DataJoint 2.0 #1311

dimitri-yatsenko · 2026-01-07T16:28:35Z

Summary

DataJoint 2.0 is a major release that modernizes the entire codebase while maintaining backward compatibility for core functionality. This release focuses on extensibility, type safety, and developer experience.

Planning: DataJoint 2.0 Plan | Milestone 2.0

Major Features

Codec System (Extensible Types)

Replaces the adapter system with a modern, composable codec architecture:

Base codecs: <blob>, <json>, <attach>, <filepath>, <object>, <hash>, <npy>
Chaining: Codecs can wrap other codecs (e.g., <blob> wraps <json> for external storage)
Auto-registration: Custom codecs register via __init_subclass__
Validation: Optional validate() method for type checking before insert

from datajoint import Codec

class MyCodec(Codec):
    python_type = MyClass
    dj_type = "<blob>"  # Storage format
    
    def encode(self, value): ...
    def decode(self, value): ...

Semantic Matching

Attribute lineage tracking ensures joins only match semantically compatible attributes:

Attributes track their origin through foreign key inheritance
Joins require matching lineage (not just matching names)
Prevents accidental matches on generic names like id or name
semantic_check=False for legacy permissive behavior

# These join on subject_id because both inherit from Subject
Session * Recording  # ✓ Works - same lineage

# These fail because 'id' has different origins
TableA * TableB  # ✗ Fails - different lineage for 'id'

Primary Key Rules

Rigorous primary key propagation through all operators:

Join: Result PK based on functional dependencies (A→B, B→A, both, neither)
Aggregation: Groups by left operand's primary key
Projection: Preserves PK attributes, drops secondary
Universal set: dj.U('attr') creates ad-hoc grouping entities

AutoPopulate 2.0 (Jobs System)

Per-table job management with enhanced tracking:

Hidden metadata: ~~_job_timestamp and ~~_job_duration columns
Per-table jobs: Each computed table has its own ~~table_name job table
Schema.jobs: List all job tables in a schema
Progress tracking: table.progress() returns (remaining, total)
Priority scheduling: Jobs ordered by priority, then timestamp

Modern Fetch & Insert API

New fetch methods:

to_dicts() - List of dictionaries
to_pandas() - DataFrame with PK as index
to_arrays(*attrs) - NumPy arrays (structured or individual)
keys() - Primary keys only
fetch1() - Single row

Insert improvements:

validate() - Check rows before inserting
chunk_size - Batch large inserts
insert_dataframe() - DataFrame with index handling
Empty inserts for tables with all-default attributes (IMPR: Error specificity on empty insert for table with default values #1280)
Polars and PyArrow support

Type Aliases

Core DataJoint types for portability:

Alias	MySQL Type
`int8`, `int16`, `int32`, `int64`	tinyint, smallint, int, bigint
`uint8`, `uint16`, `uint32`, `uint64`	unsigned variants
`float32`, `float64`	float, double
`bool`	tinyint
`uuid`	binary(16)

Object Storage

Content-addressed and object storage types:

<hash> - Content-addressed storage with deduplication
<object> - Named object storage (Zarr, folders)
<npy> - NumPy arrays as .npy files
<filepath> - Reference to managed files
<attach> - File attachments (uploaded on insert)

Virtual Schema Infrastructure (#1307)

New schema introspection API for exploring existing databases:

Schema.get_table(name) - Direct table access with auto tier prefix detection
Schema['TableName'] - Bracket notation access
for table in schema - Iterate tables in dependency order
'TableName' in schema - Check table existence
dj.virtual_schema() - Clean entry point for accessing schemas
dj.VirtualModule() - Virtual modules with custom names

CLI Improvements

The dj command-line interface for interactive exploration:

dj -s schema:alias - Load schemas as virtual modules
--host, --user, --password - Connection options
Fixed -h conflict with --help

Settings Modernization

Pydantic-based configuration with validation:

Type-safe settings with automatic validation
dj.config.override() context manager
Secrets directory support (.secrets/)
Environment variable overrides (DJ_HOST, etc.)

