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https://blog.smartere.dk/category/planets/planet-ubuntu-dk-planets/ | blog.smartere » Planet Ubuntu-DK blog.smartere // Ramblings of Mads Chr. Olesen jan 12 Floppy Disks: the best TV remote for kids Posted on mandag, januar 12, 2026 in Hal9k , Planet Ubuntu-DK , Planets Modern TVs are very poorly suited for kids. They require using complicated remotes or mobile phones, and navigating apps that continually try to lure you into watching something else than you intended to. The usual scenario ends up with the kid feeling disempowered and asking an adult to put something on. That something ends up on auto-play because then the adult is free to do other things and the kid ends up stranded powerless and comatose in front of the TV. Instead I wanted to build something for my 3-year old son that he could understand and use independently. It should empower him to make his own choices. It should be physical and tangible, i.e. it should be something he could touch and feel. It should also have some illusion that the actual media content was stored physically and not un-understandably in “the cloud”, meaning it should e.g. be destroyable — if you break the media there should be consequences. And there should be no auto-play: interact once and get one video. Floppy disks are awesome! And then I remembered the sound of a floppy disk. The mechanical click as you insert it, the whirr of the disk spinning, and the sound of the read-head moving. Floppy disks are the best storage media ever invented! Why else would the “save-icon” still be a floppy disk? Who hasn’t turned in a paper on a broken floppy disk, with the excuse ready that the floppy must have broken when the teacher asks a few days later? But kids these days have never used nor even seen a floppy disk, and I believe they deserve this experience! Building on the experience from the Big Red Fantus-Button , I already had a framework for controlling a Chromecast, and because of the netcat | bash shenanigans it was easily extendable. My first idea for datastorage was to use the shell of a floppy disk and floppy drive, and put in an RFID tag; this has been done a couple of times on the internet, such as RFIDisk or this RaspberryPi based RFID reader or this video covering how to embed an RFID tag in a floppy disk . But getting the floppy disk apart to put in an RFID tag and getting it back together was kinda wonky. When working on the project in Hal9k someone remarked: “Datastorage? The floppy disk can store data!”, and a quick prototype later this worked really, really , well. Formatting the disk and storing a single small file, “autoexec.sh”, means that all the data ends up in track 0 and is read more or less immediately. It also has the benefit that everything can be checked and edited with a USB floppy disk drive; and the major benefit that all the sounds are completely authentic: click, whirrr, brrr brrr. Autorun for floppy disks is not really a thing. The next problem to tackle was how to detect that a disk is inserted. The concept of AutoRun from Windows 95 was a beauty: insert a CD-ROM and it would automatically start whatever was on the media. Great for convenience, quite questionably for security. While in theory floppy disks are supported for AutoRun , it turns out that floppy drives basically don’t know if a disk is inserted until the operating system tries to access it! There is a pin 34 “Disk Change” that is supposed to give this information , but this is basically a lie. None of the drives in my possession had that pin connected to anything, and the internet mostly concurs. In the end I slightly modified the drive and added a simple rolling switch, that would engage when a disk was inserted. A floppy disk walks into a drive; the microcontroller says “hello!” The next challenge was to read the data on a microcontroller. Helpfully, there is the Arduino FDC Floppy library by dhansel, which I must say is most excellent. Overall, this meant that the part of the project that involved reading a file from the floppy disk FAT filesystem was basically the easiest part of all! A combined ATMega + ESP8266 UNO-like board. Not really recommended, but can be made to work. However, the Arduino FDC Floppy library is only compatible with the AVR-based Arduinos, not the ESP-based ones, because it needs to control the timing very precisely and therefore uses a healthy amount of inline assembler. This meant that I would need one AVR-based Arduino to control the floppy disk, but another ESP-based one to do the WiFi communication. Such combined boards do exist, and I ended up using such a board, but I’m not sure I would recommend it: the usage is really finagly, as you need to set the jumpers differently for programming the ATmega, or programming the ESP, or connecting the two boards serial ports together. A remote should be battery-powered A remote control should be portable, and this means battery-powered. Driving a floppy disk of of lithium batteries was interesting. There is a large spike in current draw when the disk needs to spin up of several amperes, while the power draw afterwards is more modest, a couple of hundred milliamperes. I wanted the batteries to be 18650s, because I have those in abundance. This meant a battery voltage of 3.7V nominally, up to 4.2V for a fully charged battery; 5V is needed to spin the floppy around, so a boost DC-DC converter was needed. I used an off the shelf XL6009 step-up converter board. At this point a lot of head-scratching occurred: that initial spin-up power draw would cause the microcontroller to reset. In the end a 1000uF capacitor at the microcontroller side seemed to help but not eliminate the problem. One crucial finding was that the ground side of the interface cable should absolutely not be connected to any grounds on the microcontroller side. I was using a relatively simple logic-level MOSFET, the IRLZ34N , to turn off the drive by disconnecting the ground side. If any ground is connected, the disk won’t turn off. But also: if any logic pin was being pulled to ground by the ATmega, that would also provide a path to ground. But since the ATmega cannot sink that much current this would lead to spurious resets! Obvious after the fact, but this took quite some headscratching. Setting all the logic pins to input, and thus high impedance , finally fixed the stability issues. After fixing the stability, the next challenge was how to make both of the microcontrollers sleep. Because the ATmega sleep modes are quite a lot easier to deal with, and because the initial trigger would be the floppy inserting, I decided to make the ATmega in charge overall. Then the ESP has a very simple function: when awoken, read serial in, when a newline is found then send off that complete line via WiFi, and after 30 seconds signal to the ATmega that we’re sleeping, and go back to sleep. The overall flow for the ATmega is then: A disk is inserted, this triggers a interrupt on the ATmega that wakes up. The ATmega resets the ESP, waking it from deep sleep. The ATmega sends a “diskin” message over serial to the ESP; the ESP transmits this over WiFi when available. The ATmega turns on the drive itself, and reads the disk contents, and just sends it over serial to the ESP. Spin down the disk, go to sleep. When the disk is ejected, send a “diskout” message over serial, resetting the ESP if needed. Go back to 1. The box itself is just lasercut from MDF-board. For full details see the FloppyDiskCast Git repository . Server-side handlers Responding to those commands is still the netcat | bash from the Big Red Fantus-Button , which was simply extended with a few more commands and capabilities. A few different disks to chose from, with custom printed labels. diskin always sends a “play” command to the Chromecast. diskout always sends a “pause” command to the Chromecast. Other commands like dad-music are handled in one of two ways: Play a random video from a set, if a video from that set is not already playing : e.g. dad-music will randomly play one of dad’s music tracks – gotta influence the youth! Play the next video from a list, if a video from the list is not already playing : e.g. fantus-maskinerne will play the next episode, and only the next episode. Common for both is that they should be idempotent actions, and the diskin shortcut will make the media resume without having to wait for the disk contents itself to be read and processed. This means that the “play/pause” disk just contains an empty file to work. Questionable idea meets real-world 3 year old user The little guy quickly caught on to the idea! Much fun was had just pausing and resuming music and his Fantus TV shows. He explored and prodded, and some disks were harmed in the process. One problem that I did solve was that the read head stayed on track 0 after having read everything: this means that when the remote with disk inside it is tumbled around, the disk gets damaged at track 0. To compensate for this, I move the head to track 20 after reading has finished: any damage is then done there, where we don’t store any data. As a bonus it also plays a little more mechanic melody. Comments (2) | maj 25 Ford 3000 Tractor Instrument Voltage Stabilizer – Mechanical PWM! Posted on torsdag, maj 25, 2017 in Hal9k , Planet Ubuntu-DK , Planets Some time ago we bought a nice used Ford 3000 tractor (3 cylinder diesel, Chief frontloader). It needed some work, and one of the items was a new wiring harness. After replacing all the wiring everything seemed to work fine, until one day all the instruments just died; this being a mechanical beast everything else kept working. After quite some investigation, I found out that the instrument fuse (the only fuse in the entire system) had blown. Replacing it just blew it again, so something was clearly wrong. This lead to taking out the so-called “instrument voltage stabilizer”, and disassembling it. Apparently I had connected it in such a way that the arm had raised itself, and was now short-circuiting to the case. I had already ordered a replacement, but only got what was essentially a very expensive connection: So, what was the mechanism actually doing, and is it essential? After some headscratching at Hal9k the conclusion was that it was essentially a mechanical PWM, with something like this diagram When the switch is touching the terminal current is flowing from the battery (B) to the instruments (I), but also to ground (E) through the resistor wrapped around the switch arm, causing the metal in the switch to heat up and lift. This breaks the connection, whereafter the switch cools down, and at some point makes contact again. Beautifully simple mechanism! Bending the arm back into position essentially fixed the device, and gave this waveform I have seen the function described online as “pulsating DC”, which is actually quite accurate. So, I re-assembled the stabilizer with some sealant, inserted in the instrument cluster of the tractor, and it has worked perfectly ever since. The only question is why it is done this way, if just giving a constant DC voltage from the battery also seems to work? I haven’t looked into it further, but my best guess is that the instruments are using coils to move the dials slowly, and that the PWM will heat up the coils less. In conclusion: If your voltage “stabilizer” is broken, you can probably do without it, or quite easily repair it. For reference, here are the resistance readings between B-E, and I-E: Comment (1) | jun 17 Roomba 500-series Easy Scheduling using an Arduino Posted on onsdag, juni 17, 2015 in Hal9k , Planet Ubuntu-DK , Planets I have a iRobot Roomba 500-series vacuum cleaner robot, but without any remote, or command center or anything; alas, I have to push a button everytime I want the cleaning revolution to start 🙁 But no more! It turns out the Roomba can be programmed, quite easily, to schedule automatically, and all you need is: 1 Arduino 2 wires The Roomba actually supports a serial protocol, the iRobot Roomba 500 Open Interface Specification , that allows remote control, driving, sensoring, and scheduling . Finding the serial port Remove the plastic cover. It is easiest to remove the vacuum bin, and carefully pry it off with a screwdriver. There should be a 7-pin plug, on the right side. It has the following pinout: Roomba serial pinout Program the Arduino Use this sketch (download: roombaschedule.ino ): /* Set a schedule on an iRobot Roomba 500 series, using just an Arduino. Mads Chr. Olesen, 2015. */ const byte currentDay = 3; // 0: Sunday, 1: Monday, 2: Tuesday, 3: Wednesday, 4: Thursday, 5: Friday, 6: Saturday const byte currentHour = 2; const byte currentMinute = 58; // Schedule const byte SUNDAY = 0x01, MONDAY = 0x02, TUESDAY = 0x04, WEDNESDAY = 0x08, THURSDAY = 0x10, FRIDAY = 0x20, SATURDAY = 0x40; const byte daystorun = SUNDAY | MONDAY | WEDNESDAY | FRIDAY; const byte times[14] = { 3, 0, // Sunday time 3, 0, // Monday time 3, 0, // Tuesday time 3, 0, // Wednesday time 3, 0, // Thursday time 3, 0, // Friday time 3, 0, // Saturday time }; const int ledPin = 13; void setup() { Serial.begin(115200); pinMode(ledPin, OUTPUT); digitalWrite(ledPin, 0); Serial.write(128); //Start delay(1000); Serial.write(131); //Safe mode, turns off Roomba light delay(1000); Serial.write(128); //Start, back to passive mode delay(500); //Set day time Serial.write(168); Serial.write(currentDay); Serial.write(currentHour); Serial.write(currentMinute); delay(500); //Set schedule Serial.write(167); Serial.write(daystorun); for (int i = 0; i < 14; i++) { Serial.write(times[i]); } } void loop() { digitalWrite(ledPin, 1); delay(1000); digitalWrite(ledPin, 0); delay(1000); } You need to modify the variables at the top: set currentDay, currentHour, currentMinute according to the present time. The pre-programmed schedule is to clean at 03:00 on Sunday, Monday, Wednesday and Friday. You can change this if you wish, by altering the daystorun and times variables. If you don’t modify the schedule, the Roomba should start automatically after 2 minutes. Put it all together You should now have a partially undressed Roomba, and a programmed Arduino. Now it is time to connect them. With both unpowered, connect the following: Arduino GND to Roomba ground (pin 6) Arduino TX (pin 1 on e.g. Uno) to Roomba RX (pin 3) It should look like this: Now, the moment of truth. Press the “CLEAN” button on the Roomba, the light should go on. Plug in the USB for the Arduino. The Roomba light should turn off briefly, and after a few seconds the Arduino should blink it’s LED. The schedule is now programmed, all done! Comment (1) | feb 3 Brother DS-620 on Linux Posted on mandag, februar 3, 2014 in Planet Ubuntu-DK , Planets , Ubuntu UPDATE: The drivers were temporarily unavailable; they seem to be up again, at least on the Brother US site: http://support.brother.com/g/b/downloadlist.aspx?c=us&lang=en&prod=ds620_all&os=128 I recently bought a Brother DS-620 document scanner that supposedly had support for Linux . It turns out it did, but only after a few quirks. I installed the official Linux drivers , and tried to scan a document using a GUI scanning application. Things were hanging and generally very unresponsive. I checked with the SANE command line tools, e.g. “sane-find-scanner”. It turns out things were indeed working, albeit very slowly. In dmesg I found a lot of messages like: Jan 29 22:52:13 mchro-laptop kernel: [39172.165644] usb 2-1.3: reset high-speed USB device number 32 using ehci-pci Jan 29 22:52:13 mchro-laptop kernel: [39172.333832] usb 2-1.3: reset high-speed USB device number 32 using ehci-pci Jan 29 22:52:13 mchro-laptop kernel: [39172.501677] usb 2-1.3: reset high-speed USB device number 32 using ehci-pci Jan 29 22:52:13 mchro-laptop kernel: [39172.669712] usb 2-1.3: reset high-speed USB device number 32 using ehci-pci Jan 29 22:52:13 mchro-laptop kernel: [39172.837679] usb 2-1.3: reset high-speed USB device number 32 using ehci-pci repeating several times every seconds. At this stage I was thinking that the Linux support was very crappy. After quite a lot of mucking around playing with capturing USB packets using Wireshark, it seemed the device itself was requesting a reset, and the Linux kernel was resetting it approximately 200ms later. Reading some Linux source code, and playing with USB quirks in Linux solved nothing. Finally, I gave up and booted into Windows to check if the hardware had a defect. In Windows it worked without issues. I upgraded the firmware using the Windows utility to do so. After doing this the scanner worked without issue also in Linux. So, all in all: There is official Linux support for this scanner, but it seems to require a firmware upgrade. This could definitely be better handled by the Brother documentation. Comments (9) | jan 31 Stupid sys-admin’ing, and hooray for LVM and unnecessary partitions Posted on fredag, januar 31, 2014 in Planet Ubuntu-DK , Planets , Sysadmin'ing , Ubuntu The scenario is: almost finished migrating from an old server to a new server. Only a few steps remain, namely change DNS to point to new server wipe disks on old server Done in this order, one might be unlucky that ssh’ing in to wipe the disks lands you on the new server. If you don’t discover this and run the command dd if=/dev/zero of=/dev/md2 to wipe the disks you might run it on the new server instead. BAM: you just wiped the data of your new server. Fortunately, I realised my mistake after a few seconds, and was able to recover from this with only unimportant data loss, and a little panic. /dev/md2 is actually a LVM physical partition, of which the first part now only contains zeroes; hereunder all the meta-data. LVM reported no volumes of any kind: root@server# pvs -v Scanning for physical volume names root@server# lvs -v Finding all logical volumes No volume groups found root@server # vgs -v Finding all volume groups No volume groups found After a bit of Google’ing while panicking I found out LVM keeps a backup of all its metadata in /etc/lvm/backup , and that it could be rewritten to the physical volume using: pvcreate -ff -u XXXXXX-XXXX-XXXX-XXXX-XXXX-XXXX-XXXXXX --restorefile /etc/lvm/backup/vg0 /dev/md2 where XXXXXX-XXXX-XXXX-XXXX-XXXX-XXXX-XXXXXX is the physical UUID from the backup file: ... physical_volumes { pv0 { id = "XXXXXX-XXXX-XXXX-XXXX-XXXX-XXXX-XXXXXX" device = "/dev/md2" # Hint only ... Unfortunately, I got an error: root@server# pvcreate -ff -u XXXXXX-XXXX-XXXX-XXXX-XXXX-XXXX-XXXXXX --restorefile /etc/lvm/backup/vg0 /dev/md2 Couldn't find device with uuid XXXXXX-XXXX-XXXX-XXXX-XXXX-XXXX-XXXXXX. Can't open /dev/md2 exclusively. Mounted filesystem? lsof showed nothing accessing md2, but I guess something still had references to the logical volumes. I was unable to get it to work, so I decided to reboot (while making sure the system would come up, and nothing would try to mount the (non-existent) LVM volumes). After a reboot the command worked, but still no logical volumes: root@server # pvcreate -ff -u XXXXXX-XXXX-XXXX-XXXX-XXXX-XXXX-XXXXXX --restorefile /etc/lvm/backup/vg0 /dev/md2 Couldn't find device with uuid XXXXXX-XXXX-XXXX-XXXX-XXXX-XXXX-XXXXXX. Physical volume "/dev/md2" successfully created root@server # sudo pvs PV VG Fmt Attr PSize PFree /dev/md2 lvm2 a- 648.51g 648.51g root@server # sudo lvs No volume groups found Now I had a physical volume, and could use the vgcfgrestore command: root@server # vgcfgrestore -f /etc/lvm/backup/vg0 /dev/vg0 Restored volume group vg0 root@server # sudo lvs LV VG Attr LSize Origin Snap% Move Log Copy% Convert ... home vg0 -wi-a- 20.00g I now had my logical volumes back! Now to assess the data loss… The backup file /etc/lvm/backup/vg0 lists which order the logical volumes are stored. The first volume in my case was the “home” volume. Sure enough, it would no longer mount: root@server # mount /dev/vg0/home /home mount: wrong fs type, bad option, bad superblock on /dev/mapper/vg0-home, missing codepage or helper program, or other error In some cases useful info is found in syslog - try dmesg | tail or so I actually had no important information on that file system, so I re-created it. Luckily the next volume was intact, and I could bring up the rest of the system without problems. So to sum up: LVM keeps a backup of all it’s metadata that can be restored (after a reboot), but if your keyboard is faster than your brain it can be a good idea to keep an unused volume as the first logical volume 🙂 Comments (0) | jun 18 Making objdump -S find your source code Posted on mandag, juni 18, 2012 in Planet Ubuntu-DK , Ubuntu , University We all know the situation: We want to disassemble the most awesome pre-compiled object file, with accompanying sources, using objdump and we would like to view the assembly and C-code interleaved, so we use -S. Unfortunately, objdump fails to find the sources, and we are sad 🙁 How does objdump look for the sources? Normally the paths are hardcoded in the object file in the DWARF information. To inspect the DWARF debug info: $ objdump --dwarf myobject.o | less and look for DW_TAG_compile_unit sections, where the paths should exist like: <25> DW_AT_name : C:/ARM/myfile.c Of course, this might not be the path you have on your machine, and thus objdump gives up. However, we can use an undocumented option to objdump : the -I or –include: $ objdump -I ../mysources -S myobject.o | less and voila, objdump finds the sources, inlines the C-code, and everything is awesome! Comment (1) | feb 15 Et lille slag for ytringsfriheden Posted on søndag, februar 15, 2009 in Danish , Planet Ubuntu-DK Som de fleste ved har nogle danske internet-udbydere spærret for adgangen til The Pirate Bay , bl.a. TDC. Dermed er det også blevet gjort umuligt at følge med i den nærtstående retssag mod nogle af folkene bag The Pirate Bay, hvor nyheder set fra deres synspunkt bliver publiceret på trial.thepiratebay.org . Dette synes jeg er helt uholdbart i et rets-samfund som det danske! Tænk hvis det bliver kutyme at anklagede ikke kan forsvare sig i medierne! Derfor har jeg sat et mirror af bloggen , på http://tpbtrial.smartere.dk/ så folk der har en mindre friheds-elskende internet-udbyder også kan følge med i begge sider af retssagen. Den opdaterer én gang i timen. Bemærk! Der findes ingen links til ophavsrettigt beskyttet materiale på den side jeg laver et mirror af! Det er nok det bedste eksempel på censur vi har i Danmark pt.: En side der ikke overtræder nogen som helst love, men som blot udtrykker en mening, er blevet spærret! Comments (0) | dec 12 WordPress – mildly impressed Posted on fredag, december 12, 2008 in Planet Ubuntu-DK , Sysadmin'ing , Ubuntu , University So, I just installed WordPress, because I was starting to have a too long mental list of things that I considered “blog-able”. My current estimate of what I will be blogging about is: Sysadmin’ing on a tight budget, Ubuntu Linux, MultiADM, various happenings in the Open Source world, and probably a bit about my everyday life as a student of Computer Science at Aalborg University, Denmark. But back to the title of this post. For various reasons I have previously preferred other blogging software (primarily blogging software integrated with Typo3), but I finally gave in and installed WordPress. I deemed that I was simply missing out on too much: trackbacks, tags, anti-spam measures for comments. All this warranted a separate blogging system, and WordPress is pretty much the no. 1 blogging system in use. My experience with it so far: Installation was okay, but it could have told me that the reason I didn’t get the fancy install-wizard was because I had forgot to give permissions for WordPress to modify its files. Minor nitpick: I decided to move my installation from /wordpress to just /. This resulted in all links still pointing at /wordpress. After a little detective work, and phpMyAdmin to the rescue to alter a couple of rows, and everything was working again. But overall it seems WordPress is a pretty capable and extendable, and has a nice Web 2.0-like user interface. I’m pretty sure I will grow accustomed to it over time. Comments (0) | Categories Danish Hal9k Ikke kategoriseret Planet Ubuntu-DK Planets Sysadmin'ing Ubuntu University Woodworking © blog.smartere . All Rights Reserved. WordPress Theme designed by Chris Wallace | 2026-01-13T08:48:58 |
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Right menu Cloud Cost Optimization: Engineering-Led Strategy to Reduce AWS & GCP Spend by 30-50% Aspire Softserv Aspire Softserv Aspire Softserv Follow Jan 12 Cloud Cost Optimization: Engineering-Led Strategy to Reduce AWS & GCP Spend by 30-50% # aws # cloud # devops Comments Add Comment 5 min read Hosting a Static Website on Amazon S3 (Step-by-Step) irfan pasha irfan pasha irfan pasha Follow Jan 12 Hosting a Static Website on Amazon S3 (Step-by-Step) # aws # s3 # bigneer # website Comments Add Comment 2 min read AWS Certified Generative AI Developer – Professional in 2 Weeks (Part 1: Exam Overview & Foundations) MakendranG MakendranG MakendranG Follow Jan 11 AWS Certified Generative AI Developer – Professional in 2 Weeks (Part 1: Exam Overview & Foundations) # ai # machinelearning # aws # certification 6 reactions Comments Add Comment 16 min read AWS Certified Generative AI Developer – Professional: Exam Overview & Foundation Strategy (Part 1) MakendranG MakendranG MakendranG Follow Jan 11 AWS Certified Generative AI Developer – Professional: Exam Overview & Foundation Strategy (Part 1) # ai # machinelearning # aws # certification 6 reactions Comments Add Comment 7 min read Automating AWS Security Scanning: Configuring Prowler on EC2 as a Cron Job to Detect Outdated AMIs Rohan Khanal Rohan Khanal Rohan Khanal Follow Jan 11 Automating AWS Security Scanning: Configuring Prowler on EC2 as a Cron Job to Detect Outdated AMIs # automation # aws # devops # security Comments Add Comment 13 min read It’s 2026: Stop Using AWS IAM and Start Using IAM Identity Center Manusha Chethiyawardhana Manusha Chethiyawardhana Manusha Chethiyawardhana Follow for AWS Community Builders Jan 11 It’s 2026: Stop Using AWS IAM and Start Using IAM Identity Center # aws # tutorial # devops # cloud 5 reactions Comments 1 comment 5 min read You’re Running EC2 Instances That Do Nothing Nikola Roganovic Nikola Roganovic Nikola Roganovic Follow Jan 11 You’re Running EC2 Instances That Do Nothing # aws # cloud # devops # sre 1 reaction Comments Add Comment 2 min read BootStrapping Aurora RDS Databases using Lambda and Terraform (Part 2) Santanu Das Santanu Das Santanu Das Follow Jan 11 BootStrapping Aurora RDS Databases using Lambda and Terraform (Part 2) # lambda # aws # rds # devops Comments Add Comment 10 min read Why AI Agents Need Context Graphs (And How to Build One with AWS) Brooke Jamieson Brooke Jamieson Brooke Jamieson Follow for AWS Jan 12 Why AI Agents Need Context Graphs (And How to Build One with AWS) # ai # contextgraphs # agenticai # aws 2 reactions Comments Add Comment 13 min read Call Center con voces naturales en español y acento local ensamblador ensamblador ensamblador Follow for AWS Español Jan 9 Call Center con voces naturales en español y acento local # amazonconnect # elevenlabs # conversationalai # aws 11 reactions Comments 2 comments 7 min read Linux Learning Journey – Day 2: Command-Line Practice & System Familiarity 🐧 Avinash wagh Avinash wagh Avinash wagh Follow Jan 12 Linux Learning Journey – Day 2: Command-Line Practice & System Familiarity 🐧 # linux # ubuntu # aws # learning 1 reaction Comments Add Comment 1 min read Cloud 101 with AWS: From Concepts to a Real Serverless App Warda Liaqat Warda Liaqat Warda Liaqat Follow Jan 11 Cloud 101 with AWS: From Concepts to a Real Serverless App # aws # cloudcomputing # serverless # ai 1 reaction Comments Add Comment 2 min read AWS Certified Generative AI Developer – Professional in 2 Weeks (Part 2: Advanced Learning & Exam Prep) MakendranG MakendranG MakendranG Follow Jan 11 AWS Certified Generative AI Developer – Professional in 2 Weeks (Part 2: Advanced Learning & Exam Prep) # ai # aws # certification # machinelearning 1 reaction Comments Add Comment 13 min read Tag log buckets created by AWS CDK for third party tools Johannes Konings Johannes Konings Johannes Konings Follow for AWS Community Builders Jan 11 Tag log buckets created by AWS CDK for third party tools # aws # cdk # cdknag 1 reaction Comments Add Comment 4 min read Amazon S3 Vectors: When Your Data Lake Becomes Your Vector Store Sujitha Rasamsetty Sujitha Rasamsetty Sujitha Rasamsetty Follow Jan 11 Amazon S3 Vectors: When Your Data Lake Becomes Your Vector Store # aws # awscommunity # ai # vectordatabase Comments Add Comment 6 min read Cloud Computing - Virtual Private Cloud (VPC) Setup - Complete Tutorial Hemanath Kumar J Hemanath Kumar J Hemanath Kumar J Follow Jan 11 Cloud Computing - Virtual Private Cloud (VPC) Setup - Complete Tutorial # tutorial # cloud # aws # vpc Comments Add Comment 2 min read AWS Services That Should Exist (But Don't) Marc Khaled Marc Khaled Marc Khaled Follow Jan 11 AWS Services That Should Exist (But Don't) # aws # devops # cloud # architecture Comments Add Comment 2 min read AWS IAM basics explained with real examples Sahinur Sahinur Sahinur Follow Jan 11 AWS IAM basics explained with real examples # aws # beginners # security Comments Add Comment 5 min read Complete Guide: Deploying Node.js Application on Ubuntu VPS Sahinur Sahinur Sahinur Follow Jan 11 Complete Guide: Deploying Node.js Application on Ubuntu VPS # node # devops # ubuntu # aws Comments Add Comment 4 min read AWS Pricing Models Explained: (A Beginner's Guide) chandra penugonda chandra penugonda chandra penugonda Follow Jan 11 AWS Pricing Models Explained: (A Beginner's Guide) # beginners # tutorial # cloud # aws Comments Add Comment 8 min read Building a Multi-Brand CDN Architecture: Lessons from Scaling CMS Media Delivery Nikola Lalović Nikola Lalović Nikola Lalović Follow Jan 11 Building a Multi-Brand CDN Architecture: Lessons from Scaling CMS Media Delivery # aws # webdev # programming # architecture Comments Add Comment 7 min read Can AI Translate Technical Content into Indian Languages? 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Exploring Amazon Translate (English Marathi & Hindi) # aws # ai # translation # cloud Comments Add Comment 5 min read Learning AWS as a Student: What Actually Works Pawan Joshi Pawan Joshi Pawan Joshi Follow Jan 11 Learning AWS as a Student: What Actually Works # beginners # aws # learning # awschallenge 1 reaction Comments Add Comment 1 min read Getting Started with AWS in 2026 – A Practical Beginner's Guide 🚀 Sahinur Sahinur Sahinur Follow Jan 11 Getting Started with AWS in 2026 – A Practical Beginner's Guide 🚀 # aws # cloudcomputing # beginners # devops Comments Add Comment 3 min read How I Designed an Enterprise RAG System Using AWS Bedrock, Pinecone & Neo4j Betty Waiyego Betty Waiyego Betty Waiyego Follow Jan 12 How I Designed an Enterprise RAG System Using AWS Bedrock, Pinecone & Neo4j # aws # machinelearning # ai # python Comments Add Comment 7 min read loading... 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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https://dev.to/t/awscloudpractitioner | Awscloudpractitioner - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. DUMB DEV Community Follow Memes and software development shitposting Design Community Follow Web design, graphic design and everything in-between Security Forem Follow Your central hub for all things security. From ethical hacking and CTFs to GRC and career development, for beginners and pros alike Golf Forem Follow A community of golfers and golfing enthusiasts Crypto Forem Follow A collaborative community for all things Crypto—from Bitcoin to protocol development and DeFi to NFTs and market analysis. Parenting Follow A place for parents to the share the joys, challenges, and wisdom that come from raising kids. We're here for them and for each other. Forem Core Follow Discussing the core forem open source software project — features, bugs, performance, self-hosting. Maker Forem Follow A community for makers, hobbyists, and professionals to discuss Arduino, Raspberry Pi, 3D printing, and much more. HMPL.js Forem Follow For developers using HMPL.js to build fast, lightweight web apps. A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close # awscloudpractitioner Follow Hide Create Post Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu How I Passed the AWS Certified Cloud Practitioner in 24 Days (For Free) Adedoyin Adedoyin Adedoyin Follow Jan 5 How I Passed the AWS Certified Cloud Practitioner in 24 Days (For Free) # aws # awscloudpractitioner # cloudcertification # examprep Comments Add Comment 3 min read How to Study for the AWS CCP (CLF-C02) Exam in 4 Weeks Colton Scott Colton Scott Colton Scott Follow May 30 '25 How to Study for the AWS CCP (CLF-C02) Exam in 4 Weeks # awscloudpractitioner # awscertifiedcloudpractitioner # awsccp # clfc02 1 reaction Comments Add Comment 6 min read AWS Guard Duty Jin Vincent Necesario Jin Vincent Necesario Jin Vincent Necesario Follow Jul 8 '23 AWS Guard Duty # aws # awscloudpractitioner # awscloud # awsguardduty Comments Add Comment 3 min read First impressions of the new AWS Cloud Quest: Cloud Practitioner adventure Alex Radu Alex Radu Alex Radu Follow for AWS Community Builders Apr 4 '22 First impressions of the new AWS Cloud Quest: Cloud Practitioner adventure # aws # awscloudpractitioner # awscloudquest # cloud 23 reactions Comments 5 comments 8 min read loading... trending guides/resources How I Passed the AWS Certified Cloud Practitioner in 24 Days (For Free) 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . DEV Community © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. Log in Create account | 2026-01-13T08:48:58 |
https://dev.to/shree_abhijeet | Abhijeet Yadav - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. DUMB DEV Community Follow Memes and software development shitposting Design Community Follow Web design, graphic design and everything in-between Security Forem Follow Your central hub for all things security. From ethical hacking and CTFs to GRC and career development, for beginners and pros alike Golf Forem Follow A community of golfers and golfing enthusiasts Crypto Forem Follow A collaborative community for all things Crypto—from Bitcoin to protocol development and DeFi to NFTs and market analysis. Parenting Follow A place for parents to the share the joys, challenges, and wisdom that come from raising kids. We're here for them and for each other. Forem Core Follow Discussing the core forem open source software project — features, bugs, performance, self-hosting. Maker Forem Follow A community for makers, hobbyists, and professionals to discuss Arduino, Raspberry Pi, 3D printing, and much more. HMPL.js Forem Follow For developers using HMPL.js to build fast, lightweight web apps. A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Follow User actions Abhijeet Yadav AWS Community Builder | Skilled in multi-platform solutions, currently in Windows Enterprise Team managing Windows workloads, AD, and AWS services for secure, scalable environments Location Kolkata,India Joined Joined on Apr 6, 2025 Personal website https://www.linkedin.com/in/abhijeet-yadav-021a11209/ Work Associate Cloud Engineer More info about @shree_abhijeet Badges Writing Debut Awarded for writing and sharing your first DEV post! Continue sharing your work to earn the 4 Week Writing Streak Badge. Got it Close Currently learning New AWS automation tools. Available for Open to AWS architecture, Windows enterprise, freelancing for new builds, and networking troubleshooting. Say hey for tech brainstorming, problem-solving, or cloud optimization. Post 1 post published Comment 0 comments written Tag 8 tags followed AI-Augmented Cloud Operations Abhijeet Yadav Abhijeet Yadav Abhijeet Yadav Follow Jan 7 AI-Augmented Cloud Operations # aws # serverless # aiops # automation 1 reaction Comments Add Comment 6 min read loading... 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . DEV Community © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. Log in Create account | 2026-01-13T08:48:58 |
https://www.highlight.io/docs/general/product-features/dashboards/dashboards-tutorials/user-engagement | Creating User Engagement Metrics Star us on GitHub Star Docs Sign in Sign up General Docs Welcome to highlight.io Get Started Roadmap Company Values Compliance & Security Open Source Contributing Overview GraphQL Backend Frontend (app.highlight.io) Landing Site (highlight.io) Documentation End to End SDK Example Apps Adding an SDK Application Architecture GitHub Code Spaces Code Style Good First Issues Self-hosting Self-hosted [Dev] Self-hosted [Hobby] Self-hosted [Enterprise] Telemetry Our Competitors Product Philosophy Product Features Session Replay Overview Canvas & Iframe Dev-tool Window Recording Tracking Users & Recording Events Filtering Sessions GraphQL Live Mode Performance Impact Player Session Caching Rage Clicks Request Proxying Session Search Extracting the Session URL Session Search Deep Linking Shadow Dom + Web Components Error Monitoring Overview Enhancing Errors with GitHub Error Search Filtering Errors Grouping Errors Managing Errors Manually Reporting Errors Sourcemaps General Features Overview Alerts Comments Digests Environments Search Segments Services Webhooks Logging Overview Log Alerts Log Search Tracing Overview Trace Search Dashboards Overview Dashboard Management Metrics Tutorials Service Latency Web Vitals & Page Speed User Engagement User Analytics Graphing Drilldown Event Search Dashboard Variables SQL Editor Metrics (beta) Overview Frequently Asked Questions. Integrations Integrations Overview Amplitude Integration ClickUp Integration Discord Integration Electron Support Front Integration GitHub Integration Grafana Integration Overview Setup Dashboards Alerts Height Integration Intercom Integration Jira Integration LaunchDarkly Integration Linear Integration Mixpanel Integration Nuxt Integration Pendo Integration Segment Integration Slack Integration Vercel Integration WordPress Plugin Highlight.io Changelog Overview Changelog 12 (02/17) Changelog 13 (02/24) Changelog 14 (03/03) Changelog 15 (03/11) Changelog 16 (03/19) Changelog 17 (04/07) Changelog 18 (04/26) Changelog 19 (05/22) Changelog 20 (06/06) Changelog 21 (06/21) Changelog 22 (08/07) Changelog 23 (08/22) Changelog 24 (09/11) Changelog 25 (10/03) Changelog 26 (11/08) Changelog 27 (12/22) Changelog 28 (3/6) Changelog 29 (4/2) Menu Highlight Docs Welcome to highlight.io Get Started Roadmap Company Values Compliance & Security Open Source Contributing Overview GraphQL Backend Frontend (app.highlight.io) Landing Site (highlight.io) Documentation End to End SDK Example Apps Adding an SDK Application Architecture GitHub Code Spaces Code Style Good First Issues Self-hosting Self-hosted [Dev] Self-hosted [Hobby] Self-hosted [Enterprise] Telemetry Our Competitors Product Philosophy Product Features Session Replay Overview Canvas & Iframe Dev-tool Window Recording Tracking Users & Recording Events Filtering Sessions GraphQL Live Mode Performance Impact Player Session Caching Rage Clicks Request Proxying Session Search Extracting the Session URL Session Search Deep Linking Shadow Dom + Web Components Error Monitoring Overview Enhancing Errors with GitHub Error Search Filtering Errors Grouping Errors Managing Errors Manually Reporting Errors Sourcemaps General Features Overview Alerts Comments Digests Environments Search Segments Services Webhooks Logging Overview Log Alerts Log Search Tracing Overview Trace Search Dashboards Overview Dashboard Management Metrics Tutorials Service Latency Web Vitals & Page Speed User Engagement User Analytics Graphing Drilldown Event Search Dashboard Variables SQL Editor Metrics (beta) Overview Frequently Asked Questions. Integrations Integrations Overview Amplitude Integration ClickUp Integration Discord Integration Electron Support Front Integration GitHub Integration Grafana Integration Overview Setup Dashboards Alerts Height Integration Intercom Integration Jira Integration LaunchDarkly Integration Linear Integration Mixpanel Integration Nuxt Integration Pendo Integration Segment Integration Slack Integration Vercel Integration WordPress Plugin Highlight.io Changelog Overview Changelog 12 (02/17) Changelog 13 (02/24) Changelog 14 (03/03) Changelog 15 (03/11) Changelog 16 (03/19) Changelog 17 (04/07) Changelog 18 (04/26) Changelog 19 (05/22) Changelog 20 (06/06) Changelog 21 (06/21) Changelog 22 (08/07) Changelog 23 (08/22) Changelog 24 (09/11) Changelog 25 (10/03) Changelog 26 (11/08) Changelog 27 (12/22) Changelog 28 (3/6) Changelog 29 (4/2) Getting Started Getting Started with Highlight Fullstack Mapping Browser React.js Next.js Remix Vue.js Angular Gatsby.js SvelteKit Electron highlight.run SDK Overview Canvas & WebGL Console Messages Content-Security-Policy Identifying Users iframe Recording Monkey Patches Browser OpenTelemetry Persistent Asset Storage Privacy Proxying Highlight React.js Error Boundary Recording Network Requests and Responses Recording WebSocket Events Salesforce Lightning Web Components (LWC) Data Export Sourcemap Configuration Tracking Events Troubleshooting Upgrading Highlight Versioning Sessions & Errors Other React Native (beta) Server Go Overview chi Echo Fiber Gin GORM gqlgen Logrus Manual Tracing gorilla mux JS Overview Apollo AWS Lambda Cloudflare Workers Express.js Firebase Hono Nest.js Next.js Node.js Pino tRPC Winston Python Overview AWS Lambda Azure Functions Django FastAPI Flask Google Cloud Functions Loguru Other Frameworks Python AI / LLM Libraries Python Libraries Ruby Overview Other Frameworks Ruby on Rails Rust Overview actix-web No Framework Hosting Providers Overview Metrics in AWS Logging in AWS Logging in Azure Fly.io NATS Log Shipper Logging in GCP Heroku Log Drain Render Log Stream Logging in Trigger.dev Vercel Log Drain Elixir Overview Elixir App Java: All Frameworks PHP: All Frameworks C# .NET ASP C# .NET 4 ASP Docker / Docker Compose File Fluent Forward curl OpenTelemetry Protocol (OTLP) Syslog RFC5424 Systemd / Journald Native OpenTelemetry Overview Error Monitoring Logging Tracing Browser Instrumentation Metrics Fullstack Frameworks Overview Next.js Fullstack Overview Next.js Page Router Guide Next.js App Router Guide Edge Runtime Advanced Config Remix Walkthrough Self Host & Local Dev Overview Development deployment guide. Integrations Microsoft Teams self-hosted Hobby deployment guide. Traefik SSL Proxying. Docs Home SDK Client SDK API Reference Cloudflare Worker SDK API Reference Go SDK API Reference Hono SDK API Reference Java SDK API Reference Next.JS SDK API Reference Node.JS SDK API Reference Python SDK API Reference Ruby SDK API Reference Rust SDK API Reference Docs / Highlight Docs / Product Features / Dashboards / Metrics Tutorials / Creating User Engagement Metrics Creating User Engagement Metrics Overview This tutorial guides you through creating a graph to measure and analyze user engagement metrics. By following these steps, you'll be able to track user interactions with your application and gain insights into user behavior and trends. Step-by-step Guide 1. Select the Data Source Begin by choosing the source of the metrics. For user engagement, we'll use user sessions as our data source. This will provide us with rich information about how users interact with our application. 2. Choose the Graph Type Next, select the type of graph you want to use to visualize your data. For this example, we'll use a bar graph, which is excellent for comparing values across different categories. 3. Apply Filters To focus on specific user interactions, apply filters to your data. In this case, we'll filter for sessions where the URL contains the word "session". This helps us concentrate on particular pages or features of interest. 4. Group the Data Group the sessions by a relevant attribute. For this example, we'll group by the email (or identifier) that a user reports on that session. This allows us to analyze engagement on a per-user basis. Read more about reporting identifiers in our docs . 5. Analyze the Results The resulting graph will show a count of all the emails (representing users) across all filtered sessions. This visualization allows you to: Identify your most active users Spot trends in user engagement over time Understand which parts of your application are most frequently accessed 6. Refine Your Metrics If you want to track unique users rather than total interactions, you can modify the graph to use a "count distinct" function instead of a simple count. This can be particularly useful for metrics like Daily Active Users (DAU). 7. Interpret and Act on the Data Use the insights from your graph to understand the bigger picture of your application's usage: Identify your most engaged users and what characterizes their behavior Spot any decline in engagement and investigate potential causes Recognize successful features or content that drive higher engagement Plan targeted improvements or campaigns based on user engagement patterns By consistently monitoring and analyzing these user engagement metrics, you'll be able to make data-driven decisions to improve your application's user experience and overall success. Remember to regularly review and adjust your metrics to ensure they continue to provide valuable insights as your application and user base evolve. Creating Web Vitals & Page Speed Metrics User Analytics Community / Support Suggest Edits? Follow us! [object Object] | 2026-01-13T08:48:58 |
https://dev.to/highcenburg | Vicente G. Reyes - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Follow User actions Vicente G. Reyes Web Developer | Technical Writer | OSS Contributor | Musician | Gamer | Cyclist Location Mars Joined Joined on Jan 6, 2019 Personal website https://vicentereyes.org github website twitter website Education Bachelors of Science in Computer Science Pronouns He/Him Seven Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least seven years. Got it Close Future Writing Challenge Completion Badge Awarded for completing at least one prompt in the Future Writing Challenge. Thank you for participating! 💻 Got it Close 2025 New Year Writing Challenge Completion Badge Awarded for completing at least one prompt in the New Year Writing challenge. Thank you for participating! 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Got it Close One Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least one year. Got it Close Hacktoberfest 2019 Awarded for successful completion of the 2019 Hacktoberfest challenge. Got it Close 8 Week Writing Streak The streak continues! You've written at least one post per week for 8 consecutive weeks. Unlock the 16-week badge next! Got it Close Beloved Comment Awarded for making a well-loved comment, as voted on with 25 heart (❤️) reactions by the community. Got it Close 4 Week Writing Streak You've posted at least one post per week for 4 consecutive weeks! Got it Close Show all 27 badges More info about @highcenburg Organizations ICVN Tech Studio GitHub Repositories 432Hz-Frequency-Checker This project checks if the frequency of a song is 432Hz or not. JavaScript rantr A place to Rant about anything under the sun without being able to delete or update the rant Python Skills/Languages Django, Python, ReactJS, GraphQL, Digital Ocean, Heroku, Netlify, DatoCMS, Contentful, Airtable, Webflow, Tailwind CSS, Bootstrap CSS, Bulma CSS, Foundation CSS Currently hacking on A secret side project Available for Freelance/Consulting/Fulltime work Post 204 posts published Comment 886 comments written Tag 53 tags followed Pin Pinned Exploring the Magic of 432 Hz: Building a Music Frequency Analyzer Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Nov 26 '24 Exploring the Magic of 432 Hz: Building a Music Frequency Analyzer # python # music # machinelearning 12 reactions Comments Add Comment 4 min read Speech to Musical Notation with AssemblyAI Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Nov 22 '24 Speech to Musical Notation with AssemblyAI # devchallenge # assemblyaichallenge # ai # api 20 reactions Comments 6 comments 2 min read How to Down-Pitch A Song Using Python Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Sep 25 '24 How to Down-Pitch A Song Using Python # python # music 18 reactions Comments 5 comments 3 min read Creating a URL Shortener with FastAPI, ReactJs and TailwindCSS Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Jan 2 '24 Creating a URL Shortener with FastAPI, ReactJs and TailwindCSS # python # react 34 reactions Comments 9 comments 3 min read Enhancing Code Efficiency: A Deep Dive into the Popularity Algorithm Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Nov 14 '23 Enhancing Code Efficiency: A Deep Dive into the Popularity Algorithm # python # django # algorithms 5 reactions Comments 6 comments 2 min read Problem 9: Most Frequent Element Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Jan 12 Problem 9: Most Frequent Element # python # beginners # learning 1 reaction Comments Add Comment 2 min read Want to connect with Vicente G. Reyes? Create an account to connect with Vicente G. Reyes. You can also sign in below to proceed if you already have an account. Create Account Already have an account? Sign in Problem 8: Count Vowels Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Jan 6 Problem 8: Count Vowels # python # beginners # learning 6 reactions Comments Add Comment 2 min read Problem 7: Factorial Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Dec 29 '25 Problem 7: Factorial # python # beginners # learning 1 reaction Comments Add Comment 2 min read Problem 6: Reverse a List (without using reverse()) Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Dec 22 '25 Problem 6: Reverse a List (without using reverse()) # python # beginners # learning 1 reaction Comments Add Comment 2 min read Problem 5: Palindrome Checker Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Dec 15 '25 Problem 5: Palindrome Checker # python # beginners # learning 2 reactions Comments Add Comment 1 min read Brutal Efficiency: A Tech Breakdown of My Portfolio Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Dec 12 '25 Brutal Efficiency: A Tech Breakdown of My Portfolio # showdev # react # typescript 2 reactions Comments 2 comments 2 min read Problem 4: Flatten a Nested List Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Dec 8 '25 Problem 4: Flatten a Nested List # python # beginners # learning 1 reaction Comments Add Comment 2 min read Problem 3: Mastering FizzBuzz in Python: A Step-by-Step Guide Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Nov 24 '25 Problem 3: Mastering FizzBuzz in Python: A Step-by-Step Guide # python # beginners # learning 1 reaction Comments Add Comment 3 min read Problem 2: Finding Min and Max Without Built-in Functions: A Python Tutorial Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Nov 18 '25 Problem 2: Finding Min and Max Without Built-in Functions: A Python Tutorial # python # beginners # learning 1 reaction Comments Add Comment 3 min read Problem 1: Sum of Digits: A Beginner's Guide to String Iteration in Python Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Nov 10 '25 Problem 1: Sum of Digits: A Beginner's Guide to String Iteration in Python # python # beginners # learning 1 reaction Comments Add Comment 3 min read This is one way I use AI for coding Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Nov 3 '25 This is one way I use AI for coding # ai # python # beginners 3 reactions Comments 2 comments 3 min read Understanding select_related vs prefetch_related in Django Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Sep 2 '25 Understanding select_related vs prefetch_related in Django # python # django 6 reactions Comments 2 comments 2 min read Understanding Django Relationships: OneToOneField vs ForeignKey vs ManyToManyField Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Aug 30 '25 Understanding Django Relationships: OneToOneField vs ForeignKey vs ManyToManyField # python # django 5 reactions Comments Add Comment 2 min read Reviewing FinalRoundAI: My First Experience with the AI Interview Copilot Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Aug 29 '25 Reviewing FinalRoundAI: My First Experience with the AI Interview Copilot # watercooler # career # productivity 2 reactions Comments Add Comment 2 min read Google Analytics not sending different pages aside from home page in ReactJS(Vite) Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Jul 18 '25 Google Analytics not sending different pages aside from home page in ReactJS(Vite) # help # javascript # react Comments Add Comment 1 min read Building a Python Metronome with PyQt6: A Guide to Audio and GUI Development Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Jul 6 '25 Building a Python Metronome with PyQt6: A Guide to Audio and GUI Development # python # music 7 reactions Comments Add Comment 2 min read Stuck in a Rut? Let This Random A Day to Remember Song Picker Spark Your Creativity! Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Feb 3 '25 Stuck in a Rut? Let This Random A Day to Remember Song Picker Spark Your Creativity! # javascript # music 5 reactions Comments Add Comment 3 min read Building a Contact Form Backend with FastAPI and Discord Integration Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Jan 7 '25 Building a Contact Form Backend with FastAPI and Discord Integration # python # javascript # tutorial 5 reactions Comments Add Comment 3 min read What's your tech stack? Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Jan 7 '25 What's your tech stack? # discuss # watercooler 28 reactions Comments 51 comments 1 min read Roadmap for Learning JavaScript and Beyond in 2025 Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Jan 6 '25 Roadmap for Learning JavaScript and Beyond in 2025 # devchallenge # newyearchallenge # career # javascript 28 reactions Comments 4 comments 2 min read How to Validate Rectangular Images in Django Using Python Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Dec 17 '24 How to Validate Rectangular Images in Django Using Python # python # django 6 reactions Comments Add Comment 3 min read How to Add Quotes and Commas to Each Line in a Text File Using Python Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Dec 12 '24 How to Add Quotes and Commas to Each Line in a Text File Using Python # python 5 reactions Comments Add Comment 3 min read How do you deal with pagination when scraping web pages? Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Jun 28 '24 How do you deal with pagination when scraping web pages? # help # discuss # python 4 reactions Comments 2 comments 1 min read csrfmiddlewaretoken included in the search url query Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Feb 6 '24 csrfmiddlewaretoken included in the search url query # help # django # python Comments Add Comment 1 min read Weird bug when looking at a user profile in django Vicente Antonio G. Reyes Vicente Antonio G. Reyes Vicente Antonio G. Reyes Follow Jan 16 '24 Weird bug when looking at a user profile in django # help # django # python Comments Add Comment 1 min read Can still access login page after logging in using ReactJS and dj-rest-auth Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Dec 12 '23 Can still access login page after logging in using ReactJS and dj-rest-auth # help # react # django Comments Add Comment 1 min read Notifications not showing on list Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Nov 20 '23 Notifications not showing on list # help # django # python # jinja Comments Add Comment 1 min read Understanding the Distinction: PUT vs. PATCH in API Design Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Nov 14 '23 Understanding the Distinction: PUT vs. PATCH in API Design # api # python 9 reactions Comments 6 comments 2 min read Enhancing Django Applications with a Custom Middleware Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Oct 24 '23 Enhancing Django Applications with a Custom Middleware # python # django 1 reaction Comments Add Comment 3 min read What shiny new object is good to learn now? Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Oct 18 '23 What shiny new object is good to learn now? # discuss # watercooler 3 reactions Comments 7 comments 1 min read How do you learn from a chaotic code base? Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Oct 18 '23 How do you learn from a chaotic code base? # discuss # help 4 reactions Comments 2 comments 1 min read Anyone know an alternative to Rix aside from Bard and ChatGPT? Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Oct 7 '23 Anyone know an alternative to Rix aside from Bard and ChatGPT? # help Comments Add Comment 1 min read join() argument must be str, bytes, or os.PathLike object, not 'NoneType' with Django Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Sep 23 '23 join() argument must be str, bytes, or os.PathLike object, not 'NoneType' with Django # help # python # django 1 reaction Comments Add Comment 1 min read TryHackMe or HackTheBox? Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Sep 8 '23 TryHackMe or HackTheBox? # discuss # security # cybersecurity Comments Add Comment 1 min read TemplateResponseMixin requires either a definition of 'template_name' or an implementation of 'get_template_names()' Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Aug 15 '23 TemplateResponseMixin requires either a definition of 'template_name' or an implementation of 'get_template_names()' # help # python # django 1 reaction Comments Add Comment 1 min read django.db.utils.IntegrityError: UNIQUE constraint failed: accounts_profile.user_id Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Aug 15 '23 django.db.utils.IntegrityError: UNIQUE constraint failed: accounts_profile.user_id # help # python # django Comments Add Comment 1 min read Extra field in custom registration in DRF won't save Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Aug 15 '23 Extra field in custom registration in DRF won't save # help # python # django Comments Add Comment 1 min read Profile not creating when creating a User with Django Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Aug 15 '23 Profile not creating when creating a User with Django # help # django # python 2 reactions Comments Add Comment 1 min read The output of the site I scrape includes html elements Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Jul 26 '23 The output of the site I scrape includes html elements # help # python Comments 7 comments 1 min read Why are there 2 windows on my app? I'm using ttkbootstrap Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Jul 24 '23 Why are there 2 windows on my app? I'm using ttkbootstrap # help # python Comments 1 comment 1 min read On this day 13 years ago Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Jun 20 '23 On this day 13 years ago # watercooler 1 reaction Comments Add Comment 1 min read 67:1 Uncaught (in promise) SyntaxError: Unexpected token '<', "<!DOCTYPE "... is not valid JSON P Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow May 14 '23 67:1 Uncaught (in promise) SyntaxError: Unexpected token '<', "<!DOCTYPE "... is not valid JSON P # help # react 6 reactions Comments Add Comment 1 min read RangeError: Invalid time value - date-fns Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow May 10 '23 RangeError: Invalid time value - date-fns # help # nextjs Comments Add Comment 1 min read React Components not rendering in browser Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow May 7 '23 React Components not rendering in browser # help # react # javascript Comments 2 comments 1 min read UserSignupForm.custom_signup() takes 2 positional arguments but 3 were given Vicente Antonio G. Reyes Vicente Antonio G. Reyes Vicente Antonio G. Reyes Follow Apr 17 '23 UserSignupForm.custom_signup() takes 2 positional arguments but 3 were given # help # django # python Comments 1 comment 1 min read MultipleObjectsReturned at /rants/first-rant/ get() returned more than one Rant -- it returned 2 Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Apr 14 '23 MultipleObjectsReturned at /rants/first-rant/ get() returned more than one Rant -- it returned 2 # help # django # python 2 reactions Comments Add Comment 1 min read django-admin startapp v/s python manage.py startapp Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Apr 13 '23 django-admin startapp v/s python manage.py startapp 8 reactions Comments Add Comment 1 min read react_devtools_backend.js:2655 Warning: Each child in a list should have a unique "key" prop Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Apr 10 '23 react_devtools_backend.js:2655 Warning: Each child in a list should have a unique "key" prop # help # react # javascript Comments Add Comment 1 min read Getting started with Django Rest Framework Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Apr 8 '23 Getting started with Django Rest Framework # django # python # djangorestframework 4 reactions Comments Add Comment 4 min read Pytest and pytest-django ends up with assert error Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Apr 5 '23 Pytest and pytest-django ends up with assert error # help # python # django 2 reactions Comments Add Comment 1 min read DRF ManyToMany Field getting an error when creating object Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Apr 2 '23 DRF ManyToMany Field getting an error when creating object # help # django # python Comments 2 comments 1 min read Remove "%...% in urls Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Mar 13 '23 Remove "%...% in urls # help # django # python 4 reactions Comments Add Comment 1 min read How do you recover from coding after a long break? Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Mar 9 '23 How do you recover from coding after a long break? # help # discuss 10 reactions Comments 4 comments 1 min read rant_category() got an unexpected keyword argument 'slug' Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Mar 4 '23 rant_category() got an unexpected keyword argument 'slug' # discuss # bitcoin # cryptocurrency 4 reactions Comments Add Comment 1 min read Django Model Inheritance Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Mar 1 '23 Django Model Inheritance 28 reactions Comments 2 comments 2 min read Suppressing audio with Python Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Feb 27 '23 Suppressing audio with Python # nextjs # software # webdev 9 reactions Comments Add Comment 1 min read Installing docker and postgresql on Parrot OS Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Feb 26 '23 Installing docker and postgresql on Parrot OS # help # postgres # docker 3 reactions Comments 3 comments 1 min read Recover background audio with librosa and saving it with soundfile Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Feb 20 '23 Recover background audio with librosa and saving it with soundfile # python # music 4 reactions Comments Add Comment 1 min read Show off your rubber duckies Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Feb 16 '23 Show off your rubber duckies # discuss 7 reactions Comments 3 comments 1 min read Separate vocals from a track using python Vicente G. Reyes Vicente G. Reyes Vicente G. Reyes Follow Feb 13 '23 Separate vocals from a track using python # welcome 35 reactions Comments 2 comments 4 min read loading... 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . DEV Community © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. Log in Create account | 2026-01-13T08:48:58 |
https://www.highlight.io/docs/general/company/open-source/contributing/backend | GraphQL Backend Star us on GitHub Star Docs Sign in Sign up General Docs Welcome to highlight.io Get Started Roadmap Company Values Compliance & Security Open Source Contributing Overview GraphQL Backend Frontend (app.highlight.io) Landing Site (highlight.io) Documentation End to End SDK Example Apps Adding an SDK Application Architecture GitHub Code Spaces Code Style Good First Issues Self-hosting Self-hosted [Dev] Self-hosted [Hobby] Self-hosted [Enterprise] Telemetry Our Competitors Product Philosophy Product Features Session Replay Overview Canvas & Iframe Dev-tool Window Recording Tracking Users & Recording Events Filtering Sessions GraphQL Live Mode Performance Impact Player Session Caching Rage Clicks Request Proxying Session Search Extracting the Session URL Session Search Deep Linking Shadow Dom + Web Components Error Monitoring Overview Enhancing Errors with GitHub Error Search Filtering Errors Grouping Errors Managing Errors Manually Reporting Errors Sourcemaps General Features Overview Alerts Comments Digests Environments Search Segments Services Webhooks Logging Overview Log Alerts Log Search Tracing Overview Trace Search Dashboards Overview Dashboard Management Metrics Tutorials Service Latency Web Vitals & Page Speed User Engagement User Analytics Graphing Drilldown Event Search Dashboard Variables SQL Editor Metrics (beta) Overview Frequently Asked Questions. Integrations Integrations Overview Amplitude Integration ClickUp Integration Discord Integration Electron Support Front Integration GitHub Integration Grafana Integration Overview Setup Dashboards Alerts Height Integration Intercom Integration Jira Integration LaunchDarkly Integration Linear Integration Mixpanel Integration Nuxt Integration Pendo Integration Segment Integration Slack Integration Vercel Integration WordPress Plugin Highlight.io Changelog Overview Changelog 12 (02/17) Changelog 13 (02/24) Changelog 14 (03/03) Changelog 15 (03/11) Changelog 16 (03/19) Changelog 17 (04/07) Changelog 18 (04/26) Changelog 19 (05/22) Changelog 20 (06/06) Changelog 21 (06/21) Changelog 22 (08/07) Changelog 23 (08/22) Changelog 24 (09/11) Changelog 25 (10/03) Changelog 26 (11/08) Changelog 27 (12/22) Changelog 28 (3/6) Changelog 29 (4/2) Menu Highlight Docs Welcome to highlight.io Get Started Roadmap Company Values Compliance & Security Open Source Contributing Overview GraphQL Backend Frontend (app.highlight.io) Landing Site (highlight.io) Documentation End to End SDK Example Apps Adding an SDK Application Architecture GitHub Code Spaces Code Style Good First Issues Self-hosting Self-hosted [Dev] Self-hosted [Hobby] Self-hosted [Enterprise] Telemetry Our Competitors Product Philosophy Product Features Session Replay Overview Canvas & Iframe Dev-tool Window Recording Tracking Users & Recording Events Filtering Sessions GraphQL Live Mode Performance Impact Player Session Caching Rage Clicks Request Proxying Session Search Extracting the Session URL Session Search Deep Linking Shadow Dom + Web Components Error Monitoring Overview Enhancing Errors with GitHub Error Search Filtering Errors Grouping Errors Managing Errors Manually Reporting Errors Sourcemaps General Features Overview Alerts Comments Digests Environments Search Segments Services Webhooks Logging Overview Log Alerts Log Search Tracing Overview Trace Search Dashboards Overview Dashboard Management Metrics Tutorials Service Latency Web Vitals & Page Speed User Engagement User Analytics Graphing Drilldown Event Search Dashboard Variables SQL Editor Metrics (beta) Overview Frequently Asked Questions. Integrations Integrations Overview Amplitude Integration ClickUp Integration Discord Integration Electron Support Front Integration GitHub Integration Grafana Integration Overview Setup Dashboards Alerts Height Integration Intercom Integration Jira Integration LaunchDarkly Integration Linear Integration Mixpanel Integration Nuxt Integration Pendo Integration Segment Integration Slack Integration Vercel Integration WordPress Plugin Highlight.io Changelog Overview Changelog 12 (02/17) Changelog 13 (02/24) Changelog 14 (03/03) Changelog 15 (03/11) Changelog 16 (03/19) Changelog 17 (04/07) Changelog 18 (04/26) Changelog 19 (05/22) Changelog 20 (06/06) Changelog 21 (06/21) Changelog 22 (08/07) Changelog 23 (08/22) Changelog 24 (09/11) Changelog 25 (10/03) Changelog 26 (11/08) Changelog 27 (12/22) Changelog 28 (3/6) Changelog 29 (4/2) Getting Started Getting Started with Highlight Fullstack Mapping Browser React.js Next.js Remix Vue.js Angular Gatsby.js SvelteKit Electron highlight.run SDK Overview Canvas & WebGL Console Messages Content-Security-Policy Identifying Users iframe Recording Monkey Patches Browser OpenTelemetry Persistent Asset Storage Privacy Proxying Highlight React.js Error Boundary Recording Network Requests and Responses Recording WebSocket Events Salesforce Lightning Web Components (LWC) Data Export Sourcemap Configuration Tracking Events Troubleshooting Upgrading Highlight Versioning Sessions & Errors Other React Native (beta) Server Go Overview chi Echo Fiber Gin GORM gqlgen Logrus Manual Tracing gorilla mux JS Overview Apollo AWS Lambda Cloudflare Workers Express.js Firebase Hono Nest.js Next.js Node.js Pino tRPC Winston Python Overview AWS Lambda Azure Functions Django FastAPI Flask Google Cloud Functions Loguru Other Frameworks Python AI / LLM Libraries Python Libraries Ruby Overview Other Frameworks Ruby on Rails Rust Overview actix-web No Framework Hosting Providers Overview Metrics in AWS Logging in AWS Logging in Azure Fly.io NATS Log Shipper Logging in GCP Heroku Log Drain Render Log Stream Logging in Trigger.dev Vercel Log Drain Elixir Overview Elixir App Java: All Frameworks PHP: All Frameworks C# .NET ASP C# .NET 4 ASP Docker / Docker Compose File Fluent Forward curl OpenTelemetry Protocol (OTLP) Syslog RFC5424 Systemd / Journald Native OpenTelemetry Overview Error Monitoring Logging Tracing Browser Instrumentation Metrics Fullstack Frameworks Overview Next.js Fullstack Overview Next.js Page Router Guide Next.js App Router Guide Edge Runtime Advanced Config Remix Walkthrough Self Host & Local Dev Overview Development deployment guide. Integrations Microsoft Teams self-hosted Hobby deployment guide. Traefik SSL Proxying. Docs Home SDK Client SDK API Reference Cloudflare Worker SDK API Reference Go SDK API Reference Hono SDK API Reference Java SDK API Reference Next.JS SDK API Reference Node.JS SDK API Reference Python SDK API Reference Ruby SDK API Reference Rust SDK API Reference Docs / Highlight Docs / Company / Open Source / Contributing / GraphQL Backend GraphQL Backend Frequently Asked Questions How do I migrate schema changes to PostgreSQL? Schema changes to model.go will be automigrated. New tables should be added to Models . Migrations happen automatically in dev and in a GitHub action as part of our production deploy. How do I inspect the PostgreSQL database? cd docker; docker compose exec postgres psql -h localhost -U postgres postgres; will put you in a postgresql cli connected to your local postgres docker container. Run commands such as \d to list all tables, \d projects to describe the schema of a table (i.e. projects), or show * from sessions to look at data (i.e. rows in the sessions table). How to generate the GraphQL server definitions? Per the Makefile , cd backend; make private-gen for changes to private schema.graphqls and cd backend; make public-gen for changes to public schema.graphqls . The commands can also be executed inside docker: cd backend; make private-gen; make public-gen; Open Source Contributing Overview Frontend (app.highlight.io) Community / Support Suggest Edits? Follow us! [object Object] | 2026-01-13T08:48:58 |
