I want to use mysql form ploneformgen, but I
Can't buildout plone.
buildout log http://pastie.org/5345272.js
Getting required 'MySQL-python>=1.2.1'
required by Products.ZMySQLDA 3.1.1.
We have no distributions for MySQL-python that satisfies 'MySQL-python>=1.2.1'.
Getting distribution for 'MySQL-python>=1.2.1'.
Running easy_install:
/usr/local/Plone/Python-2.6/bin/python "-c" "from setuptools.command.easy_install import main; main()" "-mUNxd" "/usr/local/Plone/zeocluster/../buildout-cache/eggs/tmpDSODu0" "-Z" "/usr/local/Plone/buildout-cache/downloads/dist/MySQL-python-1.2.4c1.zip"
path=/usr/local/Plone/buildout-cache/eggs/distribute-0.6.21-py2.6.egg
Processing MySQL-python-1.2.4c1.zip
Running MySQL-python-1.2.4c1/setup.py -q bdist_egg --dist-dir /tmp/easy_install-gFbWLf/MySQL-python-1.2.4c1/egg-dist-tmp-16g1TE
The required version of distribute (>=0.6.28) is not available,
and can't be installed while this script is running. Please
install a more recent version first, using
'easy_install -U distribute'.
(Currently using distribute 0.6.19 (/usr/local/Plone/Python-2.6/lib/python2.6/site-packages/distribute-0.6.19-py2.6.egg))
error: Setup script exited with 2
An error occured when trying to install MySQL-python 1.2.4c1. Look above this message for any errors that were output by easy_install.
While:
Installing client1.
Getting distribution for 'MySQL-python>=1.2.1'.
Error: Couldn't install: MySQL-python 1.2.4c1
*************** PICKED VERSIONS ****************
[versions]
Products.PloneFormGen = 1.7.1
Products.ZMySQLDA = 3.1.1
collective.classifieds = 1.6
plone.app.ldap = 1.2.8
quintagroup.dropdownmenu = 1.2.5
quintagroup.pfg.captcha = 1.0.5
zettwerk.ui = 1.1.1
buildout conf http://pastie.org/5345300
some links:
http://blog.mysqlboy.com/2010/08/installing-mysqldb-python-module.html
http://plone.293351.n2.nabble.com/Plone-amp-MySQL-No-quot-Z-MYSQL-Database-Connection-quot-from-ZMI-td5487160.html
It appears the MySQLdb egg requires a newer version of distribute:
The required version of distribute (>=0.6.28) is not available,
and
(Currently using distribute 0.6.19 (/usr/local/Plone/Python-2.6/lib/python2.6/site-packages/distribute-0.6.19-py2.6.egg))
Upgrade your distribute egg first; if you are using the unified installer, for example, versions.cfg pins the version. If so, edit versions.cfg to correct the version number there:
[versions]
...
# Buildout infrastructure
...
distribute = 0.6.28
While you have a perfectly good answer for the specific problem, I highly recommend forgetting about ZMySQLDA and use SQLAlchemyDA which gives you access to any database supported by SQLAlchemy (I've used all of MySQL, PostGreSQL, Oracle, SQLServer) with a single product, and is better supported.
Related
Having an issue running airflow on my M1 Mac. Keeps erroring out with error in Flask-OpenID setup command: use_2to3 is invalid. I have setuptools < 58 and still having issues.
ERROR: Could not find a version that satisfies the requirement flask-openid==1.2.5 (from versions: 0.9, 0.9.1, 1.0, 1.0.1, 1.1, 1.1.1, 1.2, 1.2.1, 1.2.2, 1.2.3, 1.2.4, 1.2.5, 1.3.0)
ERROR: No matching distribution found for flask-openid==1.2.5
Yes. It's been fixed in flask_openid 1.2.6 (It's not a problem with Airflow but with FlaskOpenID).
Looks like for some reason your setuptools is not what you think it is. See:
https://github.com/pallets-eco/flask-openid/issues/59
You have not explained a crucial things - how you are installing airflow, neither which version of Airflow you try to install - which does not help in trying to help you unfortunately, so I have to make some guesses. Here is what you can do if you cannot - for any reason - downgrade to setuptools < 0.58.