Migration Utilities

Helper functions for migrating from 0.14.x to 2.0:

analyze_blob_columns() - Identify columns needing type markers
migrate_blob_columns() - Add :<blob>: prefixes to column comments
check_migration_status() - Verify migration readiness
add_job_metadata_columns() - Add hidden job tracking columns

License Change

Changed from LGPL to Apache 2.0 license (#1235 (discussion)):

More permissive for commercial and academic use
Compatible with broader ecosystem of tools
Clearer patent grant provisions

Breaking Changes

Removed Support

Python 3.8, 3.9 (minimum 3.10)
MySQL 5.x (minimum 8.0)
Legacy fetch() with format parameter
Adapter API (use Codec)
create_virtual_module (use dj.virtual_schema() or dj.VirtualModule())
~log table (IMPR: Deprecate and Remove the ~log Table. #1298)
otumat support (IMPR: Deprecate otumat support #1252)

Removed API Components

dj.key - Use table.keys() instead
dj.key_hash() - Removed (was for legacy job debugging)
dj.schema() - Use dj.Schema() (capitalized)
dj.ERD() - Use dj.Diagram()
dj.Di() - Use dj.Diagram()

API Changes

fetch() → to_dicts(), to_pandas(), to_arrays()
fetch(format='frame') → to_pandas()
fetch(as_dict=True) → to_dicts()
Method parameter safemode → prompt (the config['safemode'] setting remains and controls the default behavior)

Semantic Changes

Joins now require lineage compatibility by default
Aggregation keeps non-matching rows by default (like LEFT JOIN)

Documentation

Developer Documentation (this repo)

Comprehensive updates in docs/:

NumPy-style docstrings for all public APIs
Architecture guides for contributors
Auto-generated API reference via mkdocstrings

User Documentation (datajoint-docs)

Full documentation site following the Diátaxis framework:

Tutorials (learning-oriented, Jupyter notebooks):

Getting Started - Installation, connection, first schema
Schema Design - Table tiers, definitions, foreign keys
Data Entry - Insert patterns, lookups, manual tables
Queries - Restriction, projection, join, aggregation, fetch
Computation - Computed tables, make(), populate patterns
Object Storage - Blobs, attachments, external storage

How-To Guides (task-oriented):

Configure object storage, Design primary keys, Model relationships
Handle computation errors, Manage large datasets, Create custom codecs
Use the CLI, Migrate from 1.x

Reference (specifications):

Table Declaration, Query Algebra, Data Manipulation
Primary Keys, Semantic Matching, Type System, Virtual Schemas
Codec API, AutoPopulate, Fetch API, Job Metadata

Project Structure

src/ layout for proper packaging (IMPR: src layout #1267)
Testcontainers for pytest-managed containers
Pre-commit hooks: ruff, mypy, unit tests (IMPR: Modernize pre-commit #1271)
GitHub Actions CI/CD
Split unit/integration tests (IMPR: split unit/integration test #1211)

Test Plan

636+ integration tests pass
117+ unit tests pass
Pre-commit hooks pass
Documentation builds successfully
Tutorials execute against test database

Closes

Related PRs

datajoint-docs PR #97 - DataJoint 2.0 Documentation
datajoint-docs PR #98 - Virtual schemas spec and CLI docs

Migration Guide

See How to Migrate from 1.x for detailed migration instructions.