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https://blog.smartere.dk/2026/01/floppy-disks-the-best-tv-remote-for-kids/#respond | blog.smartere » Floppy Disks: the best TV remote for kids blog.smartere // Ramblings of Mads Chr. Olesen Floppy Disks: the best TV remote for kids Posted on mandag, januar 12, 2026 in Hal9k , Planet Ubuntu-DK , Planets Modern TVs are very poorly suited for kids. They require using complicated remotes or mobile phones, and navigating apps that continually try to lure you into watching something else than you intended to. The usual scenario ends up with the kid feeling disempowered and asking an adult to put something on. That something ends up on auto-play because then the adult is free to do other things and the kid ends up stranded powerless and comatose in front of the TV. Instead I wanted to build something for my 3-year old son that he could understand and use independently. It should empower him to make his own choices. It should be physical and tangible, i.e. it should be something he could touch and feel. It should also have some illusion that the actual media content was stored physically and not un-understandably in “the cloud”, meaning it should e.g. be destroyable — if you break the media there should be consequences. And there should be no auto-play: interact once and get one video. Floppy disks are awesome! And then I remembered the sound of a floppy disk. The mechanical click as you insert it, the whirr of the disk spinning, and the sound of the read-head moving. Floppy disks are the best storage media ever invented! Why else would the “save-icon” still be a floppy disk? Who hasn’t turned in a paper on a broken floppy disk, with the excuse ready that the floppy must have broken when the teacher asks a few days later? But kids these days have never used nor even seen a floppy disk, and I believe they deserve this experience! Building on the experience from the Big Red Fantus-Button , I already had a framework for controlling a Chromecast, and because of the netcat | bash shenanigans it was easily extendable. My first idea for datastorage was to use the shell of a floppy disk and floppy drive, and put in an RFID tag; this has been done a couple of times on the internet, such as RFIDisk or this RaspberryPi based RFID reader or this video covering how to embed an RFID tag in a floppy disk . But getting the floppy disk apart to put in an RFID tag and getting it back together was kinda wonky. When working on the project in Hal9k someone remarked: “Datastorage? The floppy disk can store data!”, and a quick prototype later this worked really, really , well. Formatting the disk and storing a single small file, “autoexec.sh”, means that all the data ends up in track 0 and is read more or less immediately. It also has the benefit that everything can be checked and edited with a USB floppy disk drive; and the major benefit that all the sounds are completely authentic: click, whirrr, brrr brrr. Autorun for floppy disks is not really a thing. The next problem to tackle was how to detect that a disk is inserted. The concept of AutoRun from Windows 95 was a beauty: insert a CD-ROM and it would automatically start whatever was on the media. Great for convenience, quite questionably for security. While in theory floppy disks are supported for AutoRun , it turns out that floppy drives basically don’t know if a disk is inserted until the operating system tries to access it! There is a pin 34 “Disk Change” that is supposed to give this information , but this is basically a lie. None of the drives in my possession had that pin connected to anything, and the internet mostly concurs. In the end I slightly modified the drive and added a simple rolling switch, that would engage when a disk was inserted. A floppy disk walks into a drive; the microcontroller says “hello!” The next challenge was to read the data on a microcontroller. Helpfully, there is the Arduino FDC Floppy library by dhansel, which I must say is most excellent. Overall, this meant that the part of the project that involved reading a file from the floppy disk FAT filesystem was basically the easiest part of all! A combined ATMega + ESP8266 UNO-like board. Not really recommended, but can be made to work. However, the Arduino FDC Floppy library is only compatible with the AVR-based Arduinos, not the ESP-based ones, because it needs to control the timing very precisely and therefore uses a healthy amount of inline assembler. This meant that I would need one AVR-based Arduino to control the floppy disk, but another ESP-based one to do the WiFi communication. Such combined boards do exist, and I ended up using such a board, but I’m not sure I would recommend it: the usage is really finagly, as you need to set the jumpers differently for programming the ATmega, or programming the ESP, or connecting the two boards serial ports together. A remote should be battery-powered A remote control should be portable, and this means battery-powered. Driving a floppy disk of of lithium batteries was interesting. There is a large spike in current draw when the disk needs to spin up of several amperes, while the power draw afterwards is more modest, a couple of hundred milliamperes. I wanted the batteries to be 18650s, because I have those in abundance. This meant a battery voltage of 3.7V nominally, up to 4.2V for a fully charged battery; 5V is needed to spin the floppy around, so a boost DC-DC converter was needed. I used an off the shelf XL6009 step-up converter board. At this point a lot of head-scratching occurred: that initial spin-up power draw would cause the microcontroller to reset. In the end a 1000uF capacitor at the microcontroller side seemed to help but not eliminate the problem. One crucial finding was that the ground side of the interface cable should absolutely not be connected to any grounds on the microcontroller side. I was using a relatively simple logic-level MOSFET, the IRLZ34N , to turn off the drive by disconnecting the ground side. If any ground is connected, the disk won’t turn off. But also: if any logic pin was being pulled to ground by the ATmega, that would also provide a path to ground. But since the ATmega cannot sink that much current this would lead to spurious resets! Obvious after the fact, but this took quite some headscratching. Setting all the logic pins to input, and thus high impedance , finally fixed the stability issues. After fixing the stability, the next challenge was how to make both of the microcontrollers sleep. Because the ATmega sleep modes are quite a lot easier to deal with, and because the initial trigger would be the floppy inserting, I decided to make the ATmega in charge overall. Then the ESP has a very simple function: when awoken, read serial in, when a newline is found then send off that complete line via WiFi, and after 30 seconds signal to the ATmega that we’re sleeping, and go back to sleep. The overall flow for the ATmega is then: A disk is inserted, this triggers a interrupt on the ATmega that wakes up. The ATmega resets the ESP, waking it from deep sleep. The ATmega sends a “diskin” message over serial to the ESP; the ESP transmits this over WiFi when available. The ATmega turns on the drive itself, and reads the disk contents, and just sends it over serial to the ESP. Spin down the disk, go to sleep. When the disk is ejected, send a “diskout” message over serial, resetting the ESP if needed. Go back to 1. The box itself is just lasercut from MDF-board. For full details see the FloppyDiskCast Git repository . Server-side handlers Responding to those commands is still the netcat | bash from the Big Red Fantus-Button , which was simply extended with a few more commands and capabilities. A few different disks to chose from, with custom printed labels. diskin always sends a “play” command to the Chromecast. diskout always sends a “pause” command to the Chromecast. Other commands like dad-music are handled in one of two ways: Play a random video from a set, if a video from that set is not already playing : e.g. dad-music will randomly play one of dad’s music tracks – gotta influence the youth! Play the next video from a list, if a video from the list is not already playing : e.g. fantus-maskinerne will play the next episode, and only the next episode. Common for both is that they should be idempotent actions, and the diskin shortcut will make the media resume without having to wait for the disk contents itself to be read and processed. This means that the “play/pause” disk just contains an empty file to work. Questionable idea meets real-world 3 year old user The little guy quickly caught on to the idea! Much fun was had just pausing and resuming music and his Fantus TV shows. He explored and prodded, and some disks were harmed in the process. One problem that I did solve was that the read head stayed on track 0 after having read everything: this means that when the remote with disk inside it is tumbled around, the disk gets damaged at track 0. To compensate for this, I move the head to track 20 after reading has finished: any damage is then done there, where we don’t store any data. As a bonus it also plays a little more mechanic melody. « Upgrading the Olimex A20 LIME2 to 2GB RAM, by learning to BGA solder and deep diving into the U-Boot bootloader process Bring on the comments Tamara Raetz siger: 12. januar 2026 kl. 17:29 That was a lot of work to go to so that you could delay or avoid both negative and positive interactions with your son. When you engage face to face you could be teaching him qualities like patience and obedience and encouragement; you could be showing him frequently that you enjoy his company, that he is a likeable person worth your time and attention. Technology is not supposed to replace parenting, friend. Reply to this Comment Theron siger: 12. januar 2026 kl. 19:00 Awesome. I’ve wanted to do something with mini disks myself for a while. Did you consider just using the disks as a carrier and putting a RFC tag under the sticker or something? Would dramatically lower power consumption. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse Khadijah (Dana Ordalina) Posted on Jan 13 Readiness probe # devops # aws # kubernetes # beginners Readiness probe ** — это **проверка “готово ли приложение принимать трафик” . Проще говоря: “Ты уже готов работать с пользователями или ещё нет?” Чаще всего это термин из Kubernetes . Простыми словами 👇 Представь кафе: Кафе открыто , но повар ещё не готов, кухня не прогрелась, продукты не разложены. Readiness probe — это как вопрос официанту: 👉 «Можно уже пускать клиентов?» Если ответ “нет” — клиенты не заходят. Если “да” — клиентов начинают пускать. В Kubernetes что происходит Kubernetes регулярно проверяет приложение (например, по HTTP-запросу или команде). Если readiness probe успешен ✅ → pod получает трафик (его добавляют в Service / Load Balancer). Если неуспешен ❌ → pod жив , но трафик к нему не идёт . ⚠️ Важно: Readiness probe не убивает pod , он просто временно “выводится из оборота”. Чем отличается от liveness probe Коротко: Liveness probe — “Ты вообще жив?” ❌ нет → pod перезапускают Readiness probe — “Ты готов обслуживать запросы?” ❌ нет → pod живёт, но без трафика Когда readiness probe особенно нужен приложение долго стартует подключается к БД делает миграции временно перегружено зависит от внешних сервисов Погнали, наглядно и без заумных слов 😄 Реальный YAML-пример с readiness + liveness + startup apiVersion : v1 kind : Pod metadata : name : demo-app spec : containers : - name : app image : my-app:1.0 ports : - containerPort : 8080 # 1️⃣ Startup probe — ждём, пока приложение ВООБЩЕ запустится startupProbe : httpGet : path : /health/startup port : 8080 failureThreshold : 30 periodSeconds : 5 # → даём до 150 секунд на старт # 2️⃣ Readiness probe — готово ли принимать трафик readinessProbe : httpGet : path : /health/ready port : 8080 initialDelaySeconds : 5 periodSeconds : 5 failureThreshold : 3 # 3️⃣ Liveness probe — не зависло ли livenessProbe : httpGet : path : /health/live port : 8080 periodSeconds : 10 failureThreshold : 3 Enter fullscreen mode Exit fullscreen mode Что здесь происходит по шагам 🟦 Startup probe Вопрос: «Ты уже ЗАПУСТИЛСЯ?» Kubernetes не запускает readiness и liveness , пока startup probe не станет OK если не стал OK за лимит → pod перезапускают 💡 Нужен для: Java / Spring приложений с миграциями долгого старта 🟩 Readiness probe Вопрос: «Ты ГОТОВ принимать запросы?» если ❌ → pod убирают из Service pod не перезапускают когда снова ✅ → трафик возвращается 💡 Типично проверяют: подключение к БД доступность зависимостей перегрузку 🟥 Liveness probe Вопрос: «Ты вообще ЖИВ?» если ❌ → pod перезапускают 💡 Проверяет: deadlock зависшие потоки утечки памяти Сравнение: startup vs readiness (очень коротко) Probe Когда Если FAIL Для чего startup только при старте pod перезапуск долгий запуск readiness всё время убрать трафик временно не готов liveness всё время pod перезапуск приложение зависло Жизненный пример Приложение стартует так: запускается JVM (40 сек) миграции БД (30 сек) готово принимать запросы 👉 startup probe ждёт шаги 1–2 👉 readiness probe включает трафик только после шага 3 👉 liveness probe следит, чтобы всё не зависло через час Top comments (0) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse Khadijah (Dana Ordalina) Follow DevOps Engineer. AWS, Terraform, Docker and CI/CD. Building real projects and sharing my DevOps journey. Location United States Work DevOps Engineer Joined Dec 20, 2025 More from Khadijah (Dana Ordalina) Сине-зеленое развертывание на EKS # eks # aws # bluegreen # programming Kubernetes #1 # kubernetes # nginx # docker # programming 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . DEV Community © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. Log in Create account | 2026-01-13T08:48:58 |
https://blog.smartere.dk/?p=702 | blog.smartere » Floppy Disks: the best TV remote for kids blog.smartere // Ramblings of Mads Chr. Olesen Floppy Disks: the best TV remote for kids Posted on mandag, januar 12, 2026 in Hal9k , Planet Ubuntu-DK , Planets Modern TVs are very poorly suited for kids. They require using complicated remotes or mobile phones, and navigating apps that continually try to lure you into watching something else than you intended to. The usual scenario ends up with the kid feeling disempowered and asking an adult to put something on. That something ends up on auto-play because then the adult is free to do other things and the kid ends up stranded powerless and comatose in front of the TV. Instead I wanted to build something for my 3-year old son that he could understand and use independently. It should empower him to make his own choices. It should be physical and tangible, i.e. it should be something he could touch and feel. It should also have some illusion that the actual media content was stored physically and not un-understandably in “the cloud”, meaning it should e.g. be destroyable — if you break the media there should be consequences. And there should be no auto-play: interact once and get one video. Floppy disks are awesome! And then I remembered the sound of a floppy disk. The mechanical click as you insert it, the whirr of the disk spinning, and the sound of the read-head moving. Floppy disks are the best storage media ever invented! Why else would the “save-icon” still be a floppy disk? Who hasn’t turned in a paper on a broken floppy disk, with the excuse ready that the floppy must have broken when the teacher asks a few days later? But kids these days have never used nor even seen a floppy disk, and I believe they deserve this experience! Building on the experience from the Big Red Fantus-Button , I already had a framework for controlling a Chromecast, and because of the netcat | bash shenanigans it was easily extendable. My first idea for datastorage was to use the shell of a floppy disk and floppy drive, and put in an RFID tag; this has been done a couple of times on the internet, such as RFIDisk or this RaspberryPi based RFID reader or this video covering how to embed an RFID tag in a floppy disk . But getting the floppy disk apart to put in an RFID tag and getting it back together was kinda wonky. When working on the project in Hal9k someone remarked: “Datastorage? The floppy disk can store data!”, and a quick prototype later this worked really, really , well. Formatting the disk and storing a single small file, “autoexec.sh”, means that all the data ends up in track 0 and is read more or less immediately. It also has the benefit that everything can be checked and edited with a USB floppy disk drive; and the major benefit that all the sounds are completely authentic: click, whirrr, brrr brrr. Autorun for floppy disks is not really a thing. The next problem to tackle was how to detect that a disk is inserted. The concept of AutoRun from Windows 95 was a beauty: insert a CD-ROM and it would automatically start whatever was on the media. Great for convenience, quite questionably for security. While in theory floppy disks are supported for AutoRun , it turns out that floppy drives basically don’t know if a disk is inserted until the operating system tries to access it! There is a pin 34 “Disk Change” that is supposed to give this information , but this is basically a lie. None of the drives in my possession had that pin connected to anything, and the internet mostly concurs. In the end I slightly modified the drive and added a simple rolling switch, that would engage when a disk was inserted. A floppy disk walks into a drive; the microcontroller says “hello!” The next challenge was to read the data on a microcontroller. Helpfully, there is the Arduino FDC Floppy library by dhansel, which I must say is most excellent. Overall, this meant that the part of the project that involved reading a file from the floppy disk FAT filesystem was basically the easiest part of all! A combined ATMega + ESP8266 UNO-like board. Not really recommended, but can be made to work. However, the Arduino FDC Floppy library is only compatible with the AVR-based Arduinos, not the ESP-based ones, because it needs to control the timing very precisely and therefore uses a healthy amount of inline assembler. This meant that I would need one AVR-based Arduino to control the floppy disk, but another ESP-based one to do the WiFi communication. Such combined boards do exist, and I ended up using such a board, but I’m not sure I would recommend it: the usage is really finagly, as you need to set the jumpers differently for programming the ATmega, or programming the ESP, or connecting the two boards serial ports together. A remote should be battery-powered A remote control should be portable, and this means battery-powered. Driving a floppy disk of of lithium batteries was interesting. There is a large spike in current draw when the disk needs to spin up of several amperes, while the power draw afterwards is more modest, a couple of hundred milliamperes. I wanted the batteries to be 18650s, because I have those in abundance. This meant a battery voltage of 3.7V nominally, up to 4.2V for a fully charged battery; 5V is needed to spin the floppy around, so a boost DC-DC converter was needed. I used an off the shelf XL6009 step-up converter board. At this point a lot of head-scratching occurred: that initial spin-up power draw would cause the microcontroller to reset. In the end a 1000uF capacitor at the microcontroller side seemed to help but not eliminate the problem. One crucial finding was that the ground side of the interface cable should absolutely not be connected to any grounds on the microcontroller side. I was using a relatively simple logic-level MOSFET, the IRLZ34N , to turn off the drive by disconnecting the ground side. If any ground is connected, the disk won’t turn off. But also: if any logic pin was being pulled to ground by the ATmega, that would also provide a path to ground. But since the ATmega cannot sink that much current this would lead to spurious resets! Obvious after the fact, but this took quite some headscratching. Setting all the logic pins to input, and thus high impedance , finally fixed the stability issues. After fixing the stability, the next challenge was how to make both of the microcontrollers sleep. Because the ATmega sleep modes are quite a lot easier to deal with, and because the initial trigger would be the floppy inserting, I decided to make the ATmega in charge overall. Then the ESP has a very simple function: when awoken, read serial in, when a newline is found then send off that complete line via WiFi, and after 30 seconds signal to the ATmega that we’re sleeping, and go back to sleep. The overall flow for the ATmega is then: A disk is inserted, this triggers a interrupt on the ATmega that wakes up. The ATmega resets the ESP, waking it from deep sleep. The ATmega sends a “diskin” message over serial to the ESP; the ESP transmits this over WiFi when available. The ATmega turns on the drive itself, and reads the disk contents, and just sends it over serial to the ESP. Spin down the disk, go to sleep. When the disk is ejected, send a “diskout” message over serial, resetting the ESP if needed. Go back to 1. The box itself is just lasercut from MDF-board. For full details see the FloppyDiskCast Git repository . Server-side handlers Responding to those commands is still the netcat | bash from the Big Red Fantus-Button , which was simply extended with a few more commands and capabilities. A few different disks to chose from, with custom printed labels. diskin always sends a “play” command to the Chromecast. diskout always sends a “pause” command to the Chromecast. Other commands like dad-music are handled in one of two ways: Play a random video from a set, if a video from that set is not already playing : e.g. dad-music will randomly play one of dad’s music tracks – gotta influence the youth! Play the next video from a list, if a video from the list is not already playing : e.g. fantus-maskinerne will play the next episode, and only the next episode. Common for both is that they should be idempotent actions, and the diskin shortcut will make the media resume without having to wait for the disk contents itself to be read and processed. This means that the “play/pause” disk just contains an empty file to work. Questionable idea meets real-world 3 year old user The little guy quickly caught on to the idea! Much fun was had just pausing and resuming music and his Fantus TV shows. He explored and prodded, and some disks were harmed in the process. One problem that I did solve was that the read head stayed on track 0 after having read everything: this means that when the remote with disk inside it is tumbled around, the disk gets damaged at track 0. To compensate for this, I move the head to track 20 after reading has finished: any damage is then done there, where we don’t store any data. As a bonus it also plays a little more mechanic melody. « Upgrading the Olimex A20 LIME2 to 2GB RAM, by learning to BGA solder and deep diving into the U-Boot bootloader process Bring on the comments Tamara Raetz siger: 12. januar 2026 kl. 17:29 That was a lot of work to go to so that you could delay or avoid both negative and positive interactions with your son. When you engage face to face you could be teaching him qualities like patience and obedience and encouragement; you could be showing him frequently that you enjoy his company, that he is a likeable person worth your time and attention. Technology is not supposed to replace parenting, friend. Reply to this Comment Theron siger: 12. januar 2026 kl. 19:00 Awesome. I’ve wanted to do something with mini disks myself for a while. Did you consider just using the disks as a carrier and putting a RFC tag under the sticker or something? Would dramatically lower power consumption. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse Milecia Posted on Aug 1, 2019 • Edited on Aug 26, 2019 4 Design Patterns In Web Development # beginners # design # webdev Have you ever been on a team and you need to start a project from scratch? That's usually the case in many start-ups and other small companies. There are so many different programming languages, architectures, and other concerns that it can be difficult to figure out where to start. That's where design patterns come in. A design pattern is like a template for your project. It uses certain conventions and you can expect a specific kind of behavior from them. These patterns were made up of many developers' experiences so they are really like different sets of best practices. You and your team get to decide which set of best practices is the most useful for your project. Based on the design pattern you choose, you all will start to have expectations for what the code should be doing and what vocabulary you all will be using. Programming design patterns can be used across all programming languages and can be used to fit any project because they only give you a general outline of a solution. There are 23 official patterns from the book, Design Patterns - Elements of Reusable Object-Oriented Software, which is considered one of the most influential books on object-oriented theory and software development. I'm going to cover 4 of the design patterns here just to give you some insight to what a few of the patterns are and when you would use them. Singleton Design Pattern The main thing you need to know about the singleton pattern is that it only allows a class to have a single instance and it uses a global variable to store that instance. You'll use lazy loading to make sure that there is only one instance of the class because it will only create the class when you need it. That prevents multiple instances from being created. Most of the time this gets implemented in the constructor. An example of a singleton that you probably use all the time is a state object in JavaScript. If you work with some of the front-end frameworks like React or Angular, you know all about how the parent component's state gets distributed to the child components. This is a great example of singletons in action because you never want more than one instance of that state object. Strategy Design Pattern The strategy is pattern is like an advanced version of an if else statement. It's basically where you make an interface for a method you have in your base class. This interface is then used to find the right implementation of that method from one of the derived classes. The implementation, in this case, will be decided at runtime based on the client. This pattern is incredibly useful in situations where you have required and optional methods for a class. Some instances of that class won't need the optional methods and that causes a problem for inheritance solutions. You could use interfaces for the optional methods, but then you would have to write the implementation every time you used that class since there would be no default implementation. That's where the strategy pattern saves us. Instead of the client looking for an implementation, it delegates to a strategy interface and the strategy finds the right implementation. Observer Design Pattern If you've ever used the MVC pattern, you've already used the observer design pattern. The observer pattern is like the View part of MVC. You have a subject that holds all of the data and the state of that data. Then you have observers, like users, that will pull data from the subject when the data has been updated. There are so many applications for this design pattern that it became an integral part of MVC. Sending user notifications, updating, filters, and handling subscribers can all be done using the observer patter. Decorator Design Pattern Using the decorator design pattern is fairly simple. You can have a base class with methods and properties that are present when you make a new object with the class. Now say you have some instances of the class that need methods or properties that didn't come from the base class. You can add those extra methods and properties to the base class, but that could mess up your other instances. You could even make subclasses to hold specific methods and properties you need that you can't put in your base class. Either of those approaches will solve your problem, but they are clunky and inefficient. That's where the decorator pattern steps in. Instead of making your code base ugly just to add a few things to an object instance, you can tack on those specific things directly to the instance. So if you need to add a new property that holds the time for an instance, you can use the decorator pattern to add it directly to that particular instance and it won't affect any other instances of that class object. Have you ever ordered food online? Then you've probably encountered the decorator pattern. If you're getting a sandwich and you want to add special toppings, the website isn't adding those toppings to every sandwich every current user is trying to order. It just adds those special toppings to your instance of that sandwich. When you need to work with multiple instances of an object that need values added dynamically like this, the decorator pattern is a good option. I used to think that design patterns were these crazy, far-out software development guidelines. Then I found out I use them all the time! A few of the patterns I covered are used in so many applications that it would blow your mind. They are just theory at the end of the day. It's up to us as developers to use that theory in ways that make our applications easy to implement and maintain. Have you used any of the other design patterns for your projects? Most places usually pick a design pattern for their projects and stick with it so I'd like to hear from you guys about what you use. Hey! You should follow me on Twitter because reasons: https://twitter.com/FlippedCoding Top comments (19) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Collapse Expand KristijanFištrek KristijanFištrek KristijanFištrek Follow I love to code. Location Varaždin Education bacc. ing. comp. Work IT Solutions Developer Joined Jun 9, 2019 • Aug 2 '19 Dropdown menu Copy link Hide I was hoping for examples but this is great on its own 🤘 Like comment: Like comment: 16 likes Like Comment button Reply Collapse Expand Mahmoud Ahmed Mahmoud Ahmed Mahmoud Ahmed Follow Full-stack Developer Email mahmoud@web-dev.works Location Egypt Work Hammoq Inc Joined Aug 20, 2018 • Aug 6 '19 Dropdown menu Copy link Hide you can check them here: addyosmani.com/resources/essential... loredanacirstea.github.io/es6-desi... Like comment: Like comment: 7 likes Like Comment button Reply Collapse Expand KristijanFištrek KristijanFištrek KristijanFištrek Follow I love to code. Location Varaždin Education bacc. ing. comp. Work IT Solutions Developer Joined Jun 9, 2019 • Aug 6 '19 Dropdown menu Copy link Hide I love Addy Osmani examples and takes on JS patterns ^ he is my go to guy when it comes to anything JavaScript related (: but I was hoping for more customized examples from the perspective of the writer. Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Lucas Reis Lucas Reis Lucas Reis Follow Undergraduate in Computer Science, Full Stack Developer, in eternal love with Electronic Music, technology and distributed systems. Location Berlin Education Bachelor in Computer Science Work Frontend Software Engineer Joined Mar 11, 2019 • Aug 2 '19 Dropdown menu Copy link Hide Me too, it could help to visualize the situation Like comment: Like comment: 3 likes Like Comment button Reply Collapse Expand Kyle Kyle Kyle Follow Joined Feb 25, 2019 • Aug 2 '19 Dropdown menu Copy link Hide me3 Like comment: Like comment: 1 like Like Thread Thread D7460N D7460N D7460N Follow UI/UX SME 25+ yrs designing/developing the wild wild web Location United States Work Software Engineer Joined Apr 16, 2019 • Aug 2 '19 Dropdown menu Copy link Hide me4 Like comment: Like comment: 2 likes Like Thread Thread Dinh Vu Hiep Dinh Vu Hiep Dinh Vu Hiep Follow Location Vietnam Joined Aug 3, 2019 • Aug 3 '19 Dropdown menu Copy link Hide Me 5 Like comment: Like comment: 3 likes Like Thread Thread Shayegan Hooshyari Shayegan Hooshyari Shayegan Hooshyari Follow Location Tehran Education Applied Mathematics Work Backend developer at Cafebazaar Joined Jan 24, 2019 • Aug 6 '19 Dropdown menu Copy link Hide MI6 Like comment: Like comment: 4 likes Like Comment button Reply Collapse Expand Comment marked as low quality/non-constructive by the community. View Code of Conduct 1214586 1214586 1214586 Follow 308 bio permanently changing Location México Joined Mar 21, 2018 • Aug 2 '19 Dropdown menu Copy link Hide I agree. This post without examples is futile. Please put some effort on your posts! Like comment: Like comment: 3 likes Like Comment button Reply Collapse Expand Alexander Holman Alexander Holman Alexander Holman Follow Software Engineer. C++, Python, PHP, Typescript/Ecmascript, Bash. Exeter, UK Email alexander@holman.org.uk Location London, UK Education BSc Computing & IT (Software) Work Lead Software Engineer at Cancer Research UK Joined Aug 7, 2017 • Aug 3 '19 Dropdown menu Copy link Hide You could be kinder in your criticism, e.g. offer resources on posts you consider non-futile, or provide examples of what you would consider putting 'effort' into a post. Writing doesn't come easily to everyone, you can't possibly know how much effort the writer put into this. Like comment: Like comment: 16 likes Like Thread Thread Comment marked as low quality/non-constructive by the community. View Code of Conduct 1214586 1214586 1214586 Follow 308 bio permanently changing Location México Joined Mar 21, 2018 • Aug 4 '19 • Edited on Aug 4 • Edited Dropdown menu Copy link Hide I'm not being rude, friend. I already got a warning email for expressing my opinion? Don't be so soft, please. Putting effort is putting actual examples on a daily work routine, not just something copied from elsewhere. Like comment: Like comment: 2 likes Like Thread Thread Alexander Holman Alexander Holman Alexander Holman Follow Software Engineer. C++, Python, PHP, Typescript/Ecmascript, Bash. Exeter, UK Email alexander@holman.org.uk Location London, UK Education BSc Computing & IT (Software) Work Lead Software Engineer at Cancer Research UK Joined Aug 7, 2017 • Aug 4 '19 Dropdown menu Copy link Hide Wait you got a warning email and you weren't rude? Perhaps it was a mistake? I mean you must be correct, being so hard and all... Perhaps you would consider learning from your mistake and move on? Nope you accuse the author of plagiarism! And without any evidence too, remember no example means no effort, and we wouldn't want so 'hard' person to come along and remind you how without examples of daily work routines you have made no effort at all, would we? That's ignoring the fact that such a defamatory statement could be considered libel, in some areas of the world. Read the code of conduct again if you get a moment and consider if your actions have met these requirements. Here is a link incase you hadn't seen it before: dev.to/code-of-conduct Like comment: Like comment: 6 likes Like Thread Thread 1214586 1214586 1214586 Follow 308 bio permanently changing Location México Joined Mar 21, 2018 • Aug 4 '19 Dropdown menu Copy link Hide This is a good post but I think it could be awesome if you add some examples. Keep up the great work! Like comment: Like comment: 7 likes Like Comment button Reply Collapse Expand Jenny Nguyen Jenny Nguyen Jenny Nguyen Follow Joined Sep 13, 2017 • Aug 12 '19 Dropdown menu Copy link Hide Thanks for offering your perspective of these four design patterns. I didn't realise I've been using the Singleton pattern for Angular and React, nor that I've been using the Observer pattern within the MVC pattern! Looks like I also do use them all the time! Like comment: Like comment: 3 likes Like Comment button Reply Collapse Expand Propel Guru Propel Guru Propel Guru Follow Propel Guru is a best digital marketing company that is dedicated to creating memorable and enriching digital experience Location Canada Work Digital Marketing and Web Development Company Joined Jul 8, 2020 • Sep 7 '20 Dropdown menu Copy link Hide I agree with KristijanFistrek, that examples are great to know in deep, but this post is good without examples also. If you are looking for website design, you can contact our experts here ! Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Erik Erik Erik Follow Sr. Software Engineer at CallRail building microservices to support 3rd party integrations. PhD student at the University of Nebraska studying bioinformatics, machine learning, and algorithms. Email erik@erikwhiting.com Location Omaha, NE Education BS CIS (2018), MS Software Engineering (2020), PhD Computer Science (in progress) Pronouns He/Him Work Sr. Software Engineer Joined Jul 31, 2019 • Aug 2 '19 Dropdown menu Copy link Hide that was great! thank you for sharing Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Hossein Nedaee Hossein Nedaee Hossein Nedaee Follow I'm a web developer. Joined Jul 7, 2019 • Aug 13 '19 Dropdown menu Copy link Hide Thank you, it was very good Im so eager to know more about resign patters specially by real example. Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Kat Tow Kat Tow Kat Tow Follow nb they/she | front-end software developer | accessibility advocate | powerlifter Location Milwaukee, WI Work Web Developer Joined Oct 7, 2019 • Jan 31 '20 Dropdown menu Copy link Hide 'Design patterns in software' always sounded so high-level and scary - after reading your post, I know that I'm already using and understanding many of them! Thanks for a great article. Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand syed syed syed Follow Joined Nov 22, 2018 • Apr 28 '20 Dropdown menu Copy link Hide Which pattern anyone would recommend to use to create amazon like application using vanilla Javascript or with react (and both) ? thanks Like comment: Like comment: 1 like Like Comment button Reply View full discussion (19 comments) Some comments may only be visible to logged-in visitors. Sign in to view all comments. 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Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse Milecia Follow Starting classes soon! | Software/Hardware Engineer | International tech speaker | Random inventor and slightly mad scientist with extra sauce Location Under a rock somewhere Work Senior Software Engineer / Random Tech Enthusiast Joined Jun 11, 2018 More from Milecia Getting Started With Docker # docker # devops # webdev 11 Ways To Optimize Your Deployment Pipeline # devops # webdev # optimization How to Measure DevOps Metrics # devops # webdev # cicd 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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Report Abuse Igor Ganapolsky Posted on Jan 11 • Originally published at github.com AI Trading: Lesson Learned #131: Self-Healing Gap - Blog Lesson Sync # ai # trading # python # machinelearning AI Trading Journey (48 Part Series) 1 AI Trading: Lesson Learned #093: Google Recommender CAV Not Useful for Trading 2 AI Trading: Lesson Learned #094: North Star $100/day Reality Check ... 44 more parts... 3 AI Trading: Lesson Learned #105: Post-Trade RAG Sync Was Missing 4 AI Trading: LL-095: Pre-Trade Pattern Validation Wired In 5 AI Trading: Lesson Learned #093: North Star Reality Check - $100/Day Requires $50K+ Capital 6 AI Trading: Lesson Learned: Phil Town Rule 1 Violation - Unprotected Positions Lost $93.69 (Jan 7, 2026) 7 AI Trading: Lesson Learned #093: Automation Metadata Stale - No Trades Executed Jan 7 8 AI Trading: Lesson Learned #094: Daily Trading Workflow Not Triggering (Jan 7, 2026) 9 AI Trading: Lesson Learned #093: CI Triggering Blocked Without GitHub PAT (Jan 7, 2026) 10 AI Trading: Lesson Learned #107: Honest Report - System NOT Following Phil Town (Jan 7, 2026) 11 AI Trading: Lesson Learned #095: Daily Trading Workflow Failure (Jan 7, 2026) 12 AI Trading: Lesson Learned #095: Trading Workflow Regression - Jan 7, 2026 13 AI Trading: Lesson Learned #108: Strategy Verification Session (Jan 7, 2026) 14 AI Trading: Lesson Learned #110: Trailing Stops Script Existed But Never Executed 15 AI Trading: Lesson Learned #111: Paper Trading Capital Must Be Realistic 16 AI Trading: Lesson Learned #112: Pre-Market Position Protection Gap 17 AI Trading: Lesson Learned #112: Phase 1 Cleanup - ChromaDB Removed 18 AI Trading: Lesson Learned #115: PAL MCP for Adversarial Trade Validation 19 AI Trading: Lesson Learned #116: Observability Lasagna - Connecting Logs to Traces 20 AI Trading: Lesson Learned #112: Self-Healing Data Integrity System Required 21 AI Trading: Lesson Learned #117: Trust Audit - Full System Review (Jan 8, 2026) 22 AI Trading: Lesson Learned #117: ChromaDB Removal Caused 2-Day Trading Gap 23 AI Trading: Lesson Learned #119: Paper Trading API Key Mismatch After Account Reset 24 AI Trading: Lesson Learned #120: Paper Trading System Broken for 4 Days (Jan 5-9, 2026) 25 AI Trading: Lesson Learned #121: Investment Strategy Audit - Honest Assessment (Jan 9, 2026) 26 AI Trading: Lesson Learned: False PR Merge Claims - Took Credit for Auto-Merged Work 27 AI Trading: Lesson Learned #120: Paper Trading Broken - Trust Crisis (Jan 9, 2026) 28 AI Trading: Lesson Learned #122: CEO Trust Audit - Comprehensive Strategy Review (Jan 9, 2026) 29 AI Trading: Lesson Learned #123: Trust Rebuild Audit - Comprehensive Evidence-Based Review 30 AI Trading: Lesson Learned #124: GitHub Secrets ARE Configured - Stop Hallucinating 31 AI Trading: Lesson Learned #120: Capital-Aware Watchlist Required for Paper Trading 32 AI Trading: LL-120: API Access Verification Required Before Trading 33 AI Trading: Lesson Learned #125: Comprehensive Trust Audit (Jan 9, 2026) 34 AI Trading: LL-126: Alpaca API Credentials Invalid - 401 Unauthorized 35 AI Trading: LL-124: Phil Town CSP Strategy Not Executing Trades 36 AI Trading: Lesson Learned #124: Secret Exposure Incident - Jan 9, 2026 37 AI Trading: Lesson Learned #125: Stale Position Data Inconsistency (Jan 9, 2026) 38 AI Trading: Lesson Learned #126: Critical Position Review - Expired Options and Missing Stop-Losses 39 AI Trading: Lesson Learned #127: LangSmith Removal - Dead Code Cleanup 40 AI Trading: Lesson Learned #127: Comprehensive Trust Audit - CEO Questions Answered (Jan 9, 2026) 41 AI Trading: Lesson Learned #128: Comprehensive Trust Audit (Jan 10, 2026) 42 AI Trading: Lesson Learned #129: Small Account Options Strategies for 2026 43 AI Trading: Lesson Learned #129: CEO Trust Audit - Comprehensive Answers (Jan 10, 2026) 44 AI Trading: Lesson Learned #129: Backtest Evaluation Bugs Discovered via Deep Research 45 AI Trading: Lesson Learned #129: Execute Trades, Don't Just Analyze 46 AI Trading: Lesson Learned #129: Wheel Strategy Criticism - Deep Research 47 AI Trading: Lesson Learned #130: Comprehensive Investment Strategy Review (Jan 11, 2026) 48 AI Trading: Lesson Learned #131: Self-Healing Gap - Blog Lesson Sync Lesson Learned #131: Self-Healing Gap - Blog Lesson Sync ID : LL-131 Date : January 11, 2026 Severity : MEDIUM Category : self-healing, automation, blog What Happened The GitHub Pages blog showed "Jan 11:" with no content because: Lessons created during Claude sessions are on feature branches Feature branches require manual PR creation and merge The blog only shows lessons that are merged to main Root Cause Gap in self-healing : The weekend-learning workflow auto-merges RAG content, but session-created lessons don't have the same automation. Current workflow: Claude creates lesson → Feature branch Claude creates PR → Manual step PR merge → Manual or requires API call Blog sync → Automatic (after merge) Evidence Jan 11 blog entry empty because: - ll_130_investment_strategy_review_jan11.md was on branch - Branch not merged to main - Blog builds from main only Enter fullscreen mode Exit fullscreen mode Fix Applied Used GitHub PAT to: Create PR #1408 programmatically Merge PR #1408 automatically Triggered auto-sync PR #1409 (lessons → docs/_lessons) Prevention (Self-Healing Improvement Needed) Option A: Auto-merge safe lesson PRs Add to CI workflow that auto-merges PRs that only change: rag_knowledge/lessons_learned/*.md docs/_lessons/*.md Option B: Direct push for lessons (with safeguards) Allow direct push to main for lesson files only if: File matches ll_*.md pattern Content passes schema validation No code files changed Option C: Session-end hook Create hook that auto-creates and merges lesson PRs at session end. Self-Healing Status Component Self-Healing? Weekend learning RAG ✅ YES - auto-merge Daily trading ✅ YES - scheduled Session lessons ❌ NO - requires manual PR Branch cleanup ✅ YES - weekend-learning cleans Blog sync ✅ YES - after merge Action Items [ ] Implement Option A: Auto-merge lesson PRs in CI [ ] Add session-end hook for lesson PR creation [ ] Monitor for similar gaps in other components Tags self-healing , automation , blog , github-pages , lessons-learned , operational-gap This lesson was auto-published from our AI Trading repository . More lessons : rag_knowledge/lessons_learned AI Trading Journey (48 Part Series) 1 AI Trading: Lesson Learned #093: Google Recommender CAV Not Useful for Trading 2 AI Trading: Lesson Learned #094: North Star $100/day Reality Check ... 44 more parts... 3 AI Trading: Lesson Learned #105: Post-Trade RAG Sync Was Missing 4 AI Trading: LL-095: Pre-Trade Pattern Validation Wired In 5 AI Trading: Lesson Learned #093: North Star Reality Check - $100/Day Requires $50K+ Capital 6 AI Trading: Lesson Learned: Phil Town Rule 1 Violation - Unprotected Positions Lost $93.69 (Jan 7, 2026) 7 AI Trading: Lesson Learned #093: Automation Metadata Stale - No Trades Executed Jan 7 8 AI Trading: Lesson Learned #094: Daily Trading Workflow Not Triggering (Jan 7, 2026) 9 AI Trading: Lesson Learned #093: CI Triggering Blocked Without GitHub PAT (Jan 7, 2026) 10 AI Trading: Lesson Learned #107: Honest Report - System NOT Following Phil Town (Jan 7, 2026) 11 AI Trading: Lesson Learned #095: Daily Trading Workflow Failure (Jan 7, 2026) 12 AI Trading: Lesson Learned #095: Trading Workflow Regression - Jan 7, 2026 13 AI Trading: Lesson Learned #108: Strategy Verification Session (Jan 7, 2026) 14 AI Trading: Lesson Learned #110: Trailing Stops Script Existed But Never Executed 15 AI Trading: Lesson Learned #111: Paper Trading Capital Must Be Realistic 16 AI Trading: Lesson Learned #112: Pre-Market Position Protection Gap 17 AI Trading: Lesson Learned #112: Phase 1 Cleanup - ChromaDB Removed 18 AI Trading: Lesson Learned #115: PAL MCP for Adversarial Trade Validation 19 AI Trading: Lesson Learned #116: Observability Lasagna - Connecting Logs to Traces 20 AI Trading: Lesson Learned #112: Self-Healing Data Integrity System Required 21 AI Trading: Lesson Learned #117: Trust Audit - Full System Review (Jan 8, 2026) 22 AI Trading: Lesson Learned #117: ChromaDB Removal Caused 2-Day Trading Gap 23 AI Trading: Lesson Learned #119: Paper Trading API Key Mismatch After Account Reset 24 AI Trading: Lesson Learned #120: Paper Trading System Broken for 4 Days (Jan 5-9, 2026) 25 AI Trading: Lesson Learned #121: Investment Strategy Audit - Honest Assessment (Jan 9, 2026) 26 AI Trading: Lesson Learned: False PR Merge Claims - Took Credit for Auto-Merged Work 27 AI Trading: Lesson Learned #120: Paper Trading Broken - Trust Crisis (Jan 9, 2026) 28 AI Trading: Lesson Learned #122: CEO Trust Audit - Comprehensive Strategy Review (Jan 9, 2026) 29 AI Trading: Lesson Learned #123: Trust Rebuild Audit - Comprehensive Evidence-Based Review 30 AI Trading: Lesson Learned #124: GitHub Secrets ARE Configured - Stop Hallucinating 31 AI Trading: Lesson Learned #120: Capital-Aware Watchlist Required for Paper Trading 32 AI Trading: LL-120: API Access Verification Required Before Trading 33 AI Trading: Lesson Learned #125: Comprehensive Trust Audit (Jan 9, 2026) 34 AI Trading: LL-126: Alpaca API Credentials Invalid - 401 Unauthorized 35 AI Trading: LL-124: Phil Town CSP Strategy Not Executing Trades 36 AI Trading: Lesson Learned #124: Secret Exposure Incident - Jan 9, 2026 37 AI Trading: Lesson Learned #125: Stale Position Data Inconsistency (Jan 9, 2026) 38 AI Trading: Lesson Learned #126: Critical Position Review - Expired Options and Missing Stop-Losses 39 AI Trading: Lesson Learned #127: LangSmith Removal - Dead Code Cleanup 40 AI Trading: Lesson Learned #127: Comprehensive Trust Audit - CEO Questions Answered (Jan 9, 2026) 41 AI Trading: Lesson Learned #128: Comprehensive Trust Audit (Jan 10, 2026) 42 AI Trading: Lesson Learned #129: Small Account Options Strategies for 2026 43 AI Trading: Lesson Learned #129: CEO Trust Audit - Comprehensive Answers (Jan 10, 2026) 44 AI Trading: Lesson Learned #129: Backtest Evaluation Bugs Discovered via Deep Research 45 AI Trading: Lesson Learned #129: Execute Trades, Don't Just Analyze 46 AI Trading: Lesson Learned #129: Wheel Strategy Criticism - Deep Research 47 AI Trading: Lesson Learned #130: Comprehensive Investment Strategy Review (Jan 11, 2026) 48 AI Trading: Lesson Learned #131: Self-Healing Gap - Blog Lesson Sync Top comments (0) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse Igor Ganapolsky Follow Seasoned Android engineer and AI specialist with 15+ years of software development experience and a deep focus on native Android. Proven track record modernizing high-traffic apps using Kotlin. Location Florida, USA Education Manhattan College Pronouns he Work Senior AI Engineer Joined Mar 19, 2018 More from Igor Ganapolsky AI Trading: Lesson Learned #130: Comprehensive Investment Strategy Review (Jan 11, 2026) # ai # trading # python # machinelearning AI Trading: Lesson Learned #129: Wheel Strategy Criticism - Deep Research # ai # trading # python # machinelearning AI Trading: Lesson Learned #129: Execute Trades, Don't Just Analyze # ai # trading # python # machinelearning 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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https://dev.to/pratikmahalle | Pratik Mahalle - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account Forem Close Follow User actions Pratik Mahalle DevRel, That DevOps Guy, Growing with the community Location Pune, India Joined Joined on Mar 8, 2024 Email address mahallepratik683@gmail.com Personal website https://www.thatdevopsguy.tech/ github website twitter website More info about @pratikmahalle Badges Writing Debut Awarded for writing and sharing your first DEV post! Continue sharing your work to earn the 4 Week Writing Streak Badge. Got it Close One Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least one year. Got it Close Organizations AWS Community Builders Skills/Languages Full stack developer, devops, terraform, aws, gcp, azure Currently learning I am currently learning about Go Available for I am available for collaborations for events. If you are in tech or devops, just say me Hi! Post 11 posts published Comment 1 comment written Tag 0 tags followed From DevOps to Platform Engineering in the AI Era Pratik Mahalle Pratik Mahalle Pratik Mahalle Follow Jan 5 From DevOps to Platform Engineering in the AI Era # devops # platformengineering # ai # career Comments Add Comment 4 min read Want to connect with Pratik Mahalle? Create an account to connect with Pratik Mahalle. You can also sign in below to proceed if you already have an account. Create Account Already have an account? Sign in How ventoy help me to install Window Pratik Mahalle Pratik Mahalle Pratik Mahalle Follow Dec 30 '25 How ventoy help me to install Window # microsoft # linux Comments Add Comment 2 min read How can we integrate Bolna AI With Google Sheets? Pratik Mahalle Pratik Mahalle Pratik Mahalle Follow Nov 17 '25 How can we integrate Bolna AI With Google Sheets? # google # productivity # ai # automation Comments Add Comment 9 min read Is DevRel Just About Events, or Something Deeper? Pratik Mahalle Pratik Mahalle Pratik Mahalle Follow for AWS Community Builders Oct 10 '25 Is DevRel Just About Events, or Something Deeper? # techtalks # devrel # ai # documentation Comments Add Comment 6 min read MemU: Memory that works everywhere Pratik Mahalle Pratik Mahalle Pratik Mahalle Follow Aug 17 '25 MemU: Memory that works everywhere # ai # opensource # database Comments Add Comment 5 min read Chaos Engineering for Security: Breaking Systems To Strengthen Defenses Pratik Mahalle Pratik Mahalle Pratik Mahalle Follow Jul 20 '25 Chaos Engineering for Security: Breaking Systems To Strengthen Defenses # security # kubernetes # devops 1 reaction Comments Add Comment 7 min read Google's Gemini CLI: Open Source AI Agent Pratik Mahalle Pratik Mahalle Pratik Mahalle Follow Jul 4 '25 Google's Gemini CLI: Open Source AI Agent # gemini # ai # google # opensource 2 reactions Comments Add Comment 5 min read KEDA: Smarter Scaling for Kubernetes – Event-Driven and Effortless Pratik Mahalle Pratik Mahalle Pratik Mahalle Follow Jun 29 '25 KEDA: Smarter Scaling for Kubernetes – Event-Driven and Effortless # kubernetes # opensource Comments 2 comments 4 min read 🐣How to Save Money with AWS Spot Instances Pratik Mahalle Pratik Mahalle Pratik Mahalle Follow for AWS Community Builders May 20 '25 🐣How to Save Money with AWS Spot Instances # aws # contentwriting # cloud Comments Add Comment 2 min read A Beginner's Journey: Deploying Applications on Amazon EKS Pratik Mahalle Pratik Mahalle Pratik Mahalle Follow for AWS Community Builders Apr 17 '25 A Beginner's Journey: Deploying Applications on Amazon EKS # devops # kubernetes # aws # docker 4 reactions Comments Add Comment 6 min read Lift Scholarship Application is now Open! Pratik Mahalle Pratik Mahalle Pratik Mahalle Follow for AWS Community Builders Apr 16 '25 Lift Scholarship Application is now Open! # thelinuxfoundation # devops # career 11 reactions Comments 2 comments 3 min read loading... 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV Forem — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . Forem © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. 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https://stackblitz.com/enterprise | StackBlitz | Enterprise | Instant Dev Environments | Click. Code. Done. StackBlitz Toggle Menu Bolt.new WebContainers Careers Enterprise Secure development environments in your browser Secure development environments in your browser Secure development environments in your browser StackBlitz Enterprise is everything you already love about StackBlitz with the enterprise-grade security and hosting options your team requires. Get in touch Running at the most security conscious Fortune 500 companies and beyond How enterprise web developers use StackBlitz Millions of developers rely on StackBlitz every day to bridge the gap between local development and cloud-based environments. With StackBlitz Enterprise, we’re taking everything we’ve learned from building for our millions of users and bringing it to your daily workflows. What is enterprise ? Scale design system adoption with interactive documentation Provide one-click instant environments your team can use to check out and try internal libraries. Embed directly or use StackBlitz’s SDK. StackBlitz syncs directly with your private NPM registry including JFrog Artifactory, Sonatype Nexus, and more. What is enterprise ? One-click bug reproductions Eliminate time-consuming bug reproductions by asking for a StackBlitz repro link in each ticket. Complete environments can be shared with just a URL, completely removing local installations when fixing bugs. What is Enterprise ? Simplify PR reviews and team collaboration Easily move in and out of different branches, repositories, and code bases without disrupting your own local development. We like to say upgrading to StackBlitz for collaboration is like going from a hot plate to a multi-burner stove. 01 02 03 03 Deploy how and where you want From bare metal to your VPC, StackBlitz Enterprise lets you deploy StackBlitz with a single, self-hosted Kubernetes instance , regardless of how many users you add. Enterprise SSO Integrate with any SAML2-based authentication provider Desktop-grade editor Use StackBlitz with the VS Code extensions and settings you’re used to Fully integrated with your development toolchain Access your private NPM packages from the Artifactory or Nexus registry. Review code stored in GitHub Enterprise, GitLab and Bitbucket Integrate with Figma and Storybook Improve the developer experience of working with design teams and systems Access and usage controls Manage access and maintain oversight into usage with your dedicated admin portal WebContainers built in Run any Node-based toolchain entirely within the browser with our proprietary WebContainers runtime. Unlimited, instant development environments? Sounds like a security nightmare dream. If you’ve looked into implementing cloud development environments at your company, you know the pain of managing countless dev environments while keeping them free of sensitive customer data. StackBlitz runs your code in a secure, entirely browser-based Node environment. No VMs here. 1 VM-based tools Boot Time Miliseconds Minutes Network Latency None Seconds to minutes Compute Costs None Increases with usage Hosting Costs Single Kubernetes cluster, regardless of usage Increases with usage Runtime Security Code runs fully isolated within the browser sandbox Code is executed on remote VMs and delivered over the network Jacob Anstadt Senior Enterprise architect - Surescripts ”As the team has continued to expand, this workflow has started to pay dividends. The UX team is more able to design workflows that meet our users needs rather than simply designing a UI on top of a backend our developers have already built.” Read the full case study Schedule a demo Meet with our team to learn more about StackBlitz Enterprise including pricing information, installation requirements, and a live demo. Get in touch Is your company already using StackBlitz? Find out whether your organization has an existing StackBlitz Enterprise deployment. Request access Frequently-asked questions About StackBlitz Enterprise Using StackBlitz Enterprise Security Can I run my existing repositories in StackBlitz? StackBlitz Enterprise runs a Node.js development environment in the browser sandbox using our WebContainers micro-operating system. Your repository must be compatible with Node 18 (or later) to run without issues. Can StackBlitz use my private NPM packages? Yes, StackBlitz Enterprise integrates with your private registries enabling you to use private packages in StackBlitz. Products Enterprise Server Integrations Design Systems WebContainer API Web Publisher Platform Case Studies Pricing Privacy Terms of Service Support Community Docs Enterprise Sales Company Blog Careers Terms of Service Privacy Policy StackBlitz Codeflow and the Infinite Pull Request logo are trademarks of StackBlitz, Inc. © 2025 StackBlitz, Inc. | 2026-01-13T08:48:58 |
https://blog.smartere.dk/category/university/ | blog.smartere » University blog.smartere // Ramblings of Mads Chr. Olesen jun 18 Making objdump -S find your source code Posted on mandag, juni 18, 2012 in Planet Ubuntu-DK , Ubuntu , University We all know the situation: We want to disassemble the most awesome pre-compiled object file, with accompanying sources, using objdump and we would like to view the assembly and C-code interleaved, so we use -S. Unfortunately, objdump fails to find the sources, and we are sad 🙁 How does objdump look for the sources? Normally the paths are hardcoded in the object file in the DWARF information. To inspect the DWARF debug info: $ objdump --dwarf myobject.o | less and look for DW_TAG_compile_unit sections, where the paths should exist like: <25> DW_AT_name : C:/ARM/myfile.c Of course, this might not be the path you have on your machine, and thus objdump gives up. However, we can use an undocumented option to objdump : the -I or –include: $ objdump -I ../mysources -S myobject.o | less and voila, objdump finds the sources, inlines the C-code, and everything is awesome! Comment (1) | dec 12 WordPress – mildly impressed Posted on fredag, december 12, 2008 in Planet Ubuntu-DK , Sysadmin'ing , Ubuntu , University So, I just installed WordPress, because I was starting to have a too long mental list of things that I considered “blog-able”. My current estimate of what I will be blogging about is: Sysadmin’ing on a tight budget, Ubuntu Linux, MultiADM, various happenings in the Open Source world, and probably a bit about my everyday life as a student of Computer Science at Aalborg University, Denmark. But back to the title of this post. For various reasons I have previously preferred other blogging software (primarily blogging software integrated with Typo3), but I finally gave in and installed WordPress. I deemed that I was simply missing out on too much: trackbacks, tags, anti-spam measures for comments. All this warranted a separate blogging system, and WordPress is pretty much the no. 1 blogging system in use. My experience with it so far: Installation was okay, but it could have told me that the reason I didn’t get the fancy install-wizard was because I had forgot to give permissions for WordPress to modify its files. Minor nitpick: I decided to move my installation from /wordpress to just /. This resulted in all links still pointing at /wordpress. After a little detective work, and phpMyAdmin to the rescue to alter a couple of rows, and everything was working again. But overall it seems WordPress is a pretty capable and extendable, and has a nice Web 2.0-like user interface. I’m pretty sure I will grow accustomed to it over time. Comments (0) | Categories Danish Hal9k Ikke kategoriseret Planet Ubuntu-DK Planets Sysadmin'ing Ubuntu University Woodworking © blog.smartere . All Rights Reserved. WordPress Theme designed by Chris Wallace | 2026-01-13T08:48:58 |