If you are using Airlfow 2 and using constraints (as you should - this is the only supported way https://airflow.apache.org/docs/apache-airflow/stable/installation/installing-from-pypi.html) for some older version of Airflow, then possibly flask-openid is 1.2.5 in those old constraint versions. Please check it and if you REALLY want to stay with an older version, then you can download the constraint file locally, modify flask-openid version to 1.2.6 and point to the file instead of the github URL as you should do normally (If you don't use constraints - start using them immediately).
However, better option than installing an old version of Airflow, will be to update to the latest version of Airflow (currently 2.2.2 but we are about to start voting on 2.2.3), where this problem is for sure fixed (also in few other versions). Airflow folows SemVer so you should be generally safe to migrate to 2.2.2 if you've used an earlier version of Airflow 2.
If you are trying to install Airflow 1.10.* - then don't do it. Move Airflow 2 immediately. Airflow 1.10 has reached end of life in June 2021 and it's almost half a year as it did not receive any fixes - it won't receive any fixes for the Flask OpenID problem, so you are pretty much on your own here.
Also you make yourself vulnerable to unpatched security issues (Airlfow 1.10 stopped receiving also critical security fixes as of June 2021).
I need execute Data Fusion pipelines from Composer, using de operatos for this:
from airflow.providers.google.cloud.operators.datafusion import (
CloudDataFusionCreateInstanceOperator,
CloudDataFusionCreatePipelineOperator,
CloudDataFusionDeleteInstanceOperator,
CloudDataFusionDeletePipelineOperator,
CloudDataFusionGetInstanceOperator,
CloudDataFusionListPipelinesOperator,
CloudDataFusionRestartInstanceOperator,
CloudDataFusionStartPipelineOperator,
CloudDataFusionStopPipelineOperator,
CloudDataFusionUpdateInstanceOperator,
)
The issue I have is about modulo "apache-airflow-backport-providers-google", with the support of this links i knew what I need to use this modulo:
reference to install the modulo in airflow instance (answered by #Gonzalo Pérez Fernández): https://airflow.apache.org/docs/apache-airflow-providers-google/stable/operators/cloud/datafusion.html
when i tried to install python dependency on Composer like PyPi Package i get this error:
UPDATE operation on this environment failed 7 minutes ago with the following error message:
Failed to install PyPI packages.
apache-airflow-providers-google 5.0.0 has requirement google-ads>=12.0.0, but you have google-ads 7.0.0. Check the Cloud Build log at https://console.cloud.google.com/cloud-build/builds/a2ecf37a-4c47-4770-9489-6fb65e87d82f?project=341768372632 for details. For detailed instructions see https://cloud.google.com/composer/docs/troubleshooting-package-installation
the log deail is:
apache-airflow-providers-google 5.0.0 has requirement google-ads>=12.0.0, but you have google-ads 7.0.0.
apache-airflow-backport-providers-google 2021.3.3 has requirement apache-airflow~=1.10, but you have apache-airflow 2.1.2+composer.
The command '/bin/sh -c bash installer.sh $COMPOSER_PYTHON_VERSION fail' returned a non-zero code: 1
ERROR
ERROR: build step 0 "gcr.io/cloud-builders/docker" failed: step exited with non-zero status: 1
is there any way to use de module "apache-airflow-backport-providers-google" without depedency issues on composer instance?, or What would be the best way to use data fusion operators no need to change or parse package versions in python?.
Composer Image version used:
composer-1.17.0-airflow-2.1.2
Thanks.
There is no need to install apache-airflow-backport-providers-google in Airflow 2.0+. This package actually backports Airflow 2 operators into Airflow 1.10.*. In addition, in Composer version composer-1.17.0-airflow-2.1.2 the apache-airflow-providers-google==5.0.0 package is already installed according to the documentation. You should be able to import the Data Fusion operators with the code snippet you posted as is.
However, if this is not the case, you should probably handle the conflict shown in the logs when trying to reinstall apache-airflow-providers-google==5.0.0:
apache-airflow-providers-google 5.0.0 has requirement google-ads>=12.0.0, but you have google-ads 7.0.0.
