tech.datatype
upgrade to version that supports datetime types.tech.datatype
is upgrade to 5.0 (!!).deps.edn
now supported in parallel with project.clj
datafy/nav are now extensible for custom Python objects.
Extend libpython-clj.require/pydafy
and libpython-clj.require/pynav
respectively with the symbol of class you want to extend. See
respective docstrings for details.
bugfix -- python.str now loaded by import-python
Better windows anaconda support thanks to orolle.
Moved to PyGILState* functions for GIL management. This mainly due to FongHou in PRs here and here.
BREAKING CHANGE require-python
now respects prefix lists --
unfortunately, the previous syntax was incorrect.
;; WRONG (syntax version < 1.33)
(require-python '(os math))
would be equivalent to
;; (do (require-python 'os) (require-python 'math))
the correct syntax for this SHOULD have been
(require-python 'os 'math)
1.33 fixes this mistake, and provides support for prefix lists, for example:
(require-python
'[builtins :as python]
'(builtins
[list :as python.list]
[dict :as python.dict]
[tuple :as python.tuple]
[set :as python.set]
[frozenset :as python.frozenset]))
(Note: this is done for you by the function libpython-clj.require/import-python
)
This fix brought to you by jjtolton.
DecRef now happens cooperatively in python thread. We used to use separate threads
in order to do decrement the refcount on objects that aren't reachable any more. Now
it happens at the end of the with-gil
macro and thus it is possible to have all
python access confined to a single thread if this is desired for stability. It is
also quite a bit faster as the GIL is captured once and all decrefs happen after
that.
Major performance and stability enhancements.
Python executables can now be specified directly using the syntax
(py/initialize! :python-executable <executable>)
where executable can be a system installation of Python
such as "python3"
, "python3.7"
; it can also be a fully qualified
path such as "/usr/bin/python3.7"
; or any Python executable along
your discoverable system path.
Python virtual environments can now be used instead of system installations! This has been tested on Linux/Ubuntu variants with virtual environments installed with
virtualenv -p $(which <python-version>) env
and then invoked using
(py/initialize! :python-executable "/abs/path/to/env/bin/python")
Tested on Python 3.6.8 and Python 3.7.
WARNING: This is suitable for casual hacking and exploratory development -- however, at this time, we still strongly recommend using Docker and a system installation of Python in production environments.
breaking change (and remediation): require-python
no longer
automatically binds the Python module to the Clojure the namespace
symbol. If you wish to bind the module to the namespace symbol,
you need to use the :bind-ns
flag. Example:
(require-python 'requests) ;;=> nil
requests ;;=> throws Exception
(require-python '[requests :bind-ns]) ;;=> nil
(py.. requests
(get "https://www.google.com)
-content
(decode "latin-1)) ;; works
Python method helper syntax for programmatic passing of maps
to satisfy *args
, **kwargs
situations on the py.
family of
macros. Two new macros have been introduced to address this
(py* obj method args)
(py* obj method args kwargs)
(py** obj method kwargs)
(py** obj method arg1 arg2 arg3 ... argN kwargs)
and the py..
syntax has been extended to accomodate these
conventions as well.
(py.. obj (*method args))
(py.. obj (*method args kwargs))
(py.. obj (**method kwargs))
(py.. obj (**method arg1 arg2 arg3 ... argN kwargs))
Python objects are now datafy-able and nav-igable. require-python
is now rebuilt using datafy.
py.
, py.-
, and py..
added to the libpython-clj
APIs
to allow method/attribute access more consistent with idiomatic
Clojure forms.
This release is a big one. With finalizing require-python
we have a clear way
to use Python in daily use and make it look good in normal Clojure usage. There
is a demo of facial recognition using some
of the best open systems for doing this; this demo would absolutely not be possible
without this library due to the extensive use of numpy and cython to implement the
face detection. We can now interact with even very complex Python systems with
roughly the same performance as a pure Python system.
require-python
Lots of work put in to make the require-python
pathway work with
classes and some serious refactoring overall.