🤖 Generated with Claude Code

- Random hash suffix for filenames (URL-safe, filename-safe base64) - Configurable hash_length setting (default: 8, range: 4-16) - Upload-first transaction strategy with cleanup on failure - Batch insert atomicity handling - Orphaned file detection/cleanup utilities (future)

Key changes: - Support both files and folders - Immutability contract: insert, read, delete only - Deterministic bidirectional path mapping from schema/table/field/PK - Copy-first insert: copy fails → no DB insert attempted - DB-first delete: file delete is best-effort (stale files acceptable) - Fetch returns handle (FileRef), no automatic download - JSON metadata includes is_folder, file_count for folders - FileRef class with folder operations (listdir, walk)

Path changes: - Field name now comes after all primary key attributes - Groups related files together (all fields for same record in same dir) Partitioning: - partition_pattern config promotes PK attributes to path root - Enables grouping by high-level attributes (subject, experiment) - Example: {subject_id} moves subject to path start for data locality

- Keep = sign in paths (Hive convention, widely supported) - Simple types used directly: integers, dates, timestamps, strings - Conversion to path-safe strings only when necessary: - Path-unsafe characters (/, \) get URL-encoded - Long strings truncated with hash suffix - Binary/complex types hashed

- Orphan cleanup must run during maintenance windows - Uses transactions/locking to avoid race conditions - Grace period excludes recently uploaded files (in-flight inserts) - Dry-run mode for previewing deletions

- attach@store and filepath@store maintained for backward compatibility - Will be deprecated with migration warnings in future releases - Eventually removed after transition period - New pipelines should use file type exclusively

Store metadata (dj-store-meta.json): - Located at store root with project_name, created, format_version - Lists schemas using the store - Created on first file operation Client verification: - project_name required in client settings - Must match store metadata on connect - Raises DataJointError on mismatch - Ensures all clients use same configuration Also renamed hash_length to token_length throughout spec.

- Removed schemas array from dj-store-meta.json - 1:1 correspondence between database+project_name and store assumed - DataJoint performs basic project_name verification on connect - Enforcement is administrative responsibility, not DataJoint's

- Type syntax: `object` instead of `file` - Class: ObjectRef instead of FileRef - Module: objectref.py instead of fileref.py - Pattern: OBJECT matching `object$` - JSON fields: is_dir, item_count (renamed from is_folder, file_count) - Consistent with object_storage.* settings namespace - Aligns with objects/ directory in path structure

Staged Insert (direct write mode): - stage_object() context manager for writing directly to storage - StagedObject provides fs, store, full_path for Zarr/xarray - Cleanup on failure, metadata computed on success - Avoids copy overhead for large arrays ObjectRef fsspec accessors: - fs property: returns fsspec filesystem - store property: returns FSMap for Zarr/xarray - full_path property: returns full URI Updated immutability contract: - Objects immutable "after finalization" - Two insert modes: copy (existing data) and staged (direct write)

- Use dedicated staged_insert1 method instead of co-opting insert1 - Add StagedInsert class with rec dict, store(), and open() methods - Document rationale for separate method (explicit, backward compatible, type safe) - Add examples for Zarr and multiple object fields - Note that staged inserts are limited to insert1 (no multi-row)

- Filename is always {field}_{token}{ext}, no user control over base name - Extension extracted from source file (copy) or optionally provided (staged) - Replace `original_name` with `ext` in JSON schema and ObjectRef - Update path templates, examples, and StagedInsert interface - Add "Filename Convention" section explaining the design

- Rename store metadata: dj-store-meta.json → datajoint_store.json - Move objects/ directory after table name in path hierarchy - Path is now: {schema}/{Table}/objects/{pk_attrs}/{field}_{token}{ext} - Allows table folders to contain both tabular data and objects - Update all path examples and JSON samples

- Hash is null by default to avoid performance overhead for large objects - Optional hash parameter on insert: hash="sha256", "md5", or "xxhash" - Staged inserts never compute hashes (no local copy to hash from) - Folders get a manifest file (.manifest.json) with file list and sizes - Manifest enables integrity verification without content hashing - Add ObjectRef.verify() method for integrity checking

- Enables bidirectional mapping between object stores and databases - Fields are informational only, not enforced at runtime - Alternative: admins ensure unique project_name across namespace - Managed platforms may handle this mapping externally

