Here is some python code that illustrates the problem:
from pyscipopt import Model
master = Model("master LP")
relax = master.relax()
This generates the error:
builtins.AttributeError: 'pyscipopt.scip.Model' object has no attribute 'relax'
These python statements are taken from SCIP documentation --- section Column generation method for the cutting stock problem.
Note, I am using Python 3.6.5 and pyscipopt 3.0.2
The relax method does not exist in PySCIPOpt.
What you link to is a book that, I think, was originally written for using Gurobi's python interface. The authors started translating it to use it with SCIP but this is not ready yet. Actually, you can even see it in the Todo at the beginning of the page you link to.
In any case, this is not the documentation of SCIP
Check the pyscipopt github page and if you have further problems/questions, please open an issue there
I have a data file inputpy.xlsx and I am converting this file to an opl input language(1 and 0) called outputpy.xlsx, and I have a working opl model that takes my outputpy.xlsx file and outputs to an excel file(oploutput.xlsx) from cplex ide.
However, my problem is I am currently running both of them separately.
First I am running python code to make outputpy.xlsx and than I am using cplex ide to make oploutput.xlsx.
My question is :
How can I call/run my cplex code from my python code, after I created the outputpy.xlsx in python? I don't want to run python code and then run the cplex ide separately.
what I find online is some suggest using python API or doccplex, I am not sure the difference between them. I believe that using python API I have to change the cplex code for the python language, and I also can't find the nice tutorial for this.
Do you have suggestions?
Thank you in advance.
One very simple way to do this is to use oplrun instead of the IDE. Using oplrun you can run a project and/or mod file from the command line. Then you can invoke this from Python using subprocess.popen() or just os.system() (see this related question).
The description of oplrun can be found in the reference documentation in chapter IDE and OPL > oplrun command line interface
In order to run OPL directly from Python you could have a look at the doopl package.
What is the best way to call java from python?
(jython and RPC are not an option for me).
I've heard of JCC: http://pypi.python.org/pypi/JCC/1.9
a C++ code generator for calling Java from C++/Python
But this requires compiling every possible call; I would prefer another solution.
I've hear about JPype: http://jpype.sourceforge.net/
tutorial: http://www.slideshare.net/onyame/mixing-python-and-java
import jpype
jpype.startJVM(path to jvm.dll, "-ea")
javaPackage = jpype.JPackage("JavaPackageName")
javaClass = javaPackage.JavaClassName
javaObject = javaClass()
javaObject.JavaMethodName()
jpype.shutdownJVM()
This looks like what I need.
However, the last release is from Jan 2009 and I see people failing to compile JPype.
Is JPype a dead project?
Are there any other alternatives?
You could also use Py4J. There is an example on the frontpage and lots of documentation, but essentially, you just call Java methods from your python code as if they were python methods:
from py4j.java_gateway import JavaGateway
gateway = JavaGateway() # connect to the JVM
java_object = gateway.jvm.mypackage.MyClass() # invoke constructor
other_object = java_object.doThat()
other_object.doThis(1,'abc')
gateway.jvm.java.lang.System.out.println('Hello World!') # call a static method
As opposed to Jython, one part of Py4J runs in the Python VM so it is always "up to date" with the latest version of Python and you can use libraries that do not run well on Jython (e.g., lxml). The other part runs in the Java VM you want to call.
The communication is done through sockets instead of JNI and Py4J has its own protocol (to optimize certain cases, to manage memory, etc.)
Disclaimer: I am the author of Py4J
Here is my summary of this problem: 5 Ways of Calling Java from Python
http://baojie.org/blog/2014/06/16/call-java-from-python/ (cached)
Short answer: Jpype works pretty well and is proven in many projects (such as python-boilerpipe), but Pyjnius is faster and simpler than JPype
I have tried Pyjnius/Jnius, JCC, javabridge, Jpype and Py4j.
Py4j is a bit hard to use, as you need to start a gateway, adding another layer of fragility.
Pyjnius docs and Github.
From the github page:
A Python module to access Java classes as Python classes using JNI.
PyJNIus is a "Work In Progress".
Quick overview
>>> from jnius import autoclass
>>> autoclass('java.lang.System').out.println('Hello world')
Hello world
>>> Stack = autoclass('java.util.Stack')
>>> stack = Stack()
>>> stack.push('hello')
>>> stack.push('world')
>>> print stack.pop()
world
>>> print stack.pop()
hello
If you're in Python 3, there's a fork of JPype called JPype1-py3
pip install JPype1-py3
This works for me on OSX / Python 3.4.3. (You may need to export JAVA_HOME=/Library/Java/JavaVirtualMachines/your-java-version)
from jpype import *
startJVM(getDefaultJVMPath(), "-ea")
java.lang.System.out.println("hello world")
shutdownJVM()
I'm on OSX 10.10.2, and succeeded in using JPype.
Ran into installation problems with Jnius (others have too), Javabridge installed but gave mysterious errors when I tried to use it, PyJ4 has this inconvenience of having to start a Gateway server in Java first, JCC wouldn't install. Finally, JPype ended up working. There's a maintained fork of JPype on Github. It has the major advantages that (a) it installs properly and (b) it can very efficiently convert java arrays to numpy array (np_arr = java_arr[:])
The installation process was:
git clone https://github.com/originell/jpype.git
cd jpype
python setup.py install
And you should be able to import jpype
The following demo worked:
import jpype as jp
jp.startJVM(jp.getDefaultJVMPath(), "-ea")
jp.java.lang.System.out.println("hello world")
jp.shutdownJVM()
When I tried calling my own java code, I had to first compile (javac ./blah/HelloWorldJPype.java), and I had to change the JVM path from the default (otherwise you'll get inexplicable "class not found" errors). For me, this meant changing the startJVM command to:
jp.startJVM('/Library/Java/JavaVirtualMachines/jdk1.7.0_79.jdk/Contents/MacOS/libjli.dylib', "-ea")
c = jp.JClass('blah.HelloWorldJPype')
# Where my java class file is in ./blah/HelloWorldJPype.class
...
