By default the Cinnamon/Gnome/Mate desktop environment loads its own display
configuration from the file ~/.config/monitors.xml instead of using the
settings defined in /etc/X11/xorg.conf. This can be a little bit annoying if
you are using the nvidia-settings program to configure your displays (which
will use xorg.conf), since anything entered there will be overridden by
monitors.xml every reboot.
By doing the following changes we will disable the "Display Manager" in
You can use ssacli (smart storage administrator command line interface) tool to manage any of supported HP Smart Array Controllers in your Proxmox host without need to reboot your server to access Smart Storage Administrator in BIOS. That means no host downtime when managing your storage.
CLI is not as convenient as GUI interface provided by BIOS or desktop utilities, but still allows you to fully manage your controller, physical disks and logical drives on the fly with no Proxmox host downtime.
ssacli replaces older hpssacli, but shares the same syntax and adds support for newer servers and controllers.
| #!/bin/bash | |
| # README You probablyl don't need this script anymore. Please read the comments below to catch up. | |
| ## Description | |
| # Lenovo Carbon X1 Gen 7 - Audio and microphone fix - kernel 5.3+ required. | |
| # The script has only been tested for Arch and OpenSuse, | |
| # Original thread: https://forums.lenovo.com/t5/Ubuntu/Guide-X1-Carbon-7th-Generation-Ubuntu-compatability/td-p/4489823 | |
| # Prereq: Install Linux 5.3 or newer |
| # Use Pandas & SQLAlchemy. | |
| # https://stackoverflow.com/questions/23103962/how-to-write-dataframe-to-postgres-table | |
| # Note this will create a new table; see the 'faster option' at the above link for a method using 'copy' to an existing table. | |
| # However, 'copy' cannot do an upsert; that requires inserting to a temp table, then upserting form temp table to destination table. | |
| # This will lack PKs and FKs and indexes, of course, so if used naively you may see data duplication. | |
| # Also the df.to_sql command can do an append (but not upsert), using the if_exists param: | |
| # https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_sql.html |
Strongly inspired by https://gist.github.com/heymonkeyriot/9a2f429caff5c091d5429666fa080403.
On Ubuntu :
sudo apt install python3 python3-pip
Andy Thomason is a Senior Programmer at Genomics PLC. He has been witing graphics systems, games and compilers since the '70s and specialises in code performance.
| #cloud-config | |
| # Set the hostname for this machine (takes precedence over hostname assigned by DHCP lease). | |
| hostname: myhost | |
| # Authorize SSH keys for the `rancher` sudoer user | |
| ssh_authorized_keys: | |
| - ssh-rsa AAA...ZZZ example1@rancher | |
UPDATE: I have baked the ideas in this file inside a Python CLI tool called pyds-cli. Please find it here: https://github.com/ericmjl/pyds-cli
Having done a number of data projects over the years, and having seen a number of them up on GitHub, I've come to see that there's a wide range in terms of how "readable" a project is. I'd like to share some practices that I have come to adopt in my projects, which I hope will bring some organization to your projects.
Disclaimer: I'm hoping nobody takes this to be "the definitive guide" to organizing a data project; rather, I hope you, the reader, find useful tips that you can adapt to your own projects.
Disclaimer 2: What I’m writing below is primarily geared towards Python language users. Some ideas may be transferable to other languages; others may not be so. Please feel free to remix whatever you see here!
| #!/bin/bash | |
| ### steps #### | |
| # Verify the system has a cuda-capable gpu | |
| # Download and install the nvidia cuda toolkit and cudnn | |
| # Setup environmental variables | |
| # Verify the installation | |
| ### | |
| ### to verify your gpu is cuda enable check |
| import pandas as pd | |
| import pandas.io.sql as sqlio | |
| import psycopg2 | |
| conn = psycopg2.connect("host='{}' port={} dbname='{}' user={} password={}".format(host, port, dbname, username, pwd)) | |
| sql = "select count(*) from table;" | |
| dat = sqlio.read_sql_query(sql, conn) | |
| conn = None |
