I'm having some issues running the certbot-auto application on a CentOS 6 server, which has both Python 2.6 (/usr/bin/python) and 2.7 (/usr/bin/python2.7) installed.
A copy of the output from running ./certbot-auto with no arguments can be found in this paste: http://pastebin.com/g7WaZUra
The error code output is similiar to this question but my issue is almost certainly not memory related as this is a dedicated server with 32GB RAM and just a few low-traffic sites on it.
Managed to solve the issue, the development dependencies for Python 2.7 were missing. Fix by running yum install python27-devel.
Related
I have a Virtualbox VM with CentOS 5 and I'm discovering problems using yum.
I know that CentOS 5 is not supported by several years but I'm not prone to update the OS now.
In particular I am having troubles in command like:
yum update yumyum updateyum install
And the error that comes out always report some paths to python files and this string that I don't understand:
M2Crypto.SSL.SSLError: tlsv1 alert protocol version
Hope y'all got some tips or solution for this.
I am trying to run a django project on an EC2 server, however, when I run python3 manage.py runserver, it returns this error, django.core.exceptions.ImproperlyConfigured: SQLite 3.9.0 or later is required (found 3.7.17).. I then check to see what version of SQLite3 is running on my python installation on my EC2 server by running sqlite3.sqlite_version, and it returns 3.7.17. So I then try to update SQLite3 using the default AWS EC2 Amazon Linux package manager, yum, by running yum install sqlite. It then returns this, Package sqlite-3.7.17-8.amzn2.1.1.x86_64 already installed and latest version, even though it is not the latest version. How can I install the latest version of SQLite3 to fix this?
I had the same problem. Since my app is very small with little dependency, I was able to quickly switch to EC2 sever running Ubuntu. It is necessary to learn how to use Ubuntu (apt).
You can find right now in the installation:
Package: sqlite3
Version: 3.31.1-4ubuntu0.2
I have a project that uses Google Dataflow. I have been successfully using the following command (and commands like it) for months to deploy templates.
.venv/bin/python -m dataflow.registry_files.delimited_file --runner=DataflowRunner --region=us-central1 --project=myproject --staging_location=gs://mybucket-staging/staging/gr265 --template_location=gs://mybucket-code/templates/gr265 --temp_location=gs://mybucket-staging/temp/gr265 --no_use_public_ips --save_main_session --setup_file=dataflow/setup.py --projectId=myproject --datasetId=padl_staging --tableId=gr265 --configFile=gs://mybucket-code/registry/registry_files.yaml --fileType=gr265
This command continues to work on windows 10 and Debian machines in my team.
Since I upgraded to catalina (10.15.1, with python 3.7.5 and apache-beam==2.16.0 ) I get the following error:
[libprotobuf ERROR google/protobuf/descriptor_database.cc:58] File already exists in database:
[libprotobuf FATAL google/protobuf/descriptor.cc:1370] CHECK failed: GeneratedDatabase()->Add(encoded_file_descriptor, size):
libc++abi.dylib: terminating with uncaught exception of type google::protobuf::FatalException: CHECK failed: GeneratedDatabase()->Add(encoded_file_descriptor, size):
Abort trap: 6
I have done all of the following, with many reboots:
Run xcode-select --install
Run brew update-reset, brew update, brew upgrade, and brew reinstall python all to no effect (except after brew update-reset, brew doctor works again)
Run brew uninstall protobuf and brew install protobuf
Run pip3 uninstall protobuf outside of the virtual environments
Deleted and re-created my virtual environments from their requirements files.
Several bits of voodoo involving /usr/local/include that I located elsewhere on stack overflow that didn't help.
I wondered if this was just my machine, and unfortunately was able to reproduce it on the other macOS Catalina laptop in my team, but not the laptop still running macOS Mojave.
According with the Apache Beam Issue 8368 this issue is related with a pyarrow version, you have to test with pyarrow 0.15.1 beam since is the one which works on MacOS 10.15 as is mentioned in this link.
Please let us know how it works.
I just leave it here, because it is a common problem has not resolved by maintainers and I didn't found the closest convenient solution in the time.
https://github.com/protocolbuffers/protobuf/issues/1941
https://bugs.debian.org/cgi-bin/bugreport.cgi?att=1;bug=721791;filename=protobuf-2.4.1-3.1.debdiff;msg=5
The patch actually quite does not help, because in the next step the protobuf does hang in the Run function and call does not return.
The closest solution for myself was to completely avoid of any double linkage with the protobuf at any cost.
I've tried all the measures from this post and Cassandra doc.
I've tried running all the versions of Cassandra including the latest release 3.7 from tarball and Debian package, but I keep getting errors when I execute cqlsh.
Error:
Connection error: ('Unable to connect to any servers', {'127.0.0.1': TypeError('ref() does not take keyword arguments',)})
I had no problem running Cassandra before I upgraded my Linux Mint from 17.3 to 18.
I believe I installed all the necessary packages such as java 8 and python 2.7.12.
I think the problem exists in cassandra.yaml file since the default setting isn't working, but I'm not sure how to configure properly to get it running.
Any suggestions appreciated.
You are running into CASSANDRA-11850, where cqlsh breaks with Python 2.7.11+. This ticket has been marked as "Resolved" and a patch has been applied to Cassandra 3.9 which has not been released yet.
I believe I installed all the necessary packages such as java 8 and python 2.7.12.
In the interim (until 3.9 is released) you can roll back to Python 2.7.10, and cqlsh should work (not trivial). Otherwise, DataStax DevCenter should work with Cassandra 3.7.
Edit 20161020
Cassandra 3.9 was released a few weeks ago, and can now be downloaded.
refer https://issues.apache.org/jira/browse/CASSANDRA-11850
After setting environment variable
CQLSH_NO_BUNDLED=TRUE
it resolved.
I use windows 7, python 2.7.12, cassandra 3.7
Need to add following command
sudo apt install python-pip
pip install cassandra-driver
export CQLSH_NO_BUNDLED=true
This works for Ubuntu 16.04 in Amazon EC2:
sudo apt-get --no-install-recommends install python-cassandra python3-cassandra
CQLSH_NO_BUNDLED=TRUE cqlsh "$(ec2metadata --local-ipv4)"
Even if after rolling back to python 2.7.10, the issue persists. It means the python 2.7.10 is not set as the default python version.
Go to /usr/bin directory and check the different python versions available, say python2.7 corresponds to version 2.7.10 ( you can check it by running command python2.7 in your terminal and the python version will be mentioned in the first line of the Interpreter,try the same with all other python versions available in the folder to find the one which corresponds to version 2.7.10).
Now, use the following commands to make correct python version (python2.7 in my case) as default choice
update-alternatives --install /usr/bin/python python /usr/bin/python2.7
It may be possible as you have not installed cassandra-driver.
As I also faced the same problem and I solved using following such steps.
Try installing python pip then install cassandra-driver.
1.sudo apt install python-pip
2.pip install cassandra-driver
Need help with bottle, I have a clean installation of Ubuntu 11.10, i'm
trying to get bottle with the next command : sudo apt-get install python-bottle, and i get the bottle version 0.9.5-1 , that's not the last one(0.10.6-1) and does not include some features that i need.
Anybody knows why? I do not want to use easy-install or pip, help!
You'd need to upgrade your Ubuntu installation to precise (version 0.10.6) or to quantal (version 0.10.11).
Older Ubuntu releases do not get new versions of packages; python-bottle is also not part of the Ubuntu backports packages.
I strongly advise you to use a virtualenv and install the latest bottle version in there with pip. Ubuntu packages are not agile enough to follow the faster release cycles of many Python packages.