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  • Best way of learning Python + GUI when coming from .NET

    - by Oscar Mederos
    I've been developing applications in C# / VB.NET for about 3-4 years (.NET Framework v2.0, 3.5, 4). I have also developed some command-line applications or scripts in C, and Python under Linux. Sometimes I need to develop my applications in another languages, like Python, but the problem thing is that lots of those applications require a GUI. Maybe not a too complex one, but it does require some windows with buttons, text boxes, list boxes,... What books/tips/tutorials do you suggest me to start working with that language and be able to deploy my deliverables not only in .NET? Note: Learning python is not the big deal here, because I already know the basic of it. I just want to focus on the GUI. Maybe this question should be on UI instead of here? If so, please, migrate it :)

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  • How to backup MySQL (mysqldump) when Memcached installed?

    - by cewebugil
    The server OS is CentOS, with Memcached installed Before Memcached installed, I use mysqldump -u root -p --lock-tables --add-locks --disable-keys --skip-extended-insert --quick wcraze > /var/backup/backup.sql But now, Memcached has been installed. According to Wikipedia; When the table is full, subsequent inserts cause older data to be purged in least recently used (LRU) order. This means new data entry is not directly saved in MySQL, but saved in Memcached instead, until limit_maxbytes is full, the least accessed data will be saved in MySQL. This means, some data is not in the MySQL but in Memcached. So, when backup, the new entry is not in the backup data What is the right way to backup?

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  • How can I install a 32bit python on 64 bit Ubuntu

    - by moose
    I am using Ubuntu 10.10 (Linux pc07 2.6.35-27-generic #48-Ubuntu SMP Tue Feb 22 20:25:46 UTC 2011 x86_64 GNU/Linux) and the default python package (Python 2.6.6). I would like to install python-psyco to improve the performance of one of my scripts, but only python-psyco-doc is available for 64 bit. I tried a virtual machine, but the the performance boost is much less on the virtual machine than on a "real" installed 32-bit Ubuntu. So my question is: How can I install a 32Bit Python with psyco on my 64Bit Ubuntu machine? edit: I've found this article and made this: Download "Python 2.7.1 bzipped source tarball" from http://python.org/download/ Go in the directory where you decompressed "Python 2.7.1" $ OPT=-m32 LDFLAGS=-m32 ./configure --prefix=/opt/pym32 $ make But I got this error: gcc -pthread -m32 -Xlinker -export-dynamic -o python \ Modules/python.o \ libpython2.7.a -lpthread -ldl -lutil -lm libpython2.7.a(posixmodule.o): In function `posix_tmpnam': /home/moose/Downloads/Python-2.7.1/./Modules/posixmodule.c:7346: warning: the use of `tmpnam_r' is dangerous, better use `mkstemp' libpython2.7.a(posixmodule.o): In function `posix_tempnam': /home/moose/Downloads/Python-2.7.1/./Modules/posixmodule.c:7301: warning: the use of `tempnam' is dangerous, better use `mkstemp' Segmentation fault make: *** [sharedmods] Fehler 139 edit2: Now I've found http://indefinitestudies.org/2010/02/08/how-to-build-32-bit-python-on-ubuntu-9-10-x86_64/ and it seems like this worked: $ cd Python-2.7.1 $ CC="gcc -m32" LDFLAGS="-L/lib32 -L/usr/lib32 \ -Lpwd/lib32 -Wl,-rpath,/lib32 -Wl,-rpath,/usr/lib32" \ ./configure --prefix=/opt/pym32 $ make $ sudo make install But installing psyco didn't work: Download the lastest snapshot: http://psyco.sourceforge.net/download.html Extract it and go into the folder $ python setup.py install This error appeared: PROCESSOR = 'ivm' running install running build running build_py running build_ext building 'psyco._psyco' extension gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -fPIC -DALL_STATIC=1 -Ic/ivm -I/usr/include/python2.6 -c c/psyco.c -o build/temp.linux-x86_64-2.6/c/psyco.o In file included from c/psyco.c:1: c/psyco.h:9: fatal error: Python.h: Datei oder Verzeichnis nicht gefunden compilation terminated. error: command 'gcc' failed with exit status 1

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  • Python and Ruby in Oracle Tuxedo

    - by christopher.jones
    Did you know you can now develop services and applications in Python or Ruby with Oracle Tuxedo? The Tuxedo team have a blog post about it at Python and Ruby in Tuxedo. I used to think of Tuxedo as a Transaction Processing Monitor but it has evolved into much more.

