v0.4.0

New Features

• Reduce profiling memory usage by ~50%
• Reduce profiling runtime by >75%
• Improve delimiter and header detection in delimited (CSV) data
• Add progress notifications for profiling

Fixes

• Adds warnings for sampling
• Selects proper options on profile mergers
• Fix repeated tensorflow warnings
• Thresholds input for large CSV files by bytes or lines (whichever is smaller)

v0.3.5

• Enhancement: 50-90% reduced profiling time
  • Improved methods for unique row and null-in-row prediction(s)
• Enhancement: Users can now select header row for delimited files
• Bug Fix: Added header detection on delimited files with only strings

v0.3.4

• Significantly improved header detection on structured datasets
• Updated model
  • New entities: DATE, TIME, US_STATE, DRIVERS_LICENSE
  • Removed entities: INTEGER_BIG
• New [easier] way to extend labels to the model
• ML requirements installed separately via pip install dataprofiler[ml] - required for labeler
• Profiler & Labeler only load TensorFlow when necessary
• Minor bug fixes & improved testing

v0.3.2

• TensorFlow only runs when a labeler executes
• Improved CSV detection
• 2-8x memory reduction in profiling
• Various bug fixes

v0.3.1

• Dramatically reduced memory requirements for the data labeler
• Renamed the module: data_profiler -> dataprofiler
• Improved delimiter (CSV) file detection

v0.3.0

Initial Data Profiler release.
Load a file. Extract profile. Save output.
See README.md for full information regarding release.