3.1.8

https://code.kx.com/pykx/3.1/release-notes/changelog.html#pykx-318

3.1.7

https://code.kx.com/pykx/3.1/release-notes/changelog.html#pykx-317

3.1.6

https://code.kx.com/pykx/3.1/release-notes/changelog.html

3.1.5

https://code.kx.com/pykx/3.1/release-notes/changelog.html

3.1.4

https://code.kx.com/pykx/3.1/release-notes/changelog.html

3.1.3

https://code.kx.com/pykx/3.1/release-notes/changelog.html

3.1.2

The release notes below cover both the 3.1.2 and 3.1.1 releases of PyKX owing to the feature merge containing the changes for both

PyKX 3.1.1

Release Date

2025-02-14

Fixes and Improvements

• Fixed issue whereby PyKX would prompt for user inputs if a license was not found in a non-interactive session, now correctly falls back to unlicensed mode.
• Fix throwing of errors for .pykx.safeReimport, now throws an error instead of returning a value.

PyKX 3.1.2

Release Date

2025-03-18

Fixes and Improvements

• Fixes an issue when using PYKX_THREADING that could cause a segfault in some scenarios.

3.1.0

📦 PyKX 3.1.0 Released 📦

Full up-to-date release notes are available here.

🎉 Feature 🎉

• Added support for Python 3.13.
• Added support for NumPy 2.0
• Added support for the creation and management of splayed format databases when using the pykx.DB class.
• Addition of .copy() method for all pykx objects allowing users to modify copied objects without interfering with the original object.
• Addition of reshape keyword to the .np() method of kx.List objects. This can provide two benefits:
  a. Conversions of kx.List objects to NumPy by default produce an array of NumPy arrays rather than an N-Dimensional NumPy array. Setting reshape=True when handling N-Dimensional rectangular lists allows the shape to be pre-processed prior to conversion and a more natural N-Dimensional NumPy array to be generated.

>>> kx.q('2 2#4?1f').np(reshape=True)
array([[0.94997503, 0.43908099],
       [0.57590514, 0.59190043]])

b. Provide a performance boost when converting regularly shaped (rectangular) N-Dimensional lists of uniform type when the shape of the resulting numpy array is known prior to conversion

>>> import pykx as kx
>>> lst = kx.q('100000 100 10#100000000?1f')
>>> %timeit lst.np()
9.72 s ± 272 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
>>> %timeit lst.np(reshape=[100000, 100, 10])
883ms ± 19.8 ms per loop (mean ± std. dev. of 7 runs, 1 loops each)

• Added async_response keyword argument when calling AsyncQConnection objects with reuse=False and wait=False to allow keeping the connection alive until an asynchronous response message has been received.

🔧 Fixes & Improvements 🔧

• Application of the str function on empty PyKX objects could return unexpected results

>>> import pykx as kx
>>> str(kx.q('()!()'))
'()!()'
>>> str(kx.q('()'))
'()'

• When a client attempted to retrieve an object which could not be serialized from a PyKX server it resulted in the client process hanging. An appropriate error is now sent to the client.
• Database generation functionality now allows users to pass any data-type which will convert to a pykx.Table as the table parameter
• Attempting to create a partitioned databases/add a partition to a database with a sym_enum keyword but no by_field would result in a KeyError.
• Using math.inf or -math.inf when creating numeric values now creates equivalent PyKX types
• Fixed a bug where QFuture objects returned by AsyncQConnection objects could block each other unnecessarily.

🆕 Beta Features 🆕

Addition of support in Beta form for conversions between PyKX and PyTorch objects.

2.5.5

PyKX 2.5.5

Release Date

2024-11-28

Fixes and Improvements

• PyKX Pandas dependency has been raised to allow <=2.2.3 for Python>3.8
• PyKX Pandas dependency for Python 3.8 has been clamped to <2.0 due to support being dropped for it by Pandas after 2.0.3.

For release notes of all versions see here.

3.0.1

Full up-to-date release notes are available here.

🎉 Feature 🎉

• Addition of the property day to kx.Column objects to allow users to retrieve the day of month of a timestamp.

  >>> import pykx as kx
  >>> tab = kx.Table(data={
  ...     'a': kx.random.random(100, kx.TimestampAtom.inf),
  ...     'b': kx.random.random([100, 3], 10.0)
  ...     })
  >>> tab.exec(kx.Column('a').day)
  pykx.IntVector(pykx.q('7 10 12..'))

🔧 Fixes & Improvements 🔧

• Added warning to kx.q.system.load and context registration when attempting to load path with a space. Can be suppressed by enabling PYKX_SUPPRESS_WARNINGS.

• Changed %%python heading to %%py when calling Python code during jupyter_qfirst mode so as not to conflict with inbuilt Jupyter cell magics.

• Fixed kx.license.check(format='string') to remove newline characters during comparison.

• Configuration file .pykx-config now supports use of boolean toml configuration

  $ cat ~/.pykx-config
  [default]
  PYKX_QDEBUG = true
  $ python
  >>> import pykx as kx
  >>> kx.config.pykx_qdebug
  True

• Reintroduced unsetting/setting of PYKX_SKIP_UNDERQ in PyKXReimport these had been removed in the 3.0.0 release.

• Added type checking for the cast flag when calling kx.toq() or creating a kx.K variable such as kx.FloatVector() or kx.DatetimeAtom().

• Removed the need to enable PYKX_BETA_FEATURES to use pykx_threading.

• Fixed a memory leak when calling pickle.loads on a PyKX object which previously had been called with pickle.dumps.

• Removal of column type from the return of dtypes method for kx.Table objects, previously this had raised a deprecation warning

  >>> tab = kx.q('([] a:1 2 3j;b:4 5 6i)')
  >>> tab.dtypes
  pykx.Table(pykx.q('
  columns datatypes
  ---------------------
  a       "kx.LongAtom"
  b       "kx.IntAtom" 
  '))