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  • Memcached with Windows and .NET

    - by Funky81
    Is there anyone already implement memcached for production use in Windows environment? Because many blogs that I've read, it's not recommended to run memcached in Windows especially for production use, for example running memcached on windows. And one more thing, which memcached client that is good to use with c# and .net 3.5 ? I've found many alternate such as Memcached Providers @ Codeplex, Beitmemcached, and memcached provider @ Sourceforge

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  • memcached append() php ubuntu - bad protocol

    - by awongh
    I am running ubuntu gutsy(7.1) , php5 and I am trying to get memcached running locally. I installed everything as per the docs: memcached daemon, php PECL extension, libevent, etc. But now I can only run half of the example script for memcached append(): <?php $m = new Memcached(); $m->addServer('localhost', 11211); $m->setOption(Memcached::OPT_COMPRESSION, false); $m->set('foo', 'abc'); $m->append('foo', 'def'); var_dump($m->get('foo')); ?> the script terminates @ append() with an RES_BAD_PROTOCOL error message. It still runs the get(). I don't know why memcached would otherwise be working fine (connect, set, get - with the correct value of 'abc') and not work for append. it also doesnt work with prepend. I believe I have the setup correct, but I am not sure. Maybe there are compatibility problems between the versions of the dependecies? thanks much

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  • Using Memcached in Python/Django - questions.

    - by Thomas
    I am starting use Memcached to make my website faster. For constant data in my database I use this: from django.core.cache import cache cache_key = 'regions' regions = cache.get(cache_key) if result is None: """Not Found in Cache""" regions = Regions.objects.all() cache.set(cache_key, regions, 2592000) #(2592000sekund = 30 dni) return regions For seldom changed data I use signals: from django.core.cache import cache from django.db.models import signals def nuke_social_network_cache(self, instance, **kwargs): cache_key = 'networks_for_%s' % (self.instance.user_id,) cache.delete(cache_key) signals.post_save.connect(nuke_social_network_cache, sender=SocialNetworkProfile) signals.post_delete.connect(nuke_social_network_cache, sender=SocialNetworkProfile) Is it correct way? I installed django-memcached-0.1.2, which show me: Memcached Server Stats Server Keys Hits Gets Hit_Rate Traffic_In Traffic_Out Usage Uptime 127.0.0.1 15 220 276 79% 83.1 KB 364.1 KB 18.4 KB 22:21:25 Can sombody explain what columns means? And last question. I have templates where I am getting much records from a few table (relationships). So in my view I get records from one table and in templates show it and related info from others. Generating page last a few seconds for very small table (<100records). Is it some easy way to cache queries from templates? Have I to do some big structure in my view (with all related tables), cache it and send to template?

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  • How can I assert from Python C code?

    - by Joe
    I'm writing a Python class in C and I want to put assertions in my debug code. assert.h suits me fine. This only gets put in debug compiles so there's no chance of an assert failure impacting a user of the Python code*. I'm trying to divide my 'library' code (which should be separate to the code linked against Python) so I can use it from other C code. My Python methods are therefore thinnish wrappers around my pure-C code. So I can't do this in my 'library' code: if (black == white) { PyErr_SetString(PyExc_RuntimeError, "Remap failed"); } because this pollutes my pure-C code with Python. It's also far uglier than a simple assert(black != white); I believe that the Distutils compiler always sets NDEBUG, which means I can't use assert.h even in debug builds. Mac OS and Linux. Help! *one argument I've heard against asserting in C code called from Python.

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  • Python version issues

    - by MidnightLightning
    I have a Mac which uses MacPorts to have multiple versions of Python installed and use the python_select application to switch between them. Currently, this Mac has OS 10.6.6, which comes with Python 2.6.1 installed as /usr/bin/python. Using MacPorts, I've installed the python27, python31, and python_select ports and now have this issue: python_select seems to not be switching the default python properly: $ which python /usr/bin/python $ python -V Python 2.6.1 $ /usr/bin/python -V Python 2.6.1 $ sudo python_select python27 Selecting version "python27" for python $ which python /opt/local/bin/python $ ls -l /opt/local/bin/python lrwxr-xr-x 1 root admin 24B Mar 18 10:24 /opt/local/bin/python -> /opt/local/bin/python2.7 $ python -V Python 2.6.1 # <-- Wrong!!! $ /opt/local/bin/python -V Python 2.7.1 # <-- Why are you not default? So, after running python_select, which python seems to think that the /opt/local/bin version is going to be used, but in reality, it seems that the /usr/bin one is taking precedent unless I specifically call the /opt/local/bin one. Is there something I'm doing wrong?

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  • How can I get sikuli-ide to work?