https://www.highlight.io/docs/general/product-features/dashboards/dashboards-tutorials/web-vitals-page-speed | Creating Web Vitals & Page Speed Metrics Star us on GitHub Star Docs Sign in Sign up General Docs Welcome to highlight.io Get Started Roadmap Company Values Compliance & Security Open Source Contributing Overview GraphQL Backend Frontend (app.highlight.io) Landing Site (highlight.io) Documentation End to End SDK Example Apps Adding an SDK Application Architecture GitHub Code Spaces Code Style Good First Issues Self-hosting Self-hosted [Dev] Self-hosted [Hobby] Self-hosted [Enterprise] Telemetry Our Competitors Product Philosophy Product Features Session Replay Overview Canvas & Iframe Dev-tool Window Recording Tracking Users & Recording Events Filtering Sessions GraphQL Live Mode Performance Impact Player Session Caching Rage Clicks Request Proxying Session Search Extracting the Session URL Session Search Deep Linking Shadow Dom + Web Components Error Monitoring Overview Enhancing Errors with GitHub Error Search Filtering Errors Grouping Errors Managing Errors Manually Reporting Errors Sourcemaps General Features Overview Alerts Comments Digests Environments Search Segments Services Webhooks Logging Overview Log Alerts Log Search Tracing Overview Trace Search Dashboards Overview Dashboard Management Metrics Tutorials Service Latency Web Vitals & Page Speed User Engagement User Analytics Graphing Drilldown Event Search Dashboard Variables SQL Editor Metrics (beta) Overview Frequently Asked Questions. Integrations Integrations Overview Amplitude Integration ClickUp Integration Discord Integration Electron Support Front Integration GitHub Integration Grafana Integration Overview Setup Dashboards Alerts Height Integration Intercom Integration Jira Integration LaunchDarkly Integration Linear Integration Mixpanel Integration Nuxt Integration Pendo Integration Segment Integration Slack Integration Vercel Integration WordPress Plugin Highlight.io Changelog Overview Changelog 12 (02/17) Changelog 13 (02/24) Changelog 14 (03/03) Changelog 15 (03/11) Changelog 16 (03/19) Changelog 17 (04/07) Changelog 18 (04/26) Changelog 19 (05/22) Changelog 20 (06/06) Changelog 21 (06/21) Changelog 22 (08/07) Changelog 23 (08/22) Changelog 24 (09/11) Changelog 25 (10/03) Changelog 26 (11/08) Changelog 27 (12/22) Changelog 28 (3/6) Changelog 29 (4/2) Menu Highlight Docs Welcome to highlight.io Get Started Roadmap Company Values Compliance & Security Open Source Contributing Overview GraphQL Backend Frontend (app.highlight.io) Landing Site (highlight.io) Documentation End to End SDK Example Apps Adding an SDK Application Architecture GitHub Code Spaces Code Style Good First Issues Self-hosting Self-hosted [Dev] Self-hosted [Hobby] Self-hosted [Enterprise] Telemetry Our Competitors Product Philosophy Product Features Session Replay Overview Canvas & Iframe Dev-tool Window Recording Tracking Users & Recording Events Filtering Sessions GraphQL Live Mode Performance Impact Player Session Caching Rage Clicks Request Proxying Session Search Extracting the Session URL Session Search Deep Linking Shadow Dom + Web Components Error Monitoring Overview Enhancing Errors with GitHub Error Search Filtering Errors Grouping Errors Managing Errors Manually Reporting Errors Sourcemaps General Features Overview Alerts Comments Digests Environments Search Segments Services Webhooks Logging Overview Log Alerts Log Search Tracing Overview Trace Search Dashboards Overview Dashboard Management Metrics Tutorials Service Latency Web Vitals & Page Speed User Engagement User Analytics Graphing Drilldown Event Search Dashboard Variables SQL Editor Metrics (beta) Overview Frequently Asked Questions. Integrations Integrations Overview Amplitude Integration ClickUp Integration Discord Integration Electron Support Front Integration GitHub Integration Grafana Integration Overview Setup Dashboards Alerts Height Integration Intercom Integration Jira Integration LaunchDarkly Integration Linear Integration Mixpanel Integration Nuxt Integration Pendo Integration Segment Integration Slack Integration Vercel Integration WordPress Plugin Highlight.io Changelog Overview Changelog 12 (02/17) Changelog 13 (02/24) Changelog 14 (03/03) Changelog 15 (03/11) Changelog 16 (03/19) Changelog 17 (04/07) Changelog 18 (04/26) Changelog 19 (05/22) Changelog 20 (06/06) Changelog 21 (06/21) Changelog 22 (08/07) Changelog 23 (08/22) Changelog 24 (09/11) Changelog 25 (10/03) Changelog 26 (11/08) Changelog 27 (12/22) Changelog 28 (3/6) Changelog 29 (4/2) Getting Started Getting Started with Highlight Fullstack Mapping Browser React.js Next.js Remix Vue.js Angular Gatsby.js SvelteKit Electron highlight.run SDK Overview Canvas & WebGL Console Messages Content-Security-Policy Identifying Users iframe Recording Monkey Patches Browser OpenTelemetry Persistent Asset Storage Privacy Proxying Highlight React.js Error Boundary Recording Network Requests and Responses Recording WebSocket Events Salesforce Lightning Web Components (LWC) Data Export Sourcemap Configuration Tracking Events Troubleshooting Upgrading Highlight Versioning Sessions & Errors Other React Native (beta) Server Go Overview chi Echo Fiber Gin GORM gqlgen Logrus Manual Tracing gorilla mux JS Overview Apollo AWS Lambda Cloudflare Workers Express.js Firebase Hono Nest.js Next.js Node.js Pino tRPC Winston Python Overview AWS Lambda Azure Functions Django FastAPI Flask Google Cloud Functions Loguru Other Frameworks Python AI / LLM Libraries Python Libraries Ruby Overview Other Frameworks Ruby on Rails Rust Overview actix-web No Framework Hosting Providers Overview Metrics in AWS Logging in AWS Logging in Azure Fly.io NATS Log Shipper Logging in GCP Heroku Log Drain Render Log Stream Logging in Trigger.dev Vercel Log Drain Elixir Overview Elixir App Java: All Frameworks PHP: All Frameworks C# .NET ASP C# .NET 4 ASP Docker / Docker Compose File Fluent Forward curl OpenTelemetry Protocol (OTLP) Syslog RFC5424 Systemd / Journald Native OpenTelemetry Overview Error Monitoring Logging Tracing Browser Instrumentation Metrics Fullstack Frameworks Overview Next.js Fullstack Overview Next.js Page Router Guide Next.js App Router Guide Edge Runtime Advanced Config Remix Walkthrough Self Host & Local Dev Overview Development deployment guide. Integrations Microsoft Teams self-hosted Hobby deployment guide. Traefik SSL Proxying. Docs Home SDK Client SDK API Reference Cloudflare Worker SDK API Reference Go SDK API Reference Hono SDK API Reference Java SDK API Reference Next.JS SDK API Reference Node.JS SDK API Reference Python SDK API Reference Ruby SDK API Reference Rust SDK API Reference Docs / Highlight Docs / Product Features / Dashboards / Metrics Tutorials / Creating Web Vitals & Page Speed Metrics Creating Web Vitals & Page Speed Metrics Overview This tutorial guides you through creating a graph to measure and analyze page speed over time. By following these steps, you'll be able to track your application's performance and gain insights into web vitals and other important metrics. For more information, read more about how Highlight's OpenTelemetry instrumentation captures this data and how this is can relate to your backend instrumentation . Step-by-step Guide 1. Install Highlight Instrumentation Begin by installing the Highlight instrumentation on your client-side application. This will automatically start capturing OpenTelemetry data, providing you with valuable insights into your application's performance. 2. Access the Metrics Dashboard Navigate to the metrics dashboard in the Highlight UI. This is where you'll create and manage your performance metrics. 3. Create a New Metric In the dashboard, create a new metric. Select "Traces" as the metric type, as this will allow us to measure page load times and other performance indicators. 4. Choose a Graph Type Select a graph type to visualize your data. For this example, we'll use a line chart, which is excellent for showing trends over time. 5. Set the Measurement Function Choose the P90 (90th percentile) function and apply it to the duration attribute. This will give you a good representation of your page load times, excluding outliers. 6. Apply Filters Filter for all spans with the name "documentLoad". This will focus your graph on page load traces, giving you a clear picture of your application's loading performance. 7. Analyze the Results The resulting graph will show the 90th percentile of page load times over time. This visualization allows you to: Track changes in page load performance Identify trends or patterns in load times Spot sudden spikes or gradual increases in load duration 8. Explore Additional Metrics While this example focuses on page load times, you can create similar graphs for other important metrics such as: Web Vitals (LCP, FID, CLS) DNS timings Time to First Byte (TTFB) First Contentful Paint (FCP) Refer to the linked documentation for more information on these additional metrics and how to graph them. By consistently monitoring and analyzing these performance metrics, you'll be able to maintain and improve your application's overall speed and user experience. This data-driven approach will help you identify areas for optimization and measure the impact of your improvements over time. Creating Service Latency Metrics Creating User Engagement Metrics Community / Support Suggest Edits? Follow us! [object Object] | 2026-01-13T08:48:58 |
https://dev.to/whykislay/the-limitations-of-text-embeddings-in-rag-applications-a-deep-engineering-dive-3ohh | The Limitations of Text Embeddings in RAG Applications: A Deep Engineering Dive - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse Kumar Kislay Posted on Jan 12 The Limitations of Text Embeddings in RAG Applications: A Deep Engineering Dive # productivity # sre # rag # machinelearning TL;DR We have all been there. You follow the tutorial, spin up a vector database, ingest your documentation, and for a moment, it feels like magic. You ask a question, and the LLM answers. But then you push to production. Suddenly, searching for "error 500" returns "500 days of summer," asking for "code without bugs" returns buggy code, and asking "what happened last week?" results in a blank stare from your system. This report is a comprehensive, 15,000-word deep dive into why naive RAG fails. We explore the mathematical limitations of cosine similarity, the "curse of dimensionality," and the inability of embeddings to handle negation, temporal context, and structured engineering data. We will also cover how to fix it using Hybrid Search (BM25), Re-ranking (ColBERT), and Knowledge Graphs (GraphRAG), with real-world examples from our engineering journey at SyncAlly. Part I: The Honeymoon Phase and the Inevitable Crash If you are reading this, you are likely standing somewhere in the "Trough of Disillusionment" regarding Retrieval Augmented Generation (RAG). The initial promise was intoxicating. We were told that by simply chunking our data, running it through an embedding model perhaps OpenAI's text-embedding-3-small or an open-source champion from Hugging Face and storing it in a vector database, we could give our LLMs "long-term memory." It felt like we had solved the context window problem forever. You could turn paragraphs of dense technical text into lists of floating-point numbers (vectors), plot them in a high-dimensional hyperspace, and mathematically calculate "semantic similarity." It was elegant. It was modern. It was supposed to work. Then, you gave it to your users. Or worse, you gave it to your own engineering team. The complaints started rolling in immediately. A developer searches for "payment gateway timeout" and gets fifty documents about "payment success" because the vectors for "success" and "timeout" are suspiciously close in the high-dimensional space of financial transaction contexts.1 Another engineer asks, "Who changed the auth service configuration last Tuesday?" and the system retrieves a generic Wiki page about 'Authentication Best Practices' written in 2021, completely ignoring the temporal constraint of "last Tuesday". Someone else tries to find a specific error code, 0x80040115, and the system retrieves a marketing blog post about "115 ways to improve customer satisfaction" because the embedding model treated the hexadecimal code as noise and latched onto the number 115. Why does this happen? Why does a technology labeled "Artificial Intelligence" fail at basic keyword matching, boolean logic, and time perception? The answer lies deep in the fundamental architecture of dense vector retrieval. While embeddings are incredible at capturing general semantic vibes matching "car" to "automobile" or "happy" to "joyful" they are mathematically ill-equipped to handle the precision, structure, and temporal context required for complex engineering workflows. They are fuzzy matching engines in a domain that demands absolute precision. At SyncAlly, we are obsessed with developer productivity. We are building an all-in-one workspace that connects tasks, meetings, code, and calendars to stop the context-switching madness that kills engineering flow. We faced these exact issues when we tried to build our own "brain" for engineering teams. We wanted engineers to be able to ask, "Why did we decide to use PostgreSQL?" and get an answer that synthesized context from a Slack debate, a Jira ticket description, and a transcript from a Zoom sprint planning meeting. We quickly learned that a simple vector store couldn't do this. It couldn't connect the dots between the decision (Slack) and the implementation (Code) because they didn't share enough lexical overlap for a vector model to consider them "close". In this report, we are going to dissect the failures of text embeddings with surgical precision. We are not just going to complain; we are going to look at the math, the linguistics, and the operational headaches. Then, we are going to build the solutions. We will explore why Hybrid Search is non-negotiable, why Re-ranking is the secret sauce of accuracy, and why the industry is inevitably moving toward GraphRAG to solve the complex reasoning problems that vectors simply cannot touch. Part II: The Mathematical Failures of Dense Embeddings To understand why your RAG system fails, you have to understand what it is actually doing under the hood. It is compressing the infinite complexity of human language into a fixed-size vector, typically 768, 1536, or 3072 dimensions. This compression is lossy. It discards syntax, precise negation, and structural hierarchy in favor of a generalized semantic position. The Curse of Dimensionality and the Meaning of "Distance" Vector retrieval relies on K-Nearest Neighbors (KNN) or, more commonly in production, Approximate Nearest Neighbors (ANN) algorithms like Hierarchical Navigable Small World (HNSW) graphs. The core operation is measuring the distance between the user's query vector and your document vectors. The industry standard metric for this is Cosine Similarity. It measures the cosine of the angle between two vectors in a multi-dimensional space. If the vectors point in the exact same direction, the similarity is 1. If they are orthogonal (90 degrees apart), the similarity is 0. If they point in opposite directions, it is -1. Here is the problem: In very high-dimensional spaces, the concept of "distance" starts to lose its intuitive meaning. This is known as the Curse of Dimensionality.6 As the number of dimensions increases, the volume of the space increases exponentially, and the data becomes incredibly sparse. In these high-dimensional hypercubes, all points tend to become equidistant from each other. The contrast between the "nearest" neighbor and the "farthest" neighbor diminishes, making it difficult for the algorithm to distinguish between a highly relevant document and a marginally relevant one. Furthermore, recent research has highlighted that cosine similarity has significant blind spots. Crucially, it ignores the magnitude (length) of the vector. Vector A: (Small magnitude) Vector B: (Large magnitude) Cosine similarity says these two vectors are identical (Similarity = 1.0). They point in the exact same direction. But in semantic space, magnitude often correlates with specificity, information density, or confidence. A short, vague sentence ("The system crashed.") and a long, detailed technical post-mortem ("The system crashed due to a null pointer exception in the payment microservice…") might end up with identical directionality in the vector space. If your retrieval system is based solely on cosine similarity, it might retrieve the vague chunk because it is "closer" or just as close as the detailed one, simply because the noise in the detailed chunk pulls its vector slightly off-axis. This phenomenon leads to "retrieval instability," where short, noisy text outranks high-quality, information-dense text. The "Mizan" balance function has been proposed as an alternative to weight magnitude back into the equation, but most off-the-shelf vector databases (Pinecone, Weaviate, Milvus) default to cosine similarity or dot product (which requires normalized vectors, making it mathematically equivalent to cosine similarity). The Anisotropy Problem Theoretical vector spaces are isotropic meaning space is uniform in all directions. Real-world language model embedding spaces are highly anisotropic. This means that embeddings tend to occupy a narrow cone in the vector space rather than being distributed evenly. Why does this matter to you as a developer? It means that "similarity" is not uniform. Two documents might be very different semantically but still have a high cosine similarity score (e.g., 0.85) simply because all documents in that embedding model cluster together. This makes setting a "similarity threshold" for your RAG system a nightmare. You might set a threshold of 0.7 to filter out irrelevant docs, only to find that totally irrelevant noise scores a 0.75 because of the "collapsing" nature of the embedding space. This anisotropy also exacerbates the Hubness Problem, where certain vectors (hubs) appear as nearest neighbors to a disproportionately large number of other vectors, regardless of actual semantic relevance. If your query hits a "hub," you get generic garbage results. The "Exact Match" & Lexical Gap Vectors are "dense" representations. They smear the meaning of a word across hundreds of dimensions. This is a feature, not a bug, when you want to match "car" to "automobile." It allows for fuzzy matching and synonym detection. However, it is a catastrophic bug when you need lexical exactness. In engineering contexts, we often search for specific, non-negotiable identifiers: Error Codes: 0xDEADBEEF, E_ACCESSDENIED Product SKUs: SKU-9928-X Variable Names: getUserById vs getUserByName Version Numbers: v2.1.4 vs v2.1.5 Trace IDs: a1b2-c3d4-e5f6 To a vector model, v2.1.4 and v2.1.5 are nearly identical. They appear in identical linguistic contexts (e.g., "upgraded to version X"). They share similar character n-grams. They likely map to almost the same point in vector space. However, to a developer debugging a breaking change, the difference between .4 and .5 is the difference between a working system and a production outage. Case Study: The "ID" Problem We ran an experiment internally at SyncAlly where we tried to retrieve specific Jira tickets using only dense vector search. Query: "Show me ticket ENG-342" Result: The system retrieved tickets ENG-341, ENG-343, and ENG-345. Analysis: The model (OpenAI text-embedding-ada-002 at the time) effectively treated the "ENG-" prefix as the semantic anchor and the numbers as minor noise. Since the descriptions of these tickets were all related to similar engineering tasks, the vector distance between them was negligible. The specific integer "342" did not have enough semantic weight to differentiate itself from "341". This is known as the Lexical Gap. Embeddings capture meaning, but they lose surface form. In many technical domains, the surface form (the exact spelling, the exact number) is the meaning. If you are building a tool for developers, you simply cannot rely on vectors alone to handle unique identifiers. Part III: The Linguistic Failures (Logic is Hard) If math is the engine of RAG failures, linguistics is the fuel. Text embeddings are fundamentally statistical correlations of word co-occurrences. They do not "understand" logic, negation, or compositionality in the way a human or a symbolic logic system does. The Negation Blind Spot One of the most embarrassing and persistent failures of vector search is negation. Query: "Find recipes with no peanuts." Result: Retrieves recipes with peanuts. Query: "Show me functions that are not deprecated." Result: Retrieves a list of deprecated functions. Why does this happen? Consider the sentences "The function is deprecated" and "The function is not deprecated." They share almost all the same words ("The", "function", "is", "deprecated"). In a bag-of-words model, they are nearly identical. Even in sophisticated transformer models like BERT or CLIP, the token "not" acts as a modifier, but it often does not have enough "gravitational pull" to flip the vector to the opposite side of the semantic hyperspace. The vector for the sentence is still dominated by the strong semantic content of "function" and "deprecated". Recent studies on Vision-Language Models (VLMs) and text embeddings have formalized this as a "Negation Blindness." These models frequently interpret negated text pairs as semantically similar because the training data (e.g., Common Crawl) contains far fewer examples of explicit negation compared to affirmative statements. The models learn to associate "deprecated" with the concept of deprecation, but they fail to learn that "not" is a logical operator that inverts that concept. For a developer tool like SyncAlly, this is critical. If a CTO asks, "Which projects are not on track?", and the system retrieves updates about projects that are on track because they contain the words "project" and "track," the trust in the tool evaporates instantly. Polysemy and "Context Flattening" Polysemy refers to words that have multiple meanings depending on context. "Apple" (fruit) vs. "Apple" (company). "Java" (island) vs. "Java" (language). "Driver" (golf) vs. "Driver" (software) vs. "Driver" (car). Modern embeddings like BERT are contextual, meaning they look at surrounding words to determine the specific embedding for a token. So, theoretically, they should handle this. However, RAG pipelines often introduce a failure mode during the chunking phase known as Context Flattening. The Chunking Problem: To fit documents into a vector database, we must chop them into chunks (e.g., 500 tokens). Chunk 1: "…the driver failed to load during the initialization sequence…" Chunk 2: "…causing the application to crash and burn." If you search for "database driver issues," Chunk 1 might be retrieved. But what if the document was actually about a printer driver? Or a JDBC driver? Or a golf simulation game? If the chunk itself doesn't contain the clarifying context (e.g., the words "printer" or "JDBC" appeared in the previous paragraph), the embedding for Chunk 1 becomes ambiguous. The vector represents a generic "driver failure," which might match a query about a totally different type of driver. At SyncAlly, we deal with "Tasks." A "Task" in an engineering context (a Jira ticket) is very different from a "Task" in a generic To-Do app or a "Task" in an operating system process scheduler. If our RAG pipeline treats them as generic English words, we lose domain specificity. The embedding model "flattens" the rich, hierarchical context of the document into a single, flat vector for the chunk, discarding the surrounding knowledge that defines what the chunk actually means. The "Bag of Words" Legacy Despite the advancements of Transformers, embeddings often still behave somewhat like "Bag of Words" models. They struggle with compositionality understanding how the order of words changes meaning. Sentence A: "The dog bit the man." Sentence B: "The man bit the dog." These sentences contain identical words. A simple averaging of word vectors would yield identical sentence embeddings. While modern models (like OpenAI's) use attention mechanisms to capture order, they are still prone to confusion when sentences become complex or when the distinguishing information is subtle. In code search, this is fatal. A.calls(B) is fundamentally different from B.calls(A), yet embeddings often struggle to distinguish the directionality of the relationship. Part IV: The Engineering Failures (Code & Structure) You are building a RAG for developers. Naturally, you want to index code. This is where text embeddings fail spectacularly. Code is not natural language. It is a formal language with strict syntax, hierarchy, and dependency structures that text embedding models simply do not comprehend. Code is Logic, Not Prose Standard embedding models (like OpenAI's text-embedding-3 or ada-002) are trained primarily on massive corpora of natural language text (Wikipedia, Reddit, Common Crawl). They treat code like it is weirdly punctuated English. But code is highly structured logic. The Indentation Failure: In languages like Python, indentation determines the logic and control flow. Snippet A if user.is_admin: delete_database() vs Snippet B if user.is_admin: pass delete_database() To a text embedding model, these two snippets are 99% similar. They share the exact same tokens in almost the same order. But functionally, one is safe (admin only) and the other is catastrophic (deletes database for everyone). A vector search for "safe database deletion" might retrieve the catastrophic code because it matches the keywords "database" and "delete" and "admin," completely missing the semantic significance of the indentation change. The Dependency Disconnect Code does not live in isolation. A function process_payment() in payment.ts depends on UserSchema in models.ts and StripeConfig in config.ts. If you chunk payment.ts and embed it, you lose the connection to UserSchema. Query: "How is the user address validated during payment?" RAG Result: It retrieves process_payment() because it matches "payment." However, the answer-the validation logic-is inside the UserSchema file. The UserSchema file doesn't mention "payment" explicitly; it only mentions "address" and "validation." Therefore, the vector search fails to retrieve the dependency, and the LLM cannot answer the question. This is a failure of retrieval scope. Text embeddings look at files (or chunks) as independent islands. Software engineering is a graph of dependencies. When you ask a question about a function, you often need the context of the functions it calls, the classes it inherits from, and the interfaces it implements. Vectors flatten this graph into a list of disconnected point The Insight: Code retrieval requires Code-Specific Embeddings (like jina-embeddings-v2-code or Salesforce's SFR-Embedding-Code) that have been trained on Abstract Syntax Trees (ASTs) or data flow graphs. Better yet, it requires a Graph-based approach where the dependencies are explicitly modeled as edges in a database, allowing the retrieval system to "walk" from the payment function to the user schema. The "Stale Code" Problem Code changes. Fast. A function that was valid yesterday might be deprecated today. If your RAG pipeline ingests code and documentation, it faces a massive synchronization challenge. Scenario: You refactor auth.ts and rename login() to authenticate(). RAG State: Your vector database still contains the old chunk for login(). Query: "How do I log in?" Failure: The system retrieves the old, hallucinated code snippet for login(). The developer tries it, it fails, and they curse the AI. Keeping a vector index in sync with a high-velocity codebase (Git repo) is an immense engineering challenge. You cannot just "update" a vector easily; you often have to re-chunk and re-embed the file. If you use a sliding window chunking strategy, changing one line of code might shift all the window boundaries, requiring you to re-embed the entire file or even the entire module. Part V: The Context Gap (SyncAlly's Specialty) This section highlights the specific pain point we solve at SyncAlly: The Temporal and Relational Context Gap. This is where "general purpose" RAG tools fail to deliver value for engineering teams. The "Last Week" Problem Time is relative. Humans use relative time constantly. Query: "What was discussed in last week's sprint planning?" Query: "Show me the latest error logs." A vector database stores static chunks of text. It does not natively understand that "last week" is dynamic relative to NOW(). If you indexed a meeting note from 2023 that says "Next week we ship v2," and you search for "shipping v2," that note is retrieved forever, even if v2 shipped years ago. Metadata Filtering is Not Enough: You might think, "I'll just filter by date > NOW() - 7 days." Sure, if the user explicitly asks for a date range and your system is smart enough to parse "last week" into a timestamp. But users are vague. They ask, "What's the status of the new UI?" They implicitly mean "the status as of today." Vector search will retrieve the project kickoff doc from 6 months ago (high semantic match, lots of keywords about "new UI") instead of the Slack update from this morning (lower semantic match because it's short, informal, and says "UI is looking good"). Traditional RAG systems struggle with Temporal Reasoning. They treat all facts as equally valid, regardless of when they were generated. In engineering, facts decay. The "truth" about the system architecture in 2022 is a "lie" in 2024. Unless your retrieval system explicitly prioritizes recency or models the evolution of documents (e.g., using a Versioned Knowledge Graph), you will constantly serve outdated information. The Context Switching Nightmare Engineers switch tools constantly. A typical workflow spans Jira, GitHub, Slack, Notion, and Zoom. The Scenario: A decision is made in a Slack thread ("Let's use Redis for caching"). A ticket is created in Jira ("Implement Cache"). Code is written in GitHub (import redis). The RAG Failure: If you ask "Why are we using Redis?", a vector search might find the import redis code or the Jira ticket. But it likely won't find the reasoning. The reasoning is buried in a Slack thread that doesn't mention the ticket ID or the specific file name. The Slack thread might say: "MySQL is choking on the session data. We need something faster." The code says: const cache = new Redis(); There is no semantic overlap between "MySQL is choking" and new Redis(). A vector search cannot bridge this gap. This is the core value proposition of SyncAlly. We don't just embed text; we map the relationships. "You know that feeling when you can't find where a decision was made? We fixed that." We realized that to answer "Why?", you need to traverse the graph: Code -> Linked Ticket -> Linked Conversation -> Decision. Vectors cannot traverse. They can only match. Without this relational graph, your RAG system is just a glorified Ctrl+F that hallucinates. Part VI: The Solutions (Building a Better RAG) Enough about why it breaks. Let's talk about how to fix it. If you are building a serious RAG application for engineering data, you need to move beyond "Naive RAG" (Chunk -> Embed -> Retrieve). You need a sophisticated, multi-stage retrieval pipeline. Solution 1: Hybrid Search (BM25 + Vectors) This is the single most effective "quick win" for engineering RAG systems. It involves combining the semantic understanding of dense vectors with the keyword precision of BM25 (Best Matching 25). What is BM25? BM25 is the evolution of TF-IDF. It is a probabilistic retrieval algorithm that ranks documents based on the frequency of query terms in the document, relative to their frequency in the entire corpus. Crucially, it handles exact matches perfectly. If you search for 0x80040115, BM25 will find the document that contains that exact string, even if the vector model thinks it's noise. How Hybrid Search Works: Dense Retrieval: Run the query through your vector database to find semantically similar documents (e.g., "authentication error"). Sparse Retrieval: Run the query through a BM25 index to find keyword matches (e.g., "E_AUTH_FAIL"). Reciprocal Rank Fusion (RRF): Combine the two lists of results. RRF works by taking the rank of a document in each list and calculating a new score: $$Score(d) = \sum_{r \in R} \frac{1}{k + rank(d, r)}$$ Where $rank(d, r)$ is the position of document $d$ in result list $r$, and $k$ is a constant (usually 60). This ensures that a document that appears in both lists gets a huge boost, while a document that is a perfect exact match (BM25 #1) but a poor semantic match still bubbles up to the top. Implementation Snippet (Python): from rank_bm25 import BM25Okapi from langchain_community.vectorstores import FAISS from langchain_openai import OpenAIEmbeddings 1. Setup BM25 (Sparse Index) In production, use a library like Elasticsearch or MeiliSearch for this tokenized_corpus = [doc.page_content.split() for doc in documents] bm25 = BM25Okapi(tokenized_corpus) 2. Setup Vector Search (Dense Index) vector_store = FAISS.from_documents(documents, OpenAIEmbeddings()) def hybrid_search(query, k=5): # Get BM25 scores bm25_scores = bm25.get_scores(query.split()) # Get indices of top k BM25 results top_bm25_indices = sorted(range(len(bm25_scores)), key=lambda i: bm25_scores[i], reverse=True)[:k] # Get Vector results # Returns (Document, score) tuples vector_docs = vector_store.similarity_search_with_score(query, k=k) # Fuse (Simplified RRF Logic) # In a real app, you would map vector_docs back to IDs and calculate RRF scores combined_results = deduplicate_and_fuse(top_bm25_indices, vector_docs) return combined_results Enter fullscreen mode Exit fullscreen mode Why developers love this: It solves the "SKU problem," the "Error Code problem," and the "ID problem" instantly. It makes the search feel "smart" (semantic) but "reliable" (exact). Solution 2: Late Interaction & Re-ranking (ColBERT) Sometimes, Hybrid search isn't enough. You need the model to look at the query and the document together to understand nuance. Standard embeddings (Bi-Encoders) compress the query and document independently. This causes information loss. Cross-Encoders (Re-ranking): Instead of just trusting the vector DB, you retrieve a broad set of candidates (e.g., top 50), and then pass them through a Cross-Encoder (like ms-marco-MiniLM-L-6-v2 or Cohere's Rerank API). This model takes (Query, Document) as a single input pair and outputs a relevance score (0 to 1). It can "see" how the specific words in the query interact with the words in the document. Pros: Drastically improves accuracy. Cons: Very slow. You cannot run a Cross-Encoder on your entire database; only on the top N results. ColBERT (Late Interaction): ColBERT (Contextualized Late Interaction over BERT) is a fascinating middle ground. Instead of compressing a document into one vector, it keeps vectors for every token in the document. When you search, it performs "late interaction," matching every query token vector to every document token vector using a "MaxSim" operation. This preserves fine-grained details that usually get lost in a single vector. If your query is "bug in the payment retry logic," ColBERT can explicitly match "payment," "retry," and "logic" to the corresponding parts of the document, rather than hoping a single vector captures the whole idea.24 Trade-off: ColBERT is storage-intensive. Your index size will balloon because you are storing a vector for every single word in your corpus. But for "needle in a haystack" engineering queries, it is often necessary. Solution 3: GraphRAG (The Knowledge Graph Approach) This is the endgame. This is where SyncAlly focuses its R&D. GraphRAG combines Knowledge Graphs (KG) with LLMs. Instead of just chunking text, you use an LLM to extract entities and relationships during ingestion. Extraction Phase: An LLM scans your documents and identifies: Entities: PostgreSQL, Kislay (Founder), AuthService, Ticket-123. Relationships: Kislay CREATED AuthService. AuthService USES PostgreSQL. Ticket-123 MODIFIES AuthService. Querying Phase: When you ask "What databases does Kislay use?", the system doesn't just look for text similarity. It traverses the graph: Kislay -> CREATED -> AuthService -> USES -> PostgreSQL. Why GraphRAG Wins: Multi-hop Reasoning: It can connect dots across different documents. It can link a Slack message to a Jira ticket to a GitHub commit, answering "Why did we change this code?". Global Summarization: It can answer high-level questions like "What are the main themes in our sprint retrospectives?" by aggregating "communities" of nodes in the graph (e.g., detecting a cluster of nodes related to "database latency"). Explainability: It can show you the path it took to get the answer. "I found this answer because Kislay is linked to AuthService which is linked to Postgres." The Cost: Building a Knowledge Graph is hard. It requires maintaining a schema (ontology), performing entity resolution (knowing that "Phil" and "Philip" are the same person), and paying for expensive LLM calls to perform the extraction. At SyncAlly, we handle this complexity for you. We automatically build the Knowledge Graph from your connected tools, identifying entities like Tickets, PRs, and Meetings, and linking them based on mentions and timestamps. This gives you the power of GraphRAG without needing to write Cypher queries or manage a Neo4j instance. Part VII: Real-World Engineering Costs (The Horror Stories) Before you go and build your own custom RAG pipeline using open-source tools, let's talk about the hidden costs that the tutorials conveniently skip. "Building a RAG demo takes a weekend. Building a production RAG takes a year." The Maintenance Tax & Data Cleaning You will spend 80% of your time on Data Cleaning and Chunking Strategies, not on AI. PDF Parsing: Have you tried parsing a two-column PDF with tables? It is a nightmare. The text comes out garbled ("Column 1 Row 1 Column 2 Row 1…"), and your embeddings turn to trash. If the input text is garbage, the vector is garbage. Stale Data: Your documentation changes every day. How do you update the vectors? If you delete a Confluence page, do you remember to delete the vector? If you update a single paragraph, do you re-embed the whole document? This synchronization logic is painful and prone to bugs. Legacy Pipelines: As your data grows, your ingestion pipeline becomes a complex distributed system. You need queues (Kafka/RabbitMQ), retry logic for failed embeddings, and monitoring for API rate limits. Debugging Hallucinations When your RAG lies, how do you debug it? Was the retrieval bad? (Did we find the wrong docs?) Was the context window too small? (Did we cut off the answer?) Did the LLM just make it up? You need sophisticated Observability tools (like LangSmith, Arize Phoenix, or custom logging) to trace the exact chunks retrieved for every query. You need to curate "Negative Examples" queries that should return "I don't know" to test if your system hallucinates an answer when no relevant data exists. Case Study: The Silent Failure We once saw a RAG system that failed silently because a "knowledge base source" went offline. The system didn't throw an error; it just retrieved documents from the remaining sources (which were irrelevant) and the LLM confidently hallucinated an answer based on them. We had to implement "Guardrails" that check for source health before generating an answer. The "Not My Job" Problem Who owns the RAG pipeline? The AI Team? They build the prototype but don't want to carry the pager for the vector database. The Platform Team? They don't know how to optimize chunking strategies or debug embedding drift. The DevOps Team? They don't want to manage a new stateful infrastructure component (Vector DB like Milvus or Weaviate) alongside their Postgres and Redis instances. It usually falls into a black hole of ownership, leading to "Tech Debt" that accumulates rapidly. This is why we built SyncAlly. We believe developers shouldn't have to be RAG engineers just to get answers from their own data. We abstract away the vector stores, the graph construction, the embedding pipelines, and the synchronization logic. You just connect your GitHub and Slack, and it works. We handle the "plumbing" so you can focus on shipping code. Conclusion: The Future is Hybrid and Structured Text embeddings are a powerful tool, but they are not a silver bullet. They are "fuzzy" matching engines in a domain (software engineering) that demands precision, logic, and structure. Relying on them exclusively is a recipe for frustration. If you are building RAG applications today, you must follow these principles: Don't rely on vectors alone. Implement Hybrid Search (BM25 + Vectors) to capture exact keyword matches and identifiers. Respect structure. If you have metadata (dates, authors, tags), use it! Filter by metadata before or during your search to handle temporal and categorical queries. Consider the Graph. For complex, multi-hop questions ("Why did we do X?" or "How does A impact B?"), vectors will fail. You need a Knowledge Graph to model relationships. And if you don't want to build all of this yourself if you just want to stop searching through 50 browser tabs to find that one API key or design decision give SyncAlly a look. We've done the hard work of fusing GraphRAG, Vector Search, and Hybrid Retrieval into a unified workspace that actually understands your engineering context. We turn your scattered tools into a coherent knowledge base. Stop context switching. Start shipping. Discussion Devs, be honest: How many times has your "AI Search" returned completely irrelevant results because of a keyword mismatch? Have you tried implementing Hybrid Search yet? Or are you sticking with Ctrl+F? Drop your war stories (and your horror stories) in the comments below! 👇 Top comments (0) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse Kumar Kislay Follow Joined Nov 12, 2025 More from Kumar Kislay How do you keep engineering context alive when requirements change? 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https://www.highlight.io/docs/general/product-features/general-features/search | Search Star us on GitHub Star Docs Sign in Sign up General Docs Welcome to highlight.io Get Started Roadmap Company Values Compliance & Security Open Source Contributing Overview GraphQL Backend Frontend (app.highlight.io) Landing Site (highlight.io) Documentation End to End SDK Example Apps Adding an SDK Application Architecture GitHub Code Spaces Code Style Good First Issues Self-hosting Self-hosted [Dev] Self-hosted [Hobby] Self-hosted [Enterprise] Telemetry Our Competitors Product Philosophy Product Features Session Replay Overview Canvas & Iframe Dev-tool Window Recording Tracking Users & Recording Events Filtering Sessions GraphQL Live Mode Performance Impact Player Session Caching Rage Clicks Request Proxying Session Search Extracting the Session URL Session Search Deep Linking Shadow Dom + Web Components Error Monitoring Overview Enhancing Errors with GitHub Error Search Filtering Errors Grouping Errors Managing Errors Manually Reporting Errors Sourcemaps General Features Overview Alerts Comments Digests Environments Search Segments Services Webhooks Logging Overview Log Alerts Log Search Tracing Overview Trace Search Dashboards Overview Dashboard Management Metrics Tutorials Service Latency Web Vitals & Page Speed User Engagement User Analytics Graphing Drilldown Event Search Dashboard Variables SQL Editor Metrics (beta) Overview Frequently Asked Questions. 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Integrations Microsoft Teams self-hosted Hobby deployment guide. Traefik SSL Proxying. Docs Home SDK Client SDK API Reference Cloudflare Worker SDK API Reference Go SDK API Reference Hono SDK API Reference Java SDK API Reference Next.JS SDK API Reference Node.JS SDK API Reference Python SDK API Reference Ruby SDK API Reference Rust SDK API Reference Docs / Highlight Docs / Product Features / Backend General Features / Search Search Basic Syntax A search query is composed of one or more expressions . Each expression can be a comparison between a key and a value , or a logical combination of other expressions. span_name=gorm.Query You can also enter a seach value without a key to search on a default key. For logs, this would be the message and on traces it would be the span_name . gorm.Query Any custom attributes you send in sessions, logs, and traces can be filters on as well. user_id=42 Keys and Values Keys are identifiers, which can include any combination of alphanumeric characters, underscores ( _ ), periods ( . ), dashes ( - ), and asterisks ( * ). Values can be strings with any character. In order to use spaces or special characters, you must enclose the string in quotes ( " , ' ). Wildcards You can use * in values to match on part of a pattern. span_name=gorm.* matches all span_name values that start with gorm. span_name=*.Query matches all span_name values that end with .Query span_name=*orm* matches all values that contain orm Note that if you want to use a value with a space or special character, you will need to wrap the value in quotations. tag="*query error*" visited-url="https://app.highlight.io/*" Regex Expressions You can search with regex expressions by using the matches query operator =\[your regex here]\ . clickTextContent=/\w.+\w/ matches all clickTextContent that start and end with any word browser_version=/\d\.\d\.\d/ matches all browser_versions in the form [0-9].[0-9].[0-9] Note that if you want to use a regex expression with a space or special character, you will need to wrap the value in quotations. tag="/\w \w/" visited-url="/https://app.highlight.io/\d/.+/" Comparisons Comparisons are made using operators . The following operators are supported: = - Equal to != - Not equal to < - Less than <= - Less than or equal to > - Greater than >= - Greater than or equal to Exist & Not Exist You can search if a key exists or does not exist with the exists operator. For example, if you wanted all the traces with a connected session, you would do use the following query: secure_session_id exists The exists also works with the not keyword. An example is when you only want the root level spans when searching traces, then you would use this query parent_span_id not exists Logical Combinations Expressions can be combined using the logical operators AND , OR , and NOT . AND - Both expressions must be true OR - At least one of the expressions must be true NOT - The following expression must be false Note that there is an implicit AND between all filters unless you specify an OR directly. For example: service_name=private-graph span_name=gorm.Query This is equivalent to: service_name=private-graph AND span_name=gorm.Query Grouping Expressions Expressions can be grouped using parentheses ( and ) . For example: (key1=value1 AND key2=value2) OR key3=value3 You can also use parentheses to group values in an expression: service_name=(private-graph OR public-graph) Query Examples Here are some examples of valid search queries: service_name=private-graph service_name=public-graph AND span_name!=gorm.Query service_name=worker OR span_name=gorm.Query service_name!=private-graph (service_name=public-graph AND span_name=gorm.Query) OR duration>=100000 Search Segments All of our search pages allow you to save a search and reuse it later. We call these segments . Create segments for common sets of filters you want to use across Highlight. Special characters When using special characters in a value, the value should be wrapped in quotations. Special characters include spaces, operator characters ( ! , = , : , < , > ), and parentheses. More Reading See the links below for more details on searching in specific parts of the product. Session search Error search Log Search Trace Search Event search Environments Segments Community / Support Suggest Edits? Follow us! [object Object] | 2026-01-13T08:48:58 |
https://dev.to/t/jokes/page/2 | jokes Page 2 - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close jokes Follow Hide plz post the lols Create Post submission guidelines no spam don't be offensive (sexist, racist, homophobic, crude, etc.), the DEV code of conduct is still in place! make the jokes programming related-ish Older #jokes posts 1 2 3 4 5 6 7 8 9 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu 💔 Love in the Time of Microservices. Madhu Madhu Madhu Follow Oct 24 '25 💔 Love in the Time of Microservices. # jokes # springboot # funny # programming Comments Add Comment 2 min read Meme Monday Ben Halpern Ben Halpern Ben Halpern Follow Oct 6 '25 Meme Monday # discuss # watercooler # jokes 32 reactions Comments 39 comments 1 min read We Had Scrum Masters. 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Get Ready for the Vibe Code Cleanup Specialist # jokes # agile # vibecoding 1 reaction Comments 1 comment 3 min read 🐶Spring Boot, but Every Exception Is a Dog Breed Madhu Madhu Madhu Follow Oct 15 '25 🐶Spring Boot, but Every Exception Is a Dog Breed # jokes # java # springboot 9 reactions Comments 2 comments 2 min read How Shipping Code in a Rush Can Cause Uncalculated Losses DivyanshuLohani DivyanshuLohani DivyanshuLohani Follow Sep 9 '25 How Shipping Code in a Rush Can Cause Uncalculated Losses # jokes # testing # softwareengineering # product Comments Add Comment 6 min read Meme Monday Ben Halpern Ben Halpern Ben Halpern Follow Sep 29 '25 Meme Monday # discuss # jokes # watercooler 27 reactions Comments 36 comments 1 min read Meme Monday Ben Halpern Ben Halpern Ben Halpern Follow Sep 22 '25 Meme Monday # discuss # watercooler # jokes 31 reactions Comments 47 comments 1 min read Meme Monday Ben Halpern Ben Halpern Ben Halpern Follow Sep 15 '25 Meme Monday # discuss # watercooler # jokes 34 reactions Comments 51 comments 1 min read What If CSS Properties Had Personalities Dennis Persson Dennis Persson Dennis Persson Follow Sep 28 '25 What If CSS Properties Had Personalities # jokes # webdev # css # programming 27 reactions Comments 4 comments 4 min read Meme Monday Ben Halpern Ben Halpern Ben Halpern Follow Sep 8 '25 Meme Monday # discuss # watercooler # jokes 39 reactions Comments 93 comments 1 min read Meme Monday Ben Halpern Ben Halpern Ben Halpern Follow Sep 1 '25 Meme Monday # discuss # jokes # watercooler 57 reactions Comments 109 comments 1 min read Meme Monday Ben Halpern Ben Halpern Ben Halpern Follow Aug 25 '25 Meme Monday # discuss # jokes # watercooler 17 reactions Comments 45 comments 1 min read Meme Monday Ben Halpern Ben Halpern Ben Halpern Follow Aug 18 '25 Meme Monday # discuss # jokes # watercooler 26 reactions Comments 58 comments 1 min read Yeah, totally not a "Back-To-School" Challenge Dev.To AspXone AspXone AspXone Follow Aug 29 '25 Yeah, totally not a "Back-To-School" Challenge Dev.To # jokes # herokuchallenge 3 reactions Comments 7 comments 1 min read I made a professional-grade Brainfuck IDE. 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Shivam Chamoli Shivam Chamoli Shivam Chamoli Follow Oct 11 '24 How to Choose the Right Cloud Certification? # cloudcertification # azurecloud # azure # infosectrain 49 reactions Comments Add Comment 3 min read Boosting Your Knowledge with Microsoft SC-900, AZ-900, and MS-900 Fundamentals Trainings Boris Gigovic Boris Gigovic Boris Gigovic Follow Aug 30 '24 Boosting Your Knowledge with Microsoft SC-900, AZ-900, and MS-900 Fundamentals Trainings # microsoftcloud # cloudcertification # cloudtraining # learnmicrosoftazure 1 reaction Comments 5 comments 5 min read AWS Cloud Practitioner Kuljot Biring Kuljot Biring Kuljot Biring Follow Jan 27 '24 AWS Cloud Practitioner # aws # awscertified # awscloud # cloudcertification Comments Add Comment 1 min read The Cloud Resume Challenge: Conquering the Cloud Mohammad Waseq Mohammad Waseq Mohammad Waseq Follow Nov 1 '23 The Cloud Resume Challenge: Conquering the Cloud # aws # cloudcertification # mycloudstory # awsjourney 9 reactions Comments 1 comment 5 min read Which Cloud Certification is the Best Fit for You? 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https://docs.python.org/3/glossary.html#term-... | Glossary — Python 3.14.2 documentation Theme Auto Light Dark Previous topic Deprecations Next topic About this documentation This page Report a bug Show source Navigation index modules | next | previous | Python » 3.14.2 Documentation » Glossary | Theme Auto Light Dark | Glossary ¶ >>> ¶ The default Python prompt of the interactive shell. Often seen for code examples which can be executed interactively in the interpreter. ... ¶ Can refer to: The default Python prompt of the interactive shell when entering the code for an indented code block, when within a pair of matching left and right delimiters (parentheses, square brackets, curly braces or triple quotes), or after specifying a decorator. The three dots form of the Ellipsis object. abstract base class ¶ Abstract base classes complement duck-typing by providing a way to define interfaces when other techniques like hasattr() would be clumsy or subtly wrong (for example with magic methods ). ABCs introduce virtual subclasses, which are classes that don’t inherit from a class but are still recognized by isinstance() and issubclass() ; see the abc module documentation. Python comes with many built-in ABCs for data structures (in the collections.abc module), numbers (in the numbers module), streams (in the io module), import finders and loaders (in the importlib.abc module). You can create your own ABCs with the abc module. annotate function ¶ A function that can be called to retrieve the annotations of an object. This function is accessible as the __annotate__ attribute of functions, classes, and modules. Annotate functions are a subset of evaluate functions . annotation ¶ A label associated with a variable, a class attribute or a function parameter or return value, used by convention as a type hint . Annotations of local variables cannot be accessed at runtime, but annotations of global variables, class attributes, and functions can be retrieved by calling annotationlib.get_annotations() on modules, classes, and functions, respectively. See variable annotation , function annotation , PEP 484 , PEP 526 , and PEP 649 , which describe this functionality. Also see Annotations Best Practices for best practices on working with annotations. argument ¶ A value passed to a function (or method ) when calling the function. There are two kinds of argument: keyword argument : an argument preceded by an identifier (e.g. name= ) in a function call or passed as a value in a dictionary preceded by ** . For example, 3 and 5 are both keyword arguments in the following calls to complex() : complex ( real = 3 , imag = 5 ) complex ( ** { 'real' : 3 , 'imag' : 5 }) positional argument : an argument that is not a keyword argument. Positional arguments can appear at the beginning of an argument list and/or be passed as elements of an iterable preceded by * . For example, 3 and 5 are both positional arguments in the following calls: complex ( 3 , 5 ) complex ( * ( 3 , 5 )) Arguments are assigned to the named local variables in a function body. See the Calls section for the rules governing this assignment. Syntactically, any expression can be used to represent an argument; the evaluated value is assigned to the local variable. See also the parameter glossary entry, the FAQ question on the difference between arguments and parameters , and PEP 362 . asynchronous context manager ¶ An object which controls the environment seen in an async with statement by defining __aenter__() and __aexit__() methods. Introduced by PEP 492 . asynchronous generator ¶ A function which returns an asynchronous generator iterator . It looks like a coroutine function defined with async def except that it contains yield expressions for producing a series of values usable in an async for loop. Usually refers to an asynchronous generator function, but may refer to an asynchronous generator iterator in some contexts. In cases where the intended meaning isn’t clear, using the full terms avoids ambiguity. An asynchronous generator function may contain await expressions as well as async for , and async with statements. asynchronous generator iterator ¶ An object created by an asynchronous generator function. This is an asynchronous iterator which when called using the __anext__() method returns an awaitable object which will execute the body of the asynchronous generator function until the next yield expression. Each yield temporarily suspends processing, remembering the execution state (including local variables and pending try-statements). When the asynchronous generator iterator effectively resumes with another awaitable returned by __anext__() , it picks up where it left off. See PEP 492 and PEP 525 . asynchronous iterable ¶ An object, that can be used in an async for statement. Must return an asynchronous iterator from its __aiter__() method. Introduced by PEP 492 . asynchronous iterator ¶ An object that implements the __aiter__() and __anext__() methods. __anext__() must return an awaitable object. async for resolves the awaitables returned by an asynchronous iterator’s __anext__() method until it raises a StopAsyncIteration exception. Introduced by PEP 492 . atomic operation ¶ An operation that appears to execute as a single, indivisible step: no other thread can observe it half-done, and its effects become visible all at once. Python does not guarantee that high-level statements are atomic (for example, x += 1 performs multiple bytecode operations and is not atomic). Atomicity is only guaranteed where explicitly documented. See also race condition and data race . attached thread state ¶ A thread state that is active for the current OS thread. When a thread state is attached, the OS thread has access to the full Python C API and can safely invoke the bytecode interpreter. Unless a function explicitly notes otherwise, attempting to call the C API without an attached thread state will result in a fatal error or undefined behavior. A thread state can be attached and detached explicitly by the user through the C API, or implicitly by the runtime, including during blocking C calls and by the bytecode interpreter in between calls. On most builds of Python, having an attached thread state implies that the caller holds the GIL for the current interpreter, so only one OS thread can have an attached thread state at a given moment. In free-threaded builds of Python, threads can concurrently hold an attached thread state, allowing for true parallelism of the bytecode interpreter. attribute ¶ A value associated with an object which is usually referenced by name using dotted expressions. For example, if an object o has an attribute a it would be referenced as o.a . It is possible to give an object an attribute whose name is not an identifier as defined by Names (identifiers and keywords) , for example using setattr() , if the object allows it. Such an attribute will not be accessible using a dotted expression, and would instead need to be retrieved with getattr() . awaitable ¶ An object that can be used in an await expression. Can be a coroutine or an object with an __await__() method. See also PEP 492 . BDFL ¶ Benevolent Dictator For Life, a.k.a. Guido van Rossum , Python’s creator. binary file ¶ A file object able to read and write bytes-like objects . Examples of binary files are files opened in binary mode ( 'rb' , 'wb' or 'rb+' ), sys.stdin.buffer , sys.stdout.buffer , and instances of io.BytesIO and gzip.GzipFile . See also text file for a file object able to read and write str objects. borrowed reference ¶ In Python’s C API, a borrowed reference is a reference to an object, where the code using the object does not own the reference. It becomes a dangling pointer if the object is destroyed. For example, a garbage collection can remove the last strong reference to the object and so destroy it. Calling Py_INCREF() on the borrowed reference is recommended to convert it to a strong reference in-place, except when the object cannot be destroyed before the last usage of the borrowed reference. The Py_NewRef() function can be used to create a new strong reference . bytes-like object ¶ An object that supports the Buffer Protocol and can export a C- contiguous buffer. This includes all bytes , bytearray , and array.array objects, as well as many common memoryview objects. Bytes-like objects can be used for various operations that work with binary data; these include compression, saving to a binary file, and sending over a socket. Some operations need the binary data to be mutable. The documentation often refers to these as “read-write bytes-like objects”. Example mutable buffer objects include bytearray and a memoryview of a bytearray . Other operations require the binary data to be stored in immutable objects (“read-only bytes-like objects”); examples of these include bytes and a memoryview of a bytes object. bytecode ¶ Python source code is compiled into bytecode, the internal representation of a Python program in the CPython interpreter. The bytecode is also cached in .pyc files so that executing the same file is faster the second time (recompilation from source to bytecode can be avoided). This “intermediate language” is said to run on a virtual machine that executes the machine code corresponding to each bytecode. Do note that bytecodes are not expected to work between different Python virtual machines, nor to be stable between Python releases. A list of bytecode instructions can be found in the documentation for the dis module . callable ¶ A callable is an object that can be called, possibly with a set of arguments (see argument ), with the following syntax: callable ( argument1 , argument2 , argumentN ) A function , and by extension a method , is a callable. An instance of a class that implements the __call__() method is also a callable. callback ¶ A subroutine function which is passed as an argument to be executed at some point in the future. class ¶ A template for creating user-defined objects. Class definitions normally contain method definitions which operate on instances of the class. class variable ¶ A variable defined in a class and intended to be modified only at class level (i.e., not in an instance of the class). closure variable ¶ A free variable referenced from a nested scope that is defined in an outer scope rather than being resolved at runtime from the globals or builtin namespaces. May be explicitly defined with the nonlocal keyword to allow write access, or implicitly defined if the variable is only being read. For example, in the inner function in the following code, both x and print are free variables , but only x is a closure variable : def outer (): x = 0 def inner (): nonlocal x x += 1 print ( x ) return inner Due to the codeobject.co_freevars attribute (which, despite its name, only includes the names of closure variables rather than listing all referenced free variables), the more general free variable term is sometimes used even when the intended meaning is to refer specifically to closure variables. complex number ¶ An extension of the familiar real number system in which all numbers are expressed as a sum of a real part and an imaginary part. Imaginary numbers are real multiples of the imaginary unit (the square root of -1 ), often written i in mathematics or j in engineering. Python has built-in support for complex numbers, which are written with this latter notation; the imaginary part is written with a j suffix, e.g., 3+1j . To get access to complex equivalents of the math module, use cmath . Use of complex numbers is a fairly advanced mathematical feature. If you’re not aware of a need for them, it’s almost certain you can safely ignore them. concurrency ¶ The ability of a computer program to perform multiple tasks at the same time. Python provides libraries for writing programs that make use of different forms of concurrency. asyncio is a library for dealing with asynchronous tasks and coroutines. threading provides access to operating system threads and multiprocessing to operating system processes. Multi-core processors can execute threads and processes on different CPU cores at the same time (see parallelism ). concurrent modification ¶ When multiple threads modify shared data at the same time. Concurrent modification without proper synchronization can cause race conditions , and might also trigger a data race , data corruption, or both. context ¶ This term has different meanings depending on where and how it is used. Some common meanings: The temporary state or environment established by a context manager via a with statement. The collection of keyvalue bindings associated with a particular contextvars.Context object and accessed via ContextVar objects. Also see context variable . A contextvars.Context object. Also see current context . context management protocol ¶ The __enter__() and __exit__() methods called by the with statement. See PEP 343 . context manager ¶ An object which implements the context management protocol and controls the environment seen in a with statement. See PEP 343 . context variable ¶ A variable whose value depends on which context is the current context . Values are accessed via contextvars.ContextVar objects. Context variables are primarily used to isolate state between concurrent asynchronous tasks. contiguous ¶ A buffer is considered contiguous exactly if it is either C-contiguous or Fortran contiguous . Zero-dimensional buffers are C and Fortran contiguous. In one-dimensional arrays, the items must be laid out in memory next to each other, in order of increasing indexes starting from zero. In multidimensional C-contiguous arrays, the last index varies the fastest when visiting items in order of memory address. However, in Fortran contiguous arrays, the first index varies the fastest. coroutine ¶ Coroutines are a more generalized form of subroutines. Subroutines are entered at one point and exited at another point. Coroutines can be entered, exited, and resumed at many different points. They can be implemented with the async def statement. See also PEP 492 . coroutine function ¶ A function which returns a coroutine object. A coroutine function may be defined with the async def statement, and may contain await , async for , and async with keywords. These were introduced by PEP 492 . CPython ¶ The canonical implementation of the Python programming language, as distributed on python.org . The term “CPython” is used when necessary to distinguish this implementation from others such as Jython or IronPython. current context ¶ The context ( contextvars.Context object) that is currently used by ContextVar objects to access (get or set) the values of context variables . Each thread has its own current context. Frameworks for executing asynchronous tasks (see asyncio ) associate each task with a context which becomes the current context whenever the task starts or resumes execution. cyclic isolate ¶ A subgroup of one or more objects that reference each other in a reference cycle, but are not referenced by objects outside the group. The goal of the cyclic garbage collector is to identify these groups and break the reference cycles so that the memory can be reclaimed. data race ¶ A situation where multiple threads access the same memory location concurrently, at least one of the accesses is a write, and the threads do not use any synchronization to control their access. Data races lead to non-deterministic behavior and can cause data corruption. Proper use of locks and other synchronization primitives prevents data races. Note that data races can only happen in native code, but that native code might be exposed in a Python API. See also race condition and thread-safe . deadlock ¶ A situation in which two or more tasks (threads, processes, or coroutines) wait indefinitely for each other to release resources or complete actions, preventing any from making progress. For example, if thread A holds lock 1 and waits for lock 2, while thread B holds lock 2 and waits for lock 1, both threads will wait indefinitely. In Python this often arises from acquiring multiple locks in conflicting orders or from circular join/await dependencies. Deadlocks can be avoided by always acquiring multiple locks in a consistent order. See also lock and reentrant . decorator ¶ A function returning another function, usually applied as a function transformation using the @wrapper syntax. Common examples for decorators are classmethod() and staticmethod() . The decorator syntax is merely syntactic sugar, the following two function definitions are semantically equivalent: def f ( arg ): ... f = staticmethod ( f ) @staticmethod def f ( arg ): ... The same concept exists for classes, but is less commonly used there. See the documentation for function definitions and class definitions for more about decorators. descriptor ¶ Any object which defines the methods __get__() , __set__() , or __delete__() . When a class attribute is a descriptor, its special binding behavior is triggered upon attribute lookup. Normally, using a.b to get, set or delete an attribute looks up the object named b in the class dictionary for a , but if b is a descriptor, the respective descriptor method gets called. Understanding descriptors is a key to a deep understanding of Python because they are the basis for many features including functions, methods, properties, class methods, static methods, and reference to super classes. For more information about descriptors’ methods, see Implementing Descriptors or the Descriptor How To Guide . dictionary ¶ An associative array, where arbitrary keys are mapped to values. The keys can be any object with __hash__() and __eq__() methods. Called a hash in Perl. dictionary comprehension ¶ A compact way to process all or part of the elements in an iterable and return a dictionary with the results. results = {n: n ** 2 for n in range(10)} generates a dictionary containing key n mapped to value n ** 2 . See Displays for lists, sets and dictionaries . dictionary view ¶ The objects returned from dict.keys() , dict.values() , and dict.items() are called dictionary views. They provide a dynamic view on the dictionary’s entries, which means that when the dictionary changes, the view reflects these changes. To force the dictionary view to become a full list use list(dictview) . See Dictionary view objects . docstring ¶ A string literal which appears as the first expression in a class, function or module. While ignored when the suite is executed, it is recognized by the compiler and put into the __doc__ attribute of the enclosing class, function or module. Since it is available via introspection, it is the canonical place for documentation of the object. duck-typing ¶ A programming style which does not look at an object’s type to determine if it has the right interface; instead, the method or attribute is simply called or used (“If it looks like a duck and quacks like a duck, it must be a duck.”) By emphasizing interfaces rather than specific types, well-designed code improves its flexibility by allowing polymorphic substitution. Duck-typing avoids tests using type() or isinstance() . (Note, however, that duck-typing can be complemented with abstract base classes .) Instead, it typically employs hasattr() tests or EAFP programming. dunder ¶ An informal short-hand for “double underscore”, used when talking about a special method . For example, __init__ is often pronounced “dunder init”. EAFP ¶ Easier to ask for forgiveness than permission. This common Python coding style assumes the existence of valid keys or attributes and catches exceptions if the assumption proves false. This clean and fast style is characterized by the presence of many try and except statements. The technique contrasts with the LBYL style common to many other languages such as C. evaluate function ¶ A function that can be called to evaluate a lazily evaluated attribute of an object, such as the value of type aliases created with the type statement. expression ¶ A piece of syntax which can be evaluated to some value. In other words, an expression is an accumulation of expression elements like literals, names, attribute access, operators or function calls which all return a value. In contrast to many other languages, not all language constructs are expressions. There are also statement s which cannot be used as expressions, such as while . Assignments are also statements, not expressions. extension module ¶ A module written in C or C++, using Python’s C API to interact with the core and with user code. f-string ¶ f-strings ¶ String literals prefixed with f or F are commonly called “f-strings” which is short for formatted string literals . See also PEP 498 . file object ¶ An object exposing a file-oriented API (with methods such as read() or write() ) to an underlying resource. Depending on the way it was created, a file object can mediate access to a real on-disk file or to another type of storage or communication device (for example standard input/output, in-memory buffers, sockets, pipes, etc.). File objects are also called file-like objects or streams . There are actually three categories of file objects: raw binary files , buffered binary files and text files . Their interfaces are defined in the io module. The canonical way to create a file object is by using the open() function. file-like object ¶ A synonym for file object . filesystem encoding and error handler ¶ Encoding and error handler used by Python to decode bytes from the operating system and encode Unicode to the operating system. The filesystem encoding must guarantee to successfully decode all bytes below 128. If the file system encoding fails to provide this guarantee, API functions can raise UnicodeError . The sys.getfilesystemencoding() and sys.getfilesystemencodeerrors() functions can be used to get the filesystem encoding and error handler. The filesystem encoding and error handler are configured at Python startup by the PyConfig_Read() function: see filesystem_encoding and filesystem_errors members of PyConfig . See also the locale encoding . finder ¶ An object that tries to find the loader for a module that is being imported. There are two types of finder: meta path finders for use with sys.meta_path , and path entry finders for use with sys.path_hooks . See Finders and loaders and importlib for much more detail. floor division ¶ Mathematical division that rounds down to nearest integer. The floor division operator is // . For example, the expression 11 // 4 evaluates to 2 in contrast to the 2.75 returned by float true division. Note that (-11) // 4 is -3 because that is -2.75 rounded downward . See PEP 238 . free threading ¶ A threading model where multiple threads can run Python bytecode simultaneously within the same interpreter. This is in contrast to the global interpreter lock which allows only one thread to execute Python bytecode at a time. See PEP 703 . free variable ¶ Formally, as defined in the language execution model , a free variable is any variable used in a namespace which is not a local variable in that namespace. See closure variable for an example. Pragmatically, due to the name of the codeobject.co_freevars attribute, the term is also sometimes used as a synonym for closure variable . function ¶ A series of statements which returns some value to a caller. It can also be passed zero or more arguments which may be used in the execution of the body. See also parameter , method , and the Function definitions section. function annotation ¶ An annotation of a function parameter or return value. Function annotations are usually used for type hints : for example, this function is expected to take two int arguments and is also expected to have an int return value: def sum_two_numbers ( a : int , b : int ) -> int : return a + b Function annotation syntax is explained in section Function definitions . See variable annotation and PEP 484 , which describe this functionality. Also see Annotations Best Practices for best practices on working with annotations. __future__ ¶ A future statement , from __future__ import <feature> , directs the compiler to compile the current module using syntax or semantics that will become standard in a future release of Python. The __future__ module documents the possible values of feature . By importing this module and evaluating its variables, you can see when a new feature was first added to the language and when it will (or did) become the default: >>> import __future__ >>> __future__ . division _Feature((2, 2, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0), 8192) garbage collection ¶ The process of freeing memory when it is not used anymore. Python performs garbage collection via reference counting and a cyclic garbage collector that is able to detect and break reference cycles. The garbage collector can be controlled using the gc module. generator ¶ A function which returns a generator iterator . It looks like a normal function except that it contains yield expressions for producing a series of values usable in a for-loop or that can be retrieved one at a time with the next() function. Usually refers to a generator function, but may refer to a generator iterator in some contexts. In cases where the intended meaning isn’t clear, using the full terms avoids ambiguity. generator iterator ¶ An object created by a generator function. Each yield temporarily suspends processing, remembering the execution state (including local variables and pending try-statements). When the generator iterator resumes, it picks up where it left off (in contrast to functions which start fresh on every invocation). generator expression ¶ An expression that returns an iterator . It looks like a normal expression followed by a for clause defining a loop variable, range, and an optional if clause. The combined expression generates values for an enclosing function: >>> sum ( i * i for i in range ( 10 )) # sum of squares 0, 1, 4, ... 