3LC Version 2.1 Release Notes#

  1. January 2024

We proudly present 3LC Version 2.1!

This release is for early adopters of 3LC, to be deployed in their own environment, and improves incrementally upon 2.0.

Enhancements and Fixes#

tlc Python Package#

  • Added PaCMAP reduction functionality.

  • Added Segment Anything Model (SAM) example notebooks.

  • Significantly reduced the time to do import tlc.

  • Replaced SampleStructure and Element with SampleType, which more closely aligns and integrates with Schema.

  • Extended support for Tables from in-memory objects.

  • Extended functionality of TableWriter and provided an example of how to use it.

  • Improved sharing workflows by ensuring URLs are relative and aliased.

  • Improved URL indexing to more robustly handle and recover from data access errors.

  • Allowed loading of serialized tables whose types are not registered (e.g. because they depend on a Python package that is not installed).

  • Fixed issues with access to the 3LC public examples S3 bucket so anyone can access it without the need to explicitly add permission to an IAM role.


  • Made it possible to drag and drop a column onto an editable column to copy its values.

  • Added controls to allow for specifying columns to use for R-G-B colors and for radius in charts.

  • Refactored chart geometry, including providing for LOD (level of detail).

  • Made it possible to tweak parameters for certain virtual columns (e.g. min IoU for bounding box TP)

  • Added new virtual column operations: Run constants, inverse, global normalize, overlap, unique overlap

  • Made it possible to view the Log table by clicking on a new Log tab.

  • Made it so that when an error occurs, attention is called to it by flashing the Log tab red.

  • Made it so that use of dark mode is picked up from user preferences by default.


This release is provided to enterprise clients, who have been given access to install it from our private CloudRepo Python repository. Clients will be able to locally install Python wheels which contain the notebook API, the 3LC Dashboard, and documentation from Python packages.

In addition to the credentials to access the private CloudRepo, clients will also need a license key in order to use the software.

Supported Platforms#

  • Python 3.8 - Python 3.11

    • Both Conda and “vanilla” Python environments should work

  • Microsoft Windows 10 and 11 (x86)

  • macOS 13 and newer (M series)

  • Ubuntu 20.04 (x86-64) is our supported Linux platform

    • Most other GLibc based Linux distributions are expected to work, but these are untested and unsupported.

  • Chrome and Edge web-browsers, with GPU acceleration enabled

Known Issues#

  • Tables for dataset revisions are currently always stored at a location next to the input table, and it is not possible to override that behavior. This means, for example, that writing a dataset revision with an input table stored in a read-only location (on disk, in cloud storage, etc.) is not supported.

  • The Table object in the tlc Python API is designed to represent immutable columnar data, but it currently returns objects by reference when iterating or indexing. Consequently, it is possible to modify the in-memory representation of the Table, which could then get cached to disk. In general, users of the API should not make such modifications.

  • It is not currently possible to deactivate samples so that metrics are collected on only active samples.

  • The order of columns in the Dashboard filter panel does not follow the order in the tables panel, where the columns are more logically ordered. This will be addressed in an upcoming release.