🌐 Mailman 3 September 2022 - Python-list - python.org

>>> %matplotlib inline results in SyntaxError: invalid syntax
by Mike S Dec. 25, 2023

Dec. 25, 2023

I have installed Python 3.4.4 on XPSP3 and am trying to work my way through this tutorial. A Complete Tutorial on Ridge and Lasso Regression in Python http://www.analyticsvidhya.com/blog/2016/01/complete-tutorial-ridge-lasso-r… In Step 2 "Why Penalize the Magnitude of Coefficients?" we are shown this code: #Importing libraries. The same will be used throughout the article. import numpy as np import pandas as pd import random import matplotlib.pyplot as plt %matplotlib inline I get an error on the last line. I am running this code in Idle Python 3.4.4 Shell... Python 3.4.4 (v3.4.4:737efcadf5a6, Dec 20 2015, 19:28:18) [MSC v.1600 32 bit (Intel)] on win32 Type "copyright", "credits" or "license()" for more information. >>> import numpy as np >>> import pandas as pd >>> import random >>> import matplotlib.pyplot as plt >>> %matplotlib inline SyntaxError: invalid syntax What am I doing wrong? Suggested reading? TIA, Mike

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Re: How to add CC and BCC while sending mails using python
by akegb3＠gmail.com June 20, 2023

June 20, 2023

On Tuesday, September 30, 2008 8:00:16 AM UTC-8, Bernhard Walle wrote: > Hi, > > * cindy jones [2008-09-30 19:57]: > > > > Can someone tel me how to add cc's and bcc's while sending mails using > > python > > Following (tested) snippet should help: > > ------------------ 8< ------------------------------ > from smtplib import SMTP > from email.mime.image import MIMEImage > from email.mime.text import MIMEText > from email.mime.multipart import MIMEMultipart > > to = 'to_address(a)example.invalid' > cc = 'cc_address(a)example.invalid' > bcc = 'bcc_address(a)example.invalid' > > msg = MIMEMultipart() > msg['To'] = to > msg['Cc'] = cc > msg['From'] = 'bernhard(a)bwalle.de' > msg['Subject'] = 'Test' > text = MIMEText('Das ist ein Test') > text.add_header("Content-Disposition", "inline") > msg.attach(text) > > s = SMTP('test.smtp.relay') > s.sendmail(msg['From'], [to, cc, bcc], msg.as_string()) > s.quit() > ------------------ >8 ------------------------------ > > > Regards, > Bernhard Hello Bernhard, I've tried the above code and the bcc address does not receive the message, on the To & CC addresses receive it. Here are snippets from my code, perhaps something will stand out to you? to = 'ed(a)domain.gov' cc = 'ed(a)gmailmail.com' bcc = 'ed(a)home.net' msg = MIMEMultipart() msg['To'] = to msg['Cc'] = cc msg['Subject'] = 'My Subject text here' msg['From'] = 'edsboss(a)domain.gov' smtp = SMTP("smtpserver") smtp.ehlo() smtp.sendmail(msg['From'], [to, cc, bcc], msg.as_string()) Thanks in advance..hope you're still out there!! ~Ed

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Re: python developer
by Jan van den Broek Oct. 1, 2022

Oct. 1, 2022

2022-09-29, Mike Dewhirst <miked(a)dewhirst.com.au> schrieb: > This is an OpenPGP/MIME signed message (RFC 4880 and 3156) Why? [Schnipp] -- Jan v/d Broek balglaas(a)dds.nl

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Re: PyObject_CallFunctionObjArgs segfaults
by Greg Ewing Sept. 30, 2022

Sept. 30, 2022

On 1/10/22 8:18 am, MRAB wrote: > It's OK to INCREF them, provided that you DECREF them when you no longer > need them, and remember that if it's a "new reference" you'd need to > DECREF it twice. Which means there would usually be no point in doing the extra INCREF/DECREF. You still need to know whether it's a new reference or not and treat it accordingly. -- Greg

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Re: PyObject_CallFunctionObjArgs segfaults
by Jen Kris Sept. 30, 2022