- Legacy attach@store and filepath@store use hidden ~external_* tables - New object type stores all metadata inline in JSON column - Benefits: simpler schema, self-contained records, easier debugging - No reference counting complexity

- Add fsspec>=2023.1.0 as core dependency - Add optional dependencies for cloud backends (s3fs, gcsfs, adlfs) - Create new storage.py module with StorageBackend class - Unified interface for file, S3, GCS, and Azure storage - Methods: put_file, get_file, put_buffer, get_buffer, exists, remove - Refactor ExternalTable to use StorageBackend instead of protocol-specific code - Replace _upload_file, _download_file, etc. with storage backend calls - Add storage property, deprecate s3 property - Update settings.py to support GCS and Azure protocols - Add deprecation warning to s3.py Folder class - Module kept for backward compatibility - Will be removed in future version This lays the foundation for the new object type which will also use fsspec.

This commit adds a new `object` column type that provides managed file/folder storage with fsspec backend integration. Key features: - Object type declaration in declare.py (stores as JSON in MySQL) - ObjectRef class for fetch behavior with fsspec accessors (.fs, .store, .full_path) - Insert processing for file paths, folder paths, and (ext, stream) tuples - staged_insert1 context manager for direct writes (Zarr/xarray compatibility) - Path generation with partition pattern support - Store metadata file (datajoint_store.json) verification/creation - Folder manifest files for integrity verification The object type stores metadata inline (no hidden tables), supports multiple storage backends via fsspec (file, S3, GCS, Azure), and provides ObjectRef handles on fetch with direct storage access.

Remove unused mimetypes imports from objectref.py and storage.py, remove unused Path import and generate_token from staged_insert.py, and fix f-string without placeholders in objectref.py.

- Create comprehensive object.md page covering configuration, insert, fetch, staged inserts, and integration with Zarr/xarray - Update attributes.md to list object as a special DataJoint datatype - Add object_storage configuration section to settings.md - Add ObjectRef and array library integration section to fetch.md - Add object attributes and staged_insert1 section to insert.md

Apply ruff formatter changes for consistent code style.

- schema_object.py: Test table definitions for object type - test_object.py: Comprehensive tests covering: - Storage path generation utilities - Insert with file, folder, and stream - Fetch returning ObjectRef - ObjectRef methods (read, open, download, listdir, walk, verify) - Staged insert operations - Error cases - conftest.py: Object storage fixtures for testing

Co-authored-by: Davis Bennett <[email protected]>

- Replace config.external tests with stores credential tests - Update template test to check for stores structure instead of object_storage - Update get_store_spec tests for new default behavior (None instead of DEFAULT_SUBFOLDING) - Add tests for default store lookup (store=None) - Add tests for loading per-store credentials from .secrets/ - Verify partition_pattern and token_length defaults

- Update mock_stores fixture to use config.stores instead of config.object_storage - Update mock_object_storage fixture to configure stores.default and stores.local - Remove project_name from object_storage_config (now embedded in location path) - Simplify fixture by using unified stores API

- Update mock_stores_update fixture to use config.stores - Remove project_name (now embedded in location path) - Simplify fixture using unified stores API

- Add validation to prevent filepath paths starting with _hash/ or _schema/ - Update FilepathCodec docstring to clarify reserved sections - Filepath gives users maximum freedom while protecting DataJoint-managed sections - Users can organize files anywhere in store except reserved sections

- Test that filepath rejects paths starting with _hash/ - Test that filepath rejects paths starting with _schema/ - Test that filepath allows all other user-managed paths - Test filepath codec properties and registration

The 'secure' parameter is only valid for S3 stores, not for file/GCS/Azure protocols. Move the default setting to protocol-specific section to avoid validation errors when using file stores.