You can add the requirement for google-ads=12.0.0 in your PyPi dependencies and see if it works.
On Azure ML Workspace Notebook, I'm trying to get my workspace instance, as seen at
https://learn.microsoft.com/en-us/azure/machine-learning/tutorial-auto-train-models#configure-workspace.
I have a config file and I am running the notebook in an Azure compute instance.
I tried to execute Workspace.from_config().
As a result, I'm getting the 'MSIAuthentication' object has no attribute 'get_token' error.
I tried to submit both MsiAuthentication and InteractiveLoginAuthentication, as suggested in
https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/manage-azureml-service/authentication-in-azureml/authentication-in-azureml.ipynb.
There are 2 solutions I've found:
1.- Use the kernel "Python 3.6 - AzureML"
2.- pip install azureml-core --upgrade
This will upgrade
azureml-core to 1.32.0
But will downgrade:
azure-mgmt-resource to 13.0.0 (was 18.0.0)
azure-mgmt-storage down to 11.2.0 (was 18.0.0)
urllib3 to 1.26.5 (was 1.26.6)
This upgrade / downgrade allows the same package versions as in the python 3.6 anaconda install
I'm having issues with Azure Machine Learning SDK for R: "module 'azureml' has no attribute 'core'"...
For reasons that aren't my own, I have to use azureml to apply machine learning (my own stuff, written in R) to data from our data warehouse that is put in the blob storage. The modelled output should be put back into the blob storage so it can be accessed from the data warehouse.
I've written the code in R on my local machine (stored in a git repo). Preferably, I'd find some method to pull my code from git into a pipeline in the azureml environment so that it can be directly run whenever new data is available in the blob storage.
I've embarked on a tutorial-spree and found this seemingly relevant walkthrough: Train and deploy your first model with Azure ML (and this one).
But... after trying all I could think of, I'm stuck on the first steps. After installing all (or at least.. that's what I think) packages, modules, apps etc, and running the following code in RStudio:
library(azuremlsdk)
existing_ws <- get_workspace(name = name,
subscription_id = subscription_id,
resource_group)
I run into an error that I haven't been able to fix:
AttributeError: module 'azureml' has no attribute 'core'
It seems that the azuerml is supposed to have an attribute "core", but when looking at it more closely, there is indeed no such attribute.
The function "get_workspace()" is trying to access: "azureml$core$Workspace$get".
I found that "azuerML$Workspace" does exist, but then I can't figure out how to make that work.
Can anyone explain to me why I'm encountering this error?
Does anyone know of a better tutorial on how to connect my R code the azureml's cloud service?
Any pointers in the right direction are much appreciated!
EDITS - still not solved:
After advice from others, I double, triple and quadruple checked the installation.
I updated R and I'm now running:
R.version
platform x86_64-w64-mingw32
arch x86_64
os mingw32
system x86_64, mingw32
status
major 3
minor 6.2
year 2019
month 12
day 12
svn rev 77560
language R
version.string R version 3.6.2 (2019-12-12)
nickname Dark and Stormy Night
I installed Conda with Python 3.6.10.
I installed the azuremlsdk R package (I tried both provided options).
I then realized that there are some inconsistencies with the versions of the azure-modules, so I also tried installing it with the keyword 'multi-arch':
remotes::install_cran('azuremlsdk', repos = 'http://cran.us.r-project.org', INSTALL_opts=c("--no-multiarch"))
Then, I installed the azureml python sdk.