Sept. 30, 2022

To update my previous email, I found the problem, but I have a new problem. Previously I cast PyObject * value_ptr = (PyObject * )value_1 but that's not correct. Instead I used PyObject * value_ptr = PyLong_FromLong(value_1) and that works. HOWEVER, while PyObject_CallFunctionObjArgs does work now, it returns -1, which is not the right answer for random.seed. I use "long return_val = PyLong_AsLong(p_seed_calc);" to convert it to a long. So my question is why do I get -1 as return value? When I query p_seed calc : get: (gdb) p p_seed_calc $2 = (PyObject *) 0x7ffff69be120 <_Py_NoneStruct> Thanks again. Jen Sep 29, 2022, 13:02 by python-list(a)python.org: > Thanks very much to @MRAB for taking time to answer. I changed my code to conform to your answer (as best I understand your comments on references), but I still get the same error. My comments continue below the new code immediately below. > > int64_t Get_LibModules(int64_t * return_array) > { > PyObject * pName_random = PyUnicode_FromString("random"); > PyObject * pMod_random = PyImport_Import(pName_random); > > Py_INCREF(pName_random); > Py_INCREF(pMod_random); > > if (pMod_random == 0x0){ > PyErr_Print(); > return 1;} > > PyObject * pAttr_seed = PyObject_GetAttrString(pMod_random, "seed"); > PyObject * pAttr_randrange = PyObject_GetAttrString(pMod_random, "randrange"); > > Py_INCREF(pAttr_seed); > Py_INCREF(pAttr_randrange); > > return_array[0] = (int64_t)pAttr_seed; > return_array[1] = (int64_t)pAttr_randrange; > > return 0; > } > > int64_t C_API_2(PyObject * pAttr_seed, Py_ssize_t value_1) > { > PyObject * value_ptr = (PyObject * )value_1; > PyObject * p_seed_calc = PyObject_CallFunctionObjArgs(pAttr_seed, value_ptr, NULL); > > if (p_seed_calc == 0x0){ > PyErr_Print(); > return 1;} > > //Prepare return values > long return_val = PyLong_AsLong(p_seed_calc); > > return return_val; > } > > So I incremented the reference to all objects in Get_LibModules, but I still get the same segfault at PyObject_CallFunctionObjArgs. Unfortunately, reference counting is not well documented so I’m not clear what’s wrong. > > > > > Sep 29, 2022, 10:06 by python(a)mrabarnett.plus.com: > >> On 2022-09-29 16:54, Jen Kris via Python-list wrote: >> >>> Recently I completed a project where I used PyObject_CallFunctionObjArgs extensively with the NLTK library from a program written in NASM, with no problems. Now I am on a new project where I call the Python random library. I use the same setup as before, but I am getting a segfault with random.seed. >>> >>> At the start of the NASM program I call a C API program that gets PyObject pointers to “seed” and “randrange” in the same way as I did before: >>> >>> int64_t Get_LibModules(int64_t * return_array) >>> { >>> PyObject * pName_random = PyUnicode_FromString("random"); >>> PyObject * pMod_random = PyImport_Import(pName_random); >>> >> Both PyUnicode_FromString and PyImport_Import return new references or null pointers. >> >>> if (pMod_random == 0x0){ >>> PyErr_Print(); >>> >> >> You're leaking a reference here (pName_random). >> >>> return 1;} >>> >>> PyObject * pAttr_seed = PyObject_GetAttrString(pMod_random, "seed"); >>> PyObject * pAttr_randrange = PyObject_GetAttrString(pMod_random, "randrange"); >>> >>> return_array[0] = (int64_t)pAttr_seed; >>> return_array[1] = (int64_t)pAttr_randrange; >>> >> >> You're leaking 2 references here (pName_random and pMod_random). >> >>> return 0; >>> } >>> >>> Later in the same program I call a C API program to call random.seed: >>> >>> int64_t C_API_2(PyObject * pAttr_seed, Py_ssize_t value_1) >>> { >>> PyObject * p_seed_calc = PyObject_CallFunctionObjArgs(pAttr_seed, value_1); >>> >> >> It's expecting all of the arguments to be PyObject*, but value_1 is Py_ssize_t instead of PyObject* (a pointer to a _Python_ int). >> >> The argument list must end with a null pointer. >> >> It returns a new reference or a null pointer. >> >>> >>> if (p_seed_calc == 0x0){ >>> PyErr_Print(); >>> return 1;} >>> >>> //Prepare return values >>> long return_val = PyLong_AsLong(p_seed_calc); >>> >> You're leaking a reference here (p_seed_calc). >> >>> return return_val; >>> } >>> >>> The first program correctly imports “random” and gets pointers to “seed” and “randrange.” I verified that the same pointer is correctly passed into C_API_2, and the seed value (1234) is passed as Py_ssize_t value_1. But I get this segfault: >>> >>> Program received signal SIGSEGV, Segmentation fault. >>> 0x00007ffff64858d5 in _Py_INCREF (op=0x4d2) at ../Include/object.h:459 >>> 459 ../Include/object.h: No such file or directory. >>> >>> So I tried Py_INCREF in the first program: >>> >>> Py_INCREF(pMod_random); >>> Py_INCREF(pAttr_seed); >>> >>> Then I moved Py_INCREF(pAttr_seed) to the second program. Same segfault. >>> >>> Finally, I initialized “random” and “seed” in the second program, where they are used. Same segfault. >>> >>> The segfault refers to Py_INCREF, so this seems to do with reference counting, but Py_INCREF didn’t solve it. >>> >>> I’m using Python 3.8 on Ubuntu. >>> >>> Thanks for any ideas on how to solve this. >>> >>> Jen >>> >> >> -- >> https://mail.python.org/mailman/listinfo/python-list >> > > -- > https://mail.python.org/mailman/listinfo/python-list >

