabular.measure¶ Bases:
pyre.records.measureBase class for the measures in this package
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_primary= False¶
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primary(self)¶ Mark this measure as a primary key
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pyre.tabular.bool¶
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pyre.tabular.decimal¶
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pyre.tabular.float¶
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pyre.tabular.inet¶
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pyre.tabular.int¶
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pyre.tabular.identity¶
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pyre.tabular.str¶
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pyre.tabular.date¶
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pyre.tabular.dimensional¶
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pyre.tabular.time¶
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pyre.tabular.uri¶
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pyre.tabular.list¶
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pyre.tabular.set¶
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pyre.tabular.tuple¶
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class
pyre.tabular.sheet(name, **kwds)¶ Bases:
pyre.records.recordThe base class for pyre worksheets, collections of record instances
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pyre_name¶
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pyre_data¶
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pyre_immutable(self, data)¶ Iterate over {data} extracting records that are compatible with my layout and use them to populate my data set
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pyre_mutable(self, data)¶ Iterate over {data} extracting records that are compatible with my layout and use them to populate my data set
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pyre_append(self, row)¶ Add the given {row} to my data set
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pyre_new(self)¶ Create a new blank mutable record instance and add it to my data set
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__len__(self)¶ Compute the number of records in my dataset
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__iter__(self)¶ Build an iterator over my data set
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__getitem__(self, address)¶ Retrieve the portion of the sheet that corresponds to {address}
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class
pyre.tabular.inferred¶ Bases:
pyre.tabular.Dimension.DimensionA chart axis whose tick marks are the unique values found in a given sheet column
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class
axis(chart, dimension, **kwds)¶ Bases:
dict
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__get__(self, chart, cls)¶
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class
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class
pyre.tabular.interval(interval, subdivisions, **kwds)¶ Bases:
pyre.tabular.Dimension.DimensionA chart axis whose tick marks are intervals of (a subset) of the range of the values in a given sheet column.
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__get__(self, chart, cls)¶
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class
pyre.tabular.chart(sheet, **kwds)¶ The base class for imposing coördinate systems on sheets
A chart contains the specification of a number of dimensions that enable the categorization and analysis of the facts in a sheet. For example, given a sales table that contains transaction information that includes date, sku and amount, a chart with these three dimensions would simplify answering questions such as “compute the total sales of a given sku in a given time period”.
Charts are used by pivot tables as a means of imposing structure on the data and precomputing data slices. See {pyre.tabular.Pivot} and the {pyre.tabular.Dimension} subclasses for more details.
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pyre_sheets¶
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pyre_dimensions¶
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pyre_localDimensions¶
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pyre_filter(self, **kwds)¶ Create an iterable over those facts that statisfy the criteria specified in {kwds}, which is assumed to be a value specification for each dimension that is to be used to restrict the data set
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pyre.tabular.record¶
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pyre.tabular.csv¶
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class
pyre.tabular.tabulator¶ Bases:
pyre.records.templaterMetaclass that builds sheets
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class
pyre.tabular.surveyor¶ Bases:
pyre.patterns.AttributeClassifier.AttributeClassifierInspect charts and harvest their dimensions