I had a look at all the versions again (using python -m pip freeze):
azure-common==1.1.24
azure-graphrbac==0.61.1
azure-mgmt-authorization==0.60.0
azure-mgmt-containerregistry==2.8.0
azure-mgmt-keyvault==2.0.0
azure-mgmt-resource==7.0.0
azure-mgmt-storage==7.1.0
azureml==0.2.7
azureml-automl-core==1.0.83.1
azureml-core==1.0.69
azureml-dataprep==1.1.36
azureml-dataprep-native==13.2.0
azureml-pipeline==1.0.69
azureml-pipeline-core==1.0.69
azureml-pipeline-steps==1.0.69
azureml-sdk==1.0.69
azureml-telemetry==1.0.69
azureml-train==1.0.69
azureml-train-automl-client==1.0.83
azureml-train-core==1.0.69
azureml-train-restclients-hyperdrive==1.0.69
As I was surprised to see all the 1.0.69 versions, instead of the 1.0.83 versions, I re-installed the azureml python sdk using:
azuremlsdk::install_azureml(version = "1.0.83")
This worked, in the sense that indeed all versions are now 1.0.83:
azure-common==1.1.24
azure-graphrbac==0.61.1
azure-mgmt-authorization==0.60.0
azure-mgmt-containerregistry==2.8.0
azure-mgmt-keyvault==2.0.0
azure-mgmt-resource==7.0.0
azure-mgmt-storage==7.1.0
azureml==0.2.7
azureml-automl-core==1.0.83.1
azureml-core==1.0.83
azureml-dataprep==1.1.36
azureml-dataprep-native==13.2.0
azureml-pipeline==1.0.83
azureml-pipeline-core==1.0.83
azureml-pipeline-steps==1.0.83
azureml-sdk==1.0.83
azureml-telemetry==1.0.83
azureml-train==1.0.83
azureml-train-automl-client==1.0.83
azureml-train-core==1.0.83
azureml-train-restclients-hyperdrive==1.0.83
But still... I get the error with the missing core. I get it both when running:
library(azuremlsdk)
get_current_run()
and also when running:
library(azuremlsdk)
existing_ws <- get_workspace(name = name,
subscription_id = subscription_id,
resource_group)
Note that the first time running this code after starting up RStudio, I get the error:
Error in py_get_attr_impl(x, name, silent) :
AttributeError: module 'azureml' has no attribute '_base_sdk_common'
And every time after that I get this error:
Error in py_get_attr_impl(x, name, silent) :
AttributeError: module 'azureml' has no attribute 'core'
Any help would be much appreciated!
This issue was introduced by the latest reticulate 1.14 release, in which reticulate would create a default r-reticulate conda environment. Since Azure ML was installing the python SDK in an environment named r-azureml, the r-reticulate environment used by reticulate was missing the python SDK. A fix for this issue was addressed in a PR and has been merged into master. Please install from GitHub for now if you have reticulate version 1.14 and are running into this issue. We will be releasing an update to CRAN shortly.
I seemed to have fixed the issue by specifically installing the python package azureml AND azureml.core:
python -m pip install azureml
and then...
python -m pip install azureml.core
I did this for the Conda version that was called by R (r-reticulate). It's a bit odd to not be able to use the Conda environment 'r-azureml' without R switching back to 'r-reticulate', but ah well... at least I don't get my 'azureml' has no attribute 'core' anymore.
I installed the latest version of Virtuoso using yum on CentOs. I was able to successfully do that first time. However,when I restarted the virtuoso server after uploading a dataset/CSV file, I am not seeing the 'conductor tab' in the webUI.
I thought something went wrong - and tried to do a clean install. But I have somehow managed to loose conductor completely this time. Below is the log snippet of virtuoso-t.
10:41:00 INFO: PL LOG: Installing Virtuoso Conductor version 1.00.8727 (DAV)
10:41:00 INFO: Checkpoint started
10:41:00 INFO: Checkpoint finished, log reused
10:41:00 INFO: PL LOG: VAD_INSTALL: Please update server version (FATAL)
10:41:00 INFO: PL LOG: Errors where detected during installation of "Virtuoso Conductor".
You report you "installed the latest version of Virtuoso using yum" -- but what version did you actually get? We provide a CentOS-specific guide which may now be outdated if someone has produced a yum package -- but that package may also be outdated.
Please check the version you have actually installed (output of virtuoso-t -? gives the best version string), and be sure it is at least 6.1.8 (if Virtuoso v6) or 7.2.2 (if Virtuoso v7). If not, I would suggest a clean rebuild/reinstall, following our instructions, based on the latest source from GitHub.
For future, questions specifically regarding Virtuoso are often best raised on the public Virtuoso Users mailing list, the public OpenLink Support Forums, or through a confidential Support Case. ObDisclaimer: I work for OpenLink Software, producer of Virtuoso.