    - by ayckoster
    I installed sikuli-ide with sudo apt-get install sikuli-ide Everything was fine until I tried to start it from the terminal. I typed sikuli-ide But the only response I got was [info] locale: en_US The application was not started, furthermore there is no desktop file and sikuli-ide does not show up in Dash Home. I guess there is something wrong with the package. I run Ubuntu 12.10 64bit. I tried to install it (Sikuli-X-1.0rc3 (r905)-linux-x86_64.zip) from their page, now the IDE starts, but when I try to execute a simple script I get the following error: [error] Stopped [error] An error occurs at line 1 [error] Error message: Traceback (most recent call last): File "", line 1, in File "/home/ayckoster/opt/Sikuli-IDE/sikuli-script.jar/Lib/sikuli/__init__.py", line 3, in File "/home/ayckoster/opt/Sikuli-IDE/sikuli-script.jar/Lib/sikuli/Sikuli.py", line 22, in java.lang.UnsatisfiedLinkError: /home/ayckoster/opt/Sikuli-IDE/libs/libVisionProxy.so: libml.so.2.1: cannot open shared object file: No such file or directory at java.lang.ClassLoader$NativeLibrary.load(Native Method) at java.lang.ClassLoader.loadLibrary1(ClassLoader.java:1935) at java.lang.ClassLoader.loadLibrary0(ClassLoader.java:1860) at java.lang.ClassLoader.loadLibrary(ClassLoader.java:1821) at java.lang.Runtime.load0(Runtime.java:792) at java.lang.System.load(System.java:1059) at com.wapmx.nativeutils.jniloader.NativeLoader.loadLibrary(NativeLoader.java:44) at org.sikuli.script.Finder.(Finder.java:33) at java.lang.Class.forName0(Native Method) at java.lang. Class.forName(Class.java:264) at org.python.core.Py.loadAndInitClass(Py.java:895) at org.python.core.Py.findClassInternal(Py.java:830) at org.python.core.Py.findClassEx(Py.java:881) at org.python.core.packagecache.SysPackageManager.findClass(SysPackageManager.java:133) at org.python.core.packagecache.PackageManager.findClass(PackageManager.java:28) at org.python.core.packagecache.SysPackageManager.findClass(SysPackageManager.java:122) at org.python.core.PyJavaPackage.__findattr_ex__(PyJavaPackage.java:137) at org.python.core.PyObject.__findattr__(PyObject.java:863) at org.python.core.imp.import_name(imp.java:849) at org.python.core.imp.importName(imp.java:884) at org.python.core.ImportFunction.__call__(__builtin__.java:1220) at org.python.core.PyObject.__call__(PyObject.java:357) at org.python.core.__builtin__.__import__(__builtin__.java:1173) at org.python.core.imp.importFromAs(imp.java:978) at org.python.core.imp.importFrom(imp.java:954) at sikuli.Sikuli$py.f$0(/home/ayckoster/opt/Sikuli-IDE/siku li-script.jar/Lib/sikuli/Sikuli.py:211) at sikuli.Sikuli$py.call_function(/home/ayckoster/opt/Sikuli-IDE/sikuli-script.jar/Lib/sikuli/Sikuli.py) at org.python.core.PyTableCode.call(PyTableCode.java:165) at org.python.core.PyCode.call(PyCode.java:18) at org.python.core.imp.createFromCode(imp.java:386) at org.python.core.util.importer.importer_load_module(importer.java:109) at org.python.modules.zipimport.zipimporter.zipimporter_load_module(zipimporter.java:161) at org.python.modules.zipimport.zipimporter$zipimporter_load_module_exposer.__call__(Unknown Source) at org.python.core.PyBuiltinMethodNarrow.__call__(PyBuiltinMethodNarrow.java:47) at org.python.core.imp.loadFromLoader(imp.java:513) at org.python.core.imp.find_module(imp.java:467) at org.python.core.PyModule.impAttr(PyModule.java:100) at org.python.core.imp.import_next(imp.java:715) at org.python.core.imp.import_name(imp.java:824) at org.python.core.imp.importName(imp.java:884) at org.python.core.ImportFunction.__call__(__builtin__.java:1220) at org.python.core.PyObject.__call__(PyObject.java:357) at org.python.core.__builtin__.__import__(__builtin__.java:1173) at org.python.core.imp.importAll(imp.java:998) at sikuli$py.f$0(/home/ayckoster/opt/Sikuli-IDE/sikuli-script.jar/Lib/sikuli/__init__.py:3) at sikuli$py.call_function(/home/ayckoster/opt/Sikuli-IDE/sikuli-script.jar/Lib/sikuli/__init__.py) at org.python.core.PyTableCode.call(PyTableCode.java:165) at org.python.core.PyCode.call(PyCode.java:18) at org.python.core.imp.createFromCode(imp.java:386) at org.python.core.util.importer.importer_load_module(importer.java:109) at org.python.modules.zipimport.zipimporter.zipimporter_load_module(zipimporter.java:161) at org.python.modules.zipimport.zipimporter$zipimporter_load_module_exposer.__call__(Unknown Source) at org.python.core.PyBuiltinMethodNarrow.__call__(PyBuiltinMethodNarrow.java:47) at org.python.core.imp.loadFromLoader(imp.java:513) at org.python.core.imp.find_module(imp.java:467) at org.python.core.imp.import_next(imp.java:713) at or g.python.core.imp.import_name(imp.java:824) at org.python.core.imp.importName(imp.java:884) at org.python.core.ImportFunction.__call__(__builtin__.java:1220) at org.python.core.PyObject.__call__(PyObject.java:357) at org.python.core.__builtin__.__import__(__builtin__.java:1173) at org.python.core.imp.importAll(imp.java:998) at org.python.pycode._pyx2.f$0(:1) at org.python.pycode._pyx2.call_function() at org.python.core.PyTableCode.call(PyTableCode.java:165) at org.python.core.PyCode.call(PyCode.java:18) at org.python.core.Py.runCode(Py.java:1261) at org.python.core.Py.exec(Py.java:1305) at org.python.util.PythonInterpreter.exec(PythonInterpreter.java:206) at org.sikuli.script.ScriptRunner.runPython(ScriptRunner.java:61) at org.sikuli.ide.SikuliIDE$ButtonRun.runPython(SikuliIDE.java:1572) at org.sikuli.ide.SikuliIDE$ButtonRun$1.run(SikuliIDE.java:1677) java.lang.UnsatisfiedLinkError: java.lang.UnsatisfiedLinkError: /home/ayckoster/opt/Sikuli-IDE/libs/libVisionProxy.so: libml.so.2.1: cannot open shared object file: No such file or directory If I try to use the click() method from the gui it fails. So I created my own click method and it look like this: This cannot be executed and produces the error above.