copy
, make-container
)
and work in optimized ways.libpython-clj.python.numpy-test> (def test-ary (py/$a np-mod array (->> (range 9)
(partition 3)
(mapv vec))))
#'libpython-clj.python.numpy-test/test-ary
libpython-clj.python.numpy-test> test-ary
[[0 1 2]
[3 4 5]
[6 7 8]]
libpython-clj.python.numpy-test> (dfn/+ test-ary 2)
[[ 2 3 4]
[ 5 6 7]
[ 8 9 10]]
libpython-clj.python.numpy-test> (dfn/> test-ary 4)
[[False False False]
[False False True]
[ True True True]]
->jvm
and large Python dictionaries.(range 5)
- Clojure ranges <-> Python ranges when possible.collections.abc.*
so that they pass instance checks in
libraries that are checking for generic types.(as-python {:is_train false})
results in a dictionary with a none
value instead of a false value. This was found through hours of debugging why
mxnet's forward function call was returning different values in Clojure than in
Python.require-python
:reload semantics.Fixed (with tests) major issue with require-python
.
Clojure's range is now respected in two different ways:
(range)
- bridges to a Python iterable(range 5)
- copies to a Python listEquals, hashcode, nice default .toString
of Python types:
user> (require '[libpython-clj.python :as py])
nil
user> (def test-tuple (py/->py-tuple [1 2]))
#'user/test-tuple
user> (require '[libpython-clj.require :refer [require-python]])
nil
user> (require-python '[builtins :as bt])
nil
user> (bt/type test-tuple)
builtins.tuple
user> test-tuple
(1, 2)
user> (def new-tuple (py/->py-tuple [3 4]))
#'user/new-tuple
user> (= test-tuple new-tuple)
false
user> (= test-tuple (py/->py-tuple [1 2]))
true
user> (.hashCode test-tuple)
2130570162
user> (.hashCode (py/->py-tuple [1 2]))
2130570162
user> (require-python '[numpy :as np])
nil
user> (def np-ary (np/array [1 2 3]))
#'user/np-ary
user> np-ary
[1 2 3]
user> (bt/type np-ary)
numpy.ndarray
user> (py/python-type *1)
:type
Working to make more Python environments work out of the box. Currently have a
testcase for conda working in a clean install of a docker container. There is now a
new method: libpython-clj.python.interpreter/detect-startup-info
that attempts
call python3-config --prefix
and python3 --version
in order to automagically
configure the Python library.
Bugfix release. Passing infinite sequences to Python functions was causing a hang as libpython-clj attempted to copy the sequence. The current calling convention does a shallow copy of things that are list-like or map-like, while bridging things that are iterable or don't fall into the above categories.
This exposed a bug that caused reference counting to be subtly wrong when Python iterated through a bridged object. And that was my life for a day.
With too many huge things we had to skip a few versions!
require-python
works like require but it works on Python modules.
require-python
dynamically loads the module and exports it's symbols into
a Clojure namespace. There are many options available for this pathway.
This implements a big step towards embedding Python in Clojure in a simple,
clear, and easy to use way. One important thing to consider is the require
has a :reload:
option to allow you to actively develop a Python module and
test it via Clojure.
This excellent work was in large part done by James Tolton.
You can now extend a tuple of Python classes (or implement a new one). This system
allows, among many things, us to use frameworks that use derivation as part of their
public API. Please see classes-test for a documented
example of a simple pathway through the new API. Note that if you use vanilla
->py-fn
functions as part of the class definition you won't get access to the self
object.
A general stability bugfix was made that was involved in the interoperation of Clojure functions within Python. Clojure functions weren't currently adding a refcount to their return values.
Fixed a bug where the system would load multiple Python libraries, not stopping after the first valid library loaded. There are two ways to control the system's Python library loading mechanism:
initialize!
alter-var-root
the list of libraries in libpython-clj.jna.base
before
calling initialize!
.Moar syntax sugar --
user> (py/$. numpy linspace)
<function linspace at 0x7fa6642766a8>
user> (py/$.. numpy random shuffle)
<built-in method shuffle of numpy.random.mtrand.RandomState object at 0x7fa66410cca8>
libpython-clj now searches for several shared libraries instead of being hardcoded to just one of them. Because of this, there is now:
libpython-clj.jna.base/*python-library-names*
This is a sequence of library names that will be tried in order.
You can also pass in the desired library name as part of the initialize!
call and
only this name will be tried.
Can you improve this documentation? These fine people already did:
Chris Nuernberger & J.J. ToltonEdit on GitHub
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