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Re: Implementation of an lru_cache() decorator that ignores the first argument
by Robert Latest Sept. 30, 2022

Sept. 30, 2022

Hi Chris and dh, thanks for your --as usually-- thoughtful and interesting answers. Indeed, when doing these web applications I find that there are several layers of useful, maybe less useful, and unknown caching. Many of my requests rely on a notoriously unreliable read-only database outside of my control, so I cache the required data into a local DB on my server, then I do some in-memory caching of expensive data plots because I haven't figured out how to reliably exploit the client-side caching ... then every middleware on that path may or may not implement its own version of clever or not-so-clever caching. Probably not a good idea to try and outsmart that by adding yet another thing that may break or not be up-to-date at the wrong moment. That said, the only caching that SQLAlchemy does (to my knowledge) is that it stores retrieved DB items by their primary keys in the session. Not worth much since the session gets created and dumped on each request by SQA's unit of work paradigm. But the DB backend itself may be caching repeated queries. Back to Python-theory: The "Cloak" object is the only way I could think of to sneak changing data past lru_cache's key lookup mechanism. Is there some other method? Just curious.

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python developer
by Walid AlMasri Sept. 29, 2022

Sept. 29, 2022

Hi all, I has been using python in scientific computing for many years I want to become a python developer so what is a good reference to follow ? Thanks in advance ! Walid

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PyObject_CallFunctionObjArgs segfaults
by Jen Kris Sept. 29, 2022

Sept. 29, 2022

Recently I completed a project where I used PyObject_CallFunctionObjArgs extensively with the NLTK library from a program written in NASM, with no problems. Now I am on a new project where I call the Python random library. I use the same setup as before, but I am getting a segfault with random.seed. At the start of the NASM program I call a C API program that gets PyObject pointers to “seed” and “randrange” in the same way as I did before: int64_t Get_LibModules(int64_t * return_array) { PyObject * pName_random = PyUnicode_FromString("random"); PyObject * pMod_random = PyImport_Import(pName_random); if (pMod_random == 0x0){ PyErr_Print(); return 1;} PyObject * pAttr_seed = PyObject_GetAttrString(pMod_random, "seed"); PyObject * pAttr_randrange = PyObject_GetAttrString(pMod_random, "randrange"); return_array[0] = (int64_t)pAttr_seed; return_array[1] = (int64_t)pAttr_randrange; return 0; } Later in the same program I call a C API program to call random.seed: int64_t C_API_2(PyObject * pAttr_seed, Py_ssize_t value_1) { PyObject * p_seed_calc = PyObject_CallFunctionObjArgs(pAttr_seed, value_1); if (p_seed_calc == 0x0){ PyErr_Print(); return 1;} //Prepare return values long return_val = PyLong_AsLong(p_seed_calc); return return_val; } The first program correctly imports “random” and gets pointers to “seed” and “randrange.” I verified that the same pointer is correctly passed into C_API_2, and the seed value (1234) is passed as Py_ssize_t value_1. But I get this segfault: Program received signal SIGSEGV, Segmentation fault. 0x00007ffff64858d5 in _Py_INCREF (op=0x4d2) at ../Include/object.h:459 459 ../Include/object.h: No such file or directory. So I tried Py_INCREF in the first program: Py_INCREF(pMod_random); Py_INCREF(pAttr_seed); Then I moved Py_INCREF(pAttr_seed) to the second program. Same segfault. Finally, I initialized “random” and “seed” in the second program, where they are used. Same segfault. The segfault refers to Py_INCREF, so this seems to do with reference counting, but Py_INCREF didn’t solve it. I’m using Python 3.8 on Ubuntu. Thanks for any ideas on how to solve this. Jen