Allow users to configure custom prefixes for hash-addressed, schema-addressed, and filepath storage sections per store. This enables mapping DataJoint to existing storage layouts without restructuring. Configuration: - hash_prefix (default: '_hash') - Hash-addressed storage section - schema_prefix (default: '_schema') - Schema-addressed storage section - filepath_prefix (default: None) - Optional filepath restriction Features: - Validates prefixes don't overlap (mutual exclusion) - FilepathCodec enforces dynamic reserved prefixes - Optional filepath_prefix to restrict filepath paths - Backwards compatible defaults Examples: { "stores": { "legacy": { "protocol": "file", "location": "/data/existing", "hash_prefix": "content_addressed", "schema_prefix": "structured_data", "filepath_prefix": "raw_files" } } } Changes: - settings.py: Add prefix fields, validation logic - builtin_codecs.py: Dynamic prefix checking in FilepathCodec - test_settings.py: 7 new tests for prefix validation - test_codecs.py: 2 new tests for custom prefixes

Filepath storage is NOT part of the Object-Augmented Schema - it only provides references to externally-managed files. Allow separate default configuration for filepath references vs integrated storage. Configuration: - stores.default - for integrated storage (<blob>, <object>, <npy>, <attach>) - stores.filepath_default - for filepath references (<filepath>) This allows: - Integrated storage on S3 or fast filesystem - Filepath references to acquisition files on NAS or different location Example: { "stores": { "default": "main", "filepath_default": "raw_data", "main": { "protocol": "s3", "bucket": "processed-data", "location": "lab-project" }, "raw_data": { "protocol": "file", "location": "/mnt/nas/acquisition" } } } Usage: - data : <blob> # Uses stores.default (main) - arrays : <object> # Uses stores.default (main) - raw : <filepath> # Uses stores.filepath_default (raw_data) - raw : <filepath@acq> # Explicitly names store (overrides default) Changes: - settings.py: Add use_filepath_default parameter to get_store_spec() - builtin_codecs.py: FilepathCodec uses use_filepath_default=True - test_settings.py: Add 3 tests for filepath_default behavior - settings.py: Update template to include filepath_default example Architectural rationale: - Hash/schema storage: integrated into OAS, DataJoint manages lifecycle - Filepath storage: references only, users manage lifecycle - Different defaults reflect this fundamental distinction

…alidation All 24 object storage test failures were due to test fixtures not creating the directories they configured. StorageBackend validates that file protocol locations exist, so fixtures must create them. - conftest.py: Create test_project subdirectory in object_storage_config - test_update1.py: Create djtest subdirectories in mock_stores_update Test results: 520 passed, 7 skipped, 0 failures ✓

Add blank line after import statement per PEP 8 style guidelines.

- Removed hardcoded 'objects' directory level from build_object_path() - Updated path pattern comment to reflect new structure - Updated all test expectations to match new path format Previous path: {schema}/{table}/objects/{key}/{file} New path: {schema}/{table}/{key}/{file} The 'objects' literal was a legacy remnant intended for future tabular storage alongside objects. Removing it simplifies the path structure and aligns with documented behavior. Verified: - All test_object.py tests pass (43 tests) - All test_npy_codec.py tests pass (22 tests) - All test_hash_storage.py tests pass (14 tests)

- Updated SchemaCodec._build_path() to accept store_name parameter - _build_path() now retrieves partition_pattern and token_length from store spec - ObjectCodec and NpyCodec encode methods pass store_name to _build_path - Enables partitioning configuration like partition_pattern: '{mouse_id}/{session_date}' This allows organizing storage by experimental structure: - Without: {schema}/{table}/{mouse_id=X}/{session_date=Y}/... - With: {mouse_id=X}/{session_date=Y}/{schema}/{table}/... Partitioning makes storage browsable by subject/session and enables selective sync/backup of individual subjects or sessions.

