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3.0.2

  • Fixed regression in Exists predicate

3.0.1

  • Fixed regression in Exists predicate

3.0.0

  • Development in python packaging made supporting the previous namespace approach for variable plugins untenable. Since we had to redo the way we defined the data model, we took the opportunity to explicity instantiate variable objects.

2.0.6

  • fixed bug that was preventing learning of index predicates in Dedupe mode

2.0.3

  • Improved memory performance of connected components

2.0

  • Python 3 only
  • Static typing and type Hints
  • Incorporate sqlite to extend normal API to millions of records
  • Multiprocessing enabled for Windows
  • Multiprocessing mode changed to spawn for Mac OS X
  • Moved from CamelCase to lowercase_with_underscore for method names.
  • Dropped ability to save indices in save settings.
  • Moved from Deduper.match -> Dedupe.partition, RecordLink.match -> RecordLink.join, Gazetteer.match -> Gazetteer.search
  • Renamed Matching.blocker -> Matching.fingerprinter
  • Moved to autodoc for documentation
  • Dropped threshold methods
  • matchBlocks has been replaced by score, which takes pairs of records not blocks

1.10.0

  • Dropped python 2.7 support

1.9.4

  • Cleaned up block learning

1.9.3

  • Improved performance of connected components algorithm with very large components
  • Fixed pickling unpickling bug of Index predicate classes

1.9.0

  • Implemented a disagreement based active labeler to improve blocking recall

1.8.2

  • removed shelve-backed persistence in blocking data in favor of an improved in-memory implementation

1.8.0

  • matchBlocks is not a generator; match is now optionally a generator. If the generator option is turned of for the Gazette match is lazy

1.7.8

  • Speed up blocking, on our way to 3-predicates

1.7.5

  • Significantly reduced memory footprint during connected_components

1.7.3

  • Significantly reduced memory footprint during scoreDuplicates

1.7.2

  • Improper release

1.7.1

  • TempShelve class that addresses various bugs related to cleaning up tempoary shelves

1.7.0

  • Added target argument to blocker and predicates for changing the behavior of the predicates for the target and source dataset if we are linking.

1.6.8

  • Use file-backed blocking with dbm, dramatically increases size of data that can be handled without special programming

1.6.7

  • Reduce memory footprint of matching

1.6.0

  • Simplify .train method

1.5.5

  • Levenshtein search based index predicates thanks to @mattandahalfew

1.5.0

  • simplified the sample API, this might be a breaking change for some
  • the active learner interface is now more modular to allow for a different learner
  • random sampling of pairs has been improved for linking case and dedupe case, h/t to @MarkusShepherd

1.4.15

  • frozendicts have finally been removed
  • first N char predicates return their entire length if length is less than N, instead of nothing
  • crossvalidation is skipped in active learning if using default rlr learner

1.4.5

  • Block indexes can now be persisted by using the index=True argument in the writeSettings method

1.4.1

  • Now uses C version of double metaphone for speed
  • Much faster compounding of blocks in block learning

1.4.0

  • Block learning now tries to minimize the total number of comparisons not just the comparisons of distinct records. This decouples makes block learning from learning classifier learning. This change has requires new, different arguments to the train method.

1.3.8

  • Console labeler now shows fields in the order they are defined in the data model. The labeler also reports number of labeled examples
  • pud argument added to the train method. Proportion of uncovered dupes. This deprecates uncovered_dupes argument

1.3.0

  • If we have enough training data, consider Compound predicates of length 3 in addition to predicates of length 2

1.1.1

  • None now treated as missing data indicator. Warnings for deprecations of older types of missing data indicators

1.1.0

Features

  • Handle FuzzyCategoricalType in datamodel

1.0.0

Features

0.8.0

Support for Python 3.4 added. Support for Python 2.6 dropped.

Features

  • Windows OS supported
  • train method has argument for not considering index predicates
  • TfIDFNGram Index Predicate added (for shorter string)
  • SuffixArray Predicate
  • Double Metaphone Predicates
  • Predicates for numbers, OrderOfMagnitude, Round
  • Set Predicate OrderOfCardinality
  • Final, learned predicates list will now often be smaller without loss of coverage
  • Variables refactored to support external extensions like https://github.com/datamade/dedupe-variable-address
  • Categorical distance, regularized logistic regression, affine gap distance, canonicalization have been turned into separate libraries.
  • Simplejson is now dependency

0.7.5

Features

  • Individual record cluster membership scores
  • New predicates
  • New Exists Variable Type

Bug Fixes

  • Latlong predicate fixed
  • Set TFIDF canopy working properly

0.7.4

Features

  • Sampling methods now use blocked sampling

0.7.0

Version 0.7.0 is backwards compatible, except for the match method of Gazetteer class

Features

  • new index, unindex, and match methods in Gazetter Matching. Useful for streaming matching

0.6.0

Version 0.6.0 is not backwards compatible.

Features :

  • new Text, ShortString, and exact string types
  • multiple variables can be defined on same field
  • new Gazette linker for matching dirty records against a master list
  • performance improvements, particularly in memory usage
  • canonicalize function in dedupe.convenience for creating a canonical representation of a cluster of records
  • tons of bugfixes

API breaks

  • when initializing an ActiveMatching object, variable_definition replaces field_definition and is a list of dictionaries instead of a dictionary. See the documentation for details
  • also when initializing a Matching object, num_processes has been replaced by num_cores, which now defaults to the number of cpus on the machine
  • when initializing a StaticMatching object, settings_file is now expected to be a file object not a string. The readTraining, writeTraining, writeSettings methods also all now expect file objects

0.5

Version 0.5 is not backwards compatible.

Features :

  • Special case code for linking two datasets that, individually are unique
  • Parallel processing using python standard library multiprocessing
  • Much faster canopy creation using zope.index
  • Asynchronous active learning methods

API breaks :

  • duplicateClusters has been removed, it has been replaced by match and matchBlocks
  • goodThreshold has been removed, it has been replaced by threshold and thresholdBlocks
  • the meaning of train has changed. To train from training file use readTraining. To use console labeling, pass a dedupe instance to the consoleLabel function
  • The convenience function dataSample has been removed. It has been replaced by the sample methods
  • It is no longer necessary to pass frozendicts to Matching classes
  • blockingFunction has been removed and been replaced by the blocker method