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  • New Enhancements for InnoDB Memcached

    - by Calvin Sun
    In MySQL 5.6, we continued our development on InnoDB Memcached and completed a few widely desirable features that make InnoDB Memcached a competitive feature in more scenario. Notablely, they are 1) Support multiple table mapping 2) Added background thread to auto-commit long running transactions 3) Enhancement in binlog performance  Let’s go over each of these features one by one. And in the last section, we will go over a couple of internally performed performance tests. Support multiple table mapping In our earlier release, all InnoDB Memcached operations are mapped to a single InnoDB table. In the real life, user might want to use this InnoDB Memcached features on different tables. Thus being able to support access to different table at run time, and having different mapping for different connections becomes a very desirable feature. And in this GA release, we allow user just be able to do both. We will discuss the key concepts and key steps in using this feature. 1) "mapping name" in the "get" and "set" command In order to allow InnoDB Memcached map to a new table, the user (DBA) would still require to "pre-register" table(s) in InnoDB Memcached “containers” table (there is security consideration for this requirement). If you would like to know about “containers” table, please refer to my earlier blogs in blogs.innodb.com. Once registered, the InnoDB Memcached will then be able to look for such table when they are referred. Each of such registered table will have a unique "registration name" (or mapping_name) corresponding to the “name” field in the “containers” table.. To access these tables, user will include such "registration name" in their get or set commands, in the form of "get @@new_mapping_name.key", prefix "@@" is required for signaling a mapped table change. The key and the "mapping name" are separated by a configurable delimiter, by default, it is ".". So the syntax is: get [@@mapping_name.]key_name set [@@mapping_name.]key_name  or  get @@mapping_name set @@mapping_name Here is an example: Let's set up three tables in the "containers" table: The first is a map to InnoDB table "test/demo_test" table with mapping name "setup_1" INSERT INTO containers VALUES ("setup_1", "test", "demo_test", "c1", "c2", "c3", "c4", "c5", "PRIMARY");  Similarly, we set up table mappings for table "test/new_demo" with name "setup_2" and that to table "mydatabase/my_demo" with name "setup_3": INSERT INTO containers VALUES ("setup_2", "test", "new_demo", "c1", "c2", "c3", "c4", "c5", "secondary_index_x"); INSERT INTO containers VALUES ("setup_3", "my_database", "my_demo", "c1", "c2", "c3", "c4", "c5", "idx"); To switch to table "my_database/my_demo", and get the value corresponding to “key_a”, user will do: get @@setup_3.key_a (this will also output the value that corresponding to key "key_a" or simply get @@setup_3 Once this is done, this connection will switch to "my_database/my_demo" table until another table mapping switch is requested. so it can continue issue regular command like: get key_b  set key_c 0 0 7 These DMLs will all be directed to "my_database/my_demo" table. And this also implies that different connections can have different bindings (to different table). 2) Delimiter: For the delimiter "." that separates the "mapping name" and key value, we also added a configure option in the "config_options" system table with name of "table_map_delimiter": INSERT INTO config_options VALUES("table_map_delimiter", "."); So if user wants to change to a different delimiter, they can change it in the config_option table. 3) Default mapping: Once we have multiple table mapping, there should be always a "default" map setting. For this, we decided if there exists a mapping name of "default", then this will be chosen as default mapping. Otherwise, the first row of the containers table will chosen as default setting. Please note, user tables can be repeated in the "containers" table (for example, user wants to access different columns of the table in different settings), as long as they are using different mapping/configure names in the first column, which is enforced by a unique index. 4) bind command In addition, we also extend the protocol and added a bind command, its usage is fairly straightforward. To switch to "setup_3" mapping above, you simply issue: bind setup_3 This will switch this connection's InnoDB table to "my_database/my_demo" In summary, with this feature, you now can direct access to difference tables with difference session. And even a single connection, you can query into difference tables. Background thread to auto-commit long running transactions This is a feature related to the “batch” concept we discussed in earlier blogs. This “batch” feature allows us batch the read and write operations, and commit them only after certain calls. The “batch” size is controlled by the configure parameter “daemon_memcached_w_batch_size” and “daemon_memcached_r_batch_size”. This could significantly boost performance. However, it also comes with some disadvantages, for example, you will not be able to view “uncommitted” operations from SQL end unless you set transaction isolation level to read_uncommitted, and in addition, this will held certain row locks for extend period of time that might reduce the concurrency. To deal with this, we introduce a background thread that “auto-commits” the transaction if they are idle for certain amount of time (default is 5 seconds). The background thread will wake up every second and loop through every “connections” opened by Memcached, and check for idle transactions. And if such transaction is idle longer than certain limit and not being used, it will commit such transactions. This limit is configurable by change “innodb_api_bk_commit_interval”. Its default value is 5 seconds, and minimum is 1 second, and maximum is 1073741824 seconds. With the help of such background thread, you will not need to worry about long running uncommitted transactions when set daemon_memcached_w_batch_size and daemon_memcached_r_batch_size to a large number. This also reduces the number of locks that could be held due to long running transactions, and thus further increase the concurrency. Enhancement in binlog performance As you might all know, binlog operation is not done by InnoDB storage engine, rather it is handled in the MySQL layer. In order to support binlog operation through InnoDB Memcached, we would have to artificially create some MySQL constructs in order to access binlog handler APIs. In previous lab release, for simplicity consideration, we open and destroy these MySQL constructs (such as THD) for each operations. This required us to set the “batch” size always to 1 when binlog is on, no matter what “daemon_memcached_w_batch_size” and “daemon_memcached_r_batch_size” are configured to. This put a big restriction on our capability to scale, and also there are quite a bit overhead in creating destroying such constructs that bogs the performance down. With this release, we made necessary change that would keep MySQL constructs as long as they are valid for a particular connection. So there will not be repeated and redundant open and close (table) calls. And now even with binlog option is enabled (with innodb_api_enable_binlog,), we still can batch the transactions with daemon_memcached_w_batch_size and daemon_memcached_r_batch_size, thus scale the write/read performance. Although there are still overheads that makes InnoDB Memcached cannot perform as fast as when binlog is turned off. It is much better off comparing to previous release. And we are continuing optimize the solution is this area to improve the performance as much as possible. Performance Study: Amerandra of our System QA team have conducted some performance studies on queries through our InnoDB Memcached connection and plain SQL end. And it shows some interesting results. The test is conducted on a “Linux 2.6.32-300.7.1.el6uek.x86_64 ix86 (64)” machine with 16 GB Memory, Intel Xeon 2.0 GHz CPU X86_64 2 CPUs- 4 Core Each, 2 RAID DISKS (1027 GB,733.9GB). Results are described in following tables: Table 1: Performance comparison on Set operations Connections 5.6.7-RC-Memcached-plugin ( TPS / Qps) with memcached-threads=8*** 5.6.7-RC* X faster Set (QPS) Set** 8 30,000 5,600 5.36 32 59,000 13,000 4.54 128 68,000 8,000 8.50 512 63,000 6.800 9.23 * mysql-5.6.7-rc-linux2.6-x86_64 ** The “set” operation when implemented in InnoDB Memcached involves a couple of DMLs: it first query the table to see whether the “key” exists, if it does not, the new key/value pair will be inserted. If it does exist, the “value” field of matching row (by key) will be updated. So when used in above query, it is a precompiled store procedure, and query will just execute such procedures. *** added “–daemon_memcached_option=-t8” (default is 4 threads) So we can see with this “set” query, InnoDB Memcached can run 4.5 to 9 time faster than MySQL server. Table 2: Performance comparison on Get operations Connections 5.6.7-RC-Memcached-plugin ( TPS / Qps) with memcached-threads=8 5.6.7-RC* X faster Get (QPS) Get 8 42,000 27,000 1.56 32 101,000 55.000 1.83 128 117,000 52,000 2.25 512 109,000 52,000 2.10 With the “get” query (or the select query), memcached performs 1.5 to 2 times faster than normal SQL. Summary: In summary, we added several much-desired features to InnoDB Memcached in this release, allowing user to operate on different tables with this Memcached interface. We also now provide a background commit thread to commit long running idle transactions, thus allow user to configure large batch write/read without worrying about large number of rows held or not being able to see (uncommit) data. We also greatly enhanced the performance when Binlog is enabled. We will continue making efforts in both performance enhancement and functionality areas to make InnoDB Memcached a good demo case for our InnoDB APIs. Jimmy Yang, September 29, 2012

