Windows (10) doesn’t allow the same resource twice
So, the NAS* I use for years is separated into different partitions. Some for general access and things and one for music, which has a special user, which owns just read-only privileges.
Linux: no problem: mount as many shares with Gigolo and you are done.
Windows: use that 90s-style network-mount of the ‘explorer’ and add share by resource and credentials.
“\\ds213\musik” .. Works, but is awkward and not comfortable.
then you want to mount the second share with different credentials and you get “Can’t mount the same share** with different credentials”.
Workaround:
mount once by resource-name and once by ip: “\\192.168.178.178\musik”
Another approach via the hosts-file.
* DS213 from Synology: 2 bay; now running 24/7 for 5 (?) years; upgraded inbetween from 2 TByte drives to 4 TB with complete replication
** is actually “different shares at the same host”, but who am I with my limited knowledge?
RamBLE and the (german) Covid19 tracker
Quicker posts, less retardation! One of the goals for 2021 was to 0. write more often, 1. faster after ‘doing’ and 2. therefore also covering more things which were ‘touched’
There’s still a pile of topics left from 2020 xD
In Novembre a colleague and me talked about one of his acquantainces which wrote an iOS-app, which can show how many “Corona Warn App”-users are nearby. I was puzzling over this and also wondered if really some special app or some bluetooth-receiver-tinkering is needed. I still own that one BT receiver for the Raspberry.
First: So, quick check for BT sniffers in the playstore showed RamBLE.
Second: 5 min of googling found the UUID used for the exposure notification: “fd6f”.
So, let’s combine and see what is shown for an location I traverse often:
Quintessence: check the market before developing something 😉
Project Euler – mathematical riddles which require some programming skills
Took me a while to write about this, but I really love Project Euler. The page is a collection of math challenges, which require some programming (I saw just one which could have been computed by a closed formula without any help). The first ten are quite easy to solve and are more commonly known math problems. Prime numbers and combinatorics play a strong role. But then the difficulty rises quite quickly. Usually it takes me one to two hours to write a Python solution for one. If I would – like I should – write unit-tests for each single method and not for a few selected one, then I guess 50% more.
It’s great: each problem is a closed, separate problem, which requires some algorithmic thinking and – of course – some proper implementation. If you chose the wrong path time or space complexity will kill your ambitions quite quickly. But proper solutions are computed most of the time in less than a minute.
Most of the time I rely on basic python structures and common libraries. But I’ve also given NumPy, itertools, etc. a try. Speeds up the process quite a bit.
My next goal is to fix problem 47, because then I’ve handed in solutions for all of the first fifty problems.
The highest challenge (with also the highest difficulty level (for me) so far) was problem 668. Due to a really big (80 GiByte!) boolean array the computer had a hard time swapping memory. So it took almost 36 hours to finish. By the way: less than 900 people worldwide have solved this issue #tinyflakeofpride
Of course, several geniuses have dedicated pages to optimal solution strategies. Which is a nice idea. But I avoid them. Most of the times stepping back, thinking without a display about the problem and if the chosen approach was a good one, is more helpful. A solution by cheating is nothing which renders any reward.
micro:bit v2 arrived :)
Today (finally) my micro:bit v2 arrived. Had to unwrap it immediately after dinner and play around with the speech synthesis👌🏻 Some lines of microPython and the things got heated.
If you’re not creating anything nowadays, then it’s your own fault 🐒
Fablab Freising
I was always interested in continuing to tinker with 3d printers and the lasercutter. So I’ve checked which local labs are publicly available, because space at home is valuable and we have four smol ones which would like to attack any technical device ;3 Some years ago I did some prints and cuts in the FabLab Kiel, but never put any photos or reports here #sad.
The Fablab Freising looks great, very cool and friendly guys! And the fee to be a club member is also reasonable.
Read more…
digiKam workflow for proper renaming
- Import the directories with the images. Takes usually several minutes for gigabytes of data.
