Trouble accessing remote numpy objects #236
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Hi, sorry for the late response. I can reproduce the netref objects don't work as direct substitutes in all cases. For objects like numpy arrays, it is probably best to Admittedly, it would be nicer to have it working better by default, and it might be possible to improve by adding a For reference, the minimal working example is:
import numpy as np
import rpyc
c = rpyc.classic.connect('localhost', 18812)
d = c.modules['numpy'].array([1, 2, 3])
x = np.array(d) # ValueError
help(d.__array_struct__) # see belowThe last line seems to work fine from a client perspective, but shows the following exception on the server: |
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I really appreciate your response! Thanks! I don't think adding array_struct to the rpyc/core/netref will work because the help on the object says it will resolve methods in this order: |
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FYI, I made Best, Thomas |
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Thanks-
We have been using that successfully. Thanks for your response.
…-Josh
On 12/22/17 12:11 PM, Thomas G. wrote:
FYI, I made |np.array(d)| work now (bit of a hack though...). This
will be part of the next release. Give me a call, if problems still
persist (I didn't check matplotlib). However, the recommended method
should be using |rpyc.classic.obtain(d)|.
Best, Thomas
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Hi, For some reason, I can't get your example above to work, with the latest from master. On line 4, I get; That's on Python 2 and 3. I think the issue is that this only works when the remote object is already a |
pilcru
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The remote object needs to be an array already for __array__() to be accepted by Numpy.
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Hi, thanks for the info! (I wonder why it was working for me when I tested). Please feel free to submit your commit as pull-request (after retabbing to spaces!). |
pilcru
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The remote object needs to be an array already for __array__() to be accepted by Numpy.
pilcru
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The remote object needs to be an array already for __array__() to be accepted by Numpy.
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This release brings a few minor backward incompatibilities, so be sure to read on before upgrading. However, fear not: the ones that are most likely relevant to you have a relatively simple migration path. Backward Incompatibilities ^^^^^^^^^^^^^^^^^^^^^^^^^^ * ``classic.teleport_function`` now executes the function in the connection's namespace by default. To get the old behaviour, use ``teleport_function(conn, func, conn.modules[func.__module__].__dict__)`` instead. * Changed signature of ``Service.on_connect`` and ``on_disconnect``, adding the connection as argument. * Changed signature of ``Service.__init__``, removing the connection argument * no longer store connection as ``self._conn``. (allows services that serve multiple clients using the same service object, see `#198`_). * ``SlaveService`` is now split into two asymetric classes: ``SlaveService`` and ``MasterService``. The slave exposes functionality to the master but can not anymore access remote objects on the master (`#232`_, `#248`_). If you were previously using ``SlaveService``, you may experience problems when feeding the slave with netrefs to objects on the master. In this case, do any of the following: * use ``ClassicService`` (acts exactly like the old ``SlaveService``) * use ``SlaveService`` with a ``config`` that allows attribute access etc * use ``rpyc.utils.deliver`` to feed copies rather than netrefs to the slave * ``RegistryServer.on_service_removed`` is once again called whenever a service instance is removed, making it symmetric to ``on_service_added`` (`#238`_) This reverts PR `#173`_ on issue `#172`_. * Removed module ``rpyc.experimental.splitbrain``. It's too confusing and undocumented for me and I won't be developing it, so better remove it altogether. (It's still available in the ``splitbrain`` branch) * Removed module ``rpyc.experimental.retunnel``. Seemingly unused anywhere, no documentation, no clue what this is about. * ``bin/rpyc_classic.py`` will bind to ``127.0.0.1`` instead of ``0.0.0.0`` by default * ``SlaveService`` no longer serves exposed attributes (i.e., it now uses ``allow_exposed_attrs=False``) * Exposed attributes no longer hide plain attributes if one otherwise has the required permissions to access the plain attribute. (`#165`_) .. _#165: #165 .. _#172: #172 .. _#173: #173 .. _#198: #198 .. _#232: #232 .. _#238: #238 .. _#248: #248 What else is new ^^^^^^^^^^^^^^^^ * teleported functions will now be defined by default in the globals dict * Can now explicitly specify globals for teleported functions * Can now use streams as context manager * keep a hard reference to connection in netrefs, may fix some ``EOFError`` issues, in particular on Jython related (`#237`_) * handle synchronous and asynchronous requests uniformly * fix deadlock with connections talking to each other multithreadedly (`#270`_) * handle timeouts cumulatively * fix possible performance bug in ``Win32PipeStream.poll`` (oversleeping) * use readthedocs theme for documentation (`#269`_) * actually time out sync requests (`#264`_) * clarify documentation concerning exceptions in ``Connection.ping`` (`#265`_) * fix ``__hash__`` for netrefs (`#267`_, `#268`_) * rename ``async`` module to ``async_`` for py37 compatibility (`#253`_) * fix ``deliver()`` from IronPython to CPython2 (`#251`_) * fix brine string handling in py2 IronPython (`#251`_) * add gevent_ Server. For now, this requires using ``gevent.monkey.patch_all()`` before importing for rpyc. Client connections can already be made without further changes to rpyc, just using gevent's monkey patching. (`#146`_) * add function ``rpyc.lib.spawn`` to spawn daemon threads * fix several bugs in ``bin/rpycd.py`` that crashed this script on startup (`#231`_) * fix problem with MongoDB, or more generally any remote objects that have a *catch-all* ``__getattr__`` (`#165`_) * fix bug when copying remote numpy arrays (`#236`_) * added ``rpyc.utils.helpers.classpartial`` to bind arguments to services (`#244`_) * can now pass services optionally as instance or class (could only pass as class, `#244`_) * The service is now charged with setting up the connection, doing so in ``Service._connect``. This allows using custom protocols by e.g. subclassing ``Connection``. More discussions and related features in `#239`_-`#247`_. * service can now easily override protocol handlers, by updating ``conn._HANDLERS`` in ``_connect`` or ``on_connect``. For example: ``conn._HANDLERS[HANDLE_GETATTR] = self._handle_getattr``. * most protocol handlers (``Connection._handle_XXX``) now directly get the object rather than its ID as first argument. This makes overriding individual handlers feel much more high-level. And by the way it turns out that this fixes two long-standing issues (`#137`_, `#153`_) * fix bug with proxying context managers (`#228`_) * expose server classes from ``rpyc`` top level module * fix logger issue on jython .. _#137: #137 .. _#146: #146 .. _#153: #153 .. _#165: #165 .. _#228: #228 .. _#231: #231 .. _#236: #236 .. _#237: #237 .. _#239: #239 .. _#244: #244 .. _#247: #247 .. _#251: #251 .. _#253: #253 .. _#264: #264 .. _#265: #265 .. _#267: #267 .. _#268: #268 .. _#269: #269 .. _#270: #270 .. _gevent: http://www.gevent.org/
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Using Python 2.7
Numpy '1.7.1'
rpyc (3, 4, 4)
I am using rpyc.classic.connect
I also tried using rpyc.utils.zerodeploy, with the same results.
I have a remote object d
If I try to plot it, or make a local numpy array from it I get an error:
I can get it to segfault by typing: (actually this time it choked on a double free)
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