The partition_pattern was not preserving the order of attributes specified in the pattern because it was iterating over a set (unordered). This caused paths like 'neuron_id=0/mouse_id=5/session_date=2017-01-05/...' instead of the expected 'mouse_id=5/session_date=2017-01-05/neuron_id=0/...'. Changes: - Extract partition attributes as a list to preserve order - Keep a set for efficient lookup when filtering remaining PK attributes - Iterate over the ordered list when building partition path components Co-Authored-By: Claude Sonnet 4.5 <[email protected]>

Added helper functions for safe 0.14.6 → 2.0 migration using parallel schemas: New functions in datajoint.migrate: - create_parallel_schema() - Create _v20 schema copy for testing - copy_table_data() - Copy data from production to test schema - compare_query_results() - Validate results match between schemas - backup_schema() - Create full schema backup before cutover - restore_schema() - Restore from backup if needed - verify_schema_v20() - Check if schema is 2.0 compatible These functions support the parallel schema migration approach which: - Keeps production untouched during testing - Allows unlimited practice runs - Enables side-by-side validation - Provides easy rollback (just drop _v20 schemas) See: datajoint-docs/src/how-to/migrate-to-v20.md Co-Authored-By: Claude Sonnet 4.5 <[email protected]>

Added helper function for migrating external storage pointers when copying production data to _v2 schemas during git branch-based migration. Function: migrate_external_pointers_v2() - Converts BINARY(16) UUID → JSON metadata - Points to existing files (no file copying required) - Enables access to external data in _v2 test schemas - Supports deferred external storage migration approach Use case: When using git branch workflow (main: 0.14.6, migrate-to-v2: 2.0), this function allows copied production data to access external storage without moving the actual blob files until production cutover. Example: migrate_external_pointers_v2( schema='my_pipeline_v2', table='recording', attribute='signal', source_store='external-raw', dest_store='raw', copy_files=False # Keep files in place ) Co-Authored-By: Claude Sonnet 4.5 <[email protected]>

- Remove trailing whitespace from SQL query - Remove unused dest_spec variable - Fix blank line whitespace (auto-fixed by ruff)

Auto-formatted by ruff-format to collapse multi-line function calls

Unified stores configuration with configurable prefixes and filepath_default

Replace deprecated 'external storage' terminology with canonical terms: - 'object storage' for general concept - 'in-store storage' for @ modifier specifics - 'in-table storage' for database storage Changes: - builtin_codecs.py: Update BlobCodec, AttachCodec, HashCodec docstrings * 'internal/external' → 'in-table/in-store' * Update examples and get_dtype() docstrings - settings.py: Update StoresSettings docstrings - gc.py: Update module docstring and format_stats() - expression.py: Update to_dicts() docstring - heading.py, codecs.py, declare.py: Update internal comments - migrate.py: Add note explaining use of legacy terminology Ref: TERMINOLOGY.md, DOCSTRING_TERMINOLOGY_REPORT.md

Replace deprecated SQL-derived terms with accurate DataJoint terminology: - 'semijoin/antijoin' → 'restriction/anti-restriction' - Clarify that A & B restricts A (does not join attributes) Changes in source code comments: - expression.py:1081: 'antijoin' → 'anti-restriction' - condition.py:296: '(semijoin/antijoin)' → 'for restriction' - condition.py:401: '(aka semijoin and antijoin)' → removed Rationale: In relational algebra, joins combine attributes from both operands. DataJoint's A & B restricts A to matching entities—no attributes from B appear in the result. This is fundamentally restriction, not a join operation.

- List <blob> and <blob@> separately to show both inline and external modes - List <attach> and <attach@> separately to show both modes - Change <hash> to <hash@> (external only) - Change <object> to <object@> (external only) - Clarify storage mode for each codec variant - Also corrected hash algorithm from SHA256 to MD5 This makes it clear which codecs support dual modes vs external-only.