I've been integrating a lot of stuff into Python lately, including Java. The most robust method I've found is to use IKVM and a C# wrapper.
IKVM has a neat little application that allows you to take any Java JAR, and convert it directly to .Net DLL. It simply translates the JVM bytecode to CLR bytecode. See http://sourceforge.net/p/ikvm/wiki/Ikvmc/ for details.
The converted library behaves just like a native C# library, and you can use it without needing the JVM. You can then create a C# DLL wrapper project, and add a reference to the converted DLL.
You can now create some wrapper stubs that call the methods that you want to expose, and mark those methods as DllEport. See https://stackoverflow.com/a/29854281/1977538 for details.
The wrapper DLL acts just like a native C library, with the exported methods looking just like exported C methods. You can connect to them using ctype as usual.
I've tried it with Python 2.7, but it should work with 3.0 as well. Works on Windows and the Linuxes
If you happen to use C#, then this is probably the best approach to try when integrating almost anything into python.
I'm just beginning to use JPype 0.5.4.2 (july 2011) and it looks like it's working nicely...
I'm on Xubuntu 10.04
I'm assuming that if you can get from C++ to Java then you are all set. I've seen a product of the kind you mention work well. As it happens the one we used was CodeMesh. I'm not specifically endorsing this vendor, or making any statement about their product's relative quality, but I have seen it work in quite a high volume scenario.
I would say generally that if at all possible I would recommend keeping away from direct integration via JNI if you can. Some simple REST service approach, or queue-based architecture will tend to be simpler to develop and diagnose. You can get quite decent perfomance if you use such decoupled technologies carefully.
Through my own experience trying to run some java code from within python in a manner similar to how python code runs within java code in python, I was unable to find a straightforward methodology.
My solution to my problem was by running this java code as BeanShell scripts by calling the BeanShell interpreter as a shell command from within my python code after editing the java code in a temporary file with the appropriate packages and variables.
If what I am talking about is helpful in any manner, I am glad to help you share more details of my solutions.
RedHawk installs JARs for eclipse plugins from redhawk-yum-1.10.2-5-el6-x86_64.tar.gz. In RedHawk 1.9 it only installed 4 JARs for IDL parsing and editing, but in RedHawk 1.10 it installs these 4 but also 2 from Eclipse Corba Package.
gov.redhawk.eclipsecorba.idl_7.1.0.201501292343.jar
gov.redhawk.eclipsecorba.idl.source_7.1.0.201501292343.jar
gov.redhawk.eclipsecorba.idl.edit_4.1.0.201501292343.jar
gov.redhawk.eclipsecorba.idl.edit.source_4.1.0.201501292343.jar
net.sf.eclipsecorba.idl_0.7.0.218.jar
net.sf.eclipsecorba.idl.edit_0.7.0.218.jar
Many java files have the same names but there are also many differences.
From comments in the source java files it appears that the gov jars used JavaCC to build the parser while those from ECP used SableCC.
Which ones are actually used in RedHawk 1.10 or are they both used for different purposes?
I am trying to look into a parser bug and would like to know which parser to look at.
Sorry, I am not familiar with Eclipse plugin development and have not figured out how to tell what plugins are actually loaded or how they are used.
Redhawk uses the Eclipse Corba Plugin (ECP) project to provide an editor for IDL files:
http://eclipsecorba.sourceforge.net/
The editor does not support constant IDL expresions (e.g. const foo = bar + 1). Unfortunately, the project is not maintained any more (last release in 2008).
For all other IDL functions in the IDE, such as displaying IDLs under the "Target SDR" in the explorer view, the Redhawk IDE has its own parser code which handles this. The IDE's parser currently has the same limitation - it does not recognize constant IDL expressions.
RedHawk uses three distinct IDL parsers. 1) omnicpp (omniorbs version of idl2cpp) uses its own parser. 2) the code that builds a tree for the IDL Repository in Target SDR uses a plugin in gov.redhawk.eclipsecorba.idl.* which has a parser based on JavaCC compiler-compiler. 3) the IDL editor that was introduced in RedHawk 1.9 uses a different plugin in net.sf.eclipsecorba.idl.* which as a parser based on SableCC, a different compiler-compiler.
I've generated a win32com wrapper for a DLL and I'm trying to access it. It works except for one function called ReadPipeBytes. It works on two of my other machines but I'm using a different python version. This is the error:'' object has no attribute 'ReadPipeBytes'. I copied over the same dll to the other machine (its a driver, I have the same hardware I'm trying to access.) I did a compare on the wrapper files and they are almost identical except for the python versions they were generated with and the 3.3.5 generated version doesn't put u'FunctionName' where the 2.7 version does. If I copy over the wrapper file to the machine that doesn't work I get the same error (and/or the dict file).
1) Why would the version of python make a difference in reading this one particular function when the other function work fine (its not the wrapper?
2) How can python fail to use the function called readpipebytes when the other functions work and when I'm using the same files that I do on my other machines?
When you use com the language you are accessing it from needs the same "bittedness" as the com .dll or control. So If you have a 32-bit control or com dll you have to have a 32 bit win32com.