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Re: non-standard glibc location
by Sandi Cimerman Sept. 29, 2022

Sept. 29, 2022

On Friday, September 8, 2017 at 3:16:12 AM UTC+2, Fetchinson . wrote: > On 9/7/17, Thomas Jollans <tj...(a)tjol.eu> wrote: > > On 2017-09-06 16:14, Fetchinson . via Python-list wrote: > >> Hi folks, > >> > >> I'm trying to install a binary package (tensorflow) which contains > >> some binary C extensions. Now my system glibc is 2.15 but the binaries > >> in the C extensions were created (apparently) with glibc 2.17. So I > >> thought no problemo I installed glibc 2.17 to a custom location, built > >> python2.7 from source (hopefully using my custom glibc) and installed > >> pip and everything else using this custom built python. But still when > >> I try to import tensorflow I get: > >> > >> ImportError: /lib64/libc.so.6: version `GLIBC_2.17' not found > >> (required by > >> /home/nogradi/fetch/custom/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so) > >> > >> So apparently it's trying to use my system glibc, not the custom one. > >> > >> How do I tell this extension to use the custom glibc? Is it even > >> possible? > > > > It's going to use the same libc as python, so first of all check which > > libc your python interpreter is actually linked to. Maybe your custom > > build didn't do quite what you wanted. > > > > ldd `which python` # or something like that > > > > Once you've convinced yourself that python has the correct libc, you > > could try building tensorflow from source rather than installing the > > binaries. > > > > Maybe something in here helps: > > https://github.com/tensorflow/tensorflow/issues/53 > Thanks a lot for all the comments, my problem was indeed that the > compiled python was still using the system glibc. The solution was to > set the environment variables > > p=/path/to/custom/glibc > export CFLAGS=-I${p}/include > export LDFLAGS="-Wl,--rpath=${p}/lib > -Wl,--dynamic-linker=${p}/lib/ld-linux-x86-64.so.2" > > And then the compiled python was using the new glibc. > > Side note 1 on tensorflow: the compiled tensorflow binary uses unicode > ucs4, so for python I had to ./configure --enable-unicode=ucs4 because > the default is ucs2 > > Side note 2 on tensorflow: it also depends on libstdc++ and my version > was too old for that as well. Instead of compiling gcc from source > (which includes libstdc++) I copied a binary libstdc++ from a newer > linux distro and it was working fine. > > And the reason, if anyone cares, I had to go through the above is that > I couldn't compile tensorflow from source. > > Thanks again, > Daniel > > > >> > >> But maybe I have an even more basic issue: how do I link python not > >> with the system glibc but with my custom glibc? > >> > >> Cheers, > >> Daniel > >> > >> > >> > > > > > > -- > > Thomas Jollans > > -- > > https://mail.python.org/mailman/listinfo/python-list > > > > > -- > Psss, psss, put it down! - http://www.cafepress.com/putitdown First of all, thank you a lot Fetchinson, it helped on my system (Centos 6) to today recompile the newest Python (3.10.7)! Of course I had foss2018 available on the system, so I "just" had to compile glibc, zlib, and openssl 1.1.1q ... but hey it was worth it! I have my environment up and running! FYI: 1. to me it helped that since I had nonstandard openssl location to edit Modules/Setup.dist as suggested here https://stackoverflow.com/questions/5937337/building-python-with-ssl-suppor… 2. to me it helped to configure with ./configure --with-libc=/tmp/glibc/lib/libc.so --prefix=/tmp/python --with-openssl=/tmp/openssl Hope this helps someone else who will try to do the same. Cheers

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Re: on implementing a toy oop-system
by Meredith Montgomery Sept. 29, 2022

Sept. 29, 2022

ram(a)zedat.fu-berlin.de (Stefan Ram) writes: [...] >>>However, to evaluate a method call such as "o.m( a, a1, ... )", >>>currying does not necessarily have to be used. One can as well >>>determine the function to be used for "m" from the type of "o" >>>and then call that function with arguments "o", "a", "a1", ... >>Was that your last approach? > > Yes, I think so. > > (There are also languages with "multi-methods", where upon > a function call "m( o, o1, ... )" the decision which function > to call depends on all the types of all the arguments.) I think Clojure is one such. I've read Part 1 of ``Clojure in Action'' by Amit Rathore, 2012, Manning, ISBN 9781935182597. I liked it.

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