81 285 generic function ¶ A function composed of multiple functions implementing the same operation for different types. Which implementation should be used during a call is determined by the dispatch algorithm. See also the single dispatch glossary entry, the functools.singledispatch() decorator, and PEP 443 . generic type ¶ A type that can be parameterized; typically a container class such as list or dict . Used for type hints and annotations . For more details, see generic alias types , PEP 483 , PEP 484 , PEP 585 , and the typing module. GIL ¶ See global interpreter lock . global interpreter lock ¶ The mechanism used by the CPython interpreter to assure that only one thread executes Python bytecode at a time. This simplifies the CPython implementation by making the object model (including critical built-in types such as dict ) implicitly safe against concurrent access. Locking the entire interpreter makes it easier for the interpreter to be multi-threaded, at the expense of much of the parallelism afforded by multi-processor machines. However, some extension modules, either standard or third-party, are designed so as to release the GIL when doing computationally intensive tasks such as compression or hashing. Also, the GIL is always released when doing I/O. As of Python 3.13, the GIL can be disabled using the --disable-gil build configuration. After building Python with this option, code must be run with -X gil=0 or after setting the PYTHON_GIL=0 environment variable. This feature enables improved performance for multi-threaded applications and makes it easier to use multi-core CPUs efficiently. For more details, see PEP 703 . In prior versions of Python’s C API, a function might declare that it requires the GIL to be held in order to use it. This refers to having an attached thread state . global state ¶ Data that is accessible throughout a program, such as module-level variables, class variables, or C static variables in extension modules . In multi-threaded programs, global state shared between threads typically requires synchronization to avoid race conditions and data races . hash-based pyc ¶ A bytecode cache file that uses the hash rather than the last-modified time of the corresponding source file to determine its validity. See Cached bytecode invalidation . hashable ¶ An object is hashable if it has a hash value which never changes during its lifetime (it needs a __hash__() method), and can be compared to other objects (it needs an __eq__() method). Hashable objects which compare equal must have the same hash value. Hashability makes an object usable as a dictionary key and a set member, because these data structures use the hash value internally. Most of Python’s immutable built-in objects are hashable; mutable containers (such as lists or dictionaries) are not; immutable containers (such as tuples and frozensets) are only hashable if their elements are hashable. Objects which are instances of user-defined classes are hashable by default. They all compare unequal (except with themselves), and their hash value is derived from their id() . IDLE ¶ An Integrated Development and Learning Environment for Python. IDLE — Python editor and shell is a basic editor and interpreter environment which ships with the standard distribution of Python. immortal ¶ Immortal objects are a CPython implementation detail introduced in PEP 683 . If an object is immortal, its reference count is never modified, and therefore it is never deallocated while the interpreter is running. For example, True and None are immortal in CPython. Immortal objects can be identified via sys._is_immortal() , or via PyUnstable_IsImmortal() in the C API. immutable ¶ An object with a fixed value. Immutable objects include numbers, strings and tuples. Such an object cannot be altered. A new object has to be created if a different value has to be stored. They play an important role in places where a constant hash value is needed, for example as a key in a dictionary. Immutable objects are inherently thread-safe because their state cannot be modified after creation, eliminating concerns about improperly synchronized concurrent modification . import path ¶ A list of locations (or path entries ) that are searched by the path based finder for modules to import. During import, this list of locations usually comes from sys.path , but for subpackages it may also come from the parent package’s __path__ attribute. importing ¶ The process by which Python code in one module is made available to Python code in another module. importer ¶ An object that both finds and loads a module; both a finder and loader object. interactive ¶ Python has an interactive interpreter which means you can enter statements and expressions at the interpreter prompt, immediately execute them and see their results. Just launch python with no arguments (possibly by selecting it from your computer’s main menu). It is a very powerful way to test out new ideas or inspect modules and packages (remember help(x) ). For more on interactive mode, see Interactive Mode . interpreted ¶ Python is an interpreted language, as opposed to a compiled one, though the distinction can be blurry because of the presence of the bytecode compiler. This means that source files can be run directly without explicitly creating an executable which is then run. Interpreted languages typically have a shorter development/debug cycle than compiled ones, though their programs generally also run more slowly. See also interactive . interpreter shutdown ¶ When asked to shut down, the Python interpreter enters a special phase where it gradually releases all allocated resources, such as modules and various critical internal structures. It also makes several calls to the garbage collector . This can trigger the execution of code in user-defined destructors or weakref callbacks. Code executed during the shutdown phase can encounter various exceptions as the resources it relies on may not function anymore (common examples are library modules or the warnings machinery). The main reason for interpreter shutdown is that the __main__ module or the script being run has finished executing. iterable ¶ An object capable of returning its members one at a time. Examples of iterables include all sequence types (such as list , str , and tuple ) and some non-sequence types like dict , file objects , and objects of any classes you define with an __iter__() method or with a __getitem__() method that implements sequence semantics. Iterables can be used in a for loop and in many other places where a sequence is needed ( zip() , map() , …). When an iterable object is passed as an argument to the built-in function iter() , it returns an iterator for the object. This iterator is good for one pass over the set of values. When using iterables, it is usually not necessary to call iter() or deal with iterator objects yourself. The for statement does that automatically for you, creating a temporary unnamed variable to hold the iterator for the duration of the loop. See also iterator , sequence , and generator . iterator ¶ An object representing a stream of data. Repeated calls to the iterator’s __next__() method (or passing it to the built-in function next() ) return successive items in the stream. When no more data are available a StopIteration exception is raised instead. At this point, the iterator object is exhausted and any further calls to its __next__() method just raise StopIteration again. Iterators are required to have an __iter__() method that returns the iterator object itself so every iterator is also iterable and may be used in most places where other iterables are accepted. One notable exception is code which attempts multiple iteration passes. A container object (such as a list ) produces a fresh new iterator each time you pass it to the iter() function or use it in a for loop. Attempting this with an iterator will just return the same exhausted iterator object used in the previous iteration pass, making it appear like an empty container. More information can be found in Iterator Types . CPython implementation detail: CPython does not consistently apply the requirement that an iterator define __iter__() . And also please note that free-threaded CPython does not guarantee thread-safe behavior of iterator operations. key function ¶ A key function or collation function is a callable that returns a value used for sorting or ordering. For example, locale.strxfrm() is used to produce a sort key that is aware of locale specific sort conventions. A number of tools in Python accept key functions to control how elements are ordered or grouped. They include min() , max() , sorted() , list.sort() , heapq.merge() , heapq.nsmallest() , heapq.nlargest() , and itertools.groupby() . There are several ways to create a key function. For example. the str.casefold() method can serve as a key function for case insensitive sorts. Alternatively, a key function can be built from a lambda expression such as lambda r: (r[0], r[2]) . Also, operator.attrgetter() , operator.itemgetter() , and operator.methodcaller() are three key function constructors. See the Sorting HOW TO for examples of how to create and use key functions. keyword argument ¶ See argument . lambda ¶ An anonymous inline function consisting of a single expression which is evaluated when the function is called. The syntax to create a lambda function is lambda [parameters]: expression LBYL ¶ Look before you leap. This coding style explicitly tests for pre-conditions before making calls or lookups. This style contrasts with the EAFP approach and is characterized by the presence of many if statements. In a multi-threaded environment, the LBYL approach can risk introducing a race condition between “the looking” and “the leaping”. For example, the code, if key in mapping: return mapping[key] can fail if another thread removes key from mapping after the test, but before the lookup. This issue can be solved with locks or by using the EAFP approach. See also thread-safe . lexical analyzer ¶ Formal name for the tokenizer ; see token . list ¶ A built-in Python sequence . Despite its name it is more akin to an array in other languages than to a linked list since access to elements is O (1). list comprehension ¶ A compact way to process all or part of the elements in a sequence and return a list with the results. result = ['{:#04x}'.format(x) for x in range(256) if x % 2 == 0] generates a list of strings containing even hex numbers (0x..) in the range from 0 to 255. The if clause is optional. If omitted, all elements in range(256) are processed. lock ¶ A synchronization primitive that allows only one thread at a time to access a shared resource. A thread must acquire a lock before accessing the protected resource and release it afterward. If a thread attempts to acquire a lock that is already held by another thread, it will block until the lock becomes available. Python’s threading module provides Lock (a basic lock) and RLock (a reentrant lock). Locks are used to prevent race conditions and ensure thread-safe access to shared data. Alternative design patterns to locks exist such as queues, producer/consumer patterns, and thread-local state. See also deadlock , and reentrant . loader ¶ An object that loads a module. It must define the exec_module() and create_module() methods to implement the Loader interface. A loader is typically returned by a finder . See also: Finders and loaders importlib.abc.Loader PEP 302 locale encoding ¶ On Unix, it is the encoding of the LC_CTYPE locale. It can be set with locale.setlocale(locale.LC_CTYPE, new_locale) . On Windows, it is the ANSI code page (ex: "cp1252" ). On Android and VxWorks, Python uses "utf-8" as the locale encoding. locale.getencoding() can be used to get the locale encoding. See also the filesystem encoding and error handler . magic method ¶ An informal synonym for special method . mapping ¶ A container object that supports arbitrary key lookups and implements the methods specified in the collections.abc.Mapping or collections.abc.MutableMapping abstract base classes . Examples include dict , collections.defaultdict , collections.OrderedDict and collections.Counter . meta path finder ¶ A finder returned by a search of sys.meta_path . Meta path finders are related to, but different from path entry finders . See importlib.abc.MetaPathFinder for the methods that meta path finders implement. metaclass ¶ The class of a class. Class definitions create a class name, a class dictionary, and a list of base classes. The metaclass is responsible for taking those three arguments and creating the class. Most object oriented programming languages provide a default implementation. What makes Python special is that it is possible to create custom metaclasses. Most users never need this tool, but when the need arises, metaclasses can provide powerful, elegant solutions. They have been used for logging attribute access, adding thread-safety, tracking object creation, implementing singletons, and many other tasks. More information can be found in Metaclasses . method ¶ A function which is defined inside a class body. If called as an attribute of an instance of that class, the method will get the instance object as its first argument (which is usually called self ). See function and nested scope . method resolution order ¶ Method Resolution Order is the order in which base classes are searched for a member during lookup. See The Python 2.3 Method Resolution Order for details of the algorithm used by the Python interpreter since the 2.3 release. module ¶ An object that serves as an organizational unit of Python code. Modules have a namespace containing arbitrary Python objects. Modules are loaded into Python by the process of importing . See also package . module spec ¶ A namespace containing the import-related information used to load a module. An instance of importlib.machinery.ModuleSpec . See also Module specs . MRO ¶ See method resolution order . mutable ¶ An object with state that is allowed to change during the course of the program. In multi-threaded programs, mutable objects that are shared between threads require careful synchronization to avoid race conditions . See also immutable , thread-safe , and concurrent modification . named tuple ¶ The term “named tuple” applies to any type or class that inherits from tuple and whose indexable elements are also accessible using named attributes. The type or class may have other features as well. Several built-in types are named tuples, including the values returned by time.localtime() and os.stat() . Another example is sys.float_info : >>> sys . float_info [ 1 ] # indexed access 1024 >>> sys . float_info . max_exp # named field access 1024 >>> isinstance ( sys . float_info , tuple ) # kind of tuple True Some named tuples are built-in types (such as the above examples). Alternatively, a named tuple can be created from a regular class definition that inherits from tuple and that defines named fields. Such a class can be written by hand, or it can be created by inheriting typing.NamedTuple , or with the factory function collections.namedtuple() . The latter techniques also add some extra methods that may not be found in hand-written or built-in named tuples. namespace ¶ The place where a variable is stored. Namespaces are implemented as dictionaries. There are the local, global and built-in namespaces as well as nested namespaces in objects (in methods). Namespaces support modularity by preventing naming conflicts. For instance, the functions builtins.open and os.open() are distinguished by their namespaces. Namespaces also aid readability and maintainability by making it clear which module implements a function. For instance, writing random.seed() or itertools.islice() makes it clear that those functions are implemented by the random and itertools modules, respectively. namespace package ¶ A package which serves only as a container for subpackages. Namespace packages may have no physical representation, and specifically are not like a regular package because they have no __init__.py file. Namespace packages allow several individually installable packages to have a common parent package. Otherwise, it is recommended to use a regular package . For more information, see PEP 420 and Namespace packages . See also module . native code ¶ Code that is compiled to machine instructions and runs directly on the processor, as opposed to code that is interpreted or runs in a virtual machine. In the context of Python, native code typically refers to C, C++, Rust or Fortran code in extension modules that can be called from Python. See also extension module . nested scope ¶ The ability to refer to a variable in an enclosing definition. For instance, a function defined inside another function can refer to variables in the outer function. Note that nested scopes by default work only for reference and not for assignment. Local variables both read and write in the innermost scope. Likewise, global variables read and write to the global namespace. The nonlocal allows writing to outer scopes. new-style class ¶ Old name for the flavor of classes now used for all class objects. In earlier Python versions, only new-style classes could use Python’s newer, versatile features like __slots__ , descriptors, properties, __getattribute__() , class methods, and static methods. non-deterministic ¶ Behavior where the outcome of a program can vary between executions with the same inputs. In multi-threaded programs, non-deterministic behavior often results from race conditions where the relative timing or interleaving of threads affects the result. Proper synchronization using locks and other synchronization primitives helps ensure deterministic behavior. object ¶ Any data with state (attributes or value) and defined behavior (methods). Also the ultimate base class of any new-style class . optimized scope ¶ A scope where target local variable names are reliably known to the compiler when the code is compiled, allowing optimization of read and write access to these names. The local namespaces for functions, generators, coroutines, comprehensions, and generator expressions are optimized in this fashion. Note: most interpreter optimizations are applied to all scopes, only those relying on a known set of local and nonlocal variable names are restricted to optimized scopes. optional module ¶ An extension module that is part of the standard library , but may be absent in some builds of CPython , usually due to missing third-party libraries or because the module is not available for a given platform. See Requirements for optional modules for a list of optional modules that require third-party libraries. package ¶ A Python module which can contain submodules or recursively, subpackages. Technically, a package is a Python module with a __path__ attribute. See also regular package and namespace package . parallelism ¶ Executing multiple operations at the same time (e.g. on multiple CPU cores). In Python builds with the global interpreter lock (GIL) , only one thread runs Python bytecode at a time, so taking advantage of multiple CPU cores typically involves multiple processes (e.g. multiprocessing ) or native extensions that release the GIL. In free-threaded Python, multiple Python threads can run Python code simultaneously on different cores. parameter ¶ A named entity in a function (or method) definition that specifies an argument (or in some cases, arguments) that the function can accept. There are five kinds of parameter: positional-or-keyword : specifies an argument that can be passed either positionally or as a keyword argument . This is the default kind of parameter, for example foo and bar in the following: def func ( foo , bar = None ): ... positional-only : specifies an argument that can be supplied only by position. Positional-only parameters can be defined by including a / character in the parameter list of the function definition after them, for example posonly1 and posonly2 in the following: def func ( posonly1 , posonly2 , / , positional_or_keyword ): ... keyword-only : specifies an argument that can be supplied only by keyword. Keyword-only parameters can be defined by including a single var-positional parameter or bare * in the parameter list of the function definition before them, for example kw_only1 and kw_only2 in the following: def func ( arg , * , kw_only1 , kw_only2 ): ... var-positional : specifies that an arbitrary sequence of positional arguments can be provided (in addition to any positional arguments already accepted by other parameters). Such a parameter can be defined by prepending the parameter name with * , for example args in the following: def func ( * args , ** kwargs ): ... var-keyword : specifies that arbitrarily many keyword arguments can be provided (in addition to any keyword arguments already accepted by other parameters). Such a parameter can be defined by prepending the parameter name with ** , for example kwargs in the example above. Parameters can specify both optional and required arguments, as well as default values for some optional arguments. See also the argument glossary entry, the FAQ question on the difference between arguments and parameters , the inspect.Parameter class, the Function definitions section, and PEP 362 . path entry ¶ A single location on the import path which the path based finder consults to find modules for importing. path entry finder ¶ A finder returned by a callable on sys.path_hooks (i.e. a path entry hook ) which knows how to locate modules given a path entry . See importlib.abc.PathEntryFinder for the methods that path entry finders implement. path entry hook ¶ A callable on the sys.path_hooks list which returns a path entry finder if it knows how to find modules on a specific path entry . path based finder ¶ One of the default meta path finders which searches an import path for modules. path-like object ¶ An object representing a file system path. A path-like object is either a str or bytes object representing a path, or an object implementing the os.PathLike protocol. An object that supports the os.PathLike protocol can be converted to a str or bytes file system path by calling the os.fspath() function; os.fsdecode() and os.fsencode() can be used to guarantee a str or bytes result instead, respectively. Introduced by PEP 519 . PEP ¶ Python Enhancement Proposal. A PEP is a design document providing information to the Python community, or describing a new feature for Python or its processes or environment. PEPs should provide a concise technical specification and a rationale for proposed features. PEPs are intended to be the primary mechanisms for proposing major new features, for collecting community input on an issue, and for documenting the design decisions that have gone into Python. The PEP author is responsible for building consensus within the community and documenting dissenting opinions. See PEP 1 . portion ¶ A set of files in a single directory (possibly stored in a zip file) that contribute to a namespace package, as defined in PEP 420 . positional argument ¶ See argument . provisional API ¶ A provisional API is one which has been deliberately excluded from the standard library’s backwards compatibility guarantees. While major changes to such interfaces are not expected, as long as they are marked provisional, backwards incompatible changes (up to and including removal of the interface) may occur if deemed necessary by core developers. Such changes will not be made | 2026-01-13T08:48:58 |
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Integrations Microsoft Teams self-hosted Hobby deployment guide. Traefik SSL Proxying. Docs Home SDK Client SDK API Reference Cloudflare Worker SDK API Reference Go SDK API Reference Hono SDK API Reference Java SDK API Reference Next.JS SDK API Reference Node.JS SDK API Reference Python SDK API Reference Ruby SDK API Reference Rust SDK API Reference Docs / Highlight Docs / Product Features / Dashboards / Metrics Tutorials / User Analytics User Analytics Overview This tutorial walks you through creating a graph to track unique users who clicked on header links. By following these steps, you'll gain insights into user interactions with your application, helping you understand user behavior and trends. Step-by-step Guide 1. Select the Data Source Start by selecting the source of your metrics. For tracking user engagements, we'll use user events as the data source. This provides detailed information about how users interact with your application. 2. Choose the Graph Type Next, select the type of graph you want to use to visualize your data. For this example, we'll use a bar graph, which is excellent for comparing values across different categories. 3. Apply Filters To focus on specific user events, apply filters to your data. In this case, we are looking to filter down to our custom event header-link-* , where the * represents the suffix on the link clicked. 4. Apply a Function Currently, we're retrieving the total number of events. To get the distinct number of users, update the function to CountDistinct using the identifier attribute, which tracks each user’s unique identifier, such as an email or ID. Read more about reporting identifiers in our docs . 4. Group the Data Group the events by a relevant attribute. For this example, we'll group by the event name. This allows us to analyze the filtered down events into the specific event that occurred. 5. Analyze the Results The resulting graph will show a count of all the emails (representing users) across all filtered sessions. This visualization allows you to: Identify the most clicked event Spot trends in user engagement over time Understand which parts of your application are most frequently accessed 6. Refine Your Metrics If you’d prefer to track unique sessions instead of unique users, simply modify the CountDistinct function to use secure_session_id instead of the user identifier. To get more insights into searching events, read our event search docs . 7. Interpret and Act on the Data Use the insights from your graph to understand the broader context of your application's usage: Identify which parts of the page are most used Spot any decline in engagement and investigate potential causes Recognize successful features or content that drive higher engagement Plan targeted improvements or campaigns based on user engagement patterns By regularly monitoring and analyzing these metrics, you can make data-driven decisions to enhance your application's user experience and overall success. Be sure to review and adjust your metrics periodically as your application and user base evolve. Creating User Engagement Metrics Graphing Community / Support Suggest Edits? Follow us! [object Object] | 2026-01-13T08:48:58 |
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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse Amara Graham Posted on Apr 23, 2019 Help Me, Help You (Debugging Tips Before Seeking Help) # programming # productivity # beginners One of the really cool things about being a developer advocate is I get to help people, which I truly love. I love writing a snippet of code or clarifying documentation and then watching the magic that happens when a developer I've probably never met before takes it and creates something amazing with it. That's a great day in my book. But it is not always like that. Sometimes things break, and folks reach out for help. It can be frustrating for everyone involved when it appears to be "just one error" (it may not be actually!). Let me help you help me as we work through these things together. Be very clear about your problem or issue Overstate and overshare. If you can provide relevant screen shots or a link to the code, that's even better. Was this ever working? Or did you just get started? What version of the SDK or service are you using? Your OS version might also be relevant. What steps did you do to get to this point? Link to the exact tutorial or documentation. Do your homework first What steps did you take to try to debug this on your own? The answer cannot be "nothing". Did you do a search on the error? Stack Overflow? Relevant forums? A search engine? Has this happened before? Can you try an older version? Can you try a newer version? Can you reproduce it? Clouds are complicated When working in the cloud, you can have a lot more variables at play. I recommend firing off a simple GET to make sure something like your credentials are working and the service is responding. There is a reason many API docs include Curl, but maybe read my other post . Can you use Curl/Postman/ARC to test the endpoint? What region are you in? What tier of the service are you using? You may have hit a tier limit. Check for outages & maintenance. If you are on IBM Cloud, there is a widget on the dashboard (you may need to be logged in). Submit an issue (or even a PR) If you think you are experiencing a bug with an open source project, submit an issue. Often projects will have a template to follow, which look very similar to the items I outlined above! Coincidence, I think not. Be patient I cannot drop everything I'm doing to work on troubleshooting, but I try to put some time in my schedule during the week to take a look at things. This is often what you hear from OSS maintainers and can lead to burnout. I don't work weekends or evenings (unless I have very specific events) so I appreciate your patience. Following the above items will help us both tackle these challenges together. Feel free to apply these things anywhere in life or work. We are all busy, but if we meet each other halfway, everyone benefits. Do you have any tips I missed? Share them below! Top comments (3) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Collapse Expand Theofanis Despoudis Theofanis Despoudis Theofanis Despoudis Follow Senior Software Engineer @wpengine, Experienced mentor @codeimentor, Technical Writer @fixate.io, Book author Location Ireland Work Senior Software Engineer at WP Engine Joined Jun 19, 2017 • Apr 24 '19 Dropdown menu Copy link Hide You forgot the meme Like comment: Like comment: 4 likes Like Comment button Reply Collapse Expand DrBearhands DrBearhands DrBearhands Follow Education MSc. Artificial Intelligence Joined Apr 9, 2018 • Apr 24 '19 Dropdown menu Copy link Hide Ahhh, those lovely "it's not working" bugreports. So easy to close by just opening the app and seeing that it is apparently working again. Like comment: Like comment: 3 likes Like Comment button Reply Collapse Expand Amara Graham Amara Graham Amara Graham Follow Enabling developers Location Austin, TX Education BS Computer Science from Trinity University Work Developer Advocate at Kestra Joined Jan 4, 2017 • Apr 24 '19 Dropdown menu Copy link Hide Love to hate those ones. It's... fixed...? Like comment: Like comment: 3 likes Like Comment button Reply Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse Amara Graham Follow Enabling developers Location Austin, TX Education BS Computer Science from Trinity University Work Developer Advocate at Kestra Joined Jan 4, 2017 More from Amara Graham Intro to Calling Third Party AI Services in Unreal Engine # programming # gamedev # unreal Updating Your Unity Project to Watson SDK for Unity 3.1.0 (and Core SDK 0.2.0) # unity3d # programming # gamedev A Few of My Favorite (Dev) Things # github # programming # softwaredevelopment 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV Forem — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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https://www.highlight.io/docs/general/product-features/logging/log-search | Log Search Star us on GitHub Star Docs Sign in Sign up General Docs Welcome to highlight.io Get Started Roadmap Company Values Compliance & Security Open Source Contributing Overview GraphQL Backend Frontend (app.highlight.io) Landing Site (highlight.io) Documentation End to End SDK Example Apps Adding an SDK Application Architecture GitHub Code Spaces Code Style Good First Issues Self-hosting Self-hosted [Dev] Self-hosted [Hobby] Self-hosted [Enterprise] Telemetry Our Competitors Product Philosophy Product Features Session Replay Overview Canvas & Iframe Dev-tool Window Recording Tracking Users & Recording Events Filtering Sessions GraphQL Live Mode Performance Impact Player Session Caching Rage Clicks Request Proxying Session Search Extracting the Session URL Session Search Deep Linking Shadow Dom + Web Components Error Monitoring Overview Enhancing Errors with GitHub Error Search Filtering Errors Grouping Errors Managing Errors Manually Reporting Errors Sourcemaps General Features Overview Alerts Comments Digests Environments Search Segments Services Webhooks Logging Overview Log Alerts Log Search Tracing Overview Trace Search Dashboards Overview Dashboard Management Metrics Tutorials Service Latency Web Vitals & Page Speed User Engagement User Analytics Graphing Drilldown Event Search Dashboard Variables SQL Editor Metrics (beta) Overview Frequently Asked Questions. Integrations Integrations Overview Amplitude Integration ClickUp Integration Discord Integration Electron Support Front Integration GitHub Integration Grafana Integration Overview Setup Dashboards Alerts Height Integration Intercom Integration Jira Integration LaunchDarkly Integration Linear Integration Mixpanel Integration Nuxt Integration Pendo Integration Segment Integration Slack Integration Vercel Integration WordPress Plugin Highlight.io Changelog Overview Changelog 12 (02/17) Changelog 13 (02/24) Changelog 14 (03/03) Changelog 15 (03/11) Changelog 16 (03/19) Changelog 17 (04/07) Changelog 18 (04/26) Changelog 19 (05/22) Changelog 20 (06/06) Changelog 21 (06/21) Changelog 22 (08/07) Changelog 23 (08/22) Changelog 24 (09/11) Changelog 25 (10/03) Changelog 26 (11/08) Changelog 27 (12/22) Changelog 28 (3/6) Changelog 29 (4/2) Menu Highlight Docs Welcome to highlight.io Get Started Roadmap Company Values Compliance & Security Open Source Contributing Overview GraphQL Backend Frontend (app.highlight.io) Landing Site (highlight.io) Documentation End to End SDK Example Apps Adding an SDK Application Architecture GitHub Code Spaces Code Style Good First Issues Self-hosting Self-hosted [Dev] Self-hosted [Hobby] Self-hosted [Enterprise] Telemetry Our Competitors Product Philosophy Product Features Session Replay Overview Canvas & Iframe Dev-tool Window Recording Tracking Users & Recording Events Filtering Sessions GraphQL Live Mode Performance Impact Player Session Caching Rage Clicks Request Proxying Session Search Extracting the Session URL Session Search Deep Linking Shadow Dom + Web Components Error Monitoring Overview Enhancing Errors with GitHub Error Search Filtering Errors Grouping Errors Managing Errors Manually Reporting Errors Sourcemaps General Features Overview Alerts Comments Digests Environments Search Segments Services Webhooks Logging Overview Log Alerts Log Search Tracing Overview Trace Search Dashboards Overview Dashboard Management Metrics Tutorials Service Latency Web Vitals & Page Speed User Engagement User Analytics Graphing Drilldown Event Search Dashboard Variables SQL Editor Metrics (beta) Overview Frequently Asked Questions. Integrations Integrations Overview Amplitude Integration ClickUp Integration Discord Integration Electron Support Front Integration GitHub Integration Grafana Integration Overview Setup Dashboards Alerts Height Integration Intercom Integration Jira Integration LaunchDarkly Integration Linear Integration Mixpanel Integration Nuxt Integration Pendo Integration Segment Integration Slack Integration Vercel Integration WordPress Plugin Highlight.io Changelog Overview Changelog 12 (02/17) Changelog 13 (02/24) Changelog 14 (03/03) Changelog 15 (03/11) Changelog 16 (03/19) Changelog 17 (04/07) Changelog 18 (04/26) Changelog 19 (05/22) Changelog 20 (06/06) Changelog 21 (06/21) Changelog 22 (08/07) Changelog 23 (08/22) Changelog 24 (09/11) Changelog 25 (10/03) Changelog 26 (11/08) Changelog 27 (12/22) Changelog 28 (3/6) Changelog 29 (4/2) Getting Started Getting Started with Highlight Fullstack Mapping Browser React.js Next.js Remix Vue.js Angular Gatsby.js SvelteKit Electron highlight.run SDK Overview Canvas & WebGL Console Messages Content-Security-Policy Identifying Users iframe Recording Monkey Patches Browser OpenTelemetry Persistent Asset Storage Privacy Proxying Highlight React.js Error Boundary Recording Network Requests and Responses Recording WebSocket Events Salesforce Lightning Web Components (LWC) Data Export Sourcemap Configuration Tracking Events Troubleshooting Upgrading Highlight Versioning Sessions & Errors Other React Native (beta) Server Go Overview chi Echo Fiber Gin GORM gqlgen Logrus Manual Tracing gorilla mux JS Overview Apollo AWS Lambda Cloudflare Workers Express.js Firebase Hono Nest.js Next.js Node.js Pino tRPC Winston Python Overview AWS Lambda Azure Functions Django FastAPI Flask Google Cloud Functions Loguru Other Frameworks Python AI / LLM Libraries Python Libraries Ruby Overview Other Frameworks Ruby on Rails Rust Overview actix-web No Framework Hosting Providers Overview Metrics in AWS Logging in AWS Logging in Azure Fly.io NATS Log Shipper Logging in GCP Heroku Log Drain Render Log Stream Logging in Trigger.dev Vercel Log Drain Elixir Overview Elixir App Java: All Frameworks PHP: All Frameworks C# .NET ASP C# .NET 4 ASP Docker / Docker Compose File Fluent Forward curl OpenTelemetry Protocol (OTLP) Syslog RFC5424 Systemd / Journald Native OpenTelemetry Overview Error Monitoring Logging Tracing Browser Instrumentation Metrics Fullstack Frameworks Overview Next.js Fullstack Overview Next.js Page Router Guide Next.js App Router Guide Edge Runtime Advanced Config Remix Walkthrough Self Host & Local Dev Overview Development deployment guide. Integrations Microsoft Teams self-hosted Hobby deployment guide. Traefik SSL Proxying. Docs Home SDK Client SDK API Reference Cloudflare Worker SDK API Reference Go SDK API Reference Hono SDK API Reference Java SDK API Reference Next.JS SDK API Reference Node.JS SDK API Reference Python SDK API Reference Ruby SDK API Reference Rust SDK API Reference Docs / Highlight Docs / Product Features / Logging / Log Search Log Search Specification Logs are broken down into two discrete concepts: messages and attributes . Given the following log: logger.info('Queried table', { table: 'users', query: 'hello', }), The log message is Queried table and the attributes are table:users and query:hello . Searching for Logs For general information on searching logs, check out our Search docs . Default Key The default key for log search is message . If you enter an expression without a key ( graphql request ) it will be used as the key for the expression ( message="*graphql request*" ). For example given the following log: log.info("excluding session due to no user interaction events") We can find this log by typing excluding session due to no user interaction events . Autoinjected attributes By default, Highlight's SDKs will autoinject attributes to provide additional context as well as assisting in linking sessions and errors to their respective logs. Attribute Description Example code.filepath File path emitting the log. /build/backend/worker/worker.go code.function Function emitting the log. github.com/highlight-run/highlight/backend/worker.(*Worker).Start.func3 code.lineno Line number of the file where the log was emitted. 20 environment The environment specified in the SDK production host.name Hostname ip-172-31-5-211.us-east-2.compute.internal level The log level info message The log message public-graph graphql request failed os.description Description of the operating system Alpine Linux 3.17.2 (Linux ip-172-31-5-211.us-east-2.compute.internal 5.10.167-147.601.amzn2.aarch64 #1 SMP Tue Feb 14 21:50:23 UTC 2023 aarch64) os.type Type of operating system linux secure_session_id Session id that contains this log wh1jcuN5F9G6Ra5CKeCjdIk6Rbyd service_name Name of the service specified in the SDK private-graph service_version Version of the service specified in the SDK e1845285cb360410aee05c61dd0cc57f85afe6da source Broad origin of the log backend span_id Span id that contains this log 528a54addf6f91cc trace_id Trace id that contains this log 7654ff38c4631d5a51b26f7e637eea3c Helpful Tips Use the secure_session_id EXISTS search to filter out all logs that are not tied to a session. 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https://www.highlight.io/docs/general/company/open-source/contributing/code-spaces | GitHub Code Spaces Star us on GitHub Star Docs Sign in Sign up General Docs Welcome to highlight.io Get Started Roadmap Company Values Compliance & Security Open Source Contributing Overview GraphQL Backend Frontend (app.highlight.io) Landing Site (highlight.io) Documentation End to End SDK Example Apps Adding an SDK Application Architecture GitHub Code Spaces Code Style Good First Issues Self-hosting Self-hosted [Dev] Self-hosted [Hobby] Self-hosted [Enterprise] Telemetry Our Competitors Product Philosophy Product Features Session Replay Overview Canvas & Iframe Dev-tool Window Recording Tracking Users & Recording Events Filtering Sessions GraphQL Live Mode Performance Impact Player Session Caching Rage Clicks Request Proxying Session Search Extracting the Session URL Session Search Deep Linking Shadow Dom + Web Components Error Monitoring Overview Enhancing Errors with GitHub Error Search Filtering Errors Grouping Errors Managing Errors Manually Reporting Errors Sourcemaps General Features Overview Alerts Comments Digests Environments Search Segments Services Webhooks Logging Overview Log Alerts Log Search Tracing Overview Trace Search Dashboards Overview Dashboard Management Metrics Tutorials Service Latency Web Vitals & Page Speed User Engagement User Analytics Graphing Drilldown Event Search Dashboard Variables SQL Editor Metrics (beta) Overview Frequently Asked Questions. Integrations Integrations Overview Amplitude Integration ClickUp Integration Discord Integration Electron Support Front Integration GitHub Integration Grafana Integration Overview Setup Dashboards Alerts Height Integration Intercom Integration Jira Integration LaunchDarkly Integration Linear Integration Mixpanel Integration Nuxt Integration Pendo Integration Segment Integration Slack Integration Vercel Integration WordPress Plugin Highlight.io Changelog Overview Changelog 12 (02/17) Changelog 13 (02/24) Changelog 14 (03/03) Changelog 15 (03/11) Changelog 16 (03/19) Changelog 17 (04/07) Changelog 18 (04/26) Changelog 19 (05/22) Changelog 20 (06/06) Changelog 21 (06/21) Changelog 22 (08/07) Changelog 23 (08/22) Changelog 24 (09/11) Changelog 25 (10/03) Changelog 26 (11/08) Changelog 27 (12/22) Changelog 28 (3/6) Changelog 29 (4/2) Menu Highlight Docs Welcome to highlight.io Get Started Roadmap Company Values Compliance & Security Open Source Contributing Overview GraphQL Backend Frontend (app.highlight.io) Landing Site (highlight.io) Documentation End to End SDK Example Apps Adding an SDK Application Architecture GitHub Code Spaces Code Style Good First Issues Self-hosting Self-hosted [Dev] Self-hosted [Hobby] Self-hosted [Enterprise] Telemetry Our Competitors Product Philosophy Product Features Session Replay Overview Canvas & Iframe Dev-tool Window Recording Tracking Users & Recording Events Filtering Sessions GraphQL Live Mode Performance Impact Player Session Caching Rage Clicks Request Proxying Session Search Extracting the Session URL Session Search Deep Linking Shadow Dom + Web Components Error Monitoring Overview Enhancing Errors with GitHub Error Search Filtering Errors Grouping Errors Managing Errors Manually Reporting Errors Sourcemaps General Features Overview Alerts Comments Digests Environments Search Segments Services Webhooks Logging Overview Log Alerts Log Search Tracing Overview Trace Search Dashboards Overview Dashboard Management Metrics Tutorials Service Latency Web Vitals & Page Speed User Engagement User Analytics Graphing Drilldown Event Search Dashboard Variables SQL Editor Metrics (beta) Overview Frequently Asked Questions. Integrations Integrations Overview Amplitude Integration ClickUp Integration Discord Integration Electron Support Front Integration GitHub Integration Grafana Integration Overview Setup Dashboards Alerts Height Integration Intercom Integration Jira Integration LaunchDarkly Integration Linear Integration Mixpanel Integration Nuxt Integration Pendo Integration Segment Integration Slack Integration Vercel Integration WordPress Plugin Highlight.io Changelog Overview Changelog 12 (02/17) Changelog 13 (02/24) Changelog 14 (03/03) Changelog 15 (03/11) Changelog 16 (03/19) Changelog 17 (04/07) Changelog 18 (04/26) Changelog 19 (05/22) Changelog 20 (06/06) Changelog 21 (06/21) Changelog 22 (08/07) Changelog 23 (08/22) Changelog 24 (09/11) Changelog 25 (10/03) Changelog 26 (11/08) Changelog 27 (12/22) Changelog 28 (3/6) Changelog 29 (4/2) Getting Started Getting Started with Highlight Fullstack Mapping Browser React.js Next.js Remix Vue.js Angular Gatsby.js SvelteKit Electron highlight.run SDK Overview Canvas & WebGL Console Messages Content-Security-Policy Identifying Users iframe Recording Monkey Patches Browser OpenTelemetry Persistent Asset Storage Privacy Proxying Highlight React.js Error Boundary Recording Network Requests and Responses Recording WebSocket Events Salesforce Lightning Web Components (LWC) Data Export Sourcemap Configuration Tracking Events Troubleshooting Upgrading Highlight Versioning Sessions & Errors Other React Native (beta) Server Go Overview chi Echo Fiber Gin GORM gqlgen Logrus Manual Tracing gorilla mux JS Overview Apollo AWS Lambda Cloudflare Workers Express.js Firebase Hono Nest.js Next.js Node.js Pino tRPC Winston Python Overview AWS Lambda Azure Functions Django FastAPI Flask Google Cloud Functions Loguru Other Frameworks Python AI / LLM Libraries Python Libraries Ruby Overview Other Frameworks Ruby on Rails Rust Overview actix-web No Framework Hosting Providers Overview Metrics in AWS Logging in AWS Logging in Azure Fly.io NATS Log Shipper Logging in GCP Heroku Log Drain Render Log Stream Logging in Trigger.dev Vercel Log Drain Elixir Overview Elixir App Java: All Frameworks PHP: All Frameworks C# .NET ASP C# .NET 4 ASP Docker / Docker Compose File Fluent Forward curl OpenTelemetry Protocol (OTLP) Syslog RFC5424 Systemd / Journald Native OpenTelemetry Overview Error Monitoring Logging Tracing Browser Instrumentation Metrics Fullstack Frameworks Overview Next.js Fullstack Overview Next.js Page Router Guide Next.js App Router Guide Edge Runtime Advanced Config Remix Walkthrough Self Host & Local Dev Overview Development deployment guide. 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Docs Home SDK Client SDK API Reference Cloudflare Worker SDK API Reference Go SDK API Reference Hono SDK API Reference Java SDK API Reference Next.JS SDK API Reference Node.JS SDK API Reference Python SDK API Reference Ruby SDK API Reference Rust SDK API Reference Docs / Highlight Docs / Company / Open Source / Contributing / GitHub Code Spaces GitHub Code Spaces Running on GitHub Codepsaces (in browser or in VS Code) Make sure you've forked the repo Visit https://github.com/codespaces and start a codepsace for highlight/highlight Install the VS Code Extension "GitHub Codespaces" Using VS Code, enter codespace - CMD + Shift + P , type codespace , select the Highlight codespace If docker is not running (try docker ps ), run a full rebuild: press CMD + Shift + P , select Codespaces: Full Rebuild Container # from highlight/ cd docker ./run.sh # View `http://localhost:3000` Application Architecture Code Style Community / Support Suggest Edits? Follow us! 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https://dev.to/t/iot | Iot - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close # iot Follow Hide Security challenges and solutions for Internet of Things and embedded devices. Create Post Older #iot posts 1 2 3 4 5 6 7 8 9 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu I Bought a Robot Vacuum, Not a Cloud Spy Alex Root Alex Root Alex Root Follow Jan 12 I Bought a Robot Vacuum, Not a Cloud Spy # hardware # iot # embedded # diy 5 reactions Comments Add Comment 8 min read Production-Ready Low-Power IoT Trackers: EVT-DVT-PVT, Testing & Resilient Supply Chains applekoiot applekoiot applekoiot Follow Jan 12 Production-Ready Low-Power IoT Trackers: EVT-DVT-PVT, Testing & Resilient Supply Chains # iot # hardware # manufacturing # supplychain Comments Add Comment 5 min read ESP32 WiFi Security Explained for Beginners Yasir Nawaz Yasir Nawaz Yasir Nawaz Follow Jan 11 ESP32 WiFi Security Explained for Beginners # iot # esp32 # embeddedsystems Comments Add Comment 5 min read My Ray-Ban Meta Glasses AI Setup in Taiwan Evan Lin Evan Lin Evan Lin Follow Jan 11 My Ray-Ban Meta Glasses AI Setup in Taiwan # ai # iot # tutorial Comments Add Comment 2 min read Artificial Intelligence in Smart Grids — A Comprehensive Survey rachmad andri atmoko rachmad andri atmoko rachmad andri atmoko Follow Jan 10 Artificial Intelligence in Smart Grids — A Comprehensive Survey # ai # computerscience # iot Comments Add Comment 20 min read Complete ESP32 Security Guide for IoT Devices Yasir Nawaz Yasir Nawaz Yasir Nawaz Follow Jan 10 Complete ESP32 Security Guide for IoT Devices # esp32 # iot # iotsecurity # embeddedsystems Comments Add Comment 5 min read Network Communication Protocols and Artificial Intelligence Enhancement in IoT Environmental Monitoring Systems rachmad andri atmoko rachmad andri atmoko rachmad andri atmoko Follow Jan 10 Network Communication Protocols and Artificial Intelligence Enhancement in IoT Environmental Monitoring Systems # ai # iot # networking # systemdesign Comments Add Comment 29 min read Wearable Tech Data + Better Health Insights + Building a Scalable IoT Pipeline on AWS wellallyTech wellallyTech wellallyTech Follow Jan 9 Wearable Tech Data + Better Health Insights + Building a Scalable IoT Pipeline on AWS # aws # architecture # serverless # iot Comments Add Comment 3 min read Keeping Telemetry Defensible Through Dead Zones applekoiot applekoiot applekoiot Follow Jan 8 Keeping Telemetry Defensible Through Dead Zones # architecture # data # iot # networking Comments Add Comment 1 min read Home Assistant Fernzugriff: Sicher & Kostenlos via Cloudflare Tunnel (Kein Port-Forwarding!) Tim Alex Tim Alex Tim Alex Follow Jan 5 Home Assistant Fernzugriff: Sicher & Kostenlos via Cloudflare Tunnel (Kein Port-Forwarding!) # homeassistant # iot # tutorial # security Comments Add Comment 3 min read ESPHome Gerät ständig "Offline"? So fixst du API-Errors und Boot-Loops beim ESP32 Tim Alex Tim Alex Tim Alex Follow Jan 5 ESPHome Gerät ständig "Offline"? So fixst du API-Errors und Boot-Loops beim ESP32 # esphome # esp32 # iot # debugging Comments Add Comment 3 min read Tuya Geräte in Home Assistant: 100% Lokal & ohne China-Cloud (Local Key auslesen) Tim Alex Tim Alex Tim Alex Follow Jan 5 Tuya Geräte in Home Assistant: 100% Lokal & ohne China-Cloud (Local Key auslesen) # homeassistant # privacy # iot # tutorial Comments Add Comment 3 min read Zigbee Netzwerk instabil? 4 Profi-Tipps gegen "Offline"-Geräte & Interferenzen Tim Alex Tim Alex Tim Alex Follow Jan 5 Zigbee Netzwerk instabil? 4 Profi-Tipps gegen "Offline"-Geräte & Interferenzen # homeassistant # zigbee # iot # tutorial Comments Add Comment 3 min read Remote Controlled Pleasure Devices Basics: My Essential Guide for Beginners Hannah Blackwell Hannah Blackwell Hannah Blackwell Follow Jan 4 Remote Controlled Pleasure Devices Basics: My Essential Guide for Beginners # beginners # iot # tutorial Comments Add Comment 5 min read Digital Twins: Creating Virtual Mirrors of the Real World Ravish Kumar Ravish Kumar Ravish Kumar Follow Jan 3 Digital Twins: Creating Virtual Mirrors of the Real World # digitaltwins # iot # ai # cloudcomputing 1 reaction Comments Add Comment 2 min read Building a Resilient Edge Architecture for Remote Farms with Starlink + LoRa Daniel Azevedo Novais Daniel Azevedo Novais Daniel Azevedo Novais Follow Jan 2 Building a Resilient Edge Architecture for Remote Farms with Starlink + LoRa # iot # python # opensource # agriculture Comments Add Comment 1 min read CES 2026: The Year AI Got Real Cyrus Tse Cyrus Tse Cyrus Tse Follow Jan 7 CES 2026: The Year AI Got Real # news # ai # iot Comments Add Comment 6 min read A Token-Efficient Way to Send Time-Series Data into LLMs Manas Mudbari Manas Mudbari Manas Mudbari Follow Dec 31 '25 A Token-Efficient Way to Send Time-Series Data into LLMs # llm # iot # timeseries # datascience Comments Add Comment 2 min read PlatformIO on GitHub Actions with cache accelerate aKuad aKuad aKuad Follow Dec 30 '25 PlatformIO on GitHub Actions with cache accelerate # githubactions # iot Comments Add Comment 2 min read Arduino vs STM32: When the Arduino Platform Becomes Limiting Tomasz Szewczyk Tomasz Szewczyk Tomasz Szewczyk Follow Jan 11 Arduino vs STM32: When the Arduino Platform Becomes Limiting # arduino # iot # stm32 # programming 1 reaction Comments Add Comment 5 min read Strategies to Handle Faulty or Missing Sensor Readings on Dashboards William Smith William Smith William Smith Follow Dec 30 '25 Strategies to Handle Faulty or Missing Sensor Readings on Dashboards # iot # iotdashboard Comments Add Comment 6 min read LoRaWAN-Based CJ/T 188 M-Bus Heat Meter Data Acquisition: An Engineering Practice with KC22 and Edge-Bus manthink manthink manthink Follow Dec 30 '25 LoRaWAN-Based CJ/T 188 M-Bus Heat Meter Data Acquisition: An Engineering Practice with KC22 and Edge-Bus # data # architecture # iot # networking Comments Add Comment 3 min read QNX Explained for Beginners: The Operating System You Use Without Knowing It Pʀᴀɴᴀᴠ Pʀᴀɴᴀᴠ Pʀᴀɴᴀᴠ Follow Dec 30 '25 QNX Explained for Beginners: The Operating System You Use Without Knowing It # beginners # iot # systemdesign Comments Add Comment 3 min read Edge AI in Agriculture: A Practical Perspective for Real-World Farming Swapin Vidya Swapin Vidya Swapin Vidya Follow Dec 28 '25 Edge AI in Agriculture: A Practical Perspective for Real-World Farming # ai # iot # edgeai # agriculture Comments Add Comment 2 min read DEV Track Spotlight: Control Humanoid Robots and Drones with Voice and Agentic AI (DEV313) Gunnar Grosch Gunnar Grosch Gunnar Grosch Follow for AWS Dec 26 '25 DEV Track Spotlight: Control Humanoid Robots and Drones with Voice and Agentic AI (DEV313) # aws # ai # iot # robotics 1 reaction Comments Add Comment 7 min read loading... trending guides/resources Build Your Own WiFi-Controlled Drone with ESP32 (Beginner-Friendly) Choosing Your First Smart Devices for Home Assistant A Deep Dive Into ESP-CSI: Channel State Information on ESP32 Chips How to build a Heapless Vector using `MaybeUninit<T>` for Better Performance. 