Clarify dual-mode codecs in builtin_codecs docstring

claude and others added 30 commits December 20, 2025 21:21

Clarify orphan cleanup as separate maintenance procedure

5f27b75

- Orphan cleanup must run during maintenance windows - Uses transactions/locking to avoid race conditions - Grace period excludes recently uploaded files (in-flight inserts) - Dry-run mode for previewing deletions

Add legacy type deprecation notice

4f15c90

- attach@store and filepath@store maintained for backward compatibility - Will be deprecated with migration warnings in future releases - Eventually removed after transition period - New pipelines should use file type exclusively

Clarify folder manifest storage location and rationale

c340ec7

Fix unused imports (ruff lint)

4b7e7bd

Fix ruff-format: add blank lines after local imports

949b8a6

Fix ruff lint: line length and unused imports

b45df2c

Fix unused imports (ruff lint)

adf4305

Remove unused mimetypes imports from objectref.py and storage.py, remove unused Path import and generate_token from staged_insert.py, and fix f-string without placeholders in objectref.py.

Fix ruff-format: code formatting adjustments

08838f6

Apply ruff formatter changes for consistent code style.

Fix E402: move schema_object import to top of file

944c9be

Fix unused imports (ruff lint)

752248c

Fix ruff-format: add blank lines after local imports

7ef4e61

"strongly-typed" -> "type-checked" Json in documentation.

f9e7496

Co-authored-by: Davis Bennett <[email protected]>

dimitri-yatsenko and others added 24 commits January 13, 2026 23:08

test: update test_update1.py fixture for unified stores

1366776

- Update mock_stores_update fixture to use config.stores - Remove project_name (now embedded in location path) - Simplify fixture using unified stores API

test: Add unit tests for filepath reserved section validation

7df2f97

- Test that filepath rejects paths starting with _hash/ - Test that filepath rejects paths starting with _schema/ - Test that filepath allows all other user-managed paths - Test filepath codec properties and registration

fix: Only set 'secure' default for S3 protocol

fe29274

The 'secure' parameter is only valid for S3 stores, not for file/GCS/Azure protocols. Move the default setting to protocol-specific section to avoid validation errors when using file stores.

docs: clarify <filepath@> error message to enforce @ convention

2d7d935

chore: bump version to 2.0.0a22 and apply pre-commit formatting

401bffe

test: integration tests - 496 passed, 24 object storage fixture failures

5ccf3aa

test: update summary - all 520 integration tests passing ✓

6487ae4

style: apply ruff-format to conftest.py

35a2c60

Add blank line after import statement per PEP 8 style guidelines.

style: fix linting issues in migrate.py

4b0e9a8

- Remove trailing whitespace from SQL query - Remove unused dest_spec variable - Fix blank line whitespace (auto-fixed by ruff)

style: apply ruff-format to builtin_codecs.py

63ecba9

Auto-formatted by ruff-format to collapse multi-line function calls

Merge pull request #1333 from datajoint/feature/unified-stores-config

bf62620

Unified stores configuration with configurable prefixes and filepath_default

dimitri-yatsenko added breaking Not backward compatible changes feature Indicates new features labels Jan 16, 2026

dimitri-yatsenko and others added 2 commits January 16, 2026 11:06

Merge pull request #1334 from datajoint/feature/unified-stores-config

984a9be

Clarify dual-mode codecs in builtin_codecs docstring

github-actions bot removed breaking Not backward compatible changes feature Indicates new features labels Jan 16, 2026

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DataJoint 2.0 #1311

DataJoint 2.0 #1311

dimitri-yatsenko commented Jan 7, 2026 •

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Summary

Major Features

Codec System (Extensible Types)

Semantic Matching

Primary Key Rules

AutoPopulate 2.0 (Jobs System)

Modern Fetch & Insert API

Type Aliases

Object Storage

Virtual Schema Infrastructure (#1307)

CLI Improvements

Settings Modernization

Migration Utilities

License Change

Breaking Changes

Removed Support

Removed API Components

API Changes

Semantic Changes

Documentation

Developer Documentation (this repo)

User Documentation (datajoint-docs)

Project Structure

Test Plan

Closes

Milestone 2.0 Issues

Bug Fixes

Improvements

Related PRs

Migration Guide

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dimitri-yatsenko commented Jan 7, 2026 •

edited

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