- Press F2 for renaming. Use as scheme:
[date:yyyyMMdd-hhmmss]{unique:3}
Self-explaining and with a unique three digit suffix in case two identical filenames would appear. → “20200216-141529_001.JPG”
Dell Precision 3351: performance spikes on GPU0 for dwm.exe/csrss.exe (win10)
Starting point: so, I have a brand-new laptop with a fresh Win10 and the apps lag while I move windows around the desktop. Great!
The first recommendations were already checked: Win is up to date; graphics driver for the integrated Intel GPU and for the Nvidia one as well. No, I won’t roll back the system and no, a “clean start” won’t fix this either.
Of course, I was also suspicious if the virusscanner or the dockingstation-three-monitor-setup is the issue. But come one: that are just 6 mio pixel and the hardware is top notch.
Mitigation:
0. open the “Dell Power Manager” and set the “Temperaturverwaltung” to “Optimiert” (before “Ruhig”)
1. configure via the Nvidia that their GPU shall be the preferred one for apps: “Grundprofil” = “Hochleistungs-GPU”; check as well if any app has preset the integrated GPU (change this!)
2. disable automatic scaling of applications: System > Display. Under the scaling drop-down, select the Advanced scaling settings link. Disable “fix blurry ..”
3. change the display settings to Performance: run “sysdm.cpl” and then “Advanced (Erweitert)” > “Performance (Leistung)” and then put everything to performance (radio button) and just enable “smooth font rendering”
4. change the graphic settings to “High Performance” for all “classic” and “universal” apps:
Problem is, that the dwm.exe and the csrss.exe use GPU0 no matter what you configure.
Note:
The idea to disable the integrated Intel GPU via UEFI/BIOS is not possible, because the Nvidia GPU is not a full replacement card, but relies on the iGPU ..
Outlook: prevent that meeting-requests get auto-deleted after processing
Options > Mail > “Send messages”-block > uncheck “Delete meeting requests and ..”.
For the German version:
simple webscraper for last.fm with BeautifulSoup
tl;dr:
Simple webscraper with Python and BeautifulSoup for one user’s favorite tracks (‘loved songs’) at last.fm.
Repository: github
full text:
Looks like last.fm is shutting down its services (one feature at at time, lol). They started this process more or less ten years ago.
I’ve realized that I would miss my curated list of favorite tracks and I am also very bad at remembering, so … let’s automate the process of grabbing that information from their public page. I know, they offer a REST API, but I wanted to use once BS4.
Since I had somehow two free hours fourteen days ago, I went full-speed to some tutorials, played with the get-requests and how to parse. And then spent the last minutes parsing the received “artist+track”-string into something usable. Alltogether four hours were spent and I am amazed by the result. Of course, by leveraging three quite powerful libraries (beautifulsoup4, requests, lxml) and skipping TDD (;) I’ve reached the goal quite fast. And since the script works (my 1500 loved songs are scraped in less than 60 seconds), I will also not spend additional effort to make it “pretty”.
“[Full Day Workshop] Kubeflow + BERT + GPU + TensorFlow + Keras + SageMaker”
I’ve just spent the last eight hours attending a workshop about #SageMaker, #AutoPilot, #BERT, #Athena, #TensorFlow, #Spark, [..] and I am feeling a bit light-headed.
Of course, the talk and guidance given by @AntjeBarth and @ChrisFregly was really well prepared, but if you’re just a ML-beginner (like me) and if then over 9000 of new technologies drop, you have to work hard to follow the fast paced event.
Of course, I started my ML-journey in the summer of 2019, but it was more focussed on image-processing, not #NLP. I worked before with #Python, #Jupyter notebooks, TensorFlow and #Keras, but that whole SageMaker-thing was new to me.
And I see the potential: instead of running the stuff locally, you prepare, prototype and run your ML-app inside Amazon’s infrastructure. And that AutoPilot, which helps to quickstart the prototyping by trying several preprocessing-steps and models for you on your data, looks promising. Will definitely give it a second look.
Notes can be found at: https://github.com/marcelpetrick/KubeFlow_BERT_GPU_TensorFlow_Keras_SageMaker_Workshop (need lots of polishing, as always)
Crazy times we live in! And I am thankful for this block of time on a weekend 🙏