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https://forem.com/suzuki0430 | Atsushi Suzuki - Forem Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Follow User actions Atsushi Suzuki AWS Community Builder | 15x AWS Certified | Docker Captain Hooked on the TV drama Silicon Valley, I switched from sales to engineering. Developing SaaS and researching AI at a startup in Tokyo. Location Tokyo Joined Joined on Mar 11, 2021 Personal website https://www.linkedin.com/in/suzuki-09b7171a2 github website twitter website Four Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least four years. Got it Close 2 Week Community Wellness Streak Keep the community conversation going! Post at least 2 comments for 2 straight weeks and unlock the 4 Week Badge. Got it Close 1 Week Community Wellness Streak For actively engaging with the community by posting at least 2 comments in a single week. Got it Close Docker Awarded to the top Docker author each week Got it Close Three Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least three years. Got it Close Writing Debut Awarded for writing and sharing your first DEV post! Continue sharing your work to earn the 4 Week Writing Streak Badge. Got it Close 4 Week Writing Streak You've posted at least one post per week for 4 consecutive weeks! Got it Close Two Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least two years. Got it Close One Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least one year. Got it Close More info about @suzuki0430 Organizations AWS Community Builders Skills/Languages React(Native)/NestJS/TypeScript/Go/PHP/Laravel/Python/PyTorch/GraphQL/AWS(SageMaker, ECS, ECR, S3, Lambda, Amplify, Aurora, IAM, Glue, Athena, DynamoDB)/GCP(BigQuery, GCF, GCS, Vertex)Docker/Terraform Currently learning AI Post 77 posts published Comment 18 comments written Tag 14 tags followed CKA (Certified Kubernetes Administrator) Exam Report 2026: Don’t Rely on Old Guides (Mastering the Post-2025 Revision) Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Jan 13 CKA (Certified Kubernetes Administrator) Exam Report 2026: Don’t Rely on Old Guides (Mastering the Post-2025 Revision) # kubernetes # certification # devops # learning 1 reaction Comments Add Comment 5 min read Want to connect with Atsushi Suzuki? Create an account to connect with Atsushi Suzuki. You can also sign in below to proceed if you already have an account. Create Account Already have an account? Sign in I Automated My Air Conditioner with Kubernetes (kind + CronJob + SwitchBot) Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Dec 26 '25 I Automated My Air Conditioner with Kubernetes (kind + CronJob + SwitchBot) # kubernetes # containers # iot # docker Comments Add Comment 3 min read How to Re-Encrypt Aurora Snapshots with a CMK for Cross-Account Migration Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow for AWS Community Builders Nov 14 '25 How to Re-Encrypt Aurora Snapshots with a CMK for Cross-Account Migration # aws # database # security # beginners 2 reactions Comments Add Comment 4 min read Practical Terraform Tips for Secure and Reliable AWS Environments Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow for AWS Community Builders Oct 10 '25 Practical Terraform Tips for Secure and Reliable AWS Environments # aws # terraform # devops # beginners 8 reactions Comments Add Comment 6 min read How I Combined Strands Agents, Bedrock AgentCore Runtime, and AgentCore Browser to Automate AWS Docs Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow for AWS Community Builders Sep 15 '25 How I Combined Strands Agents, Bedrock AgentCore Runtime, and AgentCore Browser to Automate AWS Docs # aws # ai # python # webdev 14 reactions Comments Add Comment 6 min read Fixing the “Invalid Parameter” Error When Registering an SNS Topic for SES Feedback Notifications Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow for AWS Community Builders Sep 11 '25 Fixing the “Invalid Parameter” Error When Registering an SNS Topic for SES Feedback Notifications # aws # security # devops # cloud 3 reactions Comments Add Comment 2 min read AWS Control Tower Landing Zone Setup: Troubleshooting Account Limits and KMS Policies Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow for AWS Community Builders Sep 2 '25 AWS Control Tower Landing Zone Setup: Troubleshooting Account Limits and KMS Policies # aws # devops # tutorial # cloud 1 reaction Comments Add Comment 3 min read How I Reduced ELB Access Log Analysis Time by 80% Using AWS Data Processing MCP Server Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow for AWS Community Builders Aug 9 '25 How I Reduced ELB Access Log Analysis Time by 80% Using AWS Data Processing MCP Server # mcp # aws # devops # security 3 reactions Comments Add Comment 4 min read Run Multi-Agent AI in the Cloud Without a Local GPU Using Docker Offload and Compose Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Jul 21 '25 Run Multi-Agent AI in the Cloud Without a Local GPU Using Docker Offload and Compose # docker # ai # webdev # cloud 1 reaction Comments Add Comment 5 min read Instant Feature Flags on ECS with AWS AppConfig — Zero Redeploys Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow for AWS Community Builders Jul 13 '25 Instant Feature Flags on ECS with AWS AppConfig — Zero Redeploys # aws # devops # typescript # productivity 4 reactions Comments Add Comment 6 min read Teleport Across Gather Town Instantly with This Chrome Extension Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Jun 20 '25 Teleport Across Gather Town Instantly with This Chrome Extension # extensions # javascript # productivity # webdev 5 reactions Comments Add Comment 4 min read Prevent Unexpected Claude Code Costs with This VSCode/Cursor Extension Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Jun 3 '25 Prevent Unexpected Claude Code Costs with This VSCode/Cursor Extension # vscode # cursor # extensions # vibecoding 1 reaction Comments Add Comment 2 min read Why I Chose Service Discovery Over Service Connect for ECS Inter-Service Communication Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow for AWS Community Builders May 6 '25 Why I Chose Service Discovery Over Service Connect for ECS Inter-Service Communication # containers # devops # aws # terraform 6 reactions Comments 1 comment 5 min read How I Used Amazon Nova Reel and Gradio to Auto-Generate Stunning GIF Banners Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow for AWS Community Builders Apr 17 '25 How I Used Amazon Nova Reel and Gradio to Auto-Generate Stunning GIF Banners # aws # ai # python # machinelearning 22 reactions Comments 6 comments 3 min read Cut Your API Costs to Zero: Docker Model Runner for Local LLM Testing Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Apr 10 '25 Cut Your API Costs to Zero: Docker Model Runner for Local LLM Testing # docker # ai # llm # webdev 2 reactions Comments Add Comment 4 min read Cost Optimization Gone Wrong: Lessons from Using Arm Runners in GitHub Actions for Fargate Spot Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow for AWS Community Builders Apr 3 '25 Cost Optimization Gone Wrong: Lessons from Using Arm Runners in GitHub Actions for Fargate Spot # githubactions # aws # devops # github 5 reactions Comments Add Comment 4 min read The Easiest Way to Set Up MCP with Claude Desktop and Docker Desktop Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Mar 24 '25 The Easiest Way to Set Up MCP with Claude Desktop and Docker Desktop # docker # beginners # ai # productivity 109 reactions Comments 4 comments 3 min read Improving RAG Systems with Amazon Bedrock Knowledge Base: Practical Techniques from Real Implementation Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow for AWS Community Builders Mar 17 '25 Improving RAG Systems with Amazon Bedrock Knowledge Base: Practical Techniques from Real Implementation # aws # rag # ai # typescript 4 reactions Comments 2 comments 6 min read LLM Model Selection Made Easy: The Most Useful Leaderboards for Real-World Applications Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Mar 15 '25 LLM Model Selection Made Easy: The Most Useful Leaderboards for Real-World Applications # llm # ai # beginners # machinelearning 10 reactions Comments Add Comment 4 min read Automating Tests for Multiple Generative AI APIs Using Postman (Newman) and Exporting Responses to CSV Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Mar 2 '25 Automating Tests for Multiple Generative AI APIs Using Postman (Newman) and Exporting Responses to CSV # webdev # ai # api # llm 2 reactions Comments Add Comment 3 min read Caught in a Cost Optimization Trap: Aurora Serverless v2 with RDS Proxy Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow for AWS Community Builders Feb 2 '25 Caught in a Cost Optimization Trap: Aurora Serverless v2 with RDS Proxy # aws # serverless # devops # database 1 reaction Comments 2 comments 2 min read Resolving CORS Errors Caused by S3 and WebKit's Disk Cache Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow for AWS Community Builders Jan 18 '25 Resolving CORS Errors Caused by S3 and WebKit's Disk Cache # webdev # browser # beginners # aws 4 reactions Comments Add Comment 2 min read Simplify Environment Variable Management with GitHub Environments Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Dec 15 '24 Simplify Environment Variable Management with GitHub Environments # github # githubactions # beginners # devops 2 reactions Comments Add Comment 2 min read Automating Security Hub Findings Summary with Bedrock, Slack Notifications, and Zenhub Task Management Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Dec 14 '24 Automating Security Hub Findings Summary with Bedrock, Slack Notifications, and Zenhub Task Management # devops # aws # ai # security 4 reactions Comments 4 comments 5 min read Automating BigQuery Data Preprocessing and AutoML with Vertex AI Pipelines Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Dec 6 '24 Automating BigQuery Data Preprocessing and AutoML with Vertex AI Pipelines # machinelearning # ai # googlecloud # beginners 1 reaction Comments Add Comment 5 min read Troubleshooting the "JavaScript heap out of memory" Error in a Node.js Application on ECS Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Dec 1 '24 Troubleshooting the "JavaScript heap out of memory" Error in a Node.js Application on ECS # aws # node # beginners # devops 5 reactions Comments Add Comment 3 min read Resolving ECS Task Definition Security Risks Detected by AWS Security Hub Using Secrets Manager Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Dec 1 '24 Resolving ECS Task Definition Security Risks Detected by AWS Security Hub Using Secrets Manager # aws # security # beginners # devops 3 reactions Comments Add Comment 3 min read How to Protect ECS Containers with a Read-Only Root Filesystem Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Nov 30 '24 How to Protect ECS Containers with a Read-Only Root Filesystem # aws # devops # security # beginners 4 reactions Comments Add Comment 2 min read Automate Slack Notifications with Graphs Using Cloud Run Functions and Cloud Scheduler Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Nov 16 '24 Automate Slack Notifications with Graphs Using Cloud Run Functions and Cloud Scheduler # beginners # googlecloud # webdev # python 3 reactions Comments Add Comment 3 min read Avoiding Connection Pinning in Lambda and RDS Proxy with NestJS and Proxy Splitting Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Nov 2 '24 Avoiding Connection Pinning in Lambda and RDS Proxy with NestJS and Proxy Splitting # webdev # aws # database # beginners 1 reaction Comments Add Comment 3 min read From Lambda to Fargate: How We Optimized Node.js Performance with the Right Task Specs Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Oct 15 '24 From Lambda to Fargate: How We Optimized Node.js Performance with the Right Task Specs # aws # webdev # serverless # beginners 5 reactions Comments Add Comment 3 min read Maximizing Cost Efficiency on ECS Fargate: ARM Architecture and Fargate Spot Strategies Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Oct 12 '24 Maximizing Cost Efficiency on ECS Fargate: ARM Architecture and Fargate Spot Strategies # aws # beginners # docker # devops 7 reactions Comments Add Comment 4 min read Automating Monthly Data Deletion for Aurora MySQL with ECS, EventBridge, and DynamoDB Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Sep 15 '24 Automating Monthly Data Deletion for Aurora MySQL with ECS, EventBridge, and DynamoDB # aws # database # webdev # beginners 2 reactions Comments Add Comment 6 min read Optimizing Aurora MySQL Storage by Deleting Unnecessary Data Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Sep 14 '24 Optimizing Aurora MySQL Storage by Deleting Unnecessary Data # aws # database # mysql # beginners 4 reactions Comments 1 comment 3 min read How to Enable the `Allow GitHub Actions to create and approve pull requests` Option When It's Grayed Out Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Sep 12 '24 How to Enable the `Allow GitHub Actions to create and approve pull requests` Option When It's Grayed Out # github # beginners # githubactions # webdev 1 reaction Comments Add Comment 1 min read How to Disable TLS v1.1 and Below in AWS ELB and RDS Aurora Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Sep 2 '24 How to Disable TLS v1.1 and Below in AWS ELB and RDS Aurora # terraform # security # network # aws 3 reactions Comments Add Comment 3 min read Analyzing ELB Access Logs with Athena: Configuration and Query Examples Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Aug 15 '24 Analyzing ELB Access Logs with Athena: Configuration and Query Examples # aws # beginners # sql # devops 4 reactions Comments 1 comment 3 min read Enabling Access Logs for AWS ELB (ALB) with Terraform Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Aug 14 '24 Enabling Access Logs for AWS ELB (ALB) with Terraform # webdev # aws # terraform # beginners 4 reactions Comments Add Comment 2 min read BigQuery and XGBoost Integration: A Jupyter Notebook Tutorial for Binary Classification Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Aug 12 '24 BigQuery and XGBoost Integration: A Jupyter Notebook Tutorial for Binary Classification # googlecloud # machinelearning # python # beginners 2 reactions Comments Add Comment 4 min read Migrating Guide: RDS for MySQL to Aurora Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Aug 10 '24 Migrating Guide: RDS for MySQL to Aurora # database # aws # beginners # webdev 2 reactions Comments Add Comment 6 min read Enhance Code Security with GitHub Actions: Automatically Commenting PRs with Docker Scans Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Jul 14 '24 Enhance Code Security with GitHub Actions: Automatically Commenting PRs with Docker Scans # docker # webdev # devops # security 6 reactions Comments Add Comment 4 min read Bypassing TROCCO: Direct Data Transfer from HubSpot to BigQuery Using Cloud Functions Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Jul 6 '24 Bypassing TROCCO: Direct Data Transfer from HubSpot to BigQuery Using Cloud Functions # googlecloud # python # beginners # productivity 1 reaction Comments Add Comment 5 min read Common Pitfalls in Machine Learning Model Inference for Beginners and How to Solve Them Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Jun 9 '24 Common Pitfalls in Machine Learning Model Inference for Beginners and How to Solve Them # machinelearning # beginners # python # ai 3 reactions Comments Add Comment 2 min read Enhancing ECR Security: Scheduled Automated Container Scans and Slack Notifications Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Jun 8 '24 Enhancing ECR Security: Scheduled Automated Container Scans and Slack Notifications # security # aws # devops # beginners 1 reaction Comments Add Comment 6 min read Mastering ECS Task Scheduling: Effective Strategies to Reduce Costs Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Jun 1 '24 Mastering ECS Task Scheduling: Effective Strategies to Reduce Costs # devops # terraform # webdev # aws 8 reactions Comments 5 comments 6 min read How to Hide the X-Powered-By Header in NestJS Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow May 19 '24 How to Hide the X-Powered-By Header in NestJS # security # beginners # webdev # nestjs 8 reactions Comments 2 comments 1 min read Mastering Secure CI/CD for ECS with GitHub Actions Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow May 18 '24 Mastering Secure CI/CD for ECS with GitHub Actions # devops # docker # cicd # security 70 reactions Comments 12 comments 7 min read Optimizing S3 Bucket Management and Lifecycle with Terraform Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow May 11 '24 Optimizing S3 Bucket Management and Lifecycle with Terraform # aws # terraform # devops # beginners 2 reactions Comments Add Comment 2 min read How to Temporarily Remove and Reintegrate Cloud Resources from Terraform Management Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Apr 26 '24 How to Temporarily Remove and Reintegrate Cloud Resources from Terraform Management # webdev # terraform # aws # devops 2 reactions Comments Add Comment 2 min read Migrating from AWS SageMaker to GCP Vertex AI: A Training Environment Transition Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Apr 13 '24 Migrating from AWS SageMaker to GCP Vertex AI: A Training Environment Transition # ai # aws # googlecloud # machinelearning 6 reactions Comments 2 comments 4 min read Optimizing Team Productivity: Key Front-End Coding Practices with TypeScript and React Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Mar 18 '24 Optimizing Team Productivity: Key Front-End Coding Practices with TypeScript and React # frontend # beginners # typescript # react 6 reactions Comments Add Comment 4 min read Automating Looker Studio Data Updates with S3 CSVs Processed through BigQuery Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Mar 17 '24 Automating Looker Studio Data Updates with S3 CSVs Processed through BigQuery # webdev # gcp # beginners # devops 4 reactions Comments Add Comment 5 min read Building AI Agent for Pokémon Data Analysis & Reporting with LangChain Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Feb 12 '24 Building AI Agent for Pokémon Data Analysis & Reporting with LangChain # ai # chatgpt # python # openai 16 reactions Comments 1 comment 12 min read Optimizing Docker Images and Conda Environments in SageMaker Training Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Jan 31 '24 Optimizing Docker Images and Conda Environments in SageMaker Training # docker # devops # aws # beginners 1 reaction Comments Add Comment 5 min read Optimizing Docker Images with Multi-Stage Builds and Distroless Approach Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Jan 7 '24 Optimizing Docker Images with Multi-Stage Builds and Distroless Approach # docker # devops # beginners # go 13 reactions Comments 1 comment 4 min read Strengthening Security with IAM Roles and OpenID Connect in GitHub Actions Deploy Workflows Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Jan 6 '24 Strengthening Security with IAM Roles and OpenID Connect in GitHub Actions Deploy Workflows # devops # beginners # aws # security 3 reactions Comments Add Comment 5 min read Implementing Real-Time Responses with LangChain and LLM Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Dec 24 '23 Implementing Real-Time Responses with LangChain and LLM # ai # openai # webdev # python 11 reactions Comments Add Comment 3 min read Unanticipated Twist: Achieved All 12 AWS Certifications but Ineligible for Japan AWS All Certifications Engineers! Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Dec 4 '23 Unanticipated Twist: Achieved All 12 AWS Certifications but Ineligible for Japan AWS All Certifications Engineers! # aws # certification # webdev # development 2 reactions Comments Add Comment 4 min read Secure Connection between Lambda and RDS: Choosing and Implementing SSL/TLS Certificates Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Nov 23 '23 Secure Connection between Lambda and RDS: Choosing and Implementing SSL/TLS Certificates # webdev # aws # security # database 9 reactions Comments Add Comment 2 min read Enhancing Deployment Security through the Integration of IAM Roles and GitHub Actions Atsushi Suzuki Atsushi Suzuki Atsushi Suzuki Follow Nov 3 '23 Enhancing Deployment Security through the Integration of IAM Roles and GitHub Actions # webdev # aws # githubactions # security 3 reactions Comments Add Comment 3 min read loading... 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — Your community HQ Home About Contact Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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https://www.highlight.io/docs/getting-started/server/rust/actix | Using highlight.io with actix-web Star us on GitHub Star Docs Sign in Sign up Getting Started Getting Started with Highlight Fullstack Mapping Browser React.js Next.js Remix Vue.js Angular Gatsby.js SvelteKit Electron highlight.run SDK Overview Canvas & WebGL Console Messages Content-Security-Policy Identifying Users iframe Recording Monkey Patches Browser OpenTelemetry Persistent Asset Storage Privacy Proxying Highlight React.js Error Boundary Recording Network Requests and Responses Recording WebSocket Events Salesforce Lightning Web Components (LWC) Data Export Sourcemap Configuration Tracking Events Troubleshooting Upgrading Highlight Versioning Sessions & Errors Other React Native (beta) Server Go Overview chi Echo Fiber Gin GORM gqlgen Logrus Manual Tracing gorilla mux JS Overview Apollo AWS Lambda Cloudflare Workers Express.js Firebase Hono Nest.js Next.js Node.js Pino tRPC Winston Python Overview AWS Lambda Azure Functions Django FastAPI Flask Google Cloud Functions Loguru Other Frameworks Python AI / LLM Libraries Python Libraries Ruby Overview Other Frameworks Ruby on Rails Rust Overview actix-web No Framework Hosting Providers Overview Metrics in AWS Logging in AWS Logging in Azure Fly.io NATS Log Shipper Logging in GCP Heroku Log Drain Render Log Stream Logging in Trigger.dev Vercel Log Drain Elixir Overview Elixir App Java: All Frameworks PHP: All Frameworks C# .NET ASP C# .NET 4 ASP Docker / Docker Compose File Fluent Forward curl OpenTelemetry Protocol (OTLP) Syslog RFC5424 Systemd / Journald Native OpenTelemetry Overview Error Monitoring Logging Tracing Browser Instrumentation Metrics Fullstack Frameworks Overview Next.js Fullstack Overview Next.js Page Router Guide Next.js App Router Guide Edge Runtime Advanced Config Remix Walkthrough Self Host & Local Dev Overview Development deployment guide. 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Menu Highlight Docs Welcome to highlight.io Get Started Roadmap Company Values Compliance & Security Open Source Contributing Overview GraphQL Backend Frontend (app.highlight.io) Landing Site (highlight.io) Documentation End to End SDK Example Apps Adding an SDK Application Architecture GitHub Code Spaces Code Style Good First Issues Self-hosting Self-hosted [Dev] Self-hosted [Hobby] Self-hosted [Enterprise] Telemetry Our Competitors Product Philosophy Product Features Session Replay Overview Canvas & Iframe Dev-tool Window Recording Tracking Users & Recording Events Filtering Sessions GraphQL Live Mode Performance Impact Player Session Caching Rage Clicks Request Proxying Session Search Extracting the Session URL Session Search Deep Linking Shadow Dom + Web Components Error Monitoring Overview Enhancing Errors with GitHub Error Search Filtering Errors Grouping Errors Managing Errors Manually Reporting Errors Sourcemaps General Features Overview Alerts Comments Digests Environments Search Segments Services Webhooks Logging Overview Log Alerts Log Search Tracing Overview Trace Search Dashboards Overview Dashboard Management Metrics Tutorials Service Latency Web Vitals & Page Speed User Engagement User Analytics Graphing Drilldown Event Search Dashboard Variables SQL Editor Metrics (beta) Overview Frequently Asked Questions. Integrations Integrations Overview Amplitude Integration ClickUp Integration Discord Integration Electron Support Front Integration GitHub Integration Grafana Integration Overview Setup Dashboards Alerts Height Integration Intercom Integration Jira Integration LaunchDarkly Integration Linear Integration Mixpanel Integration Nuxt Integration Pendo Integration Segment Integration Slack Integration Vercel Integration WordPress Plugin Highlight.io Changelog Overview Changelog 12 (02/17) Changelog 13 (02/24) Changelog 14 (03/03) Changelog 15 (03/11) Changelog 16 (03/19) Changelog 17 (04/07) Changelog 18 (04/26) Changelog 19 (05/22) Changelog 20 (06/06) Changelog 21 (06/21) Changelog 22 (08/07) Changelog 23 (08/22) Changelog 24 (09/11) Changelog 25 (10/03) Changelog 26 (11/08) Changelog 27 (12/22) Changelog 28 (3/6) Changelog 29 (4/2) Getting Started Getting Started with Highlight Fullstack Mapping Browser React.js Next.js Remix Vue.js Angular Gatsby.js SvelteKit Electron highlight.run SDK Overview Canvas & WebGL Console Messages Content-Security-Policy Identifying Users iframe Recording Monkey Patches Browser OpenTelemetry Persistent Asset Storage Privacy Proxying Highlight React.js Error Boundary Recording Network Requests and Responses Recording WebSocket Events Salesforce Lightning Web Components (LWC) Data Export Sourcemap Configuration Tracking Events Troubleshooting Upgrading Highlight Versioning Sessions & Errors Other React Native (beta) Server Go Overview chi Echo Fiber Gin GORM gqlgen Logrus Manual Tracing gorilla mux JS Overview Apollo AWS Lambda Cloudflare Workers Express.js Firebase Hono Nest.js Next.js Node.js Pino tRPC Winston Python Overview AWS Lambda Azure Functions Django FastAPI Flask Google Cloud Functions Loguru Other Frameworks Python AI / LLM Libraries Python Libraries Ruby Overview Other Frameworks Ruby on Rails Rust Overview actix-web No Framework Hosting Providers Overview Metrics in AWS Logging in AWS Logging in Azure Fly.io NATS Log Shipper Logging in GCP Heroku Log Drain Render Log Stream Logging in Trigger.dev Vercel Log Drain Elixir Overview Elixir App Java: All Frameworks PHP: All Frameworks C# .NET ASP C# .NET 4 ASP Docker / Docker Compose File Fluent Forward curl OpenTelemetry Protocol (OTLP) Syslog RFC5424 Systemd / Journald Native OpenTelemetry Overview Error Monitoring Logging Tracing Browser Instrumentation Metrics Fullstack Frameworks Overview Next.js Fullstack Overview Next.js Page Router Guide Next.js App Router Guide Edge Runtime Advanced Config Remix Walkthrough Self Host & Local Dev Overview Development deployment guide. Integrations Microsoft Teams self-hosted Hobby deployment guide. Traefik SSL Proxying. Docs Home SDK Client SDK API Reference Cloudflare Worker SDK API Reference Go SDK API Reference Hono SDK API Reference Java SDK API Reference Next.JS SDK API Reference Node.JS SDK API Reference Python SDK API Reference Ruby SDK API Reference Rust SDK API Reference Docs / Getting Started / Server / Rust / Using highlight.io with actix-web Using highlight.io with actix-web Learn how to set up highlight.io with the actix-web framework. 1 Configure client-side Highlight. (optional) If you're using Highlight on the frontend for your application, make sure you've initialized it correctly and followed the fullstack mapping guide . 2 Install the Highlight Rust actix SDK. Add Highlight to your Config.toml. [dependencies] highlightio-actix = "1" 3 Initialize the Highlight Rust SDK and actix Middleware. highlightio_actix::highlight::Highlight::init initializes the SDK, and adding the highlightio_actix::HighlightActix middleware will start tracing actix. use actix_web::{App, Error, HttpServer}; use highlightio_actix::{highlight::{Highlight, HighlightConfig}, HighlightActix}; // ...your services... #[actix_web::main] async fn main() -> Result<(), Error> { let h = Highlight::init(HighlightConfig { project_id: "<YOUR_PROJECT_ID>".to_string(), service_name: "my-rust-app".to_string(), service_version: "git-sha".to_string(), ..Default::default() }).expect("Failed to initialize Highlight.io"); let _h = h.clone(); HttpServer::new(move || { App::new() .wrap(HighlightActix::new(&_h)) // ... }) .bind("127.0.0.1:8080")? .run() .await?; h.shutdown(); Ok(()) } 4 Verify your errors are being recorded. Now that you've set everything up, you can verify that the backend error handling works by throwing an error in a service. Visit the highlight errors page and check that backend errors are coming in. // ... #[get("/error")] async fn error() -> Result<impl Responder, std::io::Error> { Err(std::io::Error::new( std::io::ErrorKind::Other, "Test error" ))?; Ok(format!("You shouldn't be able to see this.")) } // ... #[actix_web::main] async fn main() -> Result<(), Error> { // ... HttpServer::new(move || { App::new() .wrap(HighlightActix::new(&h)) .service(error) // add this }) // ... } 5 Install the log crate. Highlight works with the log crate to make logging easier. [dependencies] log = "0.4" 6 Call the logging facades. Highlight::init automatically installs a logging backend, so you can call any of the log crate's macros to emit logs. NOTE: env_logger only logs errors to the console out by default, so to see your logs, run your project with the RUST_LOG=<crate name> environment variable, or RUST_LOG=trace to see everything. use log::{trace, debug, info, warn, error}; // ... #[get("/")] async fn index() -> impl Responder { info!("Hello, world! Greet endpoint called."); format!("Hello, world!") } 7 Verify your backend logs are being recorded. Visit the highlight logs portal and check that backend logs are coming in. 8 Add the tracing crate to your project. The tracing crate allows you and your dependencies to record traces that will be automatically captured by the highlight.io SDK. [dependencies] tracing = "0.1" 9 Record a trace. Use the tracing crate to create spans and events. You can read more about this on the docs.rs page of the tracing crate . use tracing::{event, span, Level}; // ... let span = span!(Level::INFO, "my_span"); let _guard = span.enter(); event!(Level::DEBUG, "something happened inside my_span"); 10 Verify your backend traces are being recorded. Visit the highlight traces portal and check that backend traces are coming in. Highlight Integration in Rust Using highlight.io without a framework in Rust [object Object] | 2026-01-13T08:48:58 |
https://blog.smartere.dk | blog.smartere blog.smartere // Ramblings of Mads Chr. Olesen jan 12 Floppy Disks: the best TV remote for kids Posted on mandag, januar 12, 2026 in Hal9k , Planet Ubuntu-DK , Planets Modern TVs are very poorly suited for kids. They require using complicated remotes or mobile phones, and navigating apps that continually try to lure you into watching something else than you intended to. The usual scenario ends up with the kid feeling disempowered and asking an adult to put something on. That something ends up on auto-play because then the adult is free to do other things and the kid ends up stranded powerless and comatose in front of the TV. Instead I wanted to build something for my 3-year old son that he could understand and use independently. It should empower him to make his own choices. It should be physical and tangible, i.e. it should be something he could touch and feel. It should also have some illusion that the actual media content was stored physically and not un-understandably in “the cloud”, meaning it should e.g. be destroyable — if you break the media there should be consequences. And there should be no auto-play: interact once and get one video. Floppy disks are awesome! And then I remembered the sound of a floppy disk. The mechanical click as you insert it, the whirr of the disk spinning, and the sound of the read-head moving. Floppy disks are the best storage media ever invented! Why else would the “save-icon” still be a floppy disk? Who hasn’t turned in a paper on a broken floppy disk, with the excuse ready that the floppy must have broken when the teacher asks a few days later? But kids these days have never used nor even seen a floppy disk, and I believe they deserve this experience! Building on the experience from the Big Red Fantus-Button , I already had a framework for controlling a Chromecast, and because of the netcat | bash shenanigans it was easily extendable. My first idea for datastorage was to use the shell of a floppy disk and floppy drive, and put in an RFID tag; this has been done a couple of times on the internet, such as RFIDisk or this RaspberryPi based RFID reader or this video covering how to embed an RFID tag in a floppy disk . But getting the floppy disk apart to put in an RFID tag and getting it back together was kinda wonky. When working on the project in Hal9k someone remarked: “Datastorage? The floppy disk can store data!”, and a quick prototype later this worked really, really , well. Formatting the disk and storing a single small file, “autoexec.sh”, means that all the data ends up in track 0 and is read more or less immediately. It also has the benefit that everything can be checked and edited with a USB floppy disk drive; and the major benefit that all the sounds are completely authentic: click, whirrr, brrr brrr. Autorun for floppy disks is not really a thing. The next problem to tackle was how to detect that a disk is inserted. The concept of AutoRun from Windows 95 was a beauty: insert a CD-ROM and it would automatically start whatever was on the media. Great for convenience, quite questionably for security. While in theory floppy disks are supported for AutoRun , it turns out that floppy drives basically don’t know if a disk is inserted until the operating system tries to access it! There is a pin 34 “Disk Change” that is supposed to give this information , but this is basically a lie. None of the drives in my possession had that pin connected to anything, and the internet mostly concurs. In the end I slightly modified the drive and added a simple rolling switch, that would engage when a disk was inserted. A floppy disk walks into a drive; the microcontroller says “hello!” The next challenge was to read the data on a microcontroller. Helpfully, there is the Arduino FDC Floppy library by dhansel, which I must say is most excellent. Overall, this meant that the part of the project that involved reading a file from the floppy disk FAT filesystem was basically the easiest part of all! A combined ATMega + ESP8266 UNO-like board. Not really recommended, but can be made to work. However, the Arduino FDC Floppy library is only compatible with the AVR-based Arduinos, not the ESP-based ones, because it needs to control the timing very precisely and therefore uses a healthy amount of inline assembler. This meant that I would need one AVR-based Arduino to control the floppy disk, but another ESP-based one to do the WiFi communication. Such combined boards do exist, and I ended up using such a board, but I’m not sure I would recommend it: the usage is really finagly, as you need to set the jumpers differently for programming the ATmega, or programming the ESP, or connecting the two boards serial ports together. A remote should be battery-powered A remote control should be portable, and this means battery-powered. Driving a floppy disk of of lithium batteries was interesting. There is a large spike in current draw when the disk needs to spin up of several amperes, while the power draw afterwards is more modest, a couple of hundred milliamperes. I wanted the batteries to be 18650s, because I have those in abundance. This meant a battery voltage of 3.7V nominally, up to 4.2V for a fully charged battery; 5V is needed to spin the floppy around, so a boost DC-DC converter was needed. I used an off the shelf XL6009 step-up converter board. At this point a lot of head-scratching occurred: that initial spin-up power draw would cause the microcontroller to reset. In the end a 1000uF capacitor at the microcontroller side seemed to help but not eliminate the problem. One crucial finding was that the ground side of the interface cable should absolutely not be connected to any grounds on the microcontroller side. I was using a relatively simple logic-level MOSFET, the IRLZ34N , to turn off the drive by disconnecting the ground side. If any ground is connected, the disk won’t turn off. But also: if any logic pin was being pulled to ground by the ATmega, that would also provide a path to ground. But since the ATmega cannot sink that much current this would lead to spurious resets! Obvious after the fact, but this took quite some headscratching. Setting all the logic pins to input, and thus high impedance , finally fixed the stability issues. After fixing the stability, the next challenge was how to make both of the microcontrollers sleep. Because the ATmega sleep modes are quite a lot easier to deal with, and because the initial trigger would be the floppy inserting, I decided to make the ATmega in charge overall. Then the ESP has a very simple function: when awoken, read serial in, when a newline is found then send off that complete line via WiFi, and after 30 seconds signal to the ATmega that we’re sleeping, and go back to sleep. The overall flow for the ATmega is then: A disk is inserted, this triggers a interrupt on the ATmega that wakes up. The ATmega resets the ESP, waking it from deep sleep. The ATmega sends a “diskin” message over serial to the ESP; the ESP transmits this over WiFi when available. The ATmega turns on the drive itself, and reads the disk contents, and just sends it over serial to the ESP. Spin down the disk, go to sleep. When the disk is ejected, send a “diskout” message over serial, resetting the ESP if needed. Go back to 1. The box itself is just lasercut from MDF-board. For full details see the FloppyDiskCast Git repository . Server-side handlers Responding to those commands is still the netcat | bash from the Big Red Fantus-Button , which was simply extended with a few more commands and capabilities. A few different disks to chose from, with custom printed labels. diskin always sends a “play” command to the Chromecast. diskout always sends a “pause” command to the Chromecast. Other commands like dad-music are handled in one of two ways: Play a random video from a set, if a video from that set is not already playing : e.g. dad-music will randomly play one of dad’s music tracks – gotta influence the youth! Play the next video from a list, if a video from the list is not already playing : e.g. fantus-maskinerne will play the next episode, and only the next episode. Common for both is that they should be idempotent actions, and the diskin shortcut will make the media resume without having to wait for the disk contents itself to be read and processed. This means that the “play/pause” disk just contains an empty file to work. Questionable idea meets real-world 3 year old user The little guy quickly caught on to the idea! Much fun was had just pausing and resuming music and his Fantus TV shows. He explored and prodded, and some disks were harmed in the process. One problem that I did solve was that the read head stayed on track 0 after having read everything: this means that when the remote with disk inside it is tumbled around, the disk gets damaged at track 0. To compensate for this, I move the head to track 20 after reading has finished: any damage is then done there, where we don’t store any data. As a bonus it also plays a little more mechanic melody. Comments (2) | apr 20 Upgrading the Olimex A20 LIME2 to 2GB RAM, by learning to BGA solder and deep diving into the U-Boot bootloader process Posted on søndag, april 20, 2025 in Hal9k , Planets As I’ve written about previously I have had the Olimex A20-OLinuXino-LIME2 in service for quite some time . But one thing that I’ve been curious about is why it’s only available with 1GB of RAM, when the A20 chip itself can support up to 2GB? Could it be upgraded to 2GB RAM by a simple swap in of a larger memory module? RAM part of the LIME2 schematic If you check the schematic the address lines are actually wired up: both A14 and A15 which are labelled NC (no-connect) on the chips are wired up on the address bus, meaning a full 2¹⁶ row addresses should be addressable. So this might actually work out! Detour: How do CPUs access memory? From a very high level the way a CPU accesses memory is the same all the way from a small microprocessor like the RP2040 up to a x86. There are a number of pins connecting the CPU and the RAM: A number of address lines, e.g. A0–A15 in our case. These are always driven by the CPU. A number of data lines, e.g. DQ0–DQ15. These are bi-directional and driven by the CPU for writes, but by the RAM for reads. A couple of signalling lines to control the communication, e.g. the shared clock, or the CPU signaling that the address lines are set with the address for a read, or the RAM signaling that the data lines are populated with the data read out. These can be quite complicated, as seen with DDR3 in this instance, where signalling talks about “banks”, “lower/upper byte data strobe”, “data masks” and “chip select”. The most crude form of using more than one RAM chip would be to use “chip select” as known from SPI or I2C communication. This is however not how it’s done on the LIME2: address, data and chip select lines are wired in parallel for the two chips. The only difference in wiring is on the “DMU”, “DML”, and “DQSU” and “DQSL” lines: these are used for lower and upper byte data strobes, meaning that the same address is setup for both chips, and then the chips are strobed one at a time – effectively allowing each chip to prepare the read in parallel. Finding compatible chips with 256Mx16 Luckily DDR chips are standardized, but it seems that the standardisation does not quite go all the way to the datasheets, in e.g. pin naming and concepts. But at least the density and organization are standardised: the 256M is the number of different addressable storage locations, and the x16 is how many bits are stored per location. Multiplying those gives the number of megabits stored, 4096 megabits in this case, so dividing by 8 gives the number of megabytes stored: 512MiB. Looking at the pinout for the specified chip ( K4B4G1646D-BYK0, a Samsung chip ): We can see it specifies only address lines A0–A14, which is enough for a 256M module. But the LIME2 schematic was helpful enough to hookup A15 to the JEDEC standard location , even if that pin is NC on all memory modules shipped. This might actually work! The last crucial parameter for selecting bigger RAM chips is the supply voltage. DDR3 comes in both standard and low-voltage (DDR3L) variants. The LIME2 schematic actually just specifies that “ When DDR3L is used, VDD&VDDQ are set to 1.35V!!! “, so to know which it is we would have to look at the particular board and measure the power supply line. But luckily, almost all DDR3L chips are backwards compatible to the 1.5V DDR3 level, so as long as we can find a DDR3L chip voltage shouldn’t be an issue. So in theory any 512Mx16 DDR3L chip should work. In practice I ended up trying two variants: Micron MT41K512M16 , which seems to be the only option on AliExpress, and cheap, but which (spoiler alert!) I did not get working ISSI IS46TR16512BL , which I did get working, but is more expensive to the point that the two needed RAM chips cost more than the LIME2 itself. Learning to BGA solder Finally, we can jump to the microscope soldering station, and learn to BGA solder. This was by far the longest part of this project. The chips come pre-balled, so in theory the job could have been as simple as desoldering the old chips and soldering on the new ones. Not so easy in practice. I ended up having to re-ball and re-solder chips , apply flux, solder-wick and ethanol in copious amount , re-attach SMD resistors that had taken a stroll under the heatgun, and battling a self-compiled U-Boot that I probably messed up badly. You get to see my frustration in a few nice pictures. I have a suspicion that I messed up U-Boot at one point, by trying to compile it with automatic impedance calibration, instead of leaving the LIME2 defaults DDR settings in. This might be the reason I couldn’t get the Micron MT41K512M16 chips to work, but I will have to investigate this more. I probably also messed up the first soldering on of a chip, by not using enough heat. My main piece of advice would be to not be too afraid to get the temperature of the chip up, if you spend more than about a minute trying to solder or desolder the chip, chances are you will be heating up the rest of the board much more than needed and the chip itself too little! The moment of seeing the board booting with 1GB from a single ISSI IS46TR16512BL was a great success though — soldering on the other ISSI chip was basically a walk in the park. Further U-Boot adventures of a curious character A serial terminal is absolutely essential for getting any kind of feedback on the early part of the boot process, and the first user-controlled software encountered on the LIME2 is U-Boot . U-Boot is the universal bootloader responsible for figuring out the basic hardware configuration (including RAM configuration), finding the (Linux) kernel and moving it into RAM and giving over control to the kernel for further booting. Curiously, U-Boot can run with absolutely no RAM chips (guess how I know!), because the SunXi early boot process happens entirely in on-chip ROM and a small on-chip SRAM . But how does U-Boot actually determine how much memory is there? Well, remember that accessing a memory location is just putting an address on the address lines and pulling some signalling pins. So U-Boot simply tries and write to increasing addresses and see if the expected data can be read back . How is the memory size then communicated to the Linux kernel? By a bootarg parameter, e.g. mem=2048M . Does this mean we can try and trick the Linux kernel into thinking it has more memory than physically present? Yes, but with disastrous results if the non-existent memory is ever attempted to be used. I now possess a unique 2GB LIME2 Until told otherwise, I will happily claim that this is the only 2GB LIME2 in existence — but do let me know if you give the procedure a try! In the end the process was much simpler than I thought: the tricky part was definitely getting the hang of BGA soldering. Don’t be afraid of raising the temperature! Peeking into the innards of U-Boot was also fascinating: there is definitely a layer below of pretty dark bit-setting magic, but the overall process is really well structured! A unique 2GB LIME2 That actually boots! Comments (3) | jan 6 Making a too cheap LED lamp safe to use Posted on mandag, januar 6, 2025 in Hal9k , Planets This could happen to you: A really cool LED lamp was found online, on a Danish and well-written homepage. Unfortunately, when the lamp arrives it is a cheap Chinese production, of questionable quality and safety. This is a non-rational quest to make such a cheap LED lamp safe to use. From the outset the wires are tiny. The wires are connected with wire nuts *gasp*! (Wire nuts are basically unheard of in Europe). The LED driver itself that converts the 230V AC into DC has absolutely no separation, and as we will see later, absolutely no safety features. It did have a cool feature of changing light color temperature by turning the lamp on and off a couple of times, though. Short-circuited 300mA Unloaded 118V. Sparky! But happily going to 300mA when shorted, going up to 118V unloaded, and full willingness to spark away, is a deal-breaker. This abomination was not being powered on in this house! It should be possible to replace the unsafe parts with safer (and more expensive) parts. The first step was understanding the mess of wires. This took quite some pondering to figure out that all the LEDs were basically in series, and that it was wired with a “common positive”, with either the white or the black wire (or both) acting as ground depending on the wanted color temperature. In the end the entire schematic was reverse engineered. That LED driver was going nowhere but the electronic garbage bin, so a replacement of decent quality had to be acquired: a constant-current LED driver (configurable from 200mA–350mA) was purchased from a reputable source. That gave the next problem: an LED driver of quality was at least double the size of the unsafe one, and did not fit in the original round enclosure. 3D-printing to the rescue, and a new bigger round enclosure was printed. Now everything should be able to fit and work! Instead of that illogical wiring of putting the LEDs in series, why not just put the two parts in parallel? Well, that won’t work. Only the path of least-resistance would light up, in this case the dome LEDs. So, back to the original wiring in series. Unfortunately, the next problem was that the new LED driver was unwilling to drive LEDs as originally wired, that seemed to require somewhere above 45V, out of spec for the new driver. More stuff had to change. Looking at the schematic, the long strip in the circle could be cut in half, and the two half put in parallel instead. This should reduce the power going to those LEDs, and thus also the light output, but should also help to decrease the required voltage. But first I had to learn again the hard way that putting LEDs in parallel they need to match quite closely: the original LED strip had 11 segments, and dividing into 6 and 5 gave lights only in the one part. Reducing to 5 and 5 segments worked really well! Finally, the total voltage of putting the two parts of the lamp in series was below what the new LED driver would supply. The only task remaining was to fit everything back into the enclosure, and add copious amounts of Kapton tape and hot glue. And finally, the spaceman could go star-fishing – safely. Comments (0) | okt 21 Giv mig nu bare elprisen.somjson.dk! (en historie om det måske værste datasæt i åbne energidata) Posted on mandag, oktober 21, 2024 in Danish , Hal9k , Planets Der findes rigtig meget åbent data om det danske energi system hos Energi Data Service , f.x. spot prisen på elektricitet og CO2 prognoser per kWh . Det er dog overordentligt svært at finde den samlede pris man betaler som forbruger per kWh, pga. det uigennemskuelige datasæt over tariffer og priser . I frustration kom udbruddet: “Giv mig nu bare elprisen.somjson.dk ” der nemt summerer alle priser og afgiter per elselskab, er open source og uden yderligere dikke-darer. Hvad koster strøm i Danmark? For en forbruger i Danmark er strømprisen en sum af forskellige priser og afgifter, nogle faste, nogle dynamiske: El-afgiften fastsat ved lov til 0,761 kr per kWh. Energinet’s eltariffer : Nettarif på 0,074 kr per kWh (år 2024), og systemtarif på 0,051 kr per kWh (år 2024). Netselskabstarif fra forsyningsselskabet ( N1 , Radius , etc.): denne varierer per time og per sæson for at forsøge at incentivere til at udligne forbruget så der ikke skal investeres i nye og større elkabler, og er indkodet i datasættet over tariffer og priser . Private forbrugere betaler C-tarif. Spot-prisen : er den anden variable, og denne varierer ud fra udbud og efterspørgsel. Moms: 25% lagt til summen af ovenstående Dette er alle de uundgåelige priser og afgifter, der kan regnes ud udelukkende fra adressen. Derudover kommer så det “frie elmarked”, hvor der skal betales til et elselskab: typisk månedsabonnement og et tillæg til spot-prisen. Tariffer og priser – det værste åbne datasæt? Som om det ikke er uoverskueligt nok i sig selv, bliver vi nødt til at snakke om datasættet Datahub Price List . Der er flere åbenlyse problemer med det: Der er flere felter man burde filtrere efter, men hvor der ikke findes en udtømmende liste over værdier, f.x. netselskab “ChargeOwner”. Det bedste man kan gøre er at downloade, hvor man så løber ind i at download kun giver 100.000 rækker – og datasættet er fuldt på over 300.000 rækker. ChargeTypeCode er per selskab – og uden systematik. Så for hvert enkelt selskab skal man finde ud af hvilken priskode de bruger for C-tariffen. Og hvad når det ændrer sig? ValidTo kan være udeladt og dermed et open ended interval, og prisen gælder så indtil data retroaktivt ændres. Det betyder også at man ikke kan filtrere på datoer, da prisen på 1. april kan være en række der har en ValidFrom 1. januar (eller tidligere). Price1-24: dette er selve timetarif-priserne. Hvis en pris ikke er udfyldt gælder Price1 – hvorfor I alverden dog tilføje den ekstra kompleksitet!?!?! For ikke at tale om tidszoner: man må antage (det er ikke dokumenteret) at alle datoer og timetal er angivet i hvad end tid der er gældende i Danmark på pågældende dato. Dette giver så problemer ved skift fra sommer-/normal-tid hvor en time gentages eller udelades: hvilken timesats bør bruges i et døgn der har 23 eller 25 timer? Giv mig nu bare elprisen.somjson.dk ! Efter at have regnet de fleste af de ovenstående problemer ud, skrev jeg en API-proxy der udstiller det API man i virkeligheden vil have: givet en dato, og et elselskab (eller en adresse), returnerer den prisen time for time som et JSON dokument . Prisen er typisk tilgængelig fra kl. 13 dagen før. Som bonus får man også CO2 udledningen med, hvis den er tilgængelig (typisk kl. 15 dagen før). Det er implementeret som en ren API proxy, dvs. det er ren omskrivning af input og data og ikke andet. Det hele er open source, men der kører en version på elprisen.somjson.dk som frit kan benyttes. Alternativer Der findes andre API’er der opfylder forskellige use-cases: Min Strøm API er rigtig modent og har egen forecast model der kan forecaste 7 dage frem, før priserne er låst på Energi Data Service. Kræver en API nøgle og er uden kildekode HomeAssistant energidataservice virker kun med Home Assistant, men fungerer på samme måde mod Energi Data Service. Strømligning API kan bruges til at udregne priser baseret på historisk forbrugsdata. Kan dog også bruges til at hente de forecastede priser. Med rate limiting, og uden kildekode. Carnot har også et åbent API og egen forecast model. Kræver API nøgle, og er uden kildekode. Billigkwh.dk har et åbent API til elpriser der også inkluderer de forskellige elselskabers abonnement. Comments (0) | okt 9 World’s Longest Multi-Cutter Blade: 30 cm Posted on onsdag, oktober 9, 2024 in Hal9k , Planets , Woodworking I had a need for an extra-extra long multi-cutter blade, so we made one in Hal9k . Until proven otherwise, we hereby claim it to be the world’s longest, at about 30 cm from rotation point to the cutting edge. Converting Starlock-MAX to Starlock-Plus Initially I thought I could get away with just a 80mm long Bosch MAIZ 32 APB which seems to be the longest commercially available. First problem was that my multi-cutter was only “Starlock-Plus” and this blade is Starlock-MAX. Turns out, you can easily get around that: just drill up the hole to 10mm, and it fits like a glove, at least on the Starlock-Plus Bosch GOP 18V-28 . World record time But as it turns out, I needed more length, and anything worth doing is worth overkilling! So sacrificing an old worn-out blade by welding on some 2mm steel plate provided a good base that would still attach to the multi-cutter. First attempt was just attaching the blade with two 2mm screws, as these are the largest that will fit in the star’s spikes and thereby prevent rotation. Initial testing: So next solution was to beef up with a central 8mm bolt instead. This worked much better if torqued enough (read: all you possibly can!), test-run went great after the initial oscillations: And ultimately the cut in the tight corner was made, one-handedly in order to be able to film: Great success! This should not be considered safe, and several warranties were probably voided, but it got the job done. Comments (2) | feb 15 Reparation af Nordlux IP S12 badeværelseslampe der ikke lyser længere Posted on torsdag, februar 15, 2024 in Danish , Hal9k , Planets Denne badeværelseslampe er udgået af produktion, og pga. monteringen og at man ofte har mere end én er det noget træls at skulle udskifte – det giver ihvertfald en del skrot uden grund. Heldigvis er konstruktionen super simpel: det er udelukkende en LED driver (230V AC til 24V DC) og en LED. Lad os starte med det nemme: LED-driveren er direkte tilgængelig bagfra, og med lidt forsigtighed kan spændingen udmåles. I dette tilfælde var der ca. 24V DC, og det er jo fint indenfor specifikationen. Selve LED’en er lidt sværere at komme til: fronten af glasset skal drejes af via de to huller deri. Jeg brugte en låseringstang af ca. korrekt dimension, med lidt forsigtighed. Lidt ridser gør nok ikke det store når lyset skinner. LED’en kan nu loddes af. En ny LED kan købes for ca. 10 kr, f.x. på AliExpress. Det rigtige søgterm er måske “Bridgelux 2020 COB LED”, jeg endte med en 7W i Warm White (3000 Kelvin). Efter lidt fidlen og lodden er den nye LED monteret, og kan testes. Stor succes! Comments (0) | okt 28 Fantus-button part 2: the physical button build and the network communication Posted on lørdag, oktober 28, 2023 in Hal9k , Planets First part of this series is here, covering the reverse engineering of the DRTV Chromecast App. I wanted the physical appearance to be extremely minimalistic, with slight references to various cubes from videogames. Because it is a remote control, it of course has to be wireless and battery-powered. The box is lasercut from 6 mm MDF , and with a giant red arcade button on top with a red LED inside. The electronics inside is a battery-powered Wemos D1 , along with 4 x 18650 Lithium battery cells. After some experimentation on the response time, which is primarily dominated by the time it takes to reconnect to the WiFi network, I initially only used “light sleep”. This resulted in a battery time of just over a week, which is okay, but not great. In order to preserve battery deep sleep would be really nice. The problem is deep sleep on the Wemos can only be interrupted by a reset. The idea was to use a MOSFET (in this case an N-channel logic level mosfet, IRFZ44N ) for the Wemos to be able to select whether a press of the button should reset it, or it should just register on a pin as normal. This circuit allows RST to be pulled low by the button, as long as D0 is high. Luckily, D0 is high during deep sleep , so as long as the Arduino code keeps D0 low button presses will not reset — but can still be registered by reading pin D1. This works out “responsively enough” because the initial start has some delay due to the Chromecast initializing the app and loading media. Any subsequent button presses within the 30 seconds the Arduino stays awake are instant though. With this setup the battery life is not a problem – I’ve only had to charge it once. As a bonus feature/bug whenever the battery gets low the Wemos will trigger a bit sporadically: this causes “Fantus-bombing” where Fantus will just randomly start; quite quickly thereafter the Fantus-button is being charged 😉 The Wemos itself is not powerful enough to do all the pyChromecast communication needed , so I setup a small Raspberry Pi to handle that part. Since I didn’t want to spend too much time and effort setting up the communication between them, I ended up using a trick from my youth: UDP broadcasting. Because UDP is datagram-oriented you can send a UDP packet to the broadcast address ( 255.255.255.255 ) and then it will be received by all hosts on the local area network: no configuration needed. In Arduino code it looks like: Udp.begin(31337); Udp.beginPacket("255.255.255.255", 31337); Udp.write("emergency-button\n"); Udp.endPacket(); ( Full Arduino code available here .) At this point I had a UDP packet that I could receive on the Raspberry Pi, and it was just a matter of writing a small server program to listen, receive and process those UDP commands. However, at this point a thought entered my mind, that derailed the project for a while: netcat | bash Why write my own server to parse and execute commands, when Bash is already fully capable of doing exactly that with more flexibility than I could ever dream of? And netcat is perfectly capable of receiving UDP packets? This is a UNIX system , after all, and UNIX is all about combining simple commands in pipelines — each doing one thing well. The diabolical simplicity of just executing commands directly from the network was a bit too insecure though. This is where Bash Restricted mode enters the project: I wouldn’t rely on it for high security (since it is trying to “ enumerate badness “), but by locking down the PATH of commands that are allowed to execute it should be relatively safe from most of the common bypass techniques : netcat -u -k -l 31337 | PATH=./handlers/ /bin/bash -r The project was now fully working: press the button, Fantus starts. Press it while Fantus is playing: Fantus pauses. Press it while Fantus is paused: Fantus resumes. The little human was delighted about his new powers over the world, and pressed the button to his hearts content (and his parents slight annoyance at times). ( Full code for handler available here .) But wouldn’t it be cool if the little human had a (limited) choice in what to view?… Comment (1) | jul 18 Fantus-button part 1: Reverse engineering the DRTV Chromecast App Posted on tirsdag, juli 18, 2023 in Hal9k , Planets I want to build a physical giant red button, that when pressed instantly starts a children’s TV-show, in my case Fantus on DRTV using a Chromecast. The first part of the build is figuring out how to remotely start a specific video on a Chromecast. Initially I thought this would be pretty simple to do from an Arduino, because back in the day you could start a video just using a HTTP request . Very much not so anymore: the Chromecast protocol has evolved into some monster using JSON inside Protobuf over TLS/TCP, with multicast DNS for discovery . Chance of getting that working on a microcontroller is near-zero. But remote control is possible using e.g. pychromecast which has support for not only the usual app of YouTube, but also a couple of custom ones like BBC. Let’s try and add support for DRTV to pychromecast, starting at the hints given on adding a new app . Using the netlog-viewer to decode the captured net-export from Chrome, and looking at the unencrypted socket communication, the appId of the DRTV app is easily found. However, one of the subsequent commands has a lot more customData than I expected, since it should more or less just be the contentId that is needed: { "items": [ { "autoplay": true, "customData": { "accountToken": { "expirationDate": "2022-07-02T00:48:35.391Z", "geoLocation": "dk", "isCountryVerified": false, "isDeviceAbroad": false, "isFallbackToken": false, "isOptedOut": false, "profileId": "c4e0...f3e", "refreshable": true, "scope": "Catalog", "type": "UserAccount", "value": "eyJ0eX...Dh8kXg" }, "chainPlayCountdown": 10, "profileToken": { "expirationDate": "2022-07-02T00:48:35.389Z", "geoLocation": "dk", "isCountryVerified": false, "isDeviceAbroad": false, "isFallbackToken": false, "isOptedOut": false, "profileId": "c4e0a...f3e", "refreshable": true, "scope": "Catalog", "type": "UserProfile", "value": "eyJ0eXAi...IkWOU5TA" }, "senderAppVersion": "2.211.33", "senderDeviceType": "web_browser", "sessionId": "cd84eb44-bce0-495b-ab6a-41ef125b945d", "showDebugOverlay": false, "userId": "" }, "media": { "contentId": " 278091 ", "contentType": "video/hls", "customData": { "accessService": "StandardVideo" }, "streamType": "BUFFERED" }, "preloadTime": 0, "startTime": 0 } ], "repeatMode": "REPEAT_OFF", "requestId": 202, "sessionId": "81bdf716-f28a-485b-8dc3-ac4881346f79", "startIndex": 0, "type": "QUEUE_LOAD" } Here I spent a long time trying without any customData , and just using the appId and contentId . Initially it seemed to work! However, it turned out it only worked if the DRTV Chromecast app was already launched from another device. If launched directly from pychromecast the app would load, show a spinner, and then go back to idle. Here much frustration was spent; I guess the customData is actually needed. And indeed, putting that in works! But where do these tokens come from, and how do we get those tokens from Python? Using Chrome’s developer tools (F12) on the DRTV page, and then searching globally (CTRL-SHIFT-f) for various terms (“expirationDate”, “customData”, “profileToken”, “accountToken” etc.) revealed some interesting code, that was as semi-readable as any pretty-printed minifyed Javascript. Eventually I found the tokens in local storage: Using these tokens work really well, and allows starting playback! Some further exploration proceeded: using the showDebugOverlay flag reveals that the DRTV player is just a rebranded Shaka Player . The autoplay functionality can be disabled by setting chainPlayCountdown to -1 , which is honestly a real oversight that it cannot be disabled officially, to not have to rush to stop the playback of the item before the next autoplays. With all the puzzle pieces ready, I prepared a pull request (still open) to add support for DRTV to pychromecast . Fantus-button part 2 will follow, detailing the hardware build and network integration with the support from pychromecast. Comment (1) | feb 20 Floating Solid Wood Alcove Shelves Posted on mandag, februar 20, 2023 in Hal9k , Planets , Woodworking I have an alcove where I wanted to put in some floating shelves. I wanted to use some solid wood I had lying around, to match the rest of the interior; this ruled out most of the methods described online: (i) building up the shelf around a bracket , and (ii) using hidden mounting hardware would be hard to get precise and would not provide support on the sides. So inspired by some of the options instead I tried to get by with just brackets on the three sides, in a solid wood shelf. I ended up with 12mm brackets of plywood in a 26mm solid wood shelf, and that was plenty sturdy. Step 1 was to cut out the rough shelves, with plenty of extra width, and rough fitting the plywood bracket pieces. It makes sense to leave as much on the top of the slit as possible, as this will be the failure point if overloaded. The excellent wood workshop at Hal9k came in very handy! Step 2 was to mount the plywood brackets in the alcove. Pretty easy to do using a laser level, biggest problem was getting the rawplugs in precise enough for the level to be kept. Step 3 was fitting the shelves individually, accounting for the crookedness of the 3 walls. The scribing method used by Rag’n’Bone Brown was pretty useful , just doing it in multiple steps to make sure not to cut off too much. Finally, all the shelves in final mounting. Getting them in took a bit of persuasion with a hammer, and minor adjustments with a knife to the plywood brackets, as it was a tight fit. The key again was small adjustments. One concern with such a tight fit would be wood movement; however most of the wood movement is “across the grain” which in this application means “in and out” from the alcove, where the wood is basically free to move as the shelves are not fastened to the brackets in any way. Another concern would be if the relatively small brackets (12x12mm) can handle the load of the relatively wide shelves (60cm wide, 35cm deep, and 2.6cm high). There are two failure scenarios: (i) the wood could split above the slit, (ii) or the bracket could deform or be pulled out. Neither seems likely as (i) applying a static (or even dynamic) load large enough to split the wood seems implausible, even at the weakest point in the middle of the front, and (ii) the tight fit counteracts the brackets ability to be pulled out since pulling out in one side would have the shelf hitting the wall on the opposite side. All in all a very satisfying project to work on and complete! Comments (0) | dec 15 Quick and dirty guide to Lithium battery-powered Wemos D1 Mini Posted on torsdag, december 15, 2022 in Hal9k The Wemos D1 Mini is an ESP8266 based prototyping board with WiFi connectivity and countless applications. It becomes even more useful in battery-powered applications, where with the proper setup, it can run low-powered for months at a time — or only hours if done incorrectly. This is the quick and dirty guide to running a Wemos D1 Mini powered by Lithium-Ion batteries: We will be blatantly ignoring several design specifications, so double check everything before using in a critical project. Several things will vary, and since there is plenty of clones of the board some boards will work better than others. Warning: Lithium-Ion batteries always command healthy respect, due to the energy they store! Do not use bad cells, and do not leave batteries unattended in places where a fire can develop, especially while charging. That being said, the setup given here should be as safe as most other Lithium-Ion battery projects. Why run off a battery? You chose a Wemos D1 because you want to do some WiFi connectivity. This narrows down the useful modes from the overwhelming large table of possibilities . The approach will be slightly different depending on why you want to run off a battery. There are 3 main usecases: Periodically wake up on a timer, do some work, connect to WiFi, and go back to sleep. Here we can utilize the deep sleep mode of the ESP8266, and get lifetimes in months. Wake up based on an external pin trigger, do some work, connect to WiFi, and go back to sleep. Here we can also utilize deep sleep , and get lifetimes in weeks/months. React with low latency to an external pin, do some work, and go to sleep while still connected to WiFi. Here we can utilize light sleep , but only get lifetimes in hours/days. Hardware setup The hardware needed is: Wemos D1 Mini TP4056 module with “discharge protection” , most modules with more than one chip has this, but be careful! Lithium-Ion battery, e.g. a 18650 cell, and probably a holder for the battery What you don’t want is anything resembling a power bank or battery shield with a regulated output (5V or 3V). These are practically useless, simply a more expensive battery holder! Two reasons: poorly built (I have several where standby is prevented by pulling 100 mA through a resistor!), and you don’t want a switching mode power supply. The keyword here is “quiescent current”: an SMPS can easily consume 5-10 mA continuously, which could very likely be the majority of the current draw. Wiring diagram. Waking on a timer – deep sleep Full code example for deep sleeping on a timer. To start deep sleep for a specified period of time: //Sleep for some time; when waking everything will be reset and setup() will run again ESP.deepSleep(30 * MICROSECONDS_PER_SEC); Note that you can’t safely sleep for more than approximately 3 hours . Power usage is approx 0.3–0.4mA when deep sleeping. Keep in mind that after waking from the timer the chip will be reset, meaning no state is available, and WiFi will have to reconnect. Reconnecting to WiFi can be anything from 3–10 seconds or even longer, meaning that will be a delay before the program can resume. Waking on an pin trigger (reset) Full code example for deep sleeping waiting for a pin trigger. The code is exactly the same as waking on a timer, with one exception: //Sleep until RESET pin is triggered ESP.deepSleep(0); The chip will be effectively comatose, sleeping until a RESET is triggered. Same caveats apply: waking up the program is restarted, and reconnecting to WiFi will be a delay. Stay connected – low latency Full code example for light sleeping connected to WiFi waiting for a pin trigger. Note that the button should be connected to D3 for this example, not RST. The key parts are: void setup() { ... WiFi.setSleepMode(WIFI_LIGHT_SLEEP, 3); // Automatic Light Sleep } void loop() { ... delay(350); // Any value between 100--500 will work, higher value more power savings // but also slower wakeup! } Simply delaying will bring power savings — simple and easy! When awake power consumption is around 75mA. Average power consumption when light sleeping with delay(200) is around 45 mA, with delay(350) and larger is around 30–40mA. Measuring battery depletion The ESP can measure it’s internal VCC supply voltage, and because the battery will start dropping below the rated 3.3V before it is depleted, this allows to get an warning when the battery starts to deplete. ADC_MODE(ADC_VCC); void loop() { if (ESP.getVcc() < 2800) { //Do something to warn of low battery } } In my experience the Vcc reading will drop below 2800 when the battery starts to be depleted. ADC readings vs. battery voltage Note that measuring the VCC while connected with USB is not possible, as the USB connection will pull up the battery and the 5V rail to 5V! Calculating battery life Here is a quick calculator for how long your Wemos D1 Mini can stay powered Number of batteries (assuming 2000 mAh capacity): Capacity (mAh): Deep sleep Waking up every (minutes): (conservatively assumes base load 1mA, 10 secs burst of 100mA for every wakeup), resulting in Average Consumption (mA): – Light sleep Average Consumption (mA): – Of course the consumption can be brought even lower: some chips are unused but partly connected and will have some leakage (LEDs, USB chip on the Wemos). Making it even leaner is outside the scope of quick and dirty. Comments (12) | « Previous Posts Categories Danish Hal9k Ikke kategoriseret Planet Ubuntu-DK Planets Sysadmin'ing Ubuntu University Woodworking © blog.smartere . All Rights Reserved. WordPress Theme designed by Chris Wallace | 2026-01-13T08:48:58 |
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https://dev.to/juweria_/what-i-wish-i-knew-before-deploying-my-first-backend-application-e07#comments | What I Wish I Knew Before Deploying My First Backend Application. - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse juweria mohamood Posted on Jan 10 What I Wish I Knew Before Deploying My First Backend Application. # programming # devops # deployment # backend When I wrote my first backend application, I thought the hard part was over once the API worked locally. The endpoints responded, tests passed, and everything felt done. Deployment proved me wrong. Getting an application to run reliably on a server was a completely different challenge—one that I underestimated at the beginning. Looking back, there are a few lessons I wish I had learned earlier that would have saved me a lot of time and frustration. This post is a reflection on those early mistakes and what I do differently now. Deployment Is Not an Afterthought At first, I treated deployment as something to “figure out later.” I focused heavily on writing features and ignored how the application would actually run in production. What I learned quickly is that deployment decisions affect how you write code: How configuration is handled How errors are logged How services communicate How scalable the app can be Now, I think about deployment early—even when building small projects—because it shapes better engineering decisions from day one. The Server Is Not Your Local Machine One of my biggest early mistakes was assuming the server environment would behave like my laptop. It doesn’t. On a server, you have to think about: Linux file permissions Open ports and firewalls Environment variables Running processes in the background The first time my app “worked locally but not on the server,” I realized how important it is to understand the environment your code runs in—not just the code itself. Hardcoding Secrets Will Eventually Hurt You In my early projects, I didn’t give much thought to secrets. API keys and credentials lived in config files or environment-specific code. This is risky. Now, I make it a rule to: Use environment variables Never commit secrets Treat configuration as a first-class part of the application It’s a small habit that prevents big problems later. Logging Matters More Than You Think When something breaks in production, you don’t have a debugger attached. Early on, I had very little logging, which made debugging production issues painful. Today, I always make sure: Errors are logged clearly Logs are meaningful, not noisy I can understand what happened without guessing Good logging turns production issues from stressful mysteries into solvable problems. What I Do Differently Now With more experience, my approach has changed: I keep deployment setups simple I document steps clearly I automate where possible I test deployments early, even for small apps Most importantly, I treat deployment as part of the development process—not a separate task. Final Thoughts If you’re new to backend development, struggling with deployment is normal. Everyone goes through it. The good news is that each mistake teaches you something valuable. Over time, deployment stops feeling scary and starts feeling like just another engineering problem you know how to solve. In upcoming posts, I’ll share practical guides on deploying backend applications step by step, including FastAPI and cloud platforms like DigitalOcean. Top comments (0) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse juweria mohamood Follow Backend & DevOps engineer sharing hands-on guides on Python, JavaScript, AWS & DigitalOcean deployments, CI/CD, and real-world production lessons. Location Mogadishu, Somalia Education BSc in Computer Science, 2025 Pronouns she/her Work Software Engineer (Full-time) Joined Jan 4, 2026 Trending on DEV Community Hot AI should not be in Code Editors # programming # ai # productivity # discuss I Didn’t “Become” a Senior Developer. I Accumulated Damage. # programming # ai # career # discuss SQLite Limitations and Internal Architecture # webdev # programming # database # architecture 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV Forem — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . Forem © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. Log in Create account | 2026-01-13T08:48:58 |