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  • Build problems when adding `__str__` method to Boost Python C++ class

    - by Rickard
    I have started to play around with boost python a bit and ran into a problem. I tried to expose a C++ class to python which posed no problems. But I can't seem to manage to implement the __str__ functionality for the class without getting build errors I don't understand. I'm using boost 1_42 prebuild by boostpro. I build the library using cmake and the vs2010 compiler. I have a very simple setup. The header-file (tutorial.h) looks like the following: #include <iostream> namespace TestBoostPython{ class TestClass { private: double m_x; public: TestClass(double x); double Get_x() const; void Set_x(double x); }; std::ostream &operator<<(std::ostream &ostr, const TestClass &ts); }; and the corresponding cpp-file looks like: #include <boost/python.hpp> #include "tutorial.h" using namespace TestBoostPython; TestClass::TestClass(double x) { m_x = x; } double TestClass::Get_x() const { return m_x; } void TestClass::Set_x(double x) { m_x = x; } std::ostream &operator<<(std::ostream &ostr, TestClass &ts) { ostr << ts.Get_x() << "\n"; return ostr; } BOOST_PYTHON_MODULE(testme) { using namespace boost::python; class_<TestClass>("TestClass", init<double>()) .add_property("x", &TestClass::Get_x, &TestClass::Set_x) .def(str(self)) ; } The CMakeLists.txt looks like the following: CMAKE_MINIMUM_REQUIRED(VERSION 2.8) project (testme) FIND_PACKAGE( Boost REQUIRED ) FIND_PACKAGE( Boost COMPONENTS python REQUIRED ) FIND_PACKAGE( PythonLibs REQUIRED ) set(Boost_USE_STATIC_LIBS OFF) set(Boost_USE_MULTITHREAD ON) INCLUDE_DIRECTORIES(${Boost_INCLUDE_DIRS}) INCLUDE_DIRECTORIES ( ${PYTHON_INCLUDE_PATH} ) add_library(testme SHARED tutorial.cpp) target_link_libraries(testme ${Boost_PYTHON_LIBRARY}) target_link_libraries(testme ${PYTHON_LIBRARY} The build error I get is the following: Compiling... tutorial.cpp C:\Program Files (x86)\boost\boost_1_42\boost/python/def_visitor.hpp(31) : error C2780: 'void boost::python::api::object_operators::visit(ClassT &,const char *,const boost::python::detail::def_helper &) const' : expects 3 arguments - 1 provided with [ U=boost::python::api::object ] C:\Program Files (x86)\boost\boost_1_42\boost/python/object_core.hpp(203) : see declaration of 'boost::python::api::object_operators::visit' with [ U=boost::python::api::object ] C:\Program Files (x86)\boost\boost_1_42\boost/python/def_visitor.hpp(67) : see reference to function template instantiation 'void boost::python::def_visitor_access::visit,classT>(const V &,classT &)' being compiled with [ DerivedVisitor=boost::python::api::object, classT=boost::python::class_, V=boost::python::def_visitor ] C:\Program Files (x86)\boost\boost_1_42\boost/python/class.hpp(225) : see reference to function template instantiation 'void boost::python::def_visitor::visit>(classT &) const' being compiled with [ DerivedVisitor=boost::python::api::object, W=TestBoostPython::TestClass, classT=boost::python::class_ ] .\tutorial.cpp(29) : see reference to function template instantiation 'boost::python::class_ &boost::python::class_::def(const boost::python::def_visitor &)' being compiled with [ W=TestBoostPython::TestClass, U=boost::python::api::object, DerivedVisitor=boost::python::api::object ] Does anyone have any idea on what went wrrong? If I remove the .def(str(self)) part from the wrapper code, everything compiles fine and the class is usable from python. I'd be very greatful for assistance. Thank you, Rickard