https://dev.to/missamarakay/help-me-help-you-debugging-tips-before-seeking-help-12jj#main-content | Help Me, Help You (Debugging Tips Before Seeking Help) - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. DUMB DEV Community Follow Memes and software development shitposting Design Community Follow Web design, graphic design and everything in-between Security Forem Follow Your central hub for all things security. From ethical hacking and CTFs to GRC and career development, for beginners and pros alike Golf Forem Follow A community of golfers and golfing enthusiasts Crypto Forem Follow A collaborative community for all things Crypto—from Bitcoin to protocol development and DeFi to NFTs and market analysis. Parenting Follow A place for parents to the share the joys, challenges, and wisdom that come from raising kids. We're here for them and for each other. Forem Core Follow Discussing the core forem open source software project — features, bugs, performance, self-hosting. Maker Forem Follow A community for makers, hobbyists, and professionals to discuss Arduino, Raspberry Pi, 3D printing, and much more. HMPL.js Forem Follow For developers using HMPL.js to build fast, lightweight web apps. A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse Amara Graham Posted on Apr 23, 2019 Help Me, Help You (Debugging Tips Before Seeking Help) # programming # productivity # beginners One of the really cool things about being a developer advocate is I get to help people, which I truly love. I love writing a snippet of code or clarifying documentation and then watching the magic that happens when a developer I've probably never met before takes it and creates something amazing with it. That's a great day in my book. But it is not always like that. Sometimes things break, and folks reach out for help. It can be frustrating for everyone involved when it appears to be "just one error" (it may not be actually!). Let me help you help me as we work through these things together. Be very clear about your problem or issue Overstate and overshare. If you can provide relevant screen shots or a link to the code, that's even better. Was this ever working? Or did you just get started? What version of the SDK or service are you using? Your OS version might also be relevant. What steps did you do to get to this point? Link to the exact tutorial or documentation. Do your homework first What steps did you take to try to debug this on your own? The answer cannot be "nothing". Did you do a search on the error? Stack Overflow? Relevant forums? A search engine? Has this happened before? Can you try an older version? Can you try a newer version? Can you reproduce it? Clouds are complicated When working in the cloud, you can have a lot more variables at play. I recommend firing off a simple GET to make sure something like your credentials are working and the service is responding. There is a reason many API docs include Curl, but maybe read my other post . Can you use Curl/Postman/ARC to test the endpoint? What region are you in? What tier of the service are you using? You may have hit a tier limit. Check for outages & maintenance. If you are on IBM Cloud, there is a widget on the dashboard (you may need to be logged in). Submit an issue (or even a PR) If you think you are experiencing a bug with an open source project, submit an issue. Often projects will have a template to follow, which look very similar to the items I outlined above! Coincidence, I think not. Be patient I cannot drop everything I'm doing to work on troubleshooting, but I try to put some time in my schedule during the week to take a look at things. This is often what you hear from OSS maintainers and can lead to burnout. I don't work weekends or evenings (unless I have very specific events) so I appreciate your patience. Following the above items will help us both tackle these challenges together. Feel free to apply these things anywhere in life or work. We are all busy, but if we meet each other halfway, everyone benefits. Do you have any tips I missed? Share them below! Top comments (3) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Collapse Expand Theofanis Despoudis Theofanis Despoudis Theofanis Despoudis Follow Senior Software Engineer @wpengine, Experienced mentor @codeimentor, Technical Writer @fixate.io, Book author Location Ireland Work Senior Software Engineer at WP Engine Joined Jun 19, 2017 • Apr 24 '19 Dropdown menu Copy link Hide You forgot the meme Like comment: Like comment: 4 likes Like Comment button Reply Collapse Expand DrBearhands DrBearhands DrBearhands Follow Education MSc. Artificial Intelligence Joined Apr 9, 2018 • Apr 24 '19 Dropdown menu Copy link Hide Ahhh, those lovely "it's not working" bugreports. So easy to close by just opening the app and seeing that it is apparently working again. Like comment: Like comment: 3 likes Like Comment button Reply Collapse Expand Amara Graham Amara Graham Amara Graham Follow Enabling developers Location Austin, TX Education BS Computer Science from Trinity University Work Developer Advocate at Kestra Joined Jan 4, 2017 • Apr 24 '19 Dropdown menu Copy link Hide Love to hate those ones. It's... fixed...? Like comment: Like comment: 3 likes Like Comment button Reply Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse Amara Graham Follow Enabling developers Location Austin, TX Education BS Computer Science from Trinity University Work Developer Advocate at Kestra Joined Jan 4, 2017 More from Amara Graham Intro to Calling Third Party AI Services in Unreal Engine # programming # gamedev # unreal Updating Your Unity Project to Watson SDK for Unity 3.1.0 (and Core SDK 0.2.0) # unity3d # programming # gamedev A Few of My Favorite (Dev) Things # github # programming # softwaredevelopment 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV Forem — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . Forem © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. Log in Create account | 2026-01-13T08:48:58 |
https://docs.python.org/3/py-modindex.html | Python Module Index — Python 3.14.2 documentation Theme Auto Light Dark Navigation index modules | Python » 3.14.2 Documentation » Python Module Index | Theme Auto Light Dark | Python Module Index _ | a | b | c | d | e | f | g | h | i | j | k | l | m | n | o | p | q | r | s | t | u | v | w | x | z   _ __future__ Future statement definitions __main__ The environment where top-level code is run. Covers command-line interfaces, import-time behavior, and ``__name__ == '__main__'``. _thread Low-level threading API. _tkinter A binary module that contains the low-level interface to Tcl/Tk.   a abc Abstract base classes according to :pep:`3119`. aifc Deprecated: Removed in 3.13. annotationlib Functionality for introspecting annotations argparse Command-line option and argument parsing library. array Space efficient arrays of uniformly typed numeric values. ast Abstract Syntax Tree classes and manipulation. asynchat Deprecated: Removed in 3.12. asyncio Asynchronous I/O. asyncore Deprecated: Removed in 3.12. atexit Register and execute cleanup functions. audioop Deprecated: Removed in 3.13.   b base64 RFC 4648: Base16, Base32, Base64 Data Encodings; Base85 and Ascii85 bdb Debugger framework. binascii Tools for converting between binary and various ASCII-encoded binary representations. bisect Array bisection algorithms for binary searching. builtins The module that provides the built-in namespace. bz2 Interfaces for bzip2 compression and decompression.   c calendar Functions for working with calendars, including some emulation of the Unix cal program. cgi Deprecated: Removed in 3.13. cgitb Deprecated: Removed in 3.13. chunk Deprecated: Removed in 3.13. cmath Mathematical functions for complex numbers. cmd Build line-oriented command interpreters. code Facilities to implement read-eval-print loops. codecs Encode and decode data and streams. codeop Compile (possibly incomplete) Python code. collections Container datatypes     collections.abc Abstract base classes for containers colorsys Conversion functions between RGB and other color systems. compileall Tools for byte-compiling all Python source files in a directory tree. compression     compression.zstd Low-level interface to compression and decompression routines in the zstd library. concurrent     concurrent.futures Execute computations concurrently using threads or processes.     concurrent.interpreters Multiple interpreters in the same process configparser Configuration file parser. contextlib Utilities for with-statement contexts. contextvars Context Variables copy Shallow and deep copy operations. copyreg Register pickle support functions. cProfile crypt Deprecated: Removed in 3.13. csv Write and read tabular data to and from delimited files. ctypes A foreign function library for Python. curses (Unix) An interface to the curses library, providing portable terminal handling.     curses.ascii Constants and set-membership functions for ASCII characters.     curses.panel A panel stack extension that adds depth to curses windows.     curses.textpad Emacs-like input editing in a curses window.   d dataclasses Generate special methods on user-defined classes. datetime Basic date and time types. dbm Interfaces to various Unix "database" formats.     dbm.dumb Portable implementation of the simple DBM interface.     dbm.gnu (Unix) GNU database manager     dbm.ndbm (Unix) The New Database Manager     dbm.sqlite3 (All) SQLite backend for dbm decimal Implementation of the General Decimal Arithmetic Specification. difflib Helpers for computing differences between objects. dis Disassembler for Python bytecode. distutils Deprecated: Removed in 3.12. doctest Test pieces of code within docstrings.   e email Package supporting the parsing, manipulating, and generating email messages.     email.charset Character Sets     email.contentmanager Storing and Retrieving Content from MIME Parts     email.encoders Encoders for email message payloads.     email.errors The exception classes used by the email package.     email.generator Generate flat text email messages from a message structure.     email.header Representing non-ASCII headers     email.headerregistry Automatic Parsing of headers based on the field name     email.iterators Iterate over a message object tree.     email.message The base class representing email messages.     email.mime Build MIME messages.     email.mime.application     email.mime.audio     email.mime.base     email.mime.image     email.mime.message     email.mime.multipart     email.mime.nonmultipart     email.mime.text     email.parser Parse flat text email messages to produce a message object structure.     email.policy Controlling the parsing and generating of messages     email.utils Miscellaneous email package utilities. encodings Encodings package     encodings.idna Internationalized Domain Names implementation     encodings.mbcs Windows ANSI codepage     encodings.utf_8_sig UTF-8 codec with BOM signature ensurepip Bootstrapping the "pip" installer into an existing Python installation or virtual environment. enum Implementation of an enumeration class. errno Standard errno system symbols.   f faulthandler Dump the Python traceback. fcntl (Unix) The fcntl() and ioctl() system calls. filecmp Compare files efficiently. fileinput Loop over standard input or a list of files. fnmatch Unix shell style filename pattern matching. fractions Rational numbers. ftplib FTP protocol client (requires sockets). functools Higher-order functions and operations on callable objects.   g gc Interface to the cycle-detecting garbage collector. getopt Portable parser for command line options; support both short and long option names. getpass Portable reading of passwords and retrieval of the userid. gettext Multilingual internationalization services. glob Unix shell style pathname pattern expansion. graphlib Functionality to operate with graph-like structures grp (Unix) The group database (getgrnam() and friends). gzip Interfaces for gzip compression and decompression using file objects.   h hashlib Secure hash and message digest algorithms. heapq Heap queue algorithm (a.k.a. priority queue). hmac Keyed-Hashing for Message Authentication (HMAC) implementation html Helpers for manipulating HTML.     html.entities Definitions of HTML general entities.     html.parser A simple parser that can handle HTML and XHTML. http HTTP status codes and messages     http.client HTTP and HTTPS protocol client (requires sockets).     http.cookiejar Classes for automatic handling of HTTP cookies.     http.cookies Support for HTTP state management (cookies).     http.server HTTP server and request handlers.   i idlelib Implementation package for the IDLE shell/editor. imaplib IMAP4 protocol client (requires sockets). imghdr Deprecated: Removed in 3.13. imp Deprecated: Removed in 3.12. importlib The implementation of the import machinery.     importlib.abc Abstract base classes related to import     importlib.machinery Importers and path hooks     importlib.metadata Accessing package metadata     importlib.resources Package resource reading, opening, and access     importlib.resources.abc Abstract base classes for resources     importlib.util Utility code for importers inspect Extract information and source code from live objects. io Core tools for working with streams. ipaddress IPv4/IPv6 manipulation library. itertools Functions creating iterators for efficient looping.   j json Encode and decode the JSON format.     json.tool A command-line interface to validate and pretty-print JSON.   k keyword Test whether a string is a keyword in Python.   l linecache Provides random access to individual lines from text files. locale Internationalization services. logging Flexible event logging system for applications.     logging.config Configuration of the logging module.     logging.handlers Handlers for the logging module. lzma A Python wrapper for the liblzma compression library.   m mailbox Manipulate mailboxes in various formats mailcap Deprecated: Removed in 3.13. marshal Convert Python objects to streams of bytes and back (with different constraints). math Mathematical functions (sin() etc.). mimetypes Mapping of filename extensions to MIME types. mmap Interface to memory-mapped files for Unix and Windows. modulefinder Find modules used by a script. msilib Deprecated: Removed in 3.13. msvcrt (Windows) Miscellaneous useful routines from the MS VC++ runtime. multiprocessing Process-based parallelism.     multiprocessing.connection API for dealing with sockets.     multiprocessing.dummy Dumb wrapper around threading.     multiprocessing.managers Share data between process with shared objects.     multiprocessing.pool Create pools of processes.     multiprocessing.shared_memory Provides shared memory for direct access across processes.     multiprocessing.sharedctypes Allocate ctypes objects from shared memory.   n netrc Loading of .netrc files. nis Deprecated: Removed in 3.13. nntplib Deprecated: Removed in 3.13. numbers Numeric abstract base classes (Complex, Real, Integral, etc.).   o operator Functions corresponding to the standard operators. optparse Command-line option parsing library. os Miscellaneous operating system interfaces.     os.path Operations on pathnames. ossaudiodev Deprecated: Removed in 3.13.   p pathlib Object-oriented filesystem paths     pathlib.types pathlib types for static type checking pdb The Python debugger for interactive interpreters. pickle Convert Python objects to streams of bytes and back. pickletools Contains extensive comments about the pickle protocols and pickle-machine opcodes, as well as some useful functions. pipes Deprecated: Removed in 3.13. pkgutil Utilities for the import system. platform Retrieves as much platform identifying data as possible. plistlib Generate and parse Apple plist files. poplib POP3 protocol client (requires sockets). posix (Unix) The most common POSIX system calls (normally used via module os). pprint Data pretty printer. profile Python source profiler. pstats Statistics object for use with the profiler. pty (Unix) Pseudo-Terminal Handling for Unix. pwd (Unix) The password database (getpwnam() and friends). py_compile Generate byte-code files from Python source files. pyclbr Supports information extraction for a Python module browser. pydoc Documentation generator and online help system.   q queue A synchronized queue class. quopri Encode and decode files using the MIME quoted-printable encoding.   r random Generate pseudo-random numbers with various common distributions. re Regular expression operations. readline (Unix) GNU readline support for Python. reprlib Alternate repr() implementation with size limits. resource (Unix) An interface to provide resource usage information on the current process. rlcompleter Python identifier completion, suitable for the GNU readline library. runpy Locate and run Python modules without importing them first.   s sched General purpose event scheduler. secrets Generate secure random numbers for managing secrets. select Wait for I/O completion on multiple streams. selectors High-level I/O multiplexing. shelve Python object persistence. shlex Simple lexical analysis for Unix shell-like languages. shutil High-level file operations, including copying. signal Set handlers for asynchronous events. site Module responsible for site-specific configuration. sitecustomize smtpd Deprecated: Removed in 3.12. smtplib SMTP protocol client (requires sockets). sndhdr Deprecated: Removed in 3.13. socket Low-level networking interface. socketserver A framework for network servers. spwd Deprecated: Removed in 3.13. sqlite3 A DB-API 2.0 implementation using SQLite 3.x. ssl TLS/SSL wrapper for socket objects stat Utilities for interpreting the results of os.stat(), os.lstat() and os.fstat(). statistics Mathematical statistics functions string Common string operations.     string.templatelib Support for template string literals. stringprep String preparation, as per RFC 3453 struct Interpret bytes as packed binary data. subprocess Subprocess management. sunau Deprecated: Removed in 3.13. symtable Interface to the compiler's internal symbol tables. sys Access system-specific parameters and functions.     sys.monitoring Access and control event monitoring sysconfig Python's configuration information syslog (Unix) An interface to the Unix syslog library routines.   t tabnanny Tool for detecting white space related problems in Python source files in a directory tree. tarfile Read and write tar-format archive files. telnetlib Deprecated: Removed in 3.13. tempfile Generate temporary files and directories. termios (Unix) POSIX style tty control. test Regression tests package containing the testing suite for Python.     test.regrtest Drives the regression test suite.     test.support Support for Python's regression test suite.     test.support.bytecode_helper Support tools for testing correct bytecode generation.     test.support.import_helper Support for import tests.     test.support.os_helper Support for os tests.     test.support.script_helper Support for Python's script execution tests.     test.support.socket_helper Support for socket tests.     test.support.threading_helper Support for threading tests.     test.support.warnings_helper Support for warnings tests. textwrap Text wrapping and filling threading Thread-based parallelism. time Time access and conversions. timeit Measure the execution time of small code snippets. tkinter Interface to Tcl/Tk for graphical user interfaces     tkinter.colorchooser (Tk) Color choosing dialog     tkinter.commondialog (Tk) Tkinter base class for dialogs     tkinter.dnd (Tk) Tkinter drag-and-drop interface     tkinter.filedialog (Tk) Dialog classes for file selection     tkinter.font (Tk) Tkinter font-wrapping class     tkinter.messagebox (Tk) Various types of alert dialogs     tkinter.scrolledtext (Tk) Text widget with a vertical scroll bar.     tkinter.simpledialog (Tk) Simple dialog windows     tkinter.ttk Tk themed widget set token Constants representing terminal nodes of the parse tree. tokenize Lexical scanner for Python source code. tomllib Parse TOML files. trace Trace or track Python statement execution. traceback Print or retrieve a stack traceback. tracemalloc Trace memory allocations. tty (Unix) Utility functions that perform common terminal control operations. turtle An educational framework for simple graphics applications turtledemo A viewer for example turtle scripts types Names for built-in types. typing Support for type hints (see :pep:`484`).   u unicodedata Access the Unicode Database. unittest Unit testing framework for Python.     unittest.mock Mock object library. urllib     urllib.error Exception classes raised by urllib.request.     urllib.parse Parse URLs into or assemble them from components.     urllib.request Extensible library for opening URLs.     urllib.response Response classes used by urllib.     urllib.robotparser Load a robots.txt file and answer questions about fetchability of other URLs. usercustomize uu Deprecated: Removed in 3.13. uuid UUID objects (universally unique identifiers) according to RFC 9562   v venv Creation of virtual environments.   w warnings Issue warning messages and control their disposition. wave Provide an interface to the WAV sound format. weakref Support for weak references and weak dictionaries. webbrowser Easy-to-use controller for web browsers. winreg (Windows) Routines and objects for manipulating the Windows registry. winsound (Windows) Access to the sound-playing machinery for Windows. wsgiref WSGI Utilities and Reference Implementation.     wsgiref.handlers WSGI server/gateway base classes.     wsgiref.headers WSGI response header tools.     wsgiref.simple_server A simple WSGI HTTP server.     wsgiref.types WSGI types for static type checking     wsgiref.util WSGI environment utilities.     wsgiref.validate WSGI conformance checker.   x xdrlib Deprecated: Removed in 3.13. xml Package containing XML processing modules     xml.dom Document Object Model API for Python.     xml.dom.minidom Minimal Document Object Model (DOM) implementation.     xml.dom.pulldom Support for building partial DOM trees from SAX events.     xml.etree.ElementInclude     xml.etree.ElementTree Implementation of the ElementTree API.     xml.parsers.expat An interface to the Expat non-validating XML parser.     xml.parsers.expat.errors     xml.parsers.expat.model     xml.sax Package containing SAX2 base classes and convenience functions.     xml.sax.handler Base classes for SAX event handlers.     xml.sax.saxutils Convenience functions and classes for use with SAX.     xml.sax.xmlreader Interface which SAX-compliant XML parsers must implement. xmlrpc Server and client modules implementing XML-RPC.     xmlrpc.client XML-RPC client access.     xmlrpc.server Basic XML-RPC server implementations.   z zipapp Manage executable Python zip archives zipfile Read and write ZIP-format archive files. zipimport Support for importing Python modules from ZIP archives. zlib Low-level interface to compression and decompression routines compatible with gzip. zoneinfo IANA time zone support « Navigation index modules | Python » 3.14.2 Documentation » Python Module Index | Theme Auto Light Dark | © Copyright 2001 Python Software Foundation. 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https://blog.smartere.dk/category/sysadmin/ | blog.smartere » Sysadmin’ing blog.smartere // Ramblings of Mads Chr. Olesen okt 4 Olimex A20-OLinuXino-LIME2 – 8 years in service, 2 PSUs and 1 SD-card down Posted on tirsdag, oktober 4, 2022 in Hal9k , Planets , Sysadmin'ing 4 years ago I posted a 4 year review of the Olimex LIME2 . It seems that the lifetime of power supplies is approximately 4 years as now another power supply died, and this time also the SD-card was expiring. The LIME2 lives on however! It was a bit hard to notice, because the battery pack of the LIME2 kept it running pretty well even with the poor power supply. So, better monitoring of the battery pack is also on the todo list. Recovering the bad SD-card Recovering the SD-card was relatively easy with minimal dataloss, when out of the LIME2: $ sudo ddrescue /dev/mmcblk0 backup.img # Put in a new SD-card $ sudo dd if=backup.img of=/dev/mmcblk0 bs=16M I have done this a couple of times with other SD-cards from Raspberry PIs, and though there is the potential for dataloss it is usually minimal. This time a few blocks were lost. Upgrading Debian from Stretch to Bullseye I took the opportunity to upgrade the Debian install while the system was offline anyway. Upgrading was generally painless, following the usual Debian method. I went through the Buster release just to be sure: $ vim /etc/apt/sources.list # replace all "stretch" with "buster" :%s/stretch/buster $ apt update && apt upgrade && apt full-upgrade $ reboot $ vim /etc/apt/sources.list # replace all "buster" with "bullseye" :%s/buster/bullseye $ apt update && apt upgrade && apt full-upgrade $ reboot The only tricky part is booting the new kernel. Since that always fails for me on the first try, I always hookup the serial console. For future reference, this is how to hookup the serial console (which is TTL 3.3V): Pinout from left as labelled on the LIME2: TX, RX, GND Now, of course the boot failed. I tried getting the flash-kernel package to work for my setup, but for historical reasons I have a separate boot partition. In the end I derived a simple bootscript from that package, that boots from p1 but loads the kernel, fdt and initrd from p2: setenv bootargs ${bootargs} console=ttyS0,115200 root=/dev/mmcblk0p2 rootwait panic=10 #setenv fk_kvers '4.19.0-21-armmp-lpae' setenv fk_kvers '5.10.0-18-armmp-lpae' setenv fdtpath dtb-${fk_kvers} load mmc 0:2 ${kernel_addr_r} /boot/vmlinuz-${fk_kvers} load mmc 0:2 ${fdt_addr_r} /boot/${fdtpath} load mmc 0:2 ${ramdisk_addr_r} /boot/initrd.img-${fk_kvers} bootz ${kernel_addr_r} ${ramdisk_addr_r}:${filesize} ${fdt_addr_r} The script can be manually input over the serial terminal, and thereby tested out. The only downside is it needs to be manually updated after each kernel upgrade. To activate the uboot bootscript: $ mount /dev/mmcblk0p1 /mnt/ $ cd /mnt # ensure boot.cmd is as above $ mkimage -C none -A arm -T script -d boot.cmd boot.scr Monitoring the LIME2 battery pack After upgrading to a recent 5.X mainline Linux kernel the battery pack is exposed in the sysfs filesystem: $ cat /sys/class/power_supply/axp20x-battery/voltage_now 4070000 # 4.07 V $ cat /sys/class/power_supply/axp20x-ac/voltage_now 4933000 # 4.93 V I setup a couple of alerting rules for these in my home monitoring setup, so hopefully the next time the LIME2 defeats a power supply I’ll get notified. Conclusion I can still warmly recommend the LIME2. It is still available, and even a bit cheaper nowadays at 40 EUR + VAT, and still a little workhorse that just keeps on going. Comment (1) | sep 29 Olimex A20-OLinuXino-LIME2 – A review after 4 years in service Posted on lørdag, september 29, 2018 in Hal9k , Planets , Sysadmin'ing Last week my A20-OLinuXino-LIME2 one board Linux computer quit working, with a power supply issue. I looked up when it was purchased, and realised it had been in 24/7 service for almost 4 years. I guess that is a good excuse to do a little review. It even turned out that it the board was fine, but the AC-DC power supply brick could not supply enough current anymore. The relevant specifications of the board, for my uses, are basically: Dual core 1 GHz ARM Cortex-A7 1 GB memory, 1 Gbit ethernet, SATA connector LiPo battery connector/charger for UPS functionality The Lime2 has been tasked with running my home monitoring system, consisting of a Debian installation with a Graphite backend, a Grafana frontend, and a ZoneMinder installation. The Graphite database is running on a software RAID0 of two disks (one on SATA, one on USB): in the beginning it was two spinning disks, but after a few years the random 2.5″ laptop disk I was using crapped out, so it was upgraded to a Samsung SSD. The power budget is strained more or less to the max with two spinning harddrives: The system was only able to boot if the battery was connected, presumably because the voltage would otherwise drop for the startup torque. This problem went away after switching to a SSD. Software wise the system started out with the Debian supplied by Olimex on a SD-card, a Debian pre-Jessie with a custom SunXi kernel. This system was reasonable, but did experience random hangs after some time of use (I belive I found a bugreport back in the day, but am unable to refind it now). The system was later upgraded to a Debian Stretch with a 4.9 kernel from stretch-backports, that supports the SunXi chipset enough for my uses . The upgrade was rather involved, requiring the correct kernel image, a custom U-boot script and the correct device tree file. Something did of course go wrong, at which point I got to be familiar with the serial console of the Lime2: there is a convenient 3 pin header, that gives access to a TTL serial. Using the serial console, I was able to identify the mistake and correct it. After the upgrade the system has been rock-stable. The system has been handling the load reasonably: The 1GB of memory is constraining, there is not really any more free memory. The processor is only really strained by the motion detection in ZoneMinder, which uses more or less one core per camera. This will hopefully be optimized a bit, as ZoneMinder is being optimized for the ARM instruction set . Handling only the Graphite/Grafana load would be a breeze, even though the system is receiving ~650 metrics per minute. All in all, I can recommend the Lime2 board for applications that need a little more umph than a Raspberry Pi, notably on the SATA and Ethernet side, and/or applications that need to be continuously available even after the power cuts out. For applications that need more than one SATA port, or more than one Ethernet port, or on-board Wifi, there are better — and more expensive — options. The price point of 45 EUR + VAT (which did not change from 4 years ago) puts the Lime2 slightly above the price of a RaspberryPi or BananaPi, but below boards like the Apu2 . In addition, Olimex has announced that the Lime2 will be available “forever” , making any system designed using the Lime2 future proof — for the foreseeable future. I ordered a new Lime2, before realising the problem was the power supply. I opted for the industrial variant that is now available. The only change, as far as I’m aware, is that the Allwinner A20 chip is rated for a larger temperature range, and it is 5 EUR more expensive. Comments (4) | jan 31 Stupid sys-admin’ing, and hooray for LVM and unnecessary partitions Posted on fredag, januar 31, 2014 in Planet Ubuntu-DK , Planets , Sysadmin'ing , Ubuntu The scenario is: almost finished migrating from an old server to a new server. Only a few steps remain, namely change DNS to point to new server wipe disks on old server Done in this order, one might be unlucky that ssh’ing in to wipe the disks lands you on the new server. If you don’t discover this and run the command dd if=/dev/zero of=/dev/md2 to wipe the disks you might run it on the new server instead. BAM: you just wiped the data of your new server. Fortunately, I realised my mistake after a few seconds, and was able to recover from this with only unimportant data loss, and a little panic. /dev/md2 is actually a LVM physical partition, of which the first part now only contains zeroes; hereunder all the meta-data. LVM reported no volumes of any kind: root@server# pvs -v Scanning for physical volume names root@server# lvs -v Finding all logical volumes No volume groups found root@server # vgs -v Finding all volume groups No volume groups found After a bit of Google’ing while panicking I found out LVM keeps a backup of all its metadata in /etc/lvm/backup , and that it could be rewritten to the physical volume using: pvcreate -ff -u XXXXXX-XXXX-XXXX-XXXX-XXXX-XXXX-XXXXXX --restorefile /etc/lvm/backup/vg0 /dev/md2 where XXXXXX-XXXX-XXXX-XXXX-XXXX-XXXX-XXXXXX is the physical UUID from the backup file: ... physical_volumes { pv0 { id = "XXXXXX-XXXX-XXXX-XXXX-XXXX-XXXX-XXXXXX" device = "/dev/md2" # Hint only ... Unfortunately, I got an error: root@server# pvcreate -ff -u XXXXXX-XXXX-XXXX-XXXX-XXXX-XXXX-XXXXXX --restorefile /etc/lvm/backup/vg0 /dev/md2 Couldn't find device with uuid XXXXXX-XXXX-XXXX-XXXX-XXXX-XXXX-XXXXXX. Can't open /dev/md2 exclusively. Mounted filesystem? lsof showed nothing accessing md2, but I guess something still had references to the logical volumes. I was unable to get it to work, so I decided to reboot (while making sure the system would come up, and nothing would try to mount the (non-existent) LVM volumes). After a reboot the command worked, but still no logical volumes: root@server # pvcreate -ff -u XXXXXX-XXXX-XXXX-XXXX-XXXX-XXXX-XXXXXX --restorefile /etc/lvm/backup/vg0 /dev/md2 Couldn't find device with uuid XXXXXX-XXXX-XXXX-XXXX-XXXX-XXXX-XXXXXX. Physical volume "/dev/md2" successfully created root@server # sudo pvs PV VG Fmt Attr PSize PFree /dev/md2 lvm2 a- 648.51g 648.51g root@server # sudo lvs No volume groups found Now I had a physical volume, and could use the vgcfgrestore command: root@server # vgcfgrestore -f /etc/lvm/backup/vg0 /dev/vg0 Restored volume group vg0 root@server # sudo lvs LV VG Attr LSize Origin Snap% Move Log Copy% Convert ... home vg0 -wi-a- 20.00g I now had my logical volumes back! Now to assess the data loss… The backup file /etc/lvm/backup/vg0 lists which order the logical volumes are stored. The first volume in my case was the “home” volume. Sure enough, it would no longer mount: root@server # mount /dev/vg0/home /home mount: wrong fs type, bad option, bad superblock on /dev/mapper/vg0-home, missing codepage or helper program, or other error In some cases useful info is found in syslog - try dmesg | tail or so I actually had no important information on that file system, so I re-created it. Luckily the next volume was intact, and I could bring up the rest of the system without problems. So to sum up: LVM keeps a backup of all it’s metadata that can be restored (after a reboot), but if your keyboard is faster than your brain it can be a good idea to keep an unused volume as the first logical volume 🙂 Comments (0) | dec 12 WordPress – mildly impressed Posted on fredag, december 12, 2008 in Planet Ubuntu-DK , Sysadmin'ing , Ubuntu , University So, I just installed WordPress, because I was starting to have a too long mental list of things that I considered “blog-able”. My current estimate of what I will be blogging about is: Sysadmin’ing on a tight budget, Ubuntu Linux, MultiADM, various happenings in the Open Source world, and probably a bit about my everyday life as a student of Computer Science at Aalborg University, Denmark. But back to the title of this post. For various reasons I have previously preferred other blogging software (primarily blogging software integrated with Typo3), but I finally gave in and installed WordPress. I deemed that I was simply missing out on too much: trackbacks, tags, anti-spam measures for comments. All this warranted a separate blogging system, and WordPress is pretty much the no. 1 blogging system in use. My experience with it so far: Installation was okay, but it could have told me that the reason I didn’t get the fancy install-wizard was because I had forgot to give permissions for WordPress to modify its files. Minor nitpick: I decided to move my installation from /wordpress to just /. This resulted in all links still pointing at /wordpress. After a little detective work, and phpMyAdmin to the rescue to alter a couple of rows, and everything was working again. But overall it seems WordPress is a pretty capable and extendable, and has a nice Web 2.0-like user interface. I’m pretty sure I will grow accustomed to it over time. Comments (0) | Categories Danish Hal9k Ikke kategoriseret Planet Ubuntu-DK Planets Sysadmin'ing Ubuntu University Woodworking © blog.smartere . All Rights Reserved. WordPress Theme designed by Chris Wallace | 2026-01-13T08:48:58 |
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https://docs.python.org/3/glossary.html#term-0 | Glossary — Python 3.14.2 documentation Theme Auto Light Dark Previous topic Deprecations Next topic About this documentation This page Report a bug Show source Navigation index modules | next | previous | Python » 3.14.2 Documentation » Glossary | Theme Auto Light Dark | Glossary ¶ >>> ¶ The default Python prompt of the interactive shell. Often seen for code examples which can be executed interactively in the interpreter. ... ¶ Can refer to: The default Python prompt of the interactive shell when entering the code for an indented code block, when within a pair of matching left and right delimiters (parentheses, square brackets, curly braces or triple quotes), or after specifying a decorator. The three dots form of the Ellipsis object. abstract base class ¶ Abstract base classes complement duck-typing by providing a way to define interfaces when other techniques like hasattr() would be clumsy or subtly wrong (for example with magic methods ). ABCs introduce virtual subclasses, which are classes that don’t inherit from a class but are still recognized by isinstance() and issubclass() ; see the abc module documentation. Python comes with many built-in ABCs for data structures (in the collections.abc module), numbers (in the numbers module), streams (in the io module), import finders and loaders (in the importlib.abc module). You can create your own ABCs with the abc module. annotate function ¶ A function that can be called to retrieve the annotations of an object. This function is accessible as the __annotate__ attribute of functions, classes, and modules. Annotate functions are a subset of evaluate functions . annotation ¶ A label associated with a variable, a class attribute or a function parameter or return value, used by convention as a type hint . Annotations of local variables cannot be accessed at runtime, but annotations of global variables, class attributes, and functions can be retrieved by calling annotationlib.get_annotations() on modules, classes, and functions, respectively. See variable annotation , function annotation , PEP 484 , PEP 526 , and PEP 649 , which describe this functionality. Also see Annotations Best Practices for best practices on working with annotations. argument ¶ A value passed to a function (or method ) when calling the function. There are two kinds of argument: keyword argument : an argument preceded by an identifier (e.g. name= ) in a function call or passed as a value in a dictionary preceded by ** . For example, 3 and 5 are both keyword arguments in the following calls to complex() : complex ( real = 3 , imag = 5 ) complex ( ** { 'real' : 3 , 'imag' : 5 }) positional argument : an argument that is not a keyword argument. Positional arguments can appear at the beginning of an argument list and/or be passed as elements of an iterable preceded by * . For example, 3 and 5 are both positional arguments in the following calls: complex ( 3 , 5 ) complex ( * ( 3 , 5 )) Arguments are assigned to the named local variables in a function body. See the Calls section for the rules governing this assignment. Syntactically, any expression can be used to represent an argument; the evaluated value is assigned to the local variable. See also the parameter glossary entry, the FAQ question on the difference between arguments and parameters , and PEP 362 . asynchronous context manager ¶ An object which controls the environment seen in an async with statement by defining __aenter__() and __aexit__() methods. Introduced by PEP 492 . asynchronous generator ¶ A function which returns an asynchronous generator iterator . It looks like a coroutine function defined with async def except that it contains yield expressions for producing a series of values usable in an async for loop. Usually refers to an asynchronous generator function, but may refer to an asynchronous generator iterator in some contexts. In cases where the intended meaning isn’t clear, using the full terms avoids ambiguity. An asynchronous generator function may contain await expressions as well as async for , and async with statements. asynchronous generator iterator ¶ An object created by an asynchronous generator function. This is an asynchronous iterator which when called using the __anext__() method returns an awaitable object which will execute the body of the asynchronous generator function until the next yield expression. Each yield temporarily suspends processing, remembering the execution state (including local variables and pending try-statements). When the asynchronous generator iterator effectively resumes with another awaitable returned by __anext__() , it picks up where it left off. See PEP 492 and PEP 525 . asynchronous iterable ¶ An object, that can be used in an async for statement. Must return an asynchronous iterator from its __aiter__() method. Introduced by PEP 492 . asynchronous iterator ¶ An object that implements the __aiter__() and __anext__() methods. __anext__() must return an awaitable object. async for resolves the awaitables returned by an asynchronous iterator’s __anext__() method until it raises a StopAsyncIteration exception. Introduced by PEP 492 . atomic operation ¶ An operation that appears to execute as a single, indivisible step: no other thread can observe it half-done, and its effects become visible all at once. Python does not guarantee that high-level statements are atomic (for example, x += 1 performs multiple bytecode operations and is not atomic). Atomicity is only guaranteed where explicitly documented. See also race condition and data race . attached thread state ¶ A thread state that is active for the current OS thread. When a thread state is attached, the OS thread has access to the full Python C API and can safely invoke the bytecode interpreter. Unless a function explicitly notes otherwise, attempting to call the C API without an attached thread state will result in a fatal error or undefined behavior. A thread state can be attached and detached explicitly by the user through the C API, or implicitly by the runtime, including during blocking C calls and by the bytecode interpreter in between calls. On most builds of Python, having an attached thread state implies that the caller holds the GIL for the current interpreter, so only one OS thread can have an attached thread state at a given moment. In free-threaded builds of Python, threads can concurrently hold an attached thread state, allowing for true parallelism of the bytecode interpreter. attribute ¶ A value associated with an object which is usually referenced by name using dotted expressions. For example, if an object o has an attribute a it would be referenced as o.a . It is possible to give an object an attribute whose name is not an identifier as defined by Names (identifiers and keywords) , for example using setattr() , if the object allows it. Such an attribute will not be accessible using a dotted expression, and would instead need to be retrieved with getattr() . awaitable ¶ An object that can be used in an await expression. Can be a coroutine or an object with an __await__() method. See also PEP 492 . BDFL ¶ Benevolent Dictator For Life, a.k.a. Guido van Rossum , Python’s creator. binary file ¶ A file object able to read and write bytes-like objects . Examples of binary files are files opened in binary mode ( 'rb' , 'wb' or 'rb+' ), sys.stdin.buffer , sys.stdout.buffer , and instances of io.BytesIO and gzip.GzipFile . See also text file for a file object able to read and write str objects. borrowed reference ¶ In Python’s C API, a borrowed reference is a reference to an object, where the code using the object does not own the reference. It becomes a dangling pointer if the object is destroyed. For example, a garbage collection can remove the last strong reference to the object and so destroy it. Calling Py_INCREF() on the borrowed reference is recommended to convert it to a strong reference in-place, except when the object cannot be destroyed before the last usage of the borrowed reference. The Py_NewRef() function can be used to create a new strong reference . bytes-like object ¶ An object that supports the Buffer Protocol and can export a C- contiguous buffer. This includes all bytes , bytearray , and array.array objects, as well as many common memoryview objects. Bytes-like objects can be used for various operations that work with binary data; these include compression, saving to a binary file, and sending over a socket. Some operations need the binary data to be mutable. The documentation often refers to these as “read-write bytes-like objects”. Example mutable buffer objects include bytearray and a memoryview of a bytearray . Other operations require the binary data to be stored in immutable objects (“read-only bytes-like objects”); examples of these include bytes and a memoryview of a bytes object. bytecode ¶ Python source code is compiled into bytecode, the internal representation of a Python program in the CPython interpreter. The bytecode is also cached in .pyc files so that executing the same file is faster the second time (recompilation from source to bytecode can be avoided). This “intermediate language” is said to run on a virtual machine that executes the machine code corresponding to each bytecode. Do note that bytecodes are not expected to work between different Python virtual machines, nor to be stable between Python releases. A list of bytecode instructions can be found in the documentation for the dis module . callable ¶ A callable is an object that can be called, possibly with a set of arguments (see argument ), with the following syntax: callable ( argument1 , argument2 , argumentN ) A function , and by extension a method , is a callable. An instance of a class that implements the __call__() method is also a callable. callback ¶ A subroutine function which is passed as an argument to be executed at some point in the future. class ¶ A template for creating user-defined objects. Class definitions normally contain method definitions which operate on instances of the class. class variable ¶ A variable defined in a class and intended to be modified only at class level (i.e., not in an instance of the class). closure variable ¶ A free variable referenced from a nested scope that is defined in an outer scope rather than being resolved at runtime from the globals or builtin namespaces. May be explicitly defined with the nonlocal keyword to allow write access, or implicitly defined if the variable is only being read. For example, in the inner function in the following code, both x and print are free variables , but only x is a closure variable : def outer (): x = 0 def inner (): nonlocal x x += 1 print ( x ) return inner Due to the codeobject.co_freevars attribute (which, despite its name, only includes the names of closure variables rather than listing all referenced free variables), the more general free variable term is sometimes used even when the intended meaning is to refer specifically to closure variables. complex number ¶ An extension of the familiar real number system in which all numbers are expressed as a sum of a real part and an imaginary part. Imaginary numbers are real multiples of the imaginary unit (the square root of -1 ), often written i in mathematics or j in engineering. Python has built-in support for complex numbers, which are written with this latter notation; the imaginary part is written with a j suffix, e.g., 3+1j . To get access to complex equivalents of the math module, use cmath . Use of complex numbers is a fairly advanced mathematical feature. If you’re not aware of a need for them, it’s almost certain you can safely ignore them. concurrency ¶ The ability of a computer program to perform multiple tasks at the same time. Python provides libraries for writing programs that make use of different forms of concurrency. asyncio is a library for dealing with asynchronous tasks and coroutines. threading provides access to operating system threads and multiprocessing to operating system processes. Multi-core processors can execute threads and processes on different CPU cores at the same time (see parallelism ). concurrent modification ¶ When multiple threads modify shared data at the same time. Concurrent modification without proper synchronization can cause race conditions , and might also trigger a data race , data corruption, or both. context ¶ This term has different meanings depending on where and how it is used. Some common meanings: The temporary state or environment established by a context manager via a with statement. The collection of keyvalue bindings associated with a particular contextvars.Context object and accessed via ContextVar objects. Also see context variable . A contextvars.Context object. Also see current context . context management protocol ¶ The __enter__() and __exit__() methods called by the with statement. See PEP 343 . context manager ¶ An object which implements the context management protocol and controls the environment seen in a with statement. See PEP 343 . context variable ¶ A variable whose value depends on which context is the current context . Values are accessed via contextvars.ContextVar objects. Context variables are primarily used to isolate state between concurrent asynchronous tasks. contiguous ¶ A buffer is considered contiguous exactly if it is either C-contiguous or Fortran contiguous . Zero-dimensional buffers are C and Fortran contiguous. In one-dimensional arrays, the items must be laid out in memory next to each other, in order of increasing indexes starting from zero. In multidimensional C-contiguous arrays, the last index varies the fastest when visiting items in order of memory address. However, in Fortran contiguous arrays, the first index varies the fastest. coroutine ¶ Coroutines are a more generalized form of subroutines. Subroutines are entered at one point and exited at another point. Coroutines can be entered, exited, and resumed at many different points. They can be implemented with the async def statement. See also PEP 492 . coroutine function ¶ A function which returns a coroutine object. A coroutine function may be defined with the async def statement, and may contain await , async for , and async with keywords. These were introduced by PEP 492 . CPython ¶ The canonical implementation of the Python programming language, as distributed on python.org . The term “CPython” is used when necessary to distinguish this implementation from others such as Jython or IronPython. current context ¶ The context ( contextvars.Context object) that is currently used by ContextVar objects to access (get or set) the values of context variables . Each thread has its own current context. Frameworks for executing asynchronous tasks (see asyncio ) associate each task with a context which becomes the current context whenever the task starts or resumes execution. cyclic isolate ¶ A subgroup of one or more objects that reference each other in a reference cycle, but are not referenced by objects outside the group. The goal of the cyclic garbage collector is to identify these groups and break the reference cycles so that the memory can be reclaimed. data race ¶ A situation where multiple threads access the same memory location concurrently, at least one of the accesses is a write, and the threads do not use any synchronization to control their access. Data races lead to non-deterministic behavior and can cause data corruption. Proper use of locks and other synchronization primitives prevents data races. Note that data races can only happen in native code, but that native code might be exposed in a Python API. See also race condition and thread-safe . deadlock ¶ A situation in which two or more tasks (threads, processes, or coroutines) wait indefinitely for each other to release resources or complete actions, preventing any from making progress. For example, if thread A holds lock 1 and waits for lock 2, while thread B holds lock 2 and waits for lock 1, both threads will wait indefinitely. In Python this often arises from acquiring multiple locks in conflicting orders or from circular join/await dependencies. Deadlocks can be avoided by always acquiring multiple locks in a consistent order. See also lock and reentrant . decorator ¶ A function returning another function, usually applied as a function transformation using the @wrapper syntax. Common examples for decorators are classmethod() and staticmethod() . The decorator syntax is merely syntactic sugar, the following two function definitions are semantically equivalent: def f ( arg ): ... f = staticmethod ( f ) @staticmethod def f ( arg ): ... The same concept exists for classes, but is less commonly used there. See the documentation for function definitions and class definitions for more about decorators. descriptor ¶ Any object which defines the methods __get__() , __set__() , or __delete__() . When a class attribute is a descriptor, its special binding behavior is triggered upon attribute lookup. Normally, using a.b to get, set or delete an attribute looks up the object named b in the class dictionary for a , but if b is a descriptor, the respective descriptor method gets called. Understanding descriptors is a key to a deep understanding of Python because they are the basis for many features including functions, methods, properties, class methods, static methods, and reference to super classes. For more information about descriptors’ methods, see Implementing Descriptors or the Descriptor How To Guide . dictionary ¶ An associative array, where arbitrary keys are mapped to values. The keys can be any object with __hash__() and __eq__() methods. Called a hash in Perl. dictionary comprehension ¶ A compact way to process all or part of the elements in an iterable and return a dictionary with the results. results = {n: n ** 2 for n in range(10)} generates a dictionary containing key n mapped to value n ** 2 . See Displays for lists, sets and dictionaries . dictionary view ¶ The objects returned from dict.keys() , dict.values() , and dict.items() are called dictionary views. They provide a dynamic view on the dictionary’s entries, which means that when the dictionary changes, the view reflects these changes. To force the dictionary view to become a full list use list(dictview) . See Dictionary view objects . docstring ¶ A string literal which appears as the first expression in a class, function or module. While ignored when the suite is executed, it is recognized by the compiler and put into the __doc__ attribute of the enclosing class, function or module. Since it is available via introspection, it is the canonical place for documentation of the object. duck-typing ¶ A programming style which does not look at an object’s type to determine if it has the right interface; instead, the method or attribute is simply called or used (“If it looks like a duck and quacks like a duck, it must be a duck.”) By emphasizing interfaces rather than specific types, well-designed code improves its flexibility by allowing polymorphic substitution. Duck-typing avoids tests using type() or isinstance() . (Note, however, that duck-typing can be complemented with abstract base classes .) Instead, it typically employs hasattr() tests or EAFP programming. dunder ¶ An informal short-hand for “double underscore”, used when talking about a special method . For example, __init__ is often pronounced “dunder init”. EAFP ¶ Easier to ask for forgiveness than permission. This common Python coding style assumes the existence of valid keys or attributes and catches exceptions if the assumption proves false. This clean and fast style is characterized by the presence of many try and except statements. The technique contrasts with the LBYL style common to many other languages such as C. evaluate function ¶ A function that can be called to evaluate a lazily evaluated attribute of an object, such as the value of type aliases created with the type statement. expression ¶ A piece of syntax which can be evaluated to some value. In other words, an expression is an accumulation of expression elements like literals, names, attribute access, operators or function calls which all return a value. In contrast to many other languages, not all language constructs are expressions. There are also statement s which cannot be used as expressions, such as while . Assignments are also statements, not expressions. extension module ¶ A module written in C or C++, using Python’s C API to interact with the core and with user code. f-string ¶ f-strings ¶ String literals prefixed with f or F are commonly called “f-strings” which is short for formatted string literals . See also PEP 498 . file object ¶ An object exposing a file-oriented API (with methods such as read() or write() ) to an underlying resource. Depending on the way it was created, a file object can mediate access to a real on-disk file or to another type of storage or communication device (for example standard input/output, in-memory buffers, sockets, pipes, etc.). File objects are also called file-like objects or streams . There are actually three categories of file objects: raw binary files , buffered binary files and text files . Their interfaces are defined in the io module. The canonical way to create a file object is by using the open() function. file-like object ¶ A synonym for file object . filesystem encoding and error handler ¶ Encoding and error handler used by Python to decode bytes from the operating system and encode Unicode to the operating system. The filesystem encoding must guarantee to successfully decode all bytes below 128. If the file system encoding fails to provide this guarantee, API functions can raise UnicodeError . The sys.getfilesystemencoding() and sys.getfilesystemencodeerrors() functions can be used to get the filesystem encoding and error handler. The filesystem encoding and error handler are configured at Python startup by the PyConfig_Read() function: see filesystem_encoding and filesystem_errors members of PyConfig . See also the locale encoding . finder ¶ An object that tries to find the loader for a module that is being imported. There are two types of finder: meta path finders for use with sys.meta_path , and path entry finders for use with sys.path_hooks . See Finders and loaders and importlib for much more detail. floor division ¶ Mathematical division that rounds down to nearest integer. The floor division operator is // . For example, the expression 11 // 4 evaluates to 2 in contrast to the 2.75 returned by float true division. Note that (-11) // 4 is -3 because that is -2.75 rounded downward . See PEP 238 . free threading ¶ A threading model where multiple threads can run Python bytecode simultaneously within the same interpreter. This is in contrast to the global interpreter lock which allows only one thread to execute Python bytecode at a time. See PEP 703 . free variable ¶ Formally, as defined in the language execution model , a free variable is any variable used in a namespace which is not a local variable in that namespace. See closure variable for an example. Pragmatically, due to the name of the codeobject.co_freevars attribute, the term is also sometimes used as a synonym for closure variable . function ¶ A series of statements which returns some value to a caller. It can also be passed zero or more arguments which may be used in the execution of the body. See also parameter , method , and the Function definitions section. function annotation ¶ An annotation of a function parameter or return value. Function annotations are usually used for type hints : for example, this function is expected to take two int arguments and is also expected to have an int return value: def sum_two_numbers ( a : int , b : int ) -> int : return a + b Function annotation syntax is explained in section Function definitions . See variable annotation and PEP 484 , which describe this functionality. Also see Annotations Best Practices for best practices on working with annotations. __future__ ¶ A future statement , from __future__ import <feature> , directs the compiler to compile the current module using syntax or semantics that will become standard in a future release of Python. The __future__ module documents the possible values of feature . By importing this module and evaluating its variables, you can see when a new feature was first added to the language and when it will (or did) become the default: >>> import __future__ >>> __future__ . division _Feature((2, 2, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0), 8192) garbage collection ¶ The process of freeing memory when it is not used anymore. Python performs garbage collection via reference counting and a cyclic garbage collector that is able to detect and break reference cycles. The garbage collector can be controlled using the gc module. generator ¶ A function which returns a generator iterator . It looks like a normal function except that it contains yield expressions for producing a series of values usable in a for-loop or that can be retrieved one at a time with the next() function. Usually refers to a generator function, but may refer to a generator iterator in some contexts. In cases where the intended meaning isn’t clear, using the full terms avoids ambiguity. generator iterator ¶ An object created by a generator function. Each yield temporarily suspends processing, remembering the execution state (including local variables and pending try-statements). When the generator iterator resumes, it picks up where it left off (in contrast to functions which start fresh on every invocation). generator expression ¶ An expression that returns an iterator . It looks like a normal expression followed by a for clause defining a loop variable, range, and an optional if clause. The combined expression generates values for an enclosing function: >>> sum ( i * i for i in range ( 10 )) # sum of squares 0, 1, 4, ... 