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  • Which key:value store to use with Python?

    - by Kurt
    So I'm looking at various key:value (where value is either strictly a single value or possibly an object) stores for use with Python, and have found a few promising ones. I have no specific requirement as of yet because I am in the evaluation phase. I'm looking for what's good, what's bad, what are the corner cases these things handle well or don't, etc. I'm sure some of you have already tried them out so I'd love to hear your findings/problems/etc. on the various key:value stores with Python. I'm looking primarily at: memcached - http://www.danga.com/memcached/ python clients: http://pypi.python.org/pypi/python-memcached/1.40 http://www.tummy.com/Community/software/python-memcached/ CouchDB - http://couchdb.apache.org/ python clients: http://code.google.com/p/couchdb-python/ Tokyo Tyrant - http://1978th.net/tokyotyrant/ python clients: http://code.google.com/p/pytyrant/ Lightcloud - http://opensource.plurk.com/LightCloud/ Based on Tokyo Tyrant, written in Python Redis - http://code.google.com/p/redis/ python clients: http://pypi.python.org/pypi/txredis/0.1.1 MemcacheDB - http://memcachedb.org/ So I started benchmarking (simply inserting keys and reading them) using a simple count to generate numeric keys and a value of "A short string of text": memcached: CentOS 5.3/python-2.4.3-24.el5_3.6, libevent 1.4.12-stable, memcached 1.4.2 with default settings, 1 gig memory, 14,000 inserts per second, 16,000 seconds to read. No real optimization, nice. memcachedb claims on the order of 17,000 to 23,000 inserts per second, 44,000 to 64,000 reads per second. I'm also wondering how the others stack up speed wise.

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  • How to organize Python modules for PyPI to support 2.x and 3.x

    - by Craig McQueen
    I have a Python module that I would like to upload to PyPI. So far, it is working for Python 2.x. It shouldn't be too hard to write a version for 3.x now. But, after following guidelines for making modules in these places: Distributing Python Modules The Hitchhiker’s Guide to Packaging it's not clear to me how to support multiple source distributions for different versions of Python, and it's not clear if/how PyPI could support it. I envisage I would have separate code for: 2.x 2.6 (maybe, as a special case to use the new buffer API) 3.x How is it possible to set up a Python module in PyPI so that someone can do: easy_install modulename and it will install the right thing whether the user is using 2.x or 3.x?

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  • How to organize Python modules for PyPI to support 2.x and 3.x

    - by Craig McQueen
    I have a Python module that I would like to upload to PyPI. So far, it is working for Python 2.x. It shouldn't be too hard to write a version for 3.x now. But, after following guidelines for making modules in these places: Distributing Python Modules The Hitchhiker’s Guide to Packaging it's not clear to me how to support multiple source distributions for different versions of Python, and it's not clear if/how PyPI could support it. I envisage I would have separate code for: 2.x 2.6 (maybe, as a special case to use the new buffer API) 3.x How is it possible to set up a Python module in PyPI so that someone can do: easy_install modulename and it will install the right thing whether the user is using 2.x or 3.x?

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  • Prevent Python from caching the imported modules

    - by Olivier
    While developing a largeish project (split in several files and folders) in Python with IPython, I run into the trouble of cached imported modules. The problem is that instructions import module only reads the module once, even if that module has changed! So each time I change something in my package, I have to quit and restart IPython. Painful. Is there any way to properly force reloading some modules? Or, better, to somehow prevent Python from caching them? I tried several approaches, but none works. In particular I run into really, really weird bugs, like some modules or variables mysteriously becoming equal to None... The only sensible resource I found is Reloading Python modules, from pyunit, but I have not checked it. I would like something like that. A good alternative would be for IPython to restart, or restart the Python interpreter somehow. So, if you develop in Python, what solution have you found to this problem?

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  • Using Crypt function Python 3.3.2

    - by adampski
    In Windows and Python version 3.3.2, I try and call the python module like so: hash2 = crypt(word, salt) I import it at the top of my program like so: from crypt import * The result I get is the following: Traceback (most recent call last): File "C:\none\of\your\business\adams.py", line 10, in <module> from crypt import * File "C:\Python33\lib\crypt.py", line 3, in <module> import _crypt ImportError: No module named '_crypt' However, when I execute the same file adams.py in Ubuntu, with Python 2.7.3, it executes perfectly - no errors. I tried the following to resolve the issue for my Windows & Python 3.3.2 (though I'm sure the OS isn't the issue, the Python version or my use of syntax is the issue): Rename the directory in the Python33 directory from Lib to lib Rename the crypt.py in lib to _crypt.py. However, it turns out the entire crypt.py module depends on an external module called _crypt.py too. Browsed internet to download anything remotely appropriate to resemble _crypt.py It's not Python, right? It's me...(?) I'm using syntaxes to import and use external modules that are acceptable in 2.7.3, but not in 3.3.2. Or have I found a bug in 3.3.2?

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  • Python 2 dict_items.sort() in Python 3

    - by DaveWeber
    I'm porting some code from Python 2 to 3. This is valid code in Python 2 syntax: def print_sorted_dictionary(dictionary): items=dictionary.items() items.sort() In Python 3, the dict_items have no method 'sort' - how can I make a workaround for this in Python 3?

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  • Broken pipe error in rails with memcached

    - by abronte
    I keep running into this error MemCacheError (Broken pipe): Broken pipe on my Rails app and I can't figure out why. When I access memcached via Rails.cache in my controller, the first 1 or 2 read/writes always seems to throw the broken pipe error. But when I access memcached by creating a new object, ActiveSupport::Cache::MemCacheStore.new, I don't seem to get this error. I also access memcached in another ruby process, and the first read always has this error regardless of the way I access memcached. I did implement a work around just by retrying the read but id rather have a better long term solution. Currently the only time I see this problem is after I restart memcached. I'm using Rails 2.3.5 and memcached 1.4.4 (I've also tried this with memcached 1.2.2).

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  • Making python 3.3 default python 3 interpreter instead of 3.2

    - by user1873947
    So, to keep it simple. Ubuntu 12.10 has python 3.2 pre installed and it is linked to "python3". I downloaded python 3.3 and it's command is "python3.3". However, I downloaded pySide for python3 from synaptic. Using "from PySide.QtCore import *" fails on python3.3. BUT, when I ran just "python3" (aka 3.2) everything works fine. Synaptic just installed lib for python3.2 which is default for python3 in ubuntu. How can I force synaptic to install modules for python3.3? Thanks

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  • MemCached on Windows x64

    - by Django Reinhardt
    This question has previously been asked, but that was a year ago and I wanted to know if there had been any developments since then. Basically we'd like to use a MemCached Server on a Windows Server 2008 R2 machine... which is only x64, obviously. I haven't found any details on a Win64 version of MemCached, but there is still the solution from the previous thread (which I haven't tried yet) to use a bit of software called MemCacheD Manager running MemCached 1.2.6. However, the current version of MCd is 1.4.4 and I was wondering if there had been any improvements since then.

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  • Memcached - doesn't seem to be working

    - by Trev
    my local.xml <session_save><![CDATA[files]]></session_save> <cache> <backend>memcached</backend> <prefix>MAGE_</prefix> <memcached> <servers> <server> <host><![CDATA[127.0.0.1]]></host> <port><![CDATA[11211]]></port> <persistent><![CDATA[1]]></persistent> </server> </servers> </memcached> </cache> /var/cache is still filling up memachced is running memcache 2685 0.0 0.3 351888 26152 ? Sl 08:07 0:19 /usr/bin/memcached -m 64 -p 11211 -u memcache -l 127.0.0.1 How do i know its working? I notice no speed increases.

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  • How to secure memcached?

    - by alfish
    In Debian, I have installed memcached (using this guide) to lower the otherwise unmanageable load on mysql database. The database is on a separate server, and memcached and Varnish are on the front server. Is it a potential security hole to leave memcached unprotected by a firewall? If so, how should I secure it? The situation is especially worrisome,as I've received (unproved) reports of cookie thefts on the server. Thanks

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  • Can I have nginx put stuff on memcached?

    - by adamo
    It is my understanding that nginx can query memcached for data that it serves, but you have to place them there using some other (homegrown) program. So the question is, can I have nginx fetch data from the backend and place them into memcached for future use for certain locations? Sort of not having to place all files from /images in it "by hand" but having them (mem)cached after being fetched for the first time? Any backend other than memcached would suffice also.

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