81 285 generic function ¶ A function composed of multiple functions implementing the same operation for different types. Which implementation should be used during a call is determined by the dispatch algorithm. See also the single dispatch glossary entry, the functools.singledispatch() decorator, and PEP 443 . generic type ¶ A type that can be parameterized; typically a container class such as list or dict . Used for type hints and annotations . For more details, see generic alias types , PEP 483 , PEP 484 , PEP 585 , and the typing module. GIL ¶ See global interpreter lock . global interpreter lock ¶ The mechanism used by the CPython interpreter to assure that only one thread executes Python bytecode at a time. This simplifies the CPython implementation by making the object model (including critical built-in types such as dict ) implicitly safe against concurrent access. Locking the entire interpreter makes it easier for the interpreter to be multi-threaded, at the expense of much of the parallelism afforded by multi-processor machines. However, some extension modules, either standard or third-party, are designed so as to release the GIL when doing computationally intensive tasks such as compression or hashing. Also, the GIL is always released when doing I/O. As of Python 3.13, the GIL can be disabled using the --disable-gil build configuration. After building Python with this option, code must be run with -X gil=0 or after setting the PYTHON_GIL=0 environment variable. This feature enables improved performance for multi-threaded applications and makes it easier to use multi-core CPUs efficiently. For more details, see PEP 703 . In prior versions of Python’s C API, a function might declare that it requires the GIL to be held in order to use it. This refers to having an attached thread state . global state ¶ Data that is accessible throughout a program, such as module-level variables, class variables, or C static variables in extension modules . In multi-threaded programs, global state shared between threads typically requires synchronization to avoid race conditions and data races . hash-based pyc ¶ A bytecode cache file that uses the hash rather than the last-modified time of the corresponding source file to determine its validity. See Cached bytecode invalidation . hashable ¶ An object is hashable if it has a hash value which never changes during its lifetime (it needs a __hash__() method), and can be compared to other objects (it needs an __eq__() method). Hashable objects which compare equal must have the same hash value. Hashability makes an object usable as a dictionary key and a set member, because these data structures use the hash value internally. Most of Python’s immutable built-in objects are hashable; mutable containers (such as lists or dictionaries) are not; immutable containers (such as tuples and frozensets) are only hashable if their elements are hashable. Objects which are instances of user-defined classes are hashable by default. They all compare unequal (except with themselves), and their hash value is derived from their id() . IDLE ¶ An Integrated Development and Learning Environment for Python. IDLE — Python editor and shell is a basic editor and interpreter environment which ships with the standard distribution of Python. immortal ¶ Immortal objects are a CPython implementation detail introduced in PEP 683 . If an object is immortal, its reference count is never modified, and therefore it is never deallocated while the interpreter is running. For example, True and None are immortal in CPython. Immortal objects can be identified via sys._is_immortal() , or via PyUnstable_IsImmortal() in the C API. immutable ¶ An object with a fixed value. Immutable objects include numbers, strings and tuples. Such an object cannot be altered. A new object has to be created if a different value has to be stored. They play an important role in places where a constant hash value is needed, for example as a key in a dictionary. Immutable objects are inherently thread-safe because their state cannot be modified after creation, eliminating concerns about improperly synchronized concurrent modification . import path ¶ A list of locations (or path entries ) that are searched by the path based finder for modules to import. During import, this list of locations usually comes from sys.path , but for subpackages it may also come from the parent package’s __path__ attribute. importing ¶ The process by which Python code in one module is made available to Python code in another module. importer ¶ An object that both finds and loads a module; both a finder and loader object. interactive ¶ Python has an interactive interpreter which means you can enter statements and expressions at the interpreter prompt, immediately execute them and see their results. Just launch python with no arguments (possibly by selecting it from your computer’s main menu). It is a very powerful way to test out new ideas or inspect modules and packages (remember help(x) ). For more on interactive mode, see Interactive Mode . interpreted ¶ Python is an interpreted language, as opposed to a compiled one, though the distinction can be blurry because of the presence of the bytecode compiler. This means that source files can be run directly without explicitly creating an executable which is then run. Interpreted languages typically have a shorter development/debug cycle than compiled ones, though their programs generally also run more slowly. See also interactive . interpreter shutdown ¶ When asked to shut down, the Python interpreter enters a special phase where it gradually releases all allocated resources, such as modules and various critical internal structures. It also makes several calls to the garbage collector . This can trigger the execution of code in user-defined destructors or weakref callbacks. Code executed during the shutdown phase can encounter various exceptions as the resources it relies on may not function anymore (common examples are library modules or the warnings machinery). The main reason for interpreter shutdown is that the __main__ module or the script being run has finished executing. iterable ¶ An object capable of returning its members one at a time. Examples of iterables include all sequence types (such as list , str , and tuple ) and some non-sequence types like dict , file objects , and objects of any classes you define with an __iter__() method or with a __getitem__() method that implements sequence semantics. Iterables can be used in a for loop and in many other places where a sequence is needed ( zip() , map() , …). When an iterable object is passed as an argument to the built-in function iter() , it returns an iterator for the object. This iterator is good for one pass over the set of values. When using iterables, it is usually not necessary to call iter() or deal with iterator objects yourself. The for statement does that automatically for you, creating a temporary unnamed variable to hold the iterator for the duration of the loop. See also iterator , sequence , and generator . iterator ¶ An object representing a stream of data. Repeated calls to the iterator’s __next__() method (or passing it to the built-in function next() ) return successive items in the stream. When no more data are available a StopIteration exception is raised instead. At this point, the iterator object is exhausted and any further calls to its __next__() method just raise StopIteration again. Iterators are required to have an __iter__() method that returns the iterator object itself so every iterator is also iterable and may be used in most places where other iterables are accepted. One notable exception is code which attempts multiple iteration passes. A container object (such as a list ) produces a fresh new iterator each time you pass it to the iter() function or use it in a for loop. Attempting this with an iterator will just return the same exhausted iterator object used in the previous iteration pass, making it appear like an empty container. More information can be found in Iterator Types . CPython implementation detail: CPython does not consistently apply the requirement that an iterator define __iter__() . And also please note that free-threaded CPython does not guarantee thread-safe behavior of iterator operations. key function ¶ A key function or collation function is a callable that returns a value used for sorting or ordering. For example, locale.strxfrm() is used to produce a sort key that is aware of locale specific sort conventions. A number of tools in Python accept key functions to control how elements are ordered or grouped. They include min() , max() , sorted() , list.sort() , heapq.merge() , heapq.nsmallest() , heapq.nlargest() , and itertools.groupby() . There are several ways to create a key function. For example. the str.casefold() method can serve as a key function for case insensitive sorts. Alternatively, a key function can be built from a lambda expression such as lambda r: (r[0], r[2]) . Also, operator.attrgetter() , operator.itemgetter() , and operator.methodcaller() are three key function constructors. See the Sorting HOW TO for examples of how to create and use key functions. keyword argument ¶ See argument . lambda ¶ An anonymous inline function consisting of a single expression which is evaluated when the function is called. The syntax to create a lambda function is lambda [parameters]: expression LBYL ¶ Look before you leap. This coding style explicitly tests for pre-conditions before making calls or lookups. This style contrasts with the EAFP approach and is characterized by the presence of many if statements. In a multi-threaded environment, the LBYL approach can risk introducing a race condition between “the looking” and “the leaping”. For example, the code, if key in mapping: return mapping[key] can fail if another thread removes key from mapping after the test, but before the lookup. This issue can be solved with locks or by using the EAFP approach. See also thread-safe . lexical analyzer ¶ Formal name for the tokenizer ; see token . list ¶ A built-in Python sequence . Despite its name it is more akin to an array in other languages than to a linked list since access to elements is O (1). list comprehension ¶ A compact way to process all or part of the elements in a sequence and return a list with the results. result = ['{:#04x}'.format(x) for x in range(256) if x % 2 == 0] generates a list of strings containing even hex numbers (0x..) in the range from 0 to 255. The if clause is optional. If omitted, all elements in range(256) are processed. lock ¶ A synchronization primitive that allows only one thread at a time to access a shared resource. A thread must acquire a lock before accessing the protected resource and release it afterward. If a thread attempts to acquire a lock that is already held by another thread, it will block until the lock becomes available. Python’s threading module provides Lock (a basic lock) and RLock (a reentrant lock). Locks are used to prevent race conditions and ensure thread-safe access to shared data. Alternative design patterns to locks exist such as queues, producer/consumer patterns, and thread-local state. See also deadlock , and reentrant . loader ¶ An object that loads a module. It must define the exec_module() and create_module() methods to implement the Loader interface. A loader is typically returned by a finder . See also: Finders and loaders importlib.abc.Loader PEP 302 locale encoding ¶ On Unix, it is the encoding of the LC_CTYPE locale. It can be set with locale.setlocale(locale.LC_CTYPE, new_locale) . On Windows, it is the ANSI code page (ex: "cp1252" ). On Android and VxWorks, Python uses "utf-8" as the locale encoding. locale.getencoding() can be used to get the locale encoding. See also the filesystem encoding and error handler . magic method ¶ An informal synonym for special method . mapping ¶ A container object that supports arbitrary key lookups and implements the methods specified in the collections.abc.Mapping or collections.abc.MutableMapping abstract base classes . Examples include dict , collections.defaultdict , collections.OrderedDict and collections.Counter . meta path finder ¶ A finder returned by a search of sys.meta_path . Meta path finders are related to, but different from path entry finders . See importlib.abc.MetaPathFinder for the methods that meta path finders implement. metaclass ¶ The class of a class. Class definitions create a class name, a class dictionary, and a list of base classes. The metaclass is responsible for taking those three arguments and creating the class. Most object oriented programming languages provide a default implementation. What makes Python special is that it is possible to create custom metaclasses. Most users never need this tool, but when the need arises, metaclasses can provide powerful, elegant solutions. They have been used for logging attribute access, adding thread-safety, tracking object creation, implementing singletons, and many other tasks. More information can be found in Metaclasses . method ¶ A function which is defined inside a class body. If called as an attribute of an instance of that class, the method will get the instance object as its first argument (which is usually called self ). See function and nested scope . method resolution order ¶ Method Resolution Order is the order in which base classes are searched for a member during lookup. See The Python 2.3 Method Resolution Order for details of the algorithm used by the Python interpreter since the 2.3 release. module ¶ An object that serves as an organizational unit of Python code. Modules have a namespace containing arbitrary Python objects. Modules are loaded into Python by the process of importing . See also package . module spec ¶ A namespace containing the import-related information used to load a module. An instance of importlib.machinery.ModuleSpec . See also Module specs . MRO ¶ See method resolution order . mutable ¶ An object with state that is allowed to change during the course of the program. In multi-threaded programs, mutable objects that are shared between threads require careful synchronization to avoid race conditions . See also immutable , thread-safe , and concurrent modification . named tuple ¶ The term “named tuple” applies to any type or class that inherits from tuple and whose indexable elements are also accessible using named attributes. The type or class may have other features as well. Several built-in types are named tuples, including the values returned by time.localtime() and os.stat() . Another example is sys.float_info : >>> sys . float_info [ 1 ] # indexed access 1024 >>> sys . float_info . max_exp # named field access 1024 >>> isinstance ( sys . float_info , tuple ) # kind of tuple True Some named tuples are built-in types (such as the above examples). Alternatively, a named tuple can be created from a regular class definition that inherits from tuple and that defines named fields. Such a class can be written by hand, or it can be created by inheriting typing.NamedTuple , or with the factory function collections.namedtuple() . The latter techniques also add some extra methods that may not be found in hand-written or built-in named tuples. namespace ¶ The place where a variable is stored. Namespaces are implemented as dictionaries. There are the local, global and built-in namespaces as well as nested namespaces in objects (in methods). Namespaces support modularity by preventing naming conflicts. For instance, the functions builtins.open and os.open() are distinguished by their namespaces. Namespaces also aid readability and maintainability by making it clear which module implements a function. For instance, writing random.seed() or itertools.islice() makes it clear that those functions are implemented by the random and itertools modules, respectively. namespace package ¶ A package which serves only as a container for subpackages. Namespace packages may have no physical representation, and specifically are not like a regular package because they have no __init__.py file. Namespace packages allow several individually installable packages to have a common parent package. Otherwise, it is recommended to use a regular package . For more information, see PEP 420 and Namespace packages . See also module . native code ¶ Code that is compiled to machine instructions and runs directly on the processor, as opposed to code that is interpreted or runs in a virtual machine. In the context of Python, native code typically refers to C, C++, Rust or Fortran code in extension modules that can be called from Python. See also extension module . nested scope ¶ The ability to refer to a variable in an enclosing definition. For instance, a function defined inside another function can refer to variables in the outer function. Note that nested scopes by default work only for reference and not for assignment. Local variables both read and write in the innermost scope. Likewise, global variables read and write to the global namespace. The nonlocal allows writing to outer scopes. new-style class ¶ Old name for the flavor of classes now used for all class objects. In earlier Python versions, only new-style classes could use Python’s newer, versatile features like __slots__ , descriptors, properties, __getattribute__() , class methods, and static methods. non-deterministic ¶ Behavior where the outcome of a program can vary between executions with the same inputs. In multi-threaded programs, non-deterministic behavior often results from race conditions where the relative timing or interleaving of threads affects the result. Proper synchronization using locks and other synchronization primitives helps ensure deterministic behavior. object ¶ Any data with state (attributes or value) and defined behavior (methods). Also the ultimate base class of any new-style class . optimized scope ¶ A scope where target local variable names are reliably known to the compiler when the code is compiled, allowing optimization of read and write access to these names. The local namespaces for functions, generators, coroutines, comprehensions, and generator expressions are optimized in this fashion. Note: most interpreter optimizations are applied to all scopes, only those relying on a known set of local and nonlocal variable names are restricted to optimized scopes. optional module ¶ An extension module that is part of the standard library , but may be absent in some builds of CPython , usually due to missing third-party libraries or because the module is not available for a given platform. See Requirements for optional modules for a list of optional modules that require third-party libraries. package ¶ A Python module which can contain submodules or recursively, subpackages. Technically, a package is a Python module with a __path__ attribute. See also regular package and namespace package . parallelism ¶ Executing multiple operations at the same time (e.g. on multiple CPU cores). In Python builds with the global interpreter lock (GIL) , only one thread runs Python bytecode at a time, so taking advantage of multiple CPU cores typically involves multiple processes (e.g. multiprocessing ) or native extensions that release the GIL. In free-threaded Python, multiple Python threads can run Python code simultaneously on different cores. parameter ¶ A named entity in a function (or method) definition that specifies an argument (or in some cases, arguments) that the function can accept. There are five kinds of parameter: positional-or-keyword : specifies an argument that can be passed either positionally or as a keyword argument . This is the default kind of parameter, for example foo and bar in the following: def func ( foo , bar = None ): ... positional-only : specifies an argument that can be supplied only by position. Positional-only parameters can be defined by including a / character in the parameter list of the function definition after them, for example posonly1 and posonly2 in the following: def func ( posonly1 , posonly2 , / , positional_or_keyword ): ... keyword-only : specifies an argument that can be supplied only by keyword. Keyword-only parameters can be defined by including a single var-positional parameter or bare * in the parameter list of the function definition before them, for example kw_only1 and kw_only2 in the following: def func ( arg , * , kw_only1 , kw_only2 ): ... var-positional : specifies that an arbitrary sequence of positional arguments can be provided (in addition to any positional arguments already accepted by other parameters). Such a parameter can be defined by prepending the parameter name with * , for example args in the following: def func ( * args , ** kwargs ): ... var-keyword : specifies that arbitrarily many keyword arguments can be provided (in addition to any keyword arguments already accepted by other parameters). Such a parameter can be defined by prepending the parameter name with ** , for example kwargs in the example above. Parameters can specify both optional and required arguments, as well as default values for some optional arguments. See also the argument glossary entry, the FAQ question on the difference between arguments and parameters , the inspect.Parameter class, the Function definitions section, and PEP 362 . path entry ¶ A single location on the import path which the path based finder consults to find modules for importing. path entry finder ¶ A finder returned by a callable on sys.path_hooks (i.e. a path entry hook ) which knows how to locate modules given a path entry . See importlib.abc.PathEntryFinder for the methods that path entry finders implement. path entry hook ¶ A callable on the sys.path_hooks list which returns a path entry finder if it knows how to find modules on a specific path entry . path based finder ¶ One of the default meta path finders which searches an import path for modules. path-like object ¶ An object representing a file system path. A path-like object is either a str or bytes object representing a path, or an object implementing the os.PathLike protocol. An object that supports the os.PathLike protocol can be converted to a str or bytes file system path by calling the os.fspath() function; os.fsdecode() and os.fsencode() can be used to guarantee a str or bytes result instead, respectively. Introduced by PEP 519 . PEP ¶ Python Enhancement Proposal. A PEP is a design document providing information to the Python community, or describing a new feature for Python or its processes or environment. PEPs should provide a concise technical specification and a rationale for proposed features. PEPs are intended to be the primary mechanisms for proposing major new features, for collecting community input on an issue, and for documenting the design decisions that have gone into Python. The PEP author is responsible for building consensus within the community and documenting dissenting opinions. See PEP 1 . portion ¶ A set of files in a single directory (possibly stored in a zip file) that contribute to a namespace package, as defined in PEP 420 . positional argument ¶ See argument . provisional API ¶ A provisional API is one which has been deliberately excluded from the standard library’s backwards compatibility guarantees. While major changes to such interfaces are not expected, as long as they are marked provisional, backwards incompatible changes (up to and including removal of the interface) may occur if deemed necessary by core developers. 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https://www.highlight.io/docs/getting-started/browser/replay-configuration/iframes | iframe Recording Star us on GitHub Star Docs Sign in Sign up Getting Started Getting Started with Highlight Fullstack Mapping Browser React.js Next.js Remix Vue.js Angular Gatsby.js SvelteKit Electron highlight.run SDK Overview Canvas & WebGL Console Messages Content-Security-Policy Identifying Users iframe Recording Monkey Patches Browser OpenTelemetry Persistent Asset Storage Privacy Proxying Highlight React.js Error Boundary Recording Network Requests and Responses Recording WebSocket Events Salesforce Lightning Web Components (LWC) Data Export Sourcemap Configuration Tracking Events Troubleshooting Upgrading Highlight Versioning Sessions & Errors Other React Native (beta) Server Go Overview chi Echo Fiber Gin GORM gqlgen Logrus Manual Tracing gorilla mux JS Overview Apollo AWS Lambda Cloudflare Workers Express.js Firebase Hono Nest.js Next.js Node.js Pino tRPC Winston Python Overview AWS Lambda Azure Functions Django FastAPI Flask Google Cloud Functions Loguru Other Frameworks Python AI / LLM Libraries Python Libraries Ruby Overview Other Frameworks Ruby on Rails Rust Overview actix-web No Framework Hosting Providers Overview Metrics in AWS Logging in AWS Logging in Azure Fly.io NATS Log Shipper Logging in GCP Heroku Log Drain Render Log Stream Logging in Trigger.dev Vercel Log Drain Elixir Overview Elixir App Java: All Frameworks PHP: All Frameworks C# .NET ASP C# .NET 4 ASP Docker / Docker Compose File Fluent Forward curl OpenTelemetry Protocol (OTLP) Syslog RFC5424 Systemd / Journald Native OpenTelemetry Overview Error Monitoring Logging Tracing Browser Instrumentation Metrics Fullstack Frameworks Overview Next.js Fullstack Overview Next.js Page Router Guide Next.js App Router Guide Edge Runtime Advanced Config Remix Walkthrough Self Host & Local Dev Overview Development deployment guide. 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Integrations Microsoft Teams self-hosted Hobby deployment guide. Traefik SSL Proxying. Docs Home SDK Client SDK API Reference Cloudflare Worker SDK API Reference Go SDK API Reference Hono SDK API Reference Java SDK API Reference Next.JS SDK API Reference Node.JS SDK API Reference Python SDK API Reference Ruby SDK API Reference Rust SDK API Reference Docs / Getting Started / Browser / highlight.run SDK / iframe Recording iframe Recording Recording within iframe elements Highlight will recreate an iframe with the same src. The iframe will not load if the src's origin has a restrictive X-Frame-Options header. Highlight only supports recording same-origin iframes because of browsers' same-origin policy. If it's possible to init Highlight within the iframe , you can record the events within as a separate session in your same project. If your iframe source becomes invalid after some time or will not render content when inserted in a different domain or website, the recording will not show the correct content that the user saw. Recording a cross-origin iframe element Cross-origin iframes are <iframe> elements in your app that reference a domain considered to be of a different origin . When your iframe uses a src tag pointing to a different origin, the iframe is not accessible from the parent page. However, the iframe can still emit messages that the parent page can hear. To support cross-origin iframes, we added functionality into our recording client that allows the iframe to forward its events to the parent session. All you need to do is add the Highlight snippet to both the parent window and the iframe. Ensure you are using highlight.run 7.1.0 or newer. Then, set the following option on both of the H.init calls: in the parent window and in the iframe. import { H } from 'highlight.run' H.init('<YOUR_PROJECT_ID>', { recordCrossOriginIframe: true, }) Ensure that you add the H.init call to both the parent page and the iframe page, and that you've set recordCrossOriginIframe in both H.init calls . Recording cross-origin iframe contents with no access to parent window If you are running an application that is deployed into a cross-origin iframe of a parent application that you do not control, you can record the session by setting the recordCrossOriginIframe option to false in the H.init call in the iframe. By default without that option, the SDK will assume that the iframe is waiting for an initialization method from highlight in the parent window, but setting the option to false will start recording for the iframe in standalone mode. You will find a session with just the contents of the iframe in highlight. 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Right menu Clear Link Between DevSecOps and Data Engineering Regnard Raquedan Regnard Raquedan Regnard Raquedan Follow Sep 13 '24 Clear Link Between DevSecOps and Data Engineering # dataengineering # devops # devsecops # cloud Comments Add Comment 1 min read Implement CIS Top 18 Controls in Your Organization Muhammad Awais Zahid Muhammad Awais Zahid Muhammad Awais Zahid Follow Sep 7 '24 Implement CIS Top 18 Controls in Your Organization # cybersecurity # security # devsecops # centerofinternetsecurity 4 reactions Comments Add Comment 4 min read Unleashing the Power of DevOps Transforming Collaboration and Efficiency kubeha kubeha kubeha Follow Sep 6 '24 Unleashing the Power of DevOps Transforming Collaboration and Efficiency # devops # devsecops # automation # monitoring Comments Add Comment 2 min read The Impact of Security Misconfigurations on Data Breach Incidents GitProtect Team GitProtect Team GitProtect Team Follow for GitProtect Aug 1 '24 The Impact of Security Misconfigurations on Data Breach Incidents # devops # devsecops # security # cybersecurity Comments Add Comment 5 min read 3 Security Teams To Think About Implementing For Your Organization Michael Levan Michael Levan Michael Levan Follow Aug 26 '24 3 Security Teams To Think About Implementing For Your Organization # cybersecurity # kubernetes # cloud # devsecops 2 reactions Comments Add Comment 3 min read DevSecOps en las pipelines de Terraform Sergio Jiménez Sergio Jiménez Sergio Jiménez Follow for bcloudsec Jul 21 '24 DevSecOps en las pipelines de Terraform # devsecops # cloudnative Comments Add Comment 3 min read Enhancing User Experience With Browser Synthetic Monitoring Supratip Banerjee Supratip Banerjee Supratip Banerjee Follow Jul 16 '24 Enhancing User Experience With Browser Synthetic Monitoring # devsecops # devops # security # cybersecurity 1 reaction Comments Add Comment 4 min read Comprehensive DevSecOps Pipeline: Secure & Scalable Kubernetes Deployment with AWS EKS, ArgoCD and Jenkins Integration Swapnil Suresh Mohite Swapnil Suresh Mohite Swapnil Suresh Mohite Follow Aug 18 '24 Comprehensive DevSecOps Pipeline: Secure & Scalable Kubernetes Deployment with AWS EKS, ArgoCD and Jenkins Integration # devsecops # devops # aws # jenkins 1 reaction Comments Add Comment 4 min read Death of DevSecOps, Part 3 Ryan Cartwright Ryan Cartwright Ryan Cartwright Follow for Resourcely Jul 5 '24 Death of DevSecOps, Part 3 # devops # devsecops # security # cloud Comments Add Comment 3 min read Securing Your Data: How to Safely Back Up a Single File on Bitbucket GitProtect Team GitProtect Team GitProtect Team Follow Jul 4 '24 Securing Your Data: How to Safely Back Up a Single File on Bitbucket # cybersecurity # devops # devsecops # coding 1 reaction Comments Add Comment 6 min read Understanding Threat Modeling: 🛡️ Securing Your Digital Assets Effectively Makita Tunsill Makita Tunsill Makita Tunsill Follow Jul 13 '24 Understanding Threat Modeling: 🛡️ Securing Your Digital Assets Effectively # threatmodeling # devsecops # cybersecurity # learning Comments Add Comment 2 min read Javascript support now in Beta! 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Salaudeen O. Abdulrasaq Salaudeen O. Abdulrasaq Salaudeen O. Abdulrasaq Follow Jul 16 '24 Secret Scanning in CI pipelines using Gitleaks and Pre-commit Hook. # devsecops # gitlab # security # gitleak 24 reactions Comments 1 comment 6 min read DevOps Meets Cybersecurity -> DevSecOps nivelepsilon nivelepsilon nivelepsilon Follow Jul 7 '24 DevOps Meets Cybersecurity -> DevSecOps # devops # devsecops # securityfirst # cicd 1 reaction Comments Add Comment 5 min read Cloud Over-Privileged Accounts: A Recipe for Disaster (and How to Avoid It) Public_Cloud Public_Cloud Public_Cloud Follow Jun 28 '24 Cloud Over-Privileged Accounts: A Recipe for Disaster (and How to Avoid It) # cloudpractitioner # threatmodeling # disasterrecovery # devsecops 1 reaction Comments Add Comment 3 min read Docker Security Checklist: Are You Production Ready? 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https://blog.smartere.dk/category/ubuntu/ | blog.smartere » Ubuntu blog.smartere // Ramblings of Mads Chr. Olesen feb 3 Brother DS-620 on Linux Posted on mandag, februar 3, 2014 in Planet Ubuntu-DK , Planets , Ubuntu UPDATE: The drivers were temporarily unavailable; they seem to be up again, at least on the Brother US site: http://support.brother.com/g/b/downloadlist.aspx?c=us&lang=en&prod=ds620_all&os=128 I recently bought a Brother DS-620 document scanner that supposedly had support for Linux . It turns out it did, but only after a few quirks. I installed the official Linux drivers , and tried to scan a document using a GUI scanning application. Things were hanging and generally very unresponsive. I checked with the SANE command line tools, e.g. “sane-find-scanner”. It turns out things were indeed working, albeit very slowly. In dmesg I found a lot of messages like: Jan 29 22:52:13 mchro-laptop kernel: [39172.165644] usb 2-1.3: reset high-speed USB device number 32 using ehci-pci Jan 29 22:52:13 mchro-laptop kernel: [39172.333832] usb 2-1.3: reset high-speed USB device number 32 using ehci-pci Jan 29 22:52:13 mchro-laptop kernel: [39172.501677] usb 2-1.3: reset high-speed USB device number 32 using ehci-pci Jan 29 22:52:13 mchro-laptop kernel: [39172.669712] usb 2-1.3: reset high-speed USB device number 32 using ehci-pci Jan 29 22:52:13 mchro-laptop kernel: [39172.837679] usb 2-1.3: reset high-speed USB device number 32 using ehci-pci repeating several times every seconds. At this stage I was thinking that the Linux support was very crappy. After quite a lot of mucking around playing with capturing USB packets using Wireshark, it seemed the device itself was requesting a reset, and the Linux kernel was resetting it approximately 200ms later. Reading some Linux source code, and playing with USB quirks in Linux solved nothing. Finally, I gave up and booted into Windows to check if the hardware had a defect. In Windows it worked without issues. I upgraded the firmware using the Windows utility to do so. After doing this the scanner worked without issue also in Linux. So, all in all: There is official Linux support for this scanner, but it seems to require a firmware upgrade. This could definitely be better handled by the Brother documentation. Comments (9) | jan 31 Stupid sys-admin’ing, and hooray for LVM and unnecessary partitions Posted on fredag, januar 31, 2014 in Planet Ubuntu-DK , Planets , Sysadmin'ing , Ubuntu The scenario is: almost finished migrating from an old server to a new server. Only a few steps remain, namely change DNS to point to new server wipe disks on old server Done in this order, one might be unlucky that ssh’ing in to wipe the disks lands you on the new server. If you don’t discover this and run the command dd if=/dev/zero of=/dev/md2 to wipe the disks you might run it on the new server instead. BAM: you just wiped the data of your new server. Fortunately, I realised my mistake after a few seconds, and was able to recover from this with only unimportant data loss, and a little panic. /dev/md2 is actually a LVM physical partition, of which the first part now only contains zeroes; hereunder all the meta-data. LVM reported no volumes of any kind: root@server# pvs -v Scanning for physical volume names root@server# lvs -v Finding all logical volumes No volume groups found root@server # vgs -v Finding all volume groups No volume groups found After a bit of Google’ing while panicking I found out LVM keeps a backup of all its metadata in /etc/lvm/backup , and that it could be rewritten to the physical volume using: pvcreate -ff -u XXXXXX-XXXX-XXXX-XXXX-XXXX-XXXX-XXXXXX --restorefile /etc/lvm/backup/vg0 /dev/md2 where XXXXXX-XXXX-XXXX-XXXX-XXXX-XXXX-XXXXXX is the physical UUID from the backup file: ... physical_volumes { pv0 { id = "XXXXXX-XXXX-XXXX-XXXX-XXXX-XXXX-XXXXXX" device = "/dev/md2" # Hint only ... Unfortunately, I got an error: root@server# pvcreate -ff -u XXXXXX-XXXX-XXXX-XXXX-XXXX-XXXX-XXXXXX --restorefile /etc/lvm/backup/vg0 /dev/md2 Couldn't find device with uuid XXXXXX-XXXX-XXXX-XXXX-XXXX-XXXX-XXXXXX. Can't open /dev/md2 exclusively. Mounted filesystem? lsof showed nothing accessing md2, but I guess something still had references to the logical volumes. I was unable to get it to work, so I decided to reboot (while making sure the system would come up, and nothing would try to mount the (non-existent) LVM volumes). After a reboot the command worked, but still no logical volumes: root@server # pvcreate -ff -u XXXXXX-XXXX-XXXX-XXXX-XXXX-XXXX-XXXXXX --restorefile /etc/lvm/backup/vg0 /dev/md2 Couldn't find device with uuid XXXXXX-XXXX-XXXX-XXXX-XXXX-XXXX-XXXXXX. Physical volume "/dev/md2" successfully created root@server # sudo pvs PV VG Fmt Attr PSize PFree /dev/md2 lvm2 a- 648.51g 648.51g root@server # sudo lvs No volume groups found Now I had a physical volume, and could use the vgcfgrestore command: root@server # vgcfgrestore -f /etc/lvm/backup/vg0 /dev/vg0 Restored volume group vg0 root@server # sudo lvs LV VG Attr LSize Origin Snap% Move Log Copy% Convert ... home vg0 -wi-a- 20.00g I now had my logical volumes back! Now to assess the data loss… The backup file /etc/lvm/backup/vg0 lists which order the logical volumes are stored. The first volume in my case was the “home” volume. Sure enough, it would no longer mount: root@server # mount /dev/vg0/home /home mount: wrong fs type, bad option, bad superblock on /dev/mapper/vg0-home, missing codepage or helper program, or other error In some cases useful info is found in syslog - try dmesg | tail or so I actually had no important information on that file system, so I re-created it. Luckily the next volume was intact, and I could bring up the rest of the system without problems. So to sum up: LVM keeps a backup of all it’s metadata that can be restored (after a reboot), but if your keyboard is faster than your brain it can be a good idea to keep an unused volume as the first logical volume 🙂 Comments (0) | jun 18 Making objdump -S find your source code Posted on mandag, juni 18, 2012 in Planet Ubuntu-DK , Ubuntu , University We all know the situation: We want to disassemble the most awesome pre-compiled object file, with accompanying sources, using objdump and we would like to view the assembly and C-code interleaved, so we use -S. Unfortunately, objdump fails to find the sources, and we are sad 🙁 How does objdump look for the sources? Normally the paths are hardcoded in the object file in the DWARF information. To inspect the DWARF debug info: $ objdump --dwarf myobject.o | less and look for DW_TAG_compile_unit sections, where the paths should exist like: <25> DW_AT_name : C:/ARM/myfile.c Of course, this might not be the path you have on your machine, and thus objdump gives up. However, we can use an undocumented option to objdump : the -I or –include: $ objdump -I ../mysources -S myobject.o | less and voila, objdump finds the sources, inlines the C-code, and everything is awesome! Comment (1) | dec 12 WordPress – mildly impressed Posted on fredag, december 12, 2008 in Planet Ubuntu-DK , Sysadmin'ing , Ubuntu , University So, I just installed WordPress, because I was starting to have a too long mental list of things that I considered “blog-able”. My current estimate of what I will be blogging about is: Sysadmin’ing on a tight budget, Ubuntu Linux, MultiADM, various happenings in the Open Source world, and probably a bit about my everyday life as a student of Computer Science at Aalborg University, Denmark. But back to the title of this post. For various reasons I have previously preferred other blogging software (primarily blogging software integrated with Typo3), but I finally gave in and installed WordPress. I deemed that I was simply missing out on too much: trackbacks, tags, anti-spam measures for comments. All this warranted a separate blogging system, and WordPress is pretty much the no. 1 blogging system in use. My experience with it so far: Installation was okay, but it could have told me that the reason I didn’t get the fancy install-wizard was because I had forgot to give permissions for WordPress to modify its files. Minor nitpick: I decided to move my installation from /wordpress to just /. This resulted in all links still pointing at /wordpress. After a little detective work, and phpMyAdmin to the rescue to alter a couple of rows, and everything was working again. But overall it seems WordPress is a pretty capable and extendable, and has a nice Web 2.0-like user interface. I’m pretty sure I will grow accustomed to it over time. Comments (0) | Categories Danish Hal9k Ikke kategoriseret Planet Ubuntu-DK Planets Sysadmin'ing Ubuntu University Woodworking © blog.smartere . All Rights Reserved. WordPress Theme designed by Chris Wallace | 2026-01-13T08:48:58 |
https://docs.python.org/3/glossary.html#term-floor-division | Glossary — Python 3.14.2 documentation Theme Auto Light Dark Previous topic Deprecations Next topic About this documentation This page Report a bug Show source Navigation index modules | next | previous | Python » 3.14.2 Documentation » Glossary | Theme Auto Light Dark | Glossary ¶ >>> ¶ The default Python prompt of the interactive shell. Often seen for code examples which can be executed interactively in the interpreter. ... ¶ Can refer to: The default Python prompt of the interactive shell when entering the code for an indented code block, when within a pair of matching left and right delimiters (parentheses, square brackets, curly braces or triple quotes), or after specifying a decorator. The three dots form of the Ellipsis object. abstract base class ¶ Abstract base classes complement duck-typing by providing a way to define interfaces when other techniques like hasattr() would be clumsy or subtly wrong (for example with magic methods ). ABCs introduce virtual subclasses, which are classes that don’t inherit from a class but are still recognized by isinstance() and issubclass() ; see the abc module documentation. Python comes with many built-in ABCs for data structures (in the collections.abc module), numbers (in the numbers module), streams (in the io module), import finders and loaders (in the importlib.abc module). You can create your own ABCs with the abc module. annotate function ¶ A function that can be called to retrieve the annotations of an object. This function is accessible as the __annotate__ attribute of functions, classes, and modules. Annotate functions are a subset of evaluate functions . annotation ¶ A label associated with a variable, a class attribute or a function parameter or return value, used by convention as a type hint . Annotations of local variables cannot be accessed at runtime, but annotations of global variables, class attributes, and functions can be retrieved by calling annotationlib.get_annotations() on modules, classes, and functions, respectively. See variable annotation , function annotation , PEP 484 , PEP 526 , and PEP 649 , which describe this functionality. Also see Annotations Best Practices for best practices on working with annotations. argument ¶ A value passed to a function (or method ) when calling the function. There are two kinds of argument: keyword argument : an argument preceded by an identifier (e.g. name= ) in a function call or passed as a value in a dictionary preceded by ** . For example, 3 and 5 are both keyword arguments in the following calls to complex() : complex ( real = 3 , imag = 5 ) complex ( ** { 'real' : 3 , 'imag' : 5 }) positional argument : an argument that is not a keyword argument. Positional arguments can appear at the beginning of an argument list and/or be passed as elements of an iterable preceded by * . For example, 3 and 5 are both positional arguments in the following calls: complex ( 3 , 5 ) complex ( * ( 3 , 5 )) Arguments are assigned to the named local variables in a function body. See the Calls section for the rules governing this assignment. Syntactically, any expression can be used to represent an argument; the evaluated value is assigned to the local variable. See also the parameter glossary entry, the FAQ question on the difference between arguments and parameters , and PEP 362 . asynchronous context manager ¶ An object which controls the environment seen in an async with statement by defining __aenter__() and __aexit__() methods. Introduced by PEP 492 . asynchronous generator ¶ A function which returns an asynchronous generator iterator . It looks like a coroutine function defined with async def except that it contains yield expressions for producing a series of values usable in an async for loop. Usually refers to an asynchronous generator function, but may refer to an asynchronous generator iterator in some contexts. In cases where the intended meaning isn’t clear, using the full terms avoids ambiguity. An asynchronous generator function may contain await expressions as well as async for , and async with statements. asynchronous generator iterator ¶ An object created by an asynchronous generator function. This is an asynchronous iterator which when called using the __anext__() method returns an awaitable object which will execute the body of the asynchronous generator function until the next yield expression. Each yield temporarily suspends processing, remembering the execution state (including local variables and pending try-statements). When the asynchronous generator iterator effectively resumes with another awaitable returned by __anext__() , it picks up where it left off. See PEP 492 and PEP 525 . asynchronous iterable ¶ An object, that can be used in an async for statement. Must return an asynchronous iterator from its __aiter__() method. Introduced by PEP 492 . asynchronous iterator ¶ An object that implements the __aiter__() and __anext__() methods. __anext__() must return an awaitable object. async for resolves the awaitables returned by an asynchronous iterator’s __anext__() method until it raises a StopAsyncIteration exception. Introduced by PEP 492 . atomic operation ¶ An operation that appears to execute as a single, indivisible step: no other thread can observe it half-done, and its effects become visible all at once. Python does not guarantee that high-level statements are atomic (for example, x += 1 performs multiple bytecode operations and is not atomic). Atomicity is only guaranteed where explicitly documented. See also race condition and data race . attached thread state ¶ A thread state that is active for the current OS thread. When a thread state is attached, the OS thread has access to the full Python C API and can safely invoke the bytecode interpreter. Unless a function explicitly notes otherwise, attempting to call the C API without an attached thread state will result in a fatal error or undefined behavior. A thread state can be attached and detached explicitly by the user through the C API, or implicitly by the runtime, including during blocking C calls and by the bytecode interpreter in between calls. On most builds of Python, having an attached thread state implies that the caller holds the GIL for the current interpreter, so only one OS thread can have an attached thread state at a given moment. In free-threaded builds of Python, threads can concurrently hold an attached thread state, allowing for true parallelism of the bytecode interpreter. attribute ¶ A value associated with an object which is usually referenced by name using dotted expressions. For example, if an object o has an attribute a it would be referenced as o.a . It is possible to give an object an attribute whose name is not an identifier as defined by Names (identifiers and keywords) , for example using setattr() , if the object allows it. Such an attribute will not be accessible using a dotted expression, and would instead need to be retrieved with getattr() . awaitable ¶ An object that can be used in an await expression. Can be a coroutine or an object with an __await__() method. See also PEP 492 . BDFL ¶ Benevolent Dictator For Life, a.k.a. Guido van Rossum , Python’s creator. binary file ¶ A file object able to read and write bytes-like objects . Examples of binary files are files opened in binary mode ( 'rb' , 'wb' or 'rb+' ), sys.stdin.buffer , sys.stdout.buffer , and instances of io.BytesIO and gzip.GzipFile . See also text file for a file object able to read and write str objects. borrowed reference ¶ In Python’s C API, a borrowed reference is a reference to an object, where the code using the object does not own the reference. It becomes a dangling pointer if the object is destroyed. For example, a garbage collection can remove the last strong reference to the object and so destroy it. Calling Py_INCREF() on the borrowed reference is recommended to convert it to a strong reference in-place, except when the object cannot be destroyed before the last usage of the borrowed reference. The Py_NewRef() function can be used to create a new strong reference . bytes-like object ¶ An object that supports the Buffer Protocol and can export a C- contiguous buffer. This includes all bytes , bytearray , and array.array objects, as well as many common memoryview objects. Bytes-like objects can be used for various operations that work with binary data; these include compression, saving to a binary file, and sending over a socket. Some operations need the binary data to be mutable. The documentation often refers to these as “read-write bytes-like objects”. Example mutable buffer objects include bytearray and a memoryview of a bytearray . Other operations require the binary data to be stored in immutable objects (“read-only bytes-like objects”); examples of these include bytes and a memoryview of a bytes object. bytecode ¶ Python source code is compiled into bytecode, the internal representation of a Python program in the CPython interpreter. The bytecode is also cached in .pyc files so that executing the same file is faster the second time (recompilation from source to bytecode can be avoided). This “intermediate language” is said to run on a virtual machine that executes the machine code corresponding to each bytecode. Do note that bytecodes are not expected to work between different Python virtual machines, nor to be stable between Python releases. A list of bytecode instructions can be found in the documentation for the dis module . callable ¶ A callable is an object that can be called, possibly with a set of arguments (see argument ), with the following syntax: callable ( argument1 , argument2 , argumentN ) A function , and by extension a method , is a callable. An instance of a class that implements the __call__() method is also a callable. callback ¶ A subroutine function which is passed as an argument to be executed at some point in the future. class ¶ A template for creating user-defined objects. Class definitions normally contain method definitions which operate on instances of the class. class variable ¶ A variable defined in a class and intended to be modified only at class level (i.e., not in an instance of the class). closure variable ¶ A free variable referenced from a nested scope that is defined in an outer scope rather than being resolved at runtime from the globals or builtin namespaces. May be explicitly defined with the nonlocal keyword to allow write access, or implicitly defined if the variable is only being read. For example, in the inner function in the following code, both x and print are free variables , but only x is a closure variable : def outer (): x = 0 def inner (): nonlocal x x += 1 print ( x ) return inner Due to the codeobject.co_freevars attribute (which, despite its name, only includes the names of closure variables rather than listing all referenced free variables), the more general free variable term is sometimes used even when the intended meaning is to refer specifically to closure variables. complex number ¶ An extension of the familiar real number system in which all numbers are expressed as a sum of a real part and an imaginary part. Imaginary numbers are real multiples of the imaginary unit (the square root of -1 ), often written i in mathematics or j in engineering. Python has built-in support for complex numbers, which are written with this latter notation; the imaginary part is written with a j suffix, e.g., 3+1j . To get access to complex equivalents of the math module, use cmath . Use of complex numbers is a fairly advanced mathematical feature. If you’re not aware of a need for them, it’s almost certain you can safely ignore them. concurrency ¶ The ability of a computer program to perform multiple tasks at the same time. Python provides libraries for writing programs that make use of different forms of concurrency. asyncio is a library for dealing with asynchronous tasks and coroutines. threading provides access to operating system threads and multiprocessing to operating system processes. Multi-core processors can execute threads and processes on different CPU cores at the same time (see parallelism ). concurrent modification ¶ When multiple threads modify shared data at the same time. Concurrent modification without proper synchronization can cause race conditions , and might also trigger a data race , data corruption, or both. context ¶ This term has different meanings depending on where and how it is used. Some common meanings: The temporary state or environment established by a context manager via a with statement. The collection of keyvalue bindings associated with a particular contextvars.Context object and accessed via ContextVar objects. Also see context variable . A contextvars.Context object. Also see current context . context management protocol ¶ The __enter__() and __exit__() methods called by the with statement. See PEP 343 . context manager ¶ An object which implements the context management protocol and controls the environment seen in a with statement. See PEP 343 . context variable ¶ A variable whose value depends on which context is the current context . Values are accessed via contextvars.ContextVar objects. Context variables are primarily used to isolate state between concurrent asynchronous tasks. contiguous ¶ A buffer is considered contiguous exactly if it is either C-contiguous or Fortran contiguous . Zero-dimensional buffers are C and Fortran contiguous. In one-dimensional arrays, the items must be laid out in memory next to each other, in order of increasing indexes starting from zero. In multidimensional C-contiguous arrays, the last index varies the fastest when visiting items in order of memory address. However, in Fortran contiguous arrays, the first index varies the fastest. coroutine ¶ Coroutines are a more generalized form of subroutines. Subroutines are entered at one point and exited at another point. Coroutines can be entered, exited, and resumed at many different points. They can be implemented with the async def statement. See also PEP 492 . coroutine function ¶ A function which returns a coroutine object. A coroutine function may be defined with the async def statement, and may contain await , async for , and async with keywords. These were introduced by PEP 492 . CPython ¶ The canonical implementation of the Python programming language, as distributed on python.org . The term “CPython” is used when necessary to distinguish this implementation from others such as Jython or IronPython. current context ¶ The context ( contextvars.Context object) that is currently used by ContextVar objects to access (get or set) the values of context variables . Each thread has its own current context. Frameworks for executing asynchronous tasks (see asyncio ) associate each task with a context which becomes the current context whenever the task starts or resumes execution. cyclic isolate ¶ A subgroup of one or more objects that reference each other in a reference cycle, but are not referenced by objects outside the group. The goal of the cyclic garbage collector is to identify these groups and break the reference cycles so that the memory can be reclaimed. data race ¶ A situation where multiple threads access the same memory location concurrently, at least one of the accesses is a write, and the threads do not use any synchronization to control their access. Data races lead to non-deterministic behavior and can cause data corruption. Proper use of locks and other synchronization primitives prevents data races. Note that data races can only happen in native code, but that native code might be exposed in a Python API. See also race condition and thread-safe . deadlock ¶ A situation in which two or more tasks (threads, processes, or coroutines) wait indefinitely for each other to release resources or complete actions, preventing any from making progress. For example, if thread A holds lock 1 and waits for lock 2, while thread B holds lock 2 and waits for lock 1, both threads will wait indefinitely. In Python this often arises from acquiring multiple locks in conflicting orders or from circular join/await dependencies. Deadlocks can be avoided by always acquiring multiple locks in a consistent order. See also lock and reentrant . decorator ¶ A function returning another function, usually applied as a function transformation using the @wrapper syntax. Common examples for decorators are classmethod() and staticmethod() . The decorator syntax is merely syntactic sugar, the following two function definitions are semantically equivalent: def f ( arg ): ... f = staticmethod ( f ) @staticmethod def f ( arg ): ... The same concept exists for classes, but is less commonly used there. See the documentation for function definitions and class definitions for more about decorators. descriptor ¶ Any object which defines the methods __get__() , __set__() , or __delete__() . When a class attribute is a descriptor, its special binding behavior is triggered upon attribute lookup. Normally, using a.b to get, set or delete an attribute looks up the object named b in the class dictionary for a , but if b is a descriptor, the respective descriptor method gets called. Understanding descriptors is a key to a deep understanding of Python because they are the basis for many features including functions, methods, properties, class methods, static methods, and reference to super classes. For more information about descriptors’ methods, see Implementing Descriptors or the Descriptor How To Guide . dictionary ¶ An associative array, where arbitrary keys are mapped to values. The keys can be any object with __hash__() and __eq__() methods. Called a hash in Perl. dictionary comprehension ¶ A compact way to process all or part of the elements in an iterable and return a dictionary with the results. results = {n: n ** 2 for n in range(10)} generates a dictionary containing key n mapped to value n ** 2 . See Displays for lists, sets and dictionaries . dictionary view ¶ The objects returned from dict.keys() , dict.values() , and dict.items() are called dictionary views. They provide a dynamic view on the dictionary’s entries, which means that when the dictionary changes, the view reflects these changes. To force the dictionary view to become a full list use list(dictview) . See Dictionary view objects . docstring ¶ A string literal which appears as the first expression in a class, function or module. While ignored when the suite is executed, it is recognized by the compiler and put into the __doc__ attribute of the enclosing class, function or module. Since it is available via introspection, it is the canonical place for documentation of the object. duck-typing ¶ A programming style which does not look at an object’s type to determine if it has the right interface; instead, the method or attribute is simply called or used (“If it looks like a duck and quacks like a duck, it must be a duck.”) By emphasizing interfaces rather than specific types, well-designed code improves its flexibility by allowing polymorphic substitution. Duck-typing avoids tests using type() or isinstance() . (Note, however, that duck-typing can be complemented with abstract base classes .) Instead, it typically employs hasattr() tests or EAFP programming. dunder ¶ An informal short-hand for “double underscore”, used when talking about a special method . For example, __init__ is often pronounced “dunder init”. EAFP ¶ Easier to ask for forgiveness than permission. This common Python coding style assumes the existence of valid keys or attributes and catches exceptions if the assumption proves false. This clean and fast style is characterized by the presence of many try and except statements. The technique contrasts with the LBYL style common to many other languages such as C. evaluate function ¶ A function that can be called to evaluate a lazily evaluated attribute of an object, such as the value of type aliases created with the type statement. expression ¶ A piece of syntax which can be evaluated to some value. In other words, an expression is an accumulation of expression elements like literals, names, attribute access, operators or function calls which all return a value. In contrast to many other languages, not all language constructs are expressions. There are also statement s which cannot be used as expressions, such as while . Assignments are also statements, not expressions. extension module ¶ A module written in C or C++, using Python’s C API to interact with the core and with user code. f-string ¶ f-strings ¶ String literals prefixed with f or F are commonly called “f-strings” which is short for formatted string literals . See also PEP 498 . file object ¶ An object exposing a file-oriented API (with methods such as read() or write() ) to an underlying resource. Depending on the way it was created, a file object can mediate access to a real on-disk file or to another type of storage or communication device (for example standard input/output, in-memory buffers, sockets, pipes, etc.). File objects are also called file-like objects or streams . There are actually three categories of file objects: raw binary files , buffered binary files and text files . Their interfaces are defined in the io module. The canonical way to create a file object is by using the open() function. file-like object ¶ A synonym for file object . filesystem encoding and error handler ¶ Encoding and error handler used by Python to decode bytes from the operating system and encode Unicode to the operating system. The filesystem encoding must guarantee to successfully decode all bytes below 128. If the file system encoding fails to provide this guarantee, API functions can raise UnicodeError . The sys.getfilesystemencoding() and sys.getfilesystemencodeerrors() functions can be used to get the filesystem encoding and error handler. The filesystem encoding and error handler are configured at Python startup by the PyConfig_Read() function: see filesystem_encoding and filesystem_errors members of PyConfig . See also the locale encoding . finder ¶ An object that tries to find the loader for a module that is being imported. There are two types of finder: meta path finders for use with sys.meta_path , and path entry finders for use with sys.path_hooks . See Finders and loaders and importlib for much more detail. floor division ¶ Mathematical division that rounds down to nearest integer. The floor division operator is // . For example, the expression 11 // 4 evaluates to 2 in contrast to the 2.75 returned by float true division. Note that (-11) // 4 is -3 because that is -2.75 rounded downward . See PEP 238 . free threading ¶ A threading model where multiple threads can run Python bytecode simultaneously within the same interpreter. This is in contrast to the global interpreter lock which allows only one thread to execute Python bytecode at a time. See PEP 703 . free variable ¶ Formally, as defined in the language execution model , a free variable is any variable used in a namespace which is not a local variable in that namespace. See closure variable for an example. Pragmatically, due to the name of the codeobject.co_freevars attribute, the term is also sometimes used as a synonym for closure variable . function ¶ A series of statements which returns some value to a caller. It can also be passed zero or more arguments which may be used in the execution of the body. See also parameter , method , and the Function definitions section. function annotation ¶ An annotation of a function parameter or return value. Function annotations are usually used for type hints : for example, this function is expected to take two int arguments and is also expected to have an int return value: def sum_two_numbers ( a : int , b : int ) -> int : return a + b Function annotation syntax is explained in section Function definitions . See variable annotation and PEP 484 , which describe this functionality. Also see Annotations Best Practices for best practices on working with annotations. __future__ ¶ A future statement , from __future__ import <feature> , directs the compiler to compile the current module using syntax or semantics that will become standard in a future release of Python. The __future__ module documents the possible values of feature . By importing this module and evaluating its variables, you can see when a new feature was first added to the language and when it will (or did) become the default: >>> import __future__ >>> __future__ . division _Feature((2, 2, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0), 8192) garbage collection ¶ The process of freeing memory when it is not used anymore. Python performs garbage collection via reference counting and a cyclic garbage collector that is able to detect and break reference cycles. The garbage collector can be controlled using the gc module. generator ¶ A function which returns a generator iterator . It looks like a normal function except that it contains yield expressions for producing a series of values usable in a for-loop or that can be retrieved one at a time with the next() function. Usually refers to a generator function, but may refer to a generator iterator in some contexts. In cases where the intended meaning isn’t clear, using the full terms avoids ambiguity. generator iterator ¶ An object created by a generator function. Each yield temporarily suspends processing, remembering the execution state (including local variables and pending try-statements). When the generator iterator resumes, it picks up where it left off (in contrast to functions which start fresh on every invocation). generator expression ¶ An expression that returns an iterator . It looks like a normal expression followed by a for clause defining a loop variable, range, and an optional if clause. The combined expression generates values for an enclosing function: >>> sum ( i * i for i in range ( 10 )) # sum of squares 0, 1, 4, ... 81 285 generic function ¶ A function composed of multiple functions implementing the same operation for different types. Which implementation should be used during a call is determined by the dispatch algorithm. See also the single dispatch glossary entry, the functools.singledispatch() decorator, and PEP 443 . generic type ¶ A type that can be parameterized; typically a container class such as list or dict . Used for type hints and annotations . For more details, see generic alias types , PEP 483 , PEP 484 , PEP 585 , and the typing module. GIL ¶ See global interpreter lock . global interpreter lock ¶ The mechanism used by the CPython interpreter to assure that only one thread executes Python bytecode at a time. This simplifies the CPython implementation by making the object model (including critical built-in types such as dict ) implicitly safe against concurrent access. Locking the entire interpreter makes it easier for the interpreter to be multi-threaded, at the expense of much of the parallelism afforded by multi-processor machines. However, some extension modules, either standard or third-party, are designed so as to release the GIL when doing computationally intensive tasks such as compression or hashing. Also, the GIL is always released when doing I/O. As of Python 3.13, the GIL can be disabled using the --disable-gil build configuration. After building Python with this option, code must be run with -X gil=0 or after setting the PYTHON_GIL=0 environment variable. This feature enables improved performance for multi-threaded applications and makes it easier to use multi-core CPUs efficiently. For more details, see PEP 703 . In prior versions of Python’s C API, a function might declare that it requires the GIL to be held in order to use it. This refers to having an attached thread state . global state ¶ Data that is accessible throughout a program, such as module-level variables, class variables, or C static variables in extension modules . In multi-threaded programs, global state shared between threads typically requires synchronization to avoid race conditions and data races . hash-based pyc ¶ A bytecode cache file that uses the hash rather than the last-modified time of the corresponding source file to determine its validity. See Cached bytecode invalidation . hashable ¶ An object is hashable if it has a hash value which never changes during its lifetime (it needs a __hash__() method), and can be compared to other objects (it needs an __eq__() method). Hashable objects which compare equal must have the same hash value. Hashability makes an object usable as a dictionary key and a set member, because these data structures use the hash value internally. Most of Python’s immutable built-in objects are hashable; mutable containers (such as lists or dictionaries) are not; immutable containers (such as tuples and frozensets) are only hashable if their elements are hashable. Objects which are instances of user-defined classes are hashable by default. They all compare unequal (except with themselves), and their hash value is derived from their id() . IDLE ¶ An Integrated Development and Learning Environment for Python. IDLE — Python editor and shell is a basic editor and interpreter environment which ships with the standard distribution of Python. immortal ¶ Immortal objects are a CPython implementation detail introduced in PEP 683 . If an object is immortal, its reference count is never modified, and therefore it is never deallocated while the interpreter is running. For example, True and None are immortal in CPython. Immortal objects can be identified via sys._is_immortal() , or via PyUnstable_IsImmortal() in the C API. immutable ¶ An object with a fixed value. Immutable objects include numbers, strings and tuples. Such an object cannot be altered. A new object has to be created if a different value has to be stored. They play an important role in places where a constant hash value is needed, for example as a key in a dictionary. Immutable objects are inherently thread-safe because their state cannot be modified after creation, eliminating concerns about improperly synchronized concurrent modification . import path ¶ A list of locations (or path entries ) that are searched by the path based finder for modules to import. During import, this list of locations usually comes from sys.path , but for subpackages it may also come from the parent package’s __path__ attribute. importing ¶ The process by which Python code in one module is made available to Python code in another module. importer ¶ An object that both finds and loads a module; both a finder and loader object. interactive ¶ Python has an interactive interpreter which means you can enter statements and expressions at the interpreter prompt, immediately execute them and see their results. Just launch python with no arguments (possibly by selecting it from your computer’s main menu). It is a very powerful way to test out new ideas or inspect modules and packages (remember help(x) ). For more on interactive mode, see Interactive Mode . interpreted ¶ Python is an interpreted language, as opposed to a compiled one, though the distinction can be blurry because of the presence of the bytecode compiler. This means that source files can be run directly without explicitly creating an executable which is then run. Interpreted languages typically have a shorter development/debug cycle than compiled ones, though their programs generally also run more slowly. See also interactive . interpreter shutdown ¶ When asked to shut down, the Python interpreter enters a special phase where it gradually releases all allocated resources, such as modules and various critical internal structures. It also makes several calls to the garbage collector . This can trigger the execution of code in user-defined destructors or weakref callbacks. Code executed during the shutdown phase can encounter various exceptions as the resources it relies on may not function anymore (common examples are library modules or the warnings machinery). The main reason for interpreter shutdown is that the __main__ module or the script being run has finished executing. iterable ¶ An object capable of returning its members one at a time. Examples of iterables include all sequence types (such as list , str , and tuple ) and some non-sequence types like dict , file objects , and objects of any classes you define with an __iter__() method or with a __getitem__() method that implements sequence semantics. Iterables can be used in a for loop and in many other places where a sequence is needed ( zip() , map() , …). When an iterable object is passed as an argument to the built-in function iter() , it returns an iterator for the object. This iterator is good for one pass over the set of values. When using iterables, it is usually not necessary to call iter() or deal with iterator objects yourself. The for statement does that automatically for you, creating a temporary unnamed variable to hold the iterator for the duration of the loop. See also iterator , sequence , and generator . iterator ¶ An object representing a stream of data. Repeated calls to the iterator’s __next__() method (or passing it to the built-in function next() ) return successive items in the stream. When no more data are available a StopIteration exception is raised instead. At this point, the iterator object is exhausted and any further calls to its __next__() method just raise StopIteration again. Iterators are required to have an __iter__() method that returns the iterator object itself so every iterator is also iterable and may be used in most places where other iterables are accepted. One notable exception is code which attempts multiple iteration passes. A container object (such as a list ) produces a fresh new iterator each time you pass it to the iter() function or use it in a for loop. Attempting this with an iterator will just return the same exhausted iterator object used in the previous iteration pass, making it appear like an empty container. More information can be found in Iterator Types . CPython implementation detail: CPython does not consistently apply the requirement that an iterator define __iter__() . And also please note that free-threaded CPython does not guarantee thread-safe behavior of iterator operations. key function ¶ A key function or collation function is a callable that returns a value used for sorting or ordering. For example, locale.strxfrm() is used to produce a sort key that is aware of locale specific sort conventions. A number of tools in Python accept key functions to control how elements are ordered or grouped. They include min() , max() , sorted() , list.sort() , heapq.merge() , heapq.nsmallest() , heapq.nlargest() , and itertools.groupby() . There are several ways to create a key function. For example. the str.casefold() method can serve as a key function for case insensitive sorts. Alternatively, a key function can be built from a lambda expression such as lambda r: (r[0], r[2]) . Also, operator.attrgetter() , operator.itemgetter() , and operator.methodcaller() are three key function constructors. See the Sorting HOW TO for examples of how to create and use key functions. keyword argument ¶ See argument . lambda ¶ An anonymous inline function consisting of a single expression which is evaluated when the function is called. The syntax to create a lambda function is lambda [parameters]: expression LBYL ¶ Look before you leap. This coding style explicitly tests for pre-conditions before making calls or lookups. This style contrasts with the EAFP approach and is characterized by the presence of many if statements. In a multi-threaded environment, the LBYL approach can risk introducing a race condition between “the looking” and “the leaping”. For example, the code, if key in mapping: return mapping[key] can fail if another thread removes key from mapping after the test, but before the lookup. This issue can be solved with locks or by using the EAFP approach. See also thread-safe . lexical analyzer ¶ Formal name for the tokenizer ; see token . list ¶ A built-in Python sequence . Despite its name it is more akin to an array in other languages than to a linked list since access to elements is O (1). list comprehension ¶ A compact way to process all or part of the elements in a sequence and return a list with the results. result = ['{:#04x}'.format(x) for x in range(256) if x % 2 == 0] generates a list of strings containing even hex numbers (0x..) in the range from 0 to 255. The if clause is optional. If omitted, all elements in range(256) are processed. lock ¶ A synchronization primitive that allows only one thread at a time to access a shared resource. A thread must acquire a lock before accessing the protected resource and release it afterward. If a thread attempts to acquire a lock that is already held by another thread, it will block until the lock becomes available. Python’s threading module provides Lock (a basic lock) and RLock (a reentrant lock). Locks are used to prevent race conditions and ensure thread-safe access to shared data. Alternative design patterns to locks exist such as queues, producer/consumer patterns, and thread-local state. See also deadlock , and reentrant . loader ¶ An object that loads a module. It must define the exec_module() and create_module() methods to implement the Loader interface. A loader is typically returned by a finder . See also: Finders and loaders importlib.abc.Loader PEP 302 locale encoding ¶ On Unix, it is the encoding of the LC_CTYPE locale. It can be set with locale.setlocale(locale.LC_CTYPE, new_locale) . On Windows, it is the ANSI code page (ex: "cp1252" ). On Android and VxWorks, Python uses "utf-8" as the locale encoding. locale.getencoding() can be used to get the locale encoding. See also the filesystem encoding and error handler . magic method ¶ An informal synonym for special method . mapping ¶ A container object that supports arbitrary key lookups and implements the methods specified in the collections.abc.Mapping or collections.abc.MutableMapping abstract base classes . Examples include dict , collections.defaultdict , collections.OrderedDict and collections.Counter . meta path finder ¶ A finder returned by a search of sys.meta_path . Meta path finders are related to, but different from path entry finders . See importlib.abc.MetaPathFinder for the methods that meta path finders implement. metaclass ¶ The class of a class. Class definitions create a class name, a class dictionary, and a list of base classes. The metaclass is responsible for taking those three arguments and creating the class. Most object oriented programming languages provide a default implementation. What makes Python special is that it is possible to create custom metaclasses. Most users never need this tool, but when the need arises, metaclasses can provide powerful, elegant solutions. They have been used for logging attribute access, adding thread-safety, tracking object creation, implementing singletons, and many other tasks. More information can be found in Metaclasses . method ¶ A function which is defined inside a class body. If called as an attribute of an instance of that class, the method will get the instance object as its first argument (which is usually called self ). See function and nested scope . method resolution order ¶ Method Resolution Order is the order in which base classes are searched for a member during lookup. See The Python 2.3 Method Resolution Order for details of the algorithm used by the Python interpreter since the 2.3 release. module ¶ An object that serves as an organizational unit of Python code. Modules have a namespace containing arbitrary Python objects. Modules are loaded into Python by the process of importing . See also package . module spec ¶ A namespace containing the import-related information used to load a module. An instance of importlib.machinery.ModuleSpec . See also Module specs . MRO ¶ See method resolution order . mutable ¶ An object with state that is allowed to change during the course of the program. In multi-threaded programs, mutable objects that are shared between threads require careful synchronization to avoid race conditions . See also immutable , thread-safe , and concurrent modification . named tuple ¶ The term “named tuple” applies to any type or class that inherits from tuple and whose indexable elements are also accessible using named attributes. The type or class may have other features as well. Several built-in types are named tuples, including the values returned by time.localtime() and os.stat() . Another example is sys.float_info : >>> sys . float_info [ 1 ] # indexed access 1024 >>> sys . float_info . max_exp # named field access 1024 >>> isinstance ( sys . float_info , tuple ) # kind of tuple True Some named tuples are built-in types (such as the above examples). Alternatively, a named tuple can be created from a regular class definition that inherits from tuple and that defines named fields. Such a class can be written by hand, or it can be created by inheriting typing.NamedTuple , or with the factory function collections.namedtuple() . The latter techniques also add some extra methods that may not be found in hand-written or built-in named tuples. namespace ¶ The place where a variable is stored. Namespaces are implemented as dictionaries. There are the local, global and built-in namespaces as well as nested namespaces in objects (in methods). Namespaces support modularity by preventing naming conflicts. For instance, the functions builtins.open and os.open() are distinguished by their namespaces. Namespaces also aid readability and maintainability by making it clear which module implements a function. For instance, writing random.seed() or itertools.islice() makes it clear that those functions are implemented by the random and itertools modules, respectively. namespace package ¶ A package which serves only as a container for subpackages. Namespace packages may have no physical representation, and specifically are not like a regular package because they have no __init__.py file. Namespace packages allow several individually installable packages to have a common parent package. Otherwise, it is recommended to use a regular package . For more information, see PEP 420 and Namespace packages . See also module . native code ¶ Code that is compiled to machine instructions and runs directly on the processor, as opposed to code that is interpreted or runs in a virtual machine. In the context of Python, native code typically refers to C, C++, Rust or Fortran code in extension modules that can be called from Python. See also extension module . nested scope ¶ The ability to refer to a variable in an enclosing definition. For instance, a function defined inside another function can refer to variables in the outer function. Note that nested scopes by default work only for reference and not for assignment. Local variables both read and write in the innermost scope. Likewise, global variables read and write to the global namespace. The nonlocal allows writing to outer scopes. new-style class ¶ Old name for the flavor of classes now used for all class objects. In earlier Python versions, only new-style classes could use Python’s newer, versatile features like __slots__ , descriptors, properties, __getattribute__() , class methods, and static methods. non-deterministic ¶ Behavior where the outcome of a program can vary between executions with the same inputs. In multi-threaded programs, non-deterministic behavior often results from race conditions where the relative timing or interleaving of threads affects the result. Proper synchronization using locks and other synchronization primitives helps ensure deterministic behavior. object ¶ Any data with state (attributes or value) and defined behavior (methods). Also the ultimate base class of any new-style class . optimized scope ¶ A scope where target local variable names are reliably known to the compiler when the code is compiled, allowing optimization of read and write access to these names. The local namespaces for functions, generators, coroutines, comprehensions, and generator expressions are optimized in this fashion. Note: most interpreter optimizations are applied to all scopes, only those relying on a known set of local and nonlocal variable names are restricted to optimized scopes. optional module ¶ An extension module that is part of the standard library , but may be absent in some builds of CPython , usually due to missing third-party libraries or because the module is not available for a given platform. See Requirements for optional modules for a list of optional modules that require third-party libraries. package ¶ A Python module which can contain submodules or recursively, subpackages. Technically, a package is a Python module with a __path__ attribute. See also regular package and namespace package . parallelism ¶ Executing multiple operations at the same time (e.g. on multiple CPU cores). In Python builds with the global interpreter lock (GIL) , only one thread runs Python bytecode at a time, so taking advantage of multiple CPU cores typically involves multiple processes (e.g. multiprocessing ) or native extensions that release the GIL. In free-threaded Python, multiple Python threads can run Python code simultaneously on different cores. parameter ¶ A named entity in a function (or method) definition that specifies an argument (or in some cases, arguments) that the function can accept. There are five kinds of parameter: positional-or-keyword : specifies an argument that can be passed either positionally or as a keyword argument . This is the default kind of parameter, for example foo and bar in the following: def func ( foo , bar = None ): ... positional-only : specifies an argument that can be supplied only by position. Positional-only parameters can be defined by including a / character in the parameter list of the function definition after them, for example posonly1 and posonly2 in the following: def func ( posonly1 , posonly2 , / , positional_or_keyword ): ... keyword-only : specifies an argument that can be supplied only by keyword. Keyword-only parameters can be defined by including a single var-positional parameter or bare * in the parameter list of the function definition before them, for example kw_only1 and kw_only2 in the following: def func ( arg , * , kw_only1 , kw_only2 ): ... var-positional : specifies that an arbitrary sequence of positional arguments can be provided (in addition to any positional arguments already accepted by other parameters). Such a parameter can be defined by prepending the parameter name with * , for example args in the following: def func ( * args , ** kwargs ): ... var-keyword : specifies that arbitrarily many keyword arguments can be provided (in addition to any keyword arguments already accepted by other parameters). Such a parameter can be defined by prepending the parameter name with ** , for example kwargs in the example above. Parameters can specify both optional and required arguments, as well as default values for some optional arguments. See also the argument glossary entry, the FAQ question on the difference between arguments and parameters , the inspect.Parameter class, the Function definitions section, and PEP 362 . path entry ¶ A single location on the import path which the path based finder consults to find modules for importing. path entry finder ¶ A finder returned by a callable on sys.path_hooks (i.e. a path entry hook ) which knows how to locate modules given a path entry . See importlib.abc.PathEntryFinder for the methods that path entry finders implement. path entry hook ¶ A callable on the sys.path_hooks list which returns a path entry finder if it knows how to find modules on a specific path entry . path based finder ¶ One of the default meta path finders which searches an import path for modules. path-like object ¶ An object representing a file system path. A path-like object is either a str or bytes object representing a path, or an object implementing the os.PathLike protocol. An object that supports the os.PathLike protocol can be converted to a str or bytes file system path by calling the os.fspath() function; os.fsdecode() and os.fsencode() can be used to guarantee a str or bytes result instead, respectively. Introduced by PEP 519 . PEP ¶ Python Enhancement Proposal. A PEP is a design document providing information to the Python community, or describing a new feature for Python or its processes or environment. PEPs should provide a concise technical specification and a rationale for proposed features. PEPs are intended to be the primary mechanisms for proposing major new features, for collecting community input on an issue, and for documenting the design decisions that have gone into Python. The PEP author is responsible for building consensus within the community and documenting dissenting opinions. See PEP 1 . portion ¶ A set of files in a single directory (possibly stored in a zip file) that contribute to a namespace package, as defined in PEP 420 . positional argument ¶ See argument . provisional API ¶ A provisional API is one which has been deliberately excluded from the standard library’s backwards compatibility guarantees. While major changes to such interfaces are not expected, as long as they are marked provisional, backwards incompatible changes (up to and including removal of the interface) may occur if deemed necessary by core developers. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close # iot Follow Hide Security challenges and solutions for Internet of Things and embedded devices. Create Post Older #iot posts 4 5 6 7 8 9 10 11 12 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu IoT Security in the 5G Era: How Connected Devices Became the New Attack Surface Sagar Sajwan Sagar Sajwan Sagar Sajwan Follow Nov 14 '25 IoT Security in the 5G Era: How Connected Devices Became the New Attack Surface # iot # cybersecurity 5 reactions Comments Add Comment 7 min read From APIs to Aquifers: A Developer's Guide to Smart Water Management Data Rachel Duncan Rachel Duncan Rachel Duncan Follow Oct 11 '25 From APIs to Aquifers: A Developer's Guide to Smart Water Management Data # bigdata # iot # dataengineering Comments Add Comment 7 min read Inside the Edge: How Real-Time Data Pipelines Power Connected Devices Abdul Shamim Abdul Shamim Abdul Shamim Follow Nov 13 '25 Inside the Edge: How Real-Time Data Pipelines Power Connected Devices # dataengineering # iot # architecture # performance 1 reaction Comments Add Comment 3 min read How Fingerprints Identify You: The Algorithm Beneath the Biometric Rithika S Rithika S Rithika S Follow for Indian Society for Technical Education - VIT Oct 23 '25 How Fingerprints Identify You: The Algorithm Beneath the Biometric # computerscience # programming # iot Comments Add Comment 8 min read Creating and Restoring Disk Images on macOS: A Guide to Using dd and diskutil Maxim Radugin Maxim Radugin Maxim Radugin Follow Oct 9 '25 Creating and Restoring Disk Images on macOS: A Guide to Using dd and diskutil # backup # osx # raspberrypi # iot Comments Add Comment 10 min read Build Your Own WiFi-Controlled Drone with ESP32 (Beginner-Friendly) David Thomas David Thomas David Thomas Follow Nov 13 '25 Build Your Own WiFi-Controlled Drone with ESP32 (Beginner-Friendly) # robotics # iot # tutorial # beginners Comments Add Comment 3 min read TFT LCD vs OLED: Why TFT Still Matters in 2025 Lynn Lynn Lynn Follow Oct 11 '25 TFT LCD vs OLED: Why TFT Still Matters in 2025 # design # iot # ui Comments Add Comment 2 min read 🚀 From MicroPython to the Moon: Building Space-Efficient IoT Devices like a Pro Yevhen Kozachenko 🇺🇦 Yevhen Kozachenko 🇺🇦 Yevhen Kozachenko 🇺🇦 Follow Oct 8 '25 🚀 From MicroPython to the Moon: Building Space-Efficient IoT Devices like a Pro # micropython # iot # embedded # python 1 reaction Comments Add Comment 4 min read IoT Platform Update: New Features and Enhancements Pavol Pavol Pavol Follow Oct 8 '25 IoT Platform Update: New Features and Enhancements # iot # totaljs # sensor # industry40 Comments Add Comment 4 min read Configuring TLS in the Mosquitto MQTT broker sheng chen sheng chen sheng chen Follow Oct 8 '25 Configuring TLS in the Mosquitto MQTT broker # iot # networking # security Comments Add Comment 4 min read Qualcomm acquires Arduino to accelerate developer access to AI solutions Saiki Sarkar Saiki Sarkar Saiki Sarkar Follow Oct 9 '25 Qualcomm acquires Arduino to accelerate developer access to AI solutions # news # ai # opensource # iot Comments Add Comment 2 min read CanKit early preview: capability discovery, a ready-to-run CAN demo Pkuyo Pkuyo Pkuyo Follow Oct 21 '25 CanKit early preview: capability discovery, a ready-to-run CAN demo # showdev # csharp # dotnet # iot 2 reactions Comments Add Comment 2 min read One Country, Two Internets: How Edge Computing Solves Brazil's Connectivity Crisis Yevheniia Mala Yevheniia Mala Yevheniia Mala Follow Nov 11 '25 One Country, Two Internets: How Edge Computing Solves Brazil's Connectivity Crisis # iot # opensource # braziliandevs Comments Add Comment 4 min read How to Build Data Pipelines for Large-Scale BIM and IoT Datasets? Reetie Lubana Reetie Lubana Reetie Lubana Follow Oct 7 '25 How to Build Data Pipelines for Large-Scale BIM and IoT Datasets? # iot # architecture # datastructures # ai Comments Add Comment 4 min read Flood Alert: How Sparse Sensing and AI are Saving Cities by Arvind Sundararajan Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Nov 8 '25 Flood Alert: How Sparse Sensing and AI are Saving Cities by Arvind Sundararajan # datascience # iot # smartcities # engineering Comments Add Comment 2 min read The $4 Sensor That Caught What a $60,000 System Missed Vishwa anuj Vishwa anuj Vishwa anuj Follow Oct 27 '25 The $4 Sensor That Caught What a $60,000 System Missed # iot # esp32 # ai 1 reaction Comments Add Comment 10 min read Starting With Luckfox Lyra Zero W Daniel Guerrero Daniel Guerrero Daniel Guerrero Follow Oct 4 '25 Starting With Luckfox Lyra Zero W # tutorial # cli # linux # iot Comments Add Comment 2 min read How I Built a Reminder System for Senior Care Centers Using Raspberry Pi and RFID Bragadheshwaran KK Bragadheshwaran KK Bragadheshwaran KK Follow Oct 5 '25 How I Built a Reminder System for Senior Care Centers Using Raspberry Pi and RFID # showdev # design # iot Comments 1 comment 2 min read 9 reasons why Edge AI development is so hard Elina Norling Elina Norling Elina Norling Follow for Embedl Hub Oct 27 '25 9 reasons why Edge AI development is so hard # ai # embedded # machinelearning # iot 6 reactions Comments Add Comment 6 min read Decoding the Deluge: Sparse Sensing for Smarter Stormwater Management by Arvind Sundararajan Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Nov 7 '25 Decoding the Deluge: Sparse Sensing for Smarter Stormwater Management by Arvind Sundararajan # datascience # engineering # ai # iot Comments Add Comment 2 min read Decoding City Storms: How Sparse Sensing Can Prevent Urban Floods by Arvind Sundararajan Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Nov 7 '25 Decoding City Storms: How Sparse Sensing Can Prevent Urban Floods by Arvind Sundararajan # datascience # iot # python # engineering Comments Add Comment 2 min read Smart Security Camera Sumit Shingole (BTech CSE 2025-29) Sumit Shingole (BTech CSE 2025-29) Sumit Shingole (BTech CSE 2025-29) Follow Oct 4 '25 Smart Security Camera # systemdesign # cloudcomputing # security # iot Comments Add Comment 2 min read Best Internet Options for Rural Communities & Country Homes Sidra Jefferi Sidra Jefferi Sidra Jefferi Follow Nov 6 '25 Best Internet Options for Rural Communities & Country Homes # discuss # beginners # learning # iot 1 reaction Comments Add Comment 5 min read Quantum-Powered Privacy: Securing the IoT with Decentralized Anomaly Detection Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Nov 5 '25 Quantum-Powered Privacy: Securing the IoT with Decentralized Anomaly Detection # machinelearning # iot # security # quantumcomputing Comments Add Comment 2 min read AI Has Gone Physical: Can We Still Keep It Safe? Abdelghani Alhijawi Abdelghani Alhijawi Abdelghani Alhijawi Follow Oct 24 '25 AI Has Gone Physical: Can We Still Keep It Safe? # ai # cybersecurity # robotics # iot Comments Add Comment 5 min read loading... 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . DEV Community © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. 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Right menu VPS Hosting for Trading Bots: Server Setup & Infrastructure Guide Aman Vaths Aman Vaths Aman Vaths Follow Jan 12 VPS Hosting for Trading Bots: Server Setup & Infrastructure Guide # forex # cryptocurrency # bot # trading Comments Add Comment 6 min read AI Trading: Lesson Learned #134: RAG Architecture Misunderstanding - Wrong Fix Applied Igor Ganapolsky Igor Ganapolsky Igor Ganapolsky Follow Jan 11 AI Trading: Lesson Learned #134: RAG Architecture Misunderstanding - Wrong Fix Applied # ai # trading # python # machinelearning Comments Add Comment 2 min read AI Trading: Lesson Learned #133: LYING - Claimed Fix Without Verification Igor Ganapolsky Igor Ganapolsky Igor Ganapolsky Follow Jan 11 AI Trading: Lesson Learned #133: LYING - Claimed Fix Without Verification # ai # trading # python # machinelearning Comments Add Comment 1 min read AI Trading: Lesson Learned #131: Self-Healing Gap - Blog Lesson Sync Igor Ganapolsky Igor Ganapolsky Igor Ganapolsky Follow Jan 11 AI Trading: Lesson Learned #131: Self-Healing Gap - 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CEO Questions Answered (Jan 9, 2026) Igor Ganapolsky Igor Ganapolsky Igor Ganapolsky Follow Jan 9 AI Trading: Lesson Learned #127: Comprehensive Trust Audit - CEO Questions Answered (Jan 9, 2026) # ai # trading # python # machinelearning Comments Add Comment 2 min read AI Trading: Lesson Learned #123: Trust Rebuild Audit - Comprehensive Evidence-Based Review Igor Ganapolsky Igor Ganapolsky Igor Ganapolsky Follow Jan 9 AI Trading: Lesson Learned #123: Trust Rebuild Audit - Comprehensive Evidence-Based Review # ai # trading # python # machinelearning Comments Add Comment 2 min read AI Trading: Lesson Learned #124: Secret Exposure Incident - Jan 9, 2026 Igor Ganapolsky Igor Ganapolsky Igor Ganapolsky Follow Jan 9 AI Trading: Lesson Learned #124: Secret Exposure Incident - Jan 9, 2026 # ai # trading # python # machinelearning Comments Add Comment 2 min read AI Trading: Lesson Learned #122: CEO Trust Audit - Comprehensive Strategy Review (Jan 9, 2026) Igor Ganapolsky Igor Ganapolsky Igor Ganapolsky Follow Jan 9 AI Trading: Lesson Learned #122: CEO Trust Audit - 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Trust Crisis (Jan 9, 2026) Igor Ganapolsky Igor Ganapolsky Igor Ganapolsky Follow Jan 9 AI Trading: Lesson Learned #120: Paper Trading Broken - Trust Crisis (Jan 9, 2026) # ai # trading # python # machinelearning Comments Add Comment 2 min read loading... trending guides/resources Building an SPA, Real-Time Trading Platform with Vanilla PHP & JavaScript Trading in the Age of Developers Complete Guide to CFD Trading: What Are CFDs & How to Automate Trading with Python (2025) AI Trading Daily Report: December 22, 2025 | $+268.86 AI Trading: Lesson Learned #121: Investment Strategy Audit - Honest Assessment (Jan 9, 2026) AI Trading: Lesson Learned #093: Google Recommender CAV Not Useful for Trading AI Trading: Lesson Learned #094: Daily Trading Workflow Not Triggering (Jan 7, 2026) AI Trading: LL-124: Phil Town CSP Strategy Not Executing Trades AI Trading: Lesson Learned #129: Backtest Evaluation Bugs Discovered via Deep Research AI Trading: Lesson Learned #093: Automation Metadata Stale - No Trades Executed Jan 7 AI Trading: Lesson Learned #108: Strategy Verification Session (Jan 7, 2026) My Backtest Was Too Good — Here’s How I Caught the Lie Build a Dogecoin Sentiment-Driven Trading Signal CLI with Remix AI Trading Daily Report: January 02, 2026 | $+100.11 AI Trading: Lesson Learned #125: Comprehensive Trust Audit (Jan 9, 2026) AI Trading: Lesson Learned #110: Trailing Stops Script Existed But Never Executed AI Trading: Lesson Learned #120: Paper Trading Broken - Trust Crisis (Jan 9, 2026) AI Trading: Lesson Learned #127: LangSmith Removal - Dead Code Cleanup AI Trading: Lesson Learned #123: Trust Rebuild Audit - Comprehensive Evidence-Based Review AI Trading: Lesson Learned #095: Daily Trading Workflow Failure (Jan 7, 2026) 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV Forem — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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https://www.highlight.io/docs/general/company/open-source/contributing/end-to-end-sdk-examples | End to End SDK Example Apps Star us on GitHub Star Docs Sign in Sign up General Docs Welcome to highlight.io Get Started Roadmap Company Values Compliance & Security Open Source Contributing Overview GraphQL Backend Frontend (app.highlight.io) Landing Site (highlight.io) Documentation End to End SDK Example Apps Adding an SDK Application Architecture GitHub Code Spaces Code Style Good First Issues Self-hosting Self-hosted [Dev] Self-hosted [Hobby] Self-hosted [Enterprise] Telemetry Our Competitors Product Philosophy Product Features Session Replay Overview Canvas & Iframe Dev-tool Window Recording Tracking Users & Recording Events Filtering Sessions GraphQL Live Mode Performance Impact Player Session Caching Rage Clicks Request Proxying Session Search Extracting the Session URL Session Search Deep Linking Shadow Dom + Web Components Error Monitoring Overview Enhancing Errors with GitHub Error Search Filtering Errors Grouping Errors Managing Errors Manually Reporting Errors Sourcemaps General Features Overview Alerts Comments Digests Environments Search Segments Services Webhooks Logging Overview Log Alerts Log Search Tracing Overview Trace Search Dashboards Overview Dashboard Management Metrics Tutorials Service Latency Web Vitals & Page Speed User Engagement User Analytics Graphing Drilldown Event Search Dashboard Variables SQL Editor Metrics (beta) Overview Frequently Asked Questions. Integrations Integrations Overview Amplitude Integration ClickUp Integration Discord Integration Electron Support Front Integration GitHub Integration Grafana Integration Overview Setup Dashboards Alerts Height Integration Intercom Integration Jira Integration LaunchDarkly Integration Linear Integration Mixpanel Integration Nuxt Integration Pendo Integration Segment Integration Slack Integration Vercel Integration WordPress Plugin Highlight.io Changelog Overview Changelog 12 (02/17) Changelog 13 (02/24) Changelog 14 (03/03) Changelog 15 (03/11) Changelog 16 (03/19) Changelog 17 (04/07) Changelog 18 (04/26) Changelog 19 (05/22) Changelog 20 (06/06) Changelog 21 (06/21) Changelog 22 (08/07) Changelog 23 (08/22) Changelog 24 (09/11) Changelog 25 (10/03) Changelog 26 (11/08) Changelog 27 (12/22) Changelog 28 (3/6) Changelog 29 (4/2) Menu Highlight Docs Welcome to highlight.io Get Started Roadmap Company Values Compliance & Security Open Source Contributing Overview GraphQL Backend Frontend (app.highlight.io) Landing Site (highlight.io) Documentation End to End SDK Example Apps Adding an SDK Application Architecture GitHub Code Spaces Code Style Good First Issues Self-hosting Self-hosted [Dev] Self-hosted [Hobby] Self-hosted [Enterprise] Telemetry Our Competitors Product Philosophy Product Features Session Replay Overview Canvas & Iframe Dev-tool Window Recording Tracking Users & Recording Events Filtering Sessions GraphQL Live Mode Performance Impact Player Session Caching Rage Clicks Request Proxying Session Search Extracting the Session URL Session Search Deep Linking Shadow Dom + Web Components Error Monitoring Overview Enhancing Errors with GitHub Error Search Filtering Errors Grouping Errors Managing Errors Manually Reporting Errors Sourcemaps General Features Overview Alerts Comments Digests Environments Search Segments Services Webhooks Logging Overview Log Alerts Log Search Tracing Overview Trace Search Dashboards Overview Dashboard Management Metrics Tutorials Service Latency Web Vitals & Page Speed User Engagement User Analytics Graphing Drilldown Event Search Dashboard Variables SQL Editor Metrics (beta) Overview Frequently Asked Questions. Integrations Integrations Overview Amplitude Integration ClickUp Integration Discord Integration Electron Support Front Integration GitHub Integration Grafana Integration Overview Setup Dashboards Alerts Height Integration Intercom Integration Jira Integration LaunchDarkly Integration Linear Integration Mixpanel Integration Nuxt Integration Pendo Integration Segment Integration Slack Integration Vercel Integration WordPress Plugin Highlight.io Changelog Overview Changelog 12 (02/17) Changelog 13 (02/24) Changelog 14 (03/03) Changelog 15 (03/11) Changelog 16 (03/19) Changelog 17 (04/07) Changelog 18 (04/26) Changelog 19 (05/22) Changelog 20 (06/06) Changelog 21 (06/21) Changelog 22 (08/07) Changelog 23 (08/22) Changelog 24 (09/11) Changelog 25 (10/03) Changelog 26 (11/08) Changelog 27 (12/22) Changelog 28 (3/6) Changelog 29 (4/2) Getting Started Getting Started with Highlight Fullstack Mapping Browser React.js Next.js Remix Vue.js Angular Gatsby.js SvelteKit Electron highlight.run SDK Overview Canvas & WebGL Console Messages Content-Security-Policy Identifying Users iframe Recording Monkey Patches Browser OpenTelemetry Persistent Asset Storage Privacy Proxying Highlight React.js Error Boundary Recording Network Requests and Responses Recording WebSocket Events Salesforce Lightning Web Components (LWC) Data Export Sourcemap Configuration Tracking Events Troubleshooting Upgrading Highlight Versioning Sessions & Errors Other React Native (beta) Server Go Overview chi Echo Fiber Gin GORM gqlgen Logrus Manual Tracing gorilla mux JS Overview Apollo AWS Lambda Cloudflare Workers Express.js Firebase Hono Nest.js Next.js Node.js Pino tRPC Winston Python Overview AWS Lambda Azure Functions Django FastAPI Flask Google Cloud Functions Loguru Other Frameworks Python AI / LLM Libraries Python Libraries Ruby Overview Other Frameworks Ruby on Rails Rust Overview actix-web No Framework Hosting Providers Overview Metrics in AWS Logging in AWS Logging in Azure Fly.io NATS Log Shipper Logging in GCP Heroku Log Drain Render Log Stream Logging in Trigger.dev Vercel Log Drain Elixir Overview Elixir App Java: All Frameworks PHP: All Frameworks C# .NET ASP C# .NET 4 ASP Docker / Docker Compose File Fluent Forward curl OpenTelemetry Protocol (OTLP) Syslog RFC5424 Systemd / Journald Native OpenTelemetry Overview Error Monitoring Logging Tracing Browser Instrumentation Metrics Fullstack Frameworks Overview Next.js Fullstack Overview Next.js Page Router Guide Next.js App Router Guide Edge Runtime Advanced Config Remix Walkthrough Self Host & Local Dev Overview Development deployment guide. Integrations Microsoft Teams self-hosted Hobby deployment guide. Traefik SSL Proxying. Docs Home SDK Client SDK API Reference Cloudflare Worker SDK API Reference Go SDK API Reference Hono SDK API Reference Java SDK API Reference Next.JS SDK API Reference Node.JS SDK API Reference Python SDK API Reference Ruby SDK API Reference Rust SDK API Reference Docs / Highlight Docs / Company / Open Source / Contributing / End to End SDK Example Apps End to End SDK Example Apps End-to-end SDK Tests The highlight repository E2E directory contains supported frameworks integrated with our SDKs for local development and testing. They are meant as examples configured for local development and will need to be updated before use in production. Running E2E Apps via docker compose The E2E example apps are meant for highlight development and to validate the SDKs are correctly capturing and reporting data to highlight. By default, the apps point data to a local highlight instance running on localhost . This can be configured by setting the XXX environment variable. The recommended way to run example apps manually is via the compose.yml file. The app_runner.py provides an interface to automating the build and startup for automation (CI). Using the compose.yml file # from the root of the highlight repository cd e2e docker compose build sdk docker compose build base docker compose build <example> docker compose up <example> # to run all examples docker compose up Using the automated app_runner.py Using the app_runner.py requires installing Python LTS and Poetry. # from the root of the highlight repository cd e2e/tests poetry install # view the help menu poetry run python src/app_runner.py --help # run the example app, making requests to the app to validate that it is healthy poetry run python src/app_runner.py <example> Documentation Adding an SDK Community / Support Suggest Edits? Follow us! [object Object] | 2026-01-13T08:48:58 |
https://stackblitz.com/design-systems | StackBlitz | Design Systems | Instant Dev Environments | Click. Code. Done. StackBlitz Toggle Menu Bolt.new WebContainers Careers Design Systems Get more out of your design systems with StackBlitz Get more out of your design systems with StackBlitz Get more out of your design systems with StackBlitz Improve developer experience, drive design system adoption, and remove the barriers to contribution with StackBlitz. Get in touch Trusted by enterprise design systems teams Your design system makes web development more efficient and consistent. StackBlitz makes design systems easier to evangelize, maintain, and evolve. Evangelize Live, interactive documentation Provide one-click instant environments your team can use to check out and try internal libraries. Embed directly or use StackBlitz’s SDK. StackBlitz syncs directly with your private NPM registry including JFrog Artifactory, Sonatype Nexus, and more. Maintain One-click bug reproductions Eliminate time-consuming bug reproductions by asking for a StackBlitz repro link in each ticket. Complete environments can be shared with just a URL, completely removing local installations when fixing bugs. Maintain Enable everyone to contribute to your documentation With StackBlitz, you can build and update statically-generated sites without a dev server. Encourage anyone on the team to update your blog, documentation, and more with our browser-based markdown editor, Web Publisher . Evolve Iterate on new ideas fast When inspiration strikes, StackBlitz helps you turn your ideas into code instantly. With pre-built starter projects and no local setup needed, you can have a working, shareable prototype in minutes. # Exploring the Mysteries of Quantum Computing ## Introduction Quantum computing is a topic that has fascinated scientists and enthusiasts alike for decades. In this article, we will delve into the world of quantum mechanics and explore how it is revolutionizing the field of computing. ## Understanding Quantum Mechanics To understand quantum computing, it's essential to grasp the basics of quantum mechanics. At the heart of quantum mechanics lies the concept of superposition, where a quantum system can e xist in multiple states simultaneously. 01 02 03 04 04 Seamlessly integrated from design to development StackBlitz integrates directly with the tools you use everyday. We fit into your flow so you can stay in yours. Open components in StackBlitz directly from Figma Dev Mode View stories Storybook in StackBlitz. Suggest changes and open a pull request without leaving your browser. Create branches, commit changes, and open and review pull requests with zero local configuration. Easily import your go-to VS Code themes, plugins, and keybindings to StackBlitz See all integrations Do more with less Make the most of your design system StackBlitz helps you stay on top of feature requests and bug reports so you can focus on building a design system your developers will love. Case Study How Google increased platform adoption & innovation with StackBlitz Case Study Scaling design systems & ensuring UI consistency at Surescripts Blog 5 lessons design systems teams can learn from open-source maintainers Webinar Improving the developer experience of enterprise design systems How StackBlitz works StackBlitz is the only truly browser-based development environment that eliminates time-consuming local configuration. Boot a fresh environment in miliseconds Every StackBlitz project is it’s own secure, instant Node development environment running entirely in your browser tab. Develop faster and more securely than local If it runs on Node, it can run in StackBlitz. Learn more about our WebContainers runtime. Work offline or with limited connectivity Unlike web IDEs that rely on a remote server, StackBlitz uses a compute power of your browser meaning you can code anywere. Stephen Fluin Developer Relations Lead ”For frameworks & design systems to succeed, they have to be incredibly easy to adopt. Setting up local environments is one of the biggest barriers.” Deploy how and where you want From bare metal to your VPC, StackBlitz Enterprise lets you deploy StackBlitz with a single, self-hosted Kubernetes instance , regardless of how many users you add. Enterprise SSO Integrate with any SAML2-based authentication provider Desktop-grade editor Use StackBlitz with the VS Code extensions and settings you’re used to Fully integrated with your development toolchain Access your private NPM packages from the Artifactory or Nexus registry. Review code stored in GitHub Enterprise, GitLab and Bitbucket Integrate with Figma and Storybook Improve the developer experience of working with design teams and systems Access and usage controls Manage access and maintain oversight into usage with your dedicated admin portal WebContainers built in Run any Node-based toolchain entirely within the browser with our proprietary WebContainers runtime. Unlock the unrealized potential of your design system Meet with our team to learn more about StackBlitz Enterprise including pricing information, installation requirements, and a live demo. Schedule a demo Products Enterprise Server Integrations Design Systems WebContainer API Web Publisher Platform Case Studies Pricing Privacy Terms of Service Support Community Docs Enterprise Sales Company Blog Careers Terms of Service Privacy Policy StackBlitz Codeflow and the Infinite Pull Request logo are trademarks of StackBlitz, Inc. © 2025 StackBlitz, Inc. | 2026-01-13T08:48:58 |
https://www.highlight.io/docs/general/product-features/dashboards/event-search | Event Search Star us on GitHub Star Docs Sign in Sign up General Docs Welcome to highlight.io Get Started Roadmap Company Values Compliance & Security Open Source Contributing Overview GraphQL Backend Frontend (app.highlight.io) Landing Site (highlight.io) Documentation End to End SDK Example Apps Adding an SDK Application Architecture GitHub Code Spaces Code Style Good First Issues Self-hosting Self-hosted [Dev] Self-hosted [Hobby] Self-hosted [Enterprise] Telemetry Our Competitors Product Philosophy Product Features Session Replay Overview Canvas & Iframe Dev-tool Window Recording Tracking Users & Recording Events Filtering Sessions GraphQL Live Mode Performance Impact Player Session Caching Rage Clicks Request Proxying Session Search Extracting the Session URL Session Search Deep Linking Shadow Dom + Web Components Error Monitoring Overview Enhancing Errors with GitHub Error Search Filtering Errors Grouping Errors Managing Errors Manually Reporting Errors Sourcemaps General Features Overview Alerts Comments Digests Environments Search Segments Services Webhooks Logging Overview Log Alerts Log Search Tracing Overview Trace Search Dashboards Overview Dashboard Management Metrics Tutorials Service Latency Web Vitals & Page Speed User Engagement User Analytics Graphing Drilldown Event Search Dashboard Variables SQL Editor Metrics (beta) Overview Frequently Asked Questions. Integrations Integrations Overview Amplitude Integration ClickUp Integration Discord Integration Electron Support Front Integration GitHub Integration Grafana Integration Overview Setup Dashboards Alerts Height Integration Intercom Integration Jira Integration LaunchDarkly Integration Linear Integration Mixpanel Integration Nuxt Integration Pendo Integration Segment Integration Slack Integration Vercel Integration WordPress Plugin Highlight.io Changelog Overview Changelog 12 (02/17) Changelog 13 (02/24) Changelog 14 (03/03) Changelog 15 (03/11) Changelog 16 (03/19) Changelog 17 (04/07) Changelog 18 (04/26) Changelog 19 (05/22) Changelog 20 (06/06) Changelog 21 (06/21) Changelog 22 (08/07) Changelog 23 (08/22) Changelog 24 (09/11) Changelog 25 (10/03) Changelog 26 (11/08) Changelog 27 (12/22) Changelog 28 (3/6) Changelog 29 (4/2) Menu Highlight Docs Welcome to highlight.io Get Started Roadmap Company Values Compliance & Security Open Source Contributing Overview GraphQL Backend Frontend (app.highlight.io) Landing Site (highlight.io) Documentation End to End SDK Example Apps Adding an SDK Application Architecture GitHub Code Spaces Code Style Good First Issues Self-hosting Self-hosted [Dev] Self-hosted [Hobby] Self-hosted [Enterprise] Telemetry Our Competitors Product Philosophy Product Features Session Replay Overview Canvas & Iframe Dev-tool Window Recording Tracking Users & Recording Events Filtering Sessions GraphQL Live Mode Performance Impact Player Session Caching Rage Clicks Request Proxying Session Search Extracting the Session URL Session Search Deep Linking Shadow Dom + Web Components Error Monitoring Overview Enhancing Errors with GitHub Error Search Filtering Errors Grouping Errors Managing Errors Manually Reporting Errors Sourcemaps General Features Overview Alerts Comments Digests Environments Search Segments Services Webhooks Logging Overview Log Alerts Log Search Tracing Overview Trace Search Dashboards Overview Dashboard Management Metrics Tutorials Service Latency Web Vitals & Page Speed User Engagement User Analytics Graphing Drilldown Event Search Dashboard Variables SQL Editor Metrics (beta) Overview Frequently Asked Questions. Integrations Integrations Overview Amplitude Integration ClickUp Integration Discord Integration Electron Support Front Integration GitHub Integration Grafana Integration Overview Setup Dashboards Alerts Height Integration Intercom Integration Jira Integration LaunchDarkly Integration Linear Integration Mixpanel Integration Nuxt Integration Pendo Integration Segment Integration Slack Integration Vercel Integration WordPress Plugin Highlight.io Changelog Overview Changelog 12 (02/17) Changelog 13 (02/24) Changelog 14 (03/03) Changelog 15 (03/11) Changelog 16 (03/19) Changelog 17 (04/07) Changelog 18 (04/26) Changelog 19 (05/22) Changelog 20 (06/06) Changelog 21 (06/21) Changelog 22 (08/07) Changelog 23 (08/22) Changelog 24 (09/11) Changelog 25 (10/03) Changelog 26 (11/08) Changelog 27 (12/22) Changelog 28 (3/6) Changelog 29 (4/2) Getting Started Getting Started with Highlight Fullstack Mapping Browser React.js Next.js Remix Vue.js Angular Gatsby.js SvelteKit Electron highlight.run SDK Overview Canvas & WebGL Console Messages Content-Security-Policy Identifying Users iframe Recording Monkey Patches Browser OpenTelemetry Persistent Asset Storage Privacy Proxying Highlight React.js Error Boundary Recording Network Requests and Responses Recording WebSocket Events Salesforce Lightning Web Components (LWC) Data Export Sourcemap Configuration Tracking Events Troubleshooting Upgrading Highlight Versioning Sessions & Errors Other React Native (beta) Server Go Overview chi Echo Fiber Gin GORM gqlgen Logrus Manual Tracing gorilla mux JS Overview Apollo AWS Lambda Cloudflare Workers Express.js Firebase Hono Nest.js Next.js Node.js Pino tRPC Winston Python Overview AWS Lambda Azure Functions Django FastAPI Flask Google Cloud Functions Loguru Other Frameworks Python AI / LLM Libraries Python Libraries Ruby Overview Other Frameworks Ruby on Rails Rust Overview actix-web No Framework Hosting Providers Overview Metrics in AWS Logging in AWS Logging in Azure Fly.io NATS Log Shipper Logging in GCP Heroku Log Drain Render Log Stream Logging in Trigger.dev Vercel Log Drain Elixir Overview Elixir App Java: All Frameworks PHP: All Frameworks C# .NET ASP C# .NET 4 ASP Docker / Docker Compose File Fluent Forward curl OpenTelemetry Protocol (OTLP) Syslog RFC5424 Systemd / Journald Native OpenTelemetry Overview Error Monitoring Logging Tracing Browser Instrumentation Metrics Fullstack Frameworks Overview Next.js Fullstack Overview Next.js Page Router Guide Next.js App Router Guide Edge Runtime Advanced Config Remix Walkthrough Self Host & Local Dev Overview Development deployment guide. Integrations Microsoft Teams self-hosted Hobby deployment guide. Traefik SSL Proxying. Docs Home SDK Client SDK API Reference Cloudflare Worker SDK API Reference Go SDK API Reference Hono SDK API Reference Java SDK API Reference Next.JS SDK API Reference Node.JS SDK API Reference Python SDK API Reference Ruby SDK API Reference Rust SDK API Reference Docs / Highlight Docs / Product Features / Dashboards / Event Search Event Search Event search lets you create metrics and alerts based on events within your sessions. While session search helps you find sessions containing specific events, event search dives deeper by analyzing the attributes passed with each event and counting occurrences, even if they happen multiple times in a session. You can filter events using a search query . For example, you can get Click events produced in the last 15 minutes service by selecting "Last 15 minutes" from the time picker and entering the following query: event=Click We also offer autocompletion to help you discover events and their attributes, as discussed below. Searching for Events For general information on searching events, check out our Search docs . Default Key The default key for trace search is event . If you enter an expression without a key ( Navigate ) it will be used as the key for the expression ( event=*Navigate* ). Searchable Attributes You can search on any attributes that you send in your events as well as any of the default attributes assigned to a event. Below is a table showing the autoinjected attributes for events: Attribute Description Example browser_name Browser the user was on Chrome browser_version Browser version the user was on 124.0.0.0 city City the user was in San Francisco country Country the user was in Greece environment The environment specified in the SDK production event Name of the event that occurred SessionsPageLoaded first_session If its the user's first session false identified If the session successfully identified the user false identifier The idenifier passed to H.init 1 ip The IP address of the user 127.0.0.1 service_version Version of the service specified in the SDK e1845285cb360410aee05c61dd0cc57f85afe6da session_active_length Time the user session was active in milliseconds 10m session_length The total length of the user session 10m session_pages_visited The number of pages visited in the session 10 os_name The user's operating system Mac OS X os_version The user's operating system version 10.15.7 secure_session_id Id of the session the event occurred in e1845285cb360410aee05c61dd0cc57f85afe6da state State the user was in Virginia You can view a full list of the available attributes to filter on by starting to type in the search box. As you type you'll get suggestions for keys to filter on. Special Events The Highlight SDK records a few events by default: Click and Navigate events, both of which have some attributes associated with them. The event search form helps navigate these attributes with additional inputs, but all can be used directly in the search query. Click Events Click Events are triggered by mouse-down actions, even on non-clickable elements (like headers or white space). Click events have 3 main attributes associated with it: clickTextContent : The text of the content that was clicked. clickTarget : The HTML element that was clicked. clickSelector : The full HTML path to the clicked element. Navigate Events Navigate events are triggered by URL changes, including reloads. Navigate event attributes are URLs, and key types include: exit_page : The user ended the session on this url. landing_page : The user landed on this url. reload : The user reloaded the page on this url. url : The user navigated to this url. Helpful Tips Digging Deeper into Events If you want to get the number of unique sessions, edit the function to CountDistinct by secure_session_id. If you would like the number of unique users, use CountDistinct with the identifier attribute. Funnels Event search also allows you to view relations of events in the form of funnels. Select the Funnel Chart view type to start seeing how many sessions include multiple events in steps. Drilldown Dashboard Variables Community / Support Suggest Edits? Follow us! [object Object] | 2026-01-13T08:48:58 |
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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close React Follow Hide Official tag for Facebook's React JavaScript library for building user interfaces Create Post submission guidelines 1️⃣ Post Facebook's React ⚛ related posts/questions/discussion topics here~ 2️⃣ There are no silly posts or questions as we all learn from each other👩🎓👨🎓 3️⃣ Adhere to dev.to 👩💻👨💻 Code of Conduct about #react React is a declarative, component-based library, you can learn once, and write anywhere Editor Guide Check out this Editor Guide or this post to learn how to add code syntax highlights, embed CodeSandbox/Codepen, etc Official Documentations & Source Docs Tutorial Community Blog Source code on GitHub Improving Your Chances for a Reply by putting a minimal example to either JSFiddle , Code Sandbox , or StackBlitz . Describe what you want it to do, and things you've tried. Don't just post big blocks of code! Where else to ask questions StackOverflow tagged with [reactjs] Beginner's Thread / Easy Questions (Jan 2020) on r/reactjs subreddit. Note: a new "Beginner's Thread" created as sticky post on the first day of each month Learn in Public Don't afraid to post an article or being wrong. Learn in public . Older #react posts 1 2 3 4 5 6 7 8 9 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu Building Advanced Data Tables with AG Grid in React Michael Turner Michael Turner Michael Turner Follow Jan 12 Building Advanced Data Tables with AG Grid in React # react # tutorial # beginners # programming Comments Add Comment 6 min read React + Django vs MERN Stack: A Real-World Comparison Rishikesh Rishikesh Rishikesh Follow Jan 12 React + Django vs MERN Stack: A Real-World Comparison # react # djangoapi # mern # development Comments Add Comment 2 min read Getting Started with Fortune Sheet in React: Building Your First Spreadsheet Michael Turner Michael Turner Michael Turner Follow Jan 12 Getting Started with Fortune Sheet in React: Building Your First Spreadsheet # react # webdev # programming # tutorial Comments Add Comment 5 min read From Rusty to Release: How an Infinite Loop Taught Me to Respect React DevTools Beleke Ian Beleke Ian Beleke Ian Follow Jan 12 From Rusty to Release: How an Infinite Loop Taught Me to Respect React DevTools # react # webdev # beginners # programming 1 reaction Comments Add Comment 2 min read Project BookMyShow: Day 6 Vishwa Pratap Singh Vishwa Pratap Singh Vishwa Pratap Singh Follow Jan 11 Project BookMyShow: Day 6 # showdev # webdev # laravel # react Comments Add Comment 1 min read Advanced Data Table Implementation with ka-table in React Michael Turner Michael Turner Michael Turner Follow Jan 12 Advanced Data Table Implementation with ka-table in React # react # webdev # programming # javascript Comments Add Comment 6 min read Power Up React: Mastering Lists, Keys, and Component Patterns! (React Day 4) Vasu Ghanta Vasu Ghanta Vasu Ghanta Follow Jan 12 Power Up React: Mastering Lists, Keys, and Component Patterns! (React Day 4) # javascript # react # tutorial 1 reaction Comments Add Comment 4 min read ReactJS Hook Pattern ~UseImperativeHandle~ Ogasawara Kakeru Ogasawara Kakeru Ogasawara Kakeru Follow Jan 12 ReactJS Hook Pattern ~UseImperativeHandle~ # programming # javascript # react # learning Comments Add Comment 1 min read Building a React Dashboard in 2026: What Actually Matters (From a Dev Perspective) Vaibhav Gupta Vaibhav Gupta Vaibhav Gupta Follow Jan 12 Building a React Dashboard in 2026: What Actually Matters (From a Dev Perspective) # webdev # react # opensource # frontend Comments Add Comment 2 min read Building a Regulatory-Compliant Accessibility Scanner: From WCAG to Legal Compliance Labontese Labontese Labontese Follow Jan 11 Building a Regulatory-Compliant Accessibility Scanner: From WCAG to Legal Compliance # a11y # typescript # react # webdev Comments Add Comment 6 min read Book Review: Ecosystem Competition Strategy Evan Lin Evan Lin Evan Lin Follow Jan 11 Book Review: Ecosystem Competition Strategy # discuss # react # performance Comments Add Comment 10 min read 3D Anatomy Modeling: Build Interactive Features to Visualize Muscle Engagement wellallyTech wellallyTech wellallyTech Follow Jan 12 3D Anatomy Modeling: Build Interactive Features to Visualize Muscle Engagement # frontend # react # threejs # datavisualization Comments Add Comment 2 min read Polyfil - useReducer Bishoy Semsem Bishoy Semsem Bishoy Semsem Follow Jan 11 Polyfil - useReducer # react # webdev Comments Add Comment 6 min read I built a tool to detect ISP Throttling on Steam using React + Vite Murilo Evangelinos Murilo Evangelinos Murilo Evangelinos Follow Jan 11 I built a tool to detect ISP Throttling on Steam using React + Vite # showdev # networking # react # tooling Comments Add Comment 1 min read I Built 18 Free Developer Tools That Run 100% in Your Browser Palak Kanani Palak Kanani Palak Kanani Follow Jan 11 I Built 18 Free Developer Tools That Run 100% in Your Browser # webdev # javascript # react # productivity Comments Add Comment 1 min read Polyfill - useEffect (React) ZeeshanAli-0704 ZeeshanAli-0704 ZeeshanAli-0704 Follow Jan 11 Polyfill - useEffect (React) # javascript # react # tutorial Comments Add Comment 5 min read Polyfil - useReducer ZeeshanAli-0704 ZeeshanAli-0704 ZeeshanAli-0704 Follow Jan 11 Polyfil - useReducer # interview # tutorial # javascript # react Comments Add Comment 5 min read From CSV to insights: building an open-source analytics SaaS salaheddine Ennouami salaheddine Ennouami salaheddine Ennouami Follow Jan 11 From CSV to insights: building an open-source analytics SaaS # data # datascience # webdev # react Comments Add Comment 1 min read ReactJS Design Pattern ~Context Selector~ Ogasawara Kakeru Ogasawara Kakeru Ogasawara Kakeru Follow Jan 11 ReactJS Design Pattern ~Context Selector~ # programming # javascript # react # learning Comments Add Comment 1 min read Dark Mode with Tailwind v4 & next-themes Abu Jakaria Abu Jakaria Abu Jakaria Follow Jan 10 Dark Mode with Tailwind v4 & next-themes # react # webdev # tailwindcss # darkmode Comments Add Comment 2 min read Real-Time Dashboards: Building a Heart Rate Monitor Enhances Remote Health Tracking wellallyTech wellallyTech wellallyTech Follow Jan 11 Real-Time Dashboards: Building a Heart Rate Monitor Enhances Remote Health Tracking # node # tutorial # fullstack # react Comments Add Comment 2 min read Mastering React's Dynamic Side: State, Events, and Conditional Rendering! (React Day 3) Vasu Ghanta Vasu Ghanta Vasu Ghanta Follow Jan 11 Mastering React's Dynamic Side: State, Events, and Conditional Rendering! (React Day 3) # react # babel # javascript # webdev Comments Add Comment 4 min read Today I Truly Understood Custom Hooks (And Built My Own) Usama Usama Usama Follow Jan 10 Today I Truly Understood Custom Hooks (And Built My Own) # react # frontend # learning # webdev 2 reactions Comments 2 comments 2 min read mkdir backend cd backend npm init -y npm install express mongoose cors dotenv Areeba Malik Areeba Malik Areeba Malik Follow Jan 11 mkdir backend cd backend npm init -y npm install express mongoose cors dotenv # tutorial # mongodb # node # react Comments 1 comment 3 min read My Portfolio on Google Cloud Run YogoCastro YogoCastro YogoCastro Follow Jan 11 My Portfolio on Google Cloud Run # portfolio # devops # docker # react Comments Add Comment 1 min read loading... 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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https://www.highlight.io/docs/general/product-features/logging/log-alerts | Log Alerts Star us on GitHub Star Docs Sign in Sign up General Docs Welcome to highlight.io Get Started Roadmap Company Values Compliance & Security Open Source Contributing Overview GraphQL Backend Frontend (app.highlight.io) Landing Site (highlight.io) Documentation End to End SDK Example Apps Adding an SDK Application Architecture GitHub Code Spaces Code Style Good First Issues Self-hosting Self-hosted [Dev] Self-hosted [Hobby] Self-hosted [Enterprise] Telemetry Our Competitors Product Philosophy Product Features Session Replay Overview Canvas & Iframe Dev-tool Window Recording Tracking Users & Recording Events Filtering Sessions GraphQL Live Mode Performance Impact Player Session Caching Rage Clicks Request Proxying Session Search Extracting the Session URL Session Search Deep Linking Shadow Dom + Web Components Error Monitoring Overview Enhancing Errors with GitHub Error Search Filtering Errors Grouping Errors Managing Errors Manually Reporting Errors Sourcemaps General Features Overview Alerts Comments Digests Environments Search Segments Services Webhooks Logging Overview Log Alerts Log Search Tracing Overview Trace Search Dashboards Overview Dashboard Management Metrics Tutorials Service Latency Web Vitals & Page Speed User Engagement User Analytics Graphing Drilldown Event Search Dashboard Variables SQL Editor Metrics (beta) Overview Frequently Asked Questions. Integrations Integrations Overview Amplitude Integration ClickUp Integration Discord Integration Electron Support Front Integration GitHub Integration Grafana Integration Overview Setup Dashboards Alerts Height Integration Intercom Integration Jira Integration LaunchDarkly Integration Linear Integration Mixpanel Integration Nuxt Integration Pendo Integration Segment Integration Slack Integration Vercel Integration WordPress Plugin Highlight.io Changelog Overview Changelog 12 (02/17) Changelog 13 (02/24) Changelog 14 (03/03) Changelog 15 (03/11) Changelog 16 (03/19) Changelog 17 (04/07) Changelog 18 (04/26) Changelog 19 (05/22) Changelog 20 (06/06) Changelog 21 (06/21) Changelog 22 (08/07) Changelog 23 (08/22) Changelog 24 (09/11) Changelog 25 (10/03) Changelog 26 (11/08) Changelog 27 (12/22) Changelog 28 (3/6) Changelog 29 (4/2) Menu Highlight Docs Welcome to highlight.io Get Started Roadmap Company Values Compliance & Security Open Source Contributing Overview GraphQL Backend Frontend (app.highlight.io) Landing Site (highlight.io) Documentation End to End SDK Example Apps Adding an SDK Application Architecture GitHub Code Spaces Code Style Good First Issues Self-hosting Self-hosted [Dev] Self-hosted [Hobby] Self-hosted [Enterprise] Telemetry Our Competitors Product Philosophy Product Features Session Replay Overview Canvas & Iframe Dev-tool Window Recording Tracking Users & Recording Events Filtering Sessions GraphQL Live Mode Performance Impact Player Session Caching Rage Clicks Request Proxying Session Search Extracting the Session URL Session Search Deep Linking Shadow Dom + Web Components Error Monitoring Overview Enhancing Errors with GitHub Error Search Filtering Errors Grouping Errors Managing Errors Manually Reporting Errors Sourcemaps General Features Overview Alerts Comments Digests Environments Search Segments Services Webhooks Logging Overview Log Alerts Log Search Tracing Overview Trace Search Dashboards Overview Dashboard Management Metrics Tutorials Service Latency Web Vitals & Page Speed User Engagement User Analytics Graphing Drilldown Event Search Dashboard Variables SQL Editor Metrics (beta) Overview Frequently Asked Questions. Integrations Integrations Overview Amplitude Integration ClickUp Integration Discord Integration Electron Support Front Integration GitHub Integration Grafana Integration Overview Setup Dashboards Alerts Height Integration Intercom Integration Jira Integration LaunchDarkly Integration Linear Integration Mixpanel Integration Nuxt Integration Pendo Integration Segment Integration Slack Integration Vercel Integration WordPress Plugin Highlight.io Changelog Overview Changelog 12 (02/17) Changelog 13 (02/24) Changelog 14 (03/03) Changelog 15 (03/11) Changelog 16 (03/19) Changelog 17 (04/07) Changelog 18 (04/26) Changelog 19 (05/22) Changelog 20 (06/06) Changelog 21 (06/21) Changelog 22 (08/07) Changelog 23 (08/22) Changelog 24 (09/11) Changelog 25 (10/03) Changelog 26 (11/08) Changelog 27 (12/22) Changelog 28 (3/6) Changelog 29 (4/2) Getting Started Getting Started with Highlight Fullstack Mapping Browser React.js Next.js Remix Vue.js Angular Gatsby.js SvelteKit Electron highlight.run SDK Overview Canvas & WebGL Console Messages Content-Security-Policy Identifying Users iframe Recording Monkey Patches Browser OpenTelemetry Persistent Asset Storage Privacy Proxying Highlight React.js Error Boundary Recording Network Requests and Responses Recording WebSocket Events Salesforce Lightning Web Components (LWC) Data Export Sourcemap Configuration Tracking Events Troubleshooting Upgrading Highlight Versioning Sessions & Errors Other React Native (beta) Server Go Overview chi Echo Fiber Gin GORM gqlgen Logrus Manual Tracing gorilla mux JS Overview Apollo AWS Lambda Cloudflare Workers Express.js Firebase Hono Nest.js Next.js Node.js Pino tRPC Winston Python Overview AWS Lambda Azure Functions Django FastAPI Flask Google Cloud Functions Loguru Other Frameworks Python AI / LLM Libraries Python Libraries Ruby Overview Other Frameworks Ruby on Rails Rust Overview actix-web No Framework Hosting Providers Overview Metrics in AWS Logging in AWS Logging in Azure Fly.io NATS Log Shipper Logging in GCP Heroku Log Drain Render Log Stream Logging in Trigger.dev Vercel Log Drain Elixir Overview Elixir App Java: All Frameworks PHP: All Frameworks C# .NET ASP C# .NET 4 ASP Docker / Docker Compose File Fluent Forward curl OpenTelemetry Protocol (OTLP) Syslog RFC5424 Systemd / Journald Native OpenTelemetry Overview Error Monitoring Logging Tracing Browser Instrumentation Metrics Fullstack Frameworks Overview Next.js Fullstack Overview Next.js Page Router Guide Next.js App Router Guide Edge Runtime Advanced Config Remix Walkthrough Self Host & Local Dev Overview Development deployment guide. Integrations Microsoft Teams self-hosted Hobby deployment guide. Traefik SSL Proxying. Docs Home SDK Client SDK API Reference Cloudflare Worker SDK API Reference Go SDK API Reference Hono SDK API Reference Java SDK API Reference Next.JS SDK API Reference Node.JS SDK API Reference Python SDK API Reference Ruby SDK API Reference Rust SDK API Reference Docs / Highlight Docs / Product Features / Logging / Log Alerts Log Alerts Logs alerts are a way to get notified when the count of logs for a query is over or under a threshold for a specific time range. Creating an alert Query When you set up an alert, you can include a query to count only the logs that match. The query format follows the same specification as on the logs page. You can read more here . Alert Threshold You can control the number of logs needed to trigger an alert by setting an alert threshold. You can choose to alert if the actual log count is above or below this threshold. Alert Frequency You can adjust the time range for which logs are searched and aggregated. Shorter frequencies can be helpful to be alerted quickly about an issue, while longer frequencies can help reduce noise by aggregating across a larger time range. Notifications Log alerts can be configured to notify you via Slack, Discord, email, or webhooks. For more details, see alerts . Logging Features Log Search Community / Support Suggest Edits? Follow us! [object Object] | 2026-01-13T08:48:58 |
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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Learning Follow Hide “I have no special talent. I am only passionately curious.” - Albert Einstein Create Post Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu I tried to capture system audio in the browser. Here's what I learned. Flo Flo Flo Follow Jan 12 I tried to capture system audio in the browser. Here's what I learned. # api # javascript # learning # webdev 5 reactions Comments Add Comment 2 min read Thinking in First Principles: How to Question an Async Queue–Based Design Mohammad-Idrees Mohammad-Idrees Mohammad-Idrees Follow Jan 13 Thinking in First Principles: How to Question an Async Queue–Based Design # architecture # interview # learning # systemdesign Comments Add Comment 4 min read J'ai galéré pendant 3 semaines pour monter un cluster Kubernetes (et voilà ce que j'ai appris) BeardDemon BeardDemon BeardDemon Follow Jan 10 J'ai galéré pendant 3 semaines pour monter un cluster Kubernetes (et voilà ce que j'ai appris) # devops # kubernetes # learning Comments Add Comment 6 min read I built an interactive SHA-256 visualizer to finally understand how it works Jamal ER-RAKIBI Jamal ER-RAKIBI Jamal ER-RAKIBI Follow Jan 12 I built an interactive SHA-256 visualizer to finally understand how it works # showdev # algorithms # learning # security Comments Add Comment 1 min read My 2026 Roadmap: How I’m Future-Proofing My Fullstack Career in the Age of AI Aleksandr Fomin Aleksandr Fomin Aleksandr Fomin Follow Jan 12 My 2026 Roadmap: How I’m Future-Proofing My Fullstack Career in the Age of AI # ai # learning # career # careerdevelopment Comments Add Comment 4 min read The Features I Killed to Ship The 80 Percent App in 4 Weeks Malawige Inusha Thathsara Gunasekara Malawige Inusha Thathsara Gunasekara Malawige Inusha Thathsara Gunasekara Follow Jan 12 The Features I Killed to Ship The 80 Percent App in 4 Weeks # flutter # softwareengineering # devops # learning Comments Add Comment 4 min read I built an AI tutor to learn GeoGuessr-style visual geography (not a solver) TunaDev TunaDev TunaDev Follow Jan 12 I built an AI tutor to learn GeoGuessr-style visual geography (not a solver) # showdev # ai # learning # opensource Comments Add Comment 1 min read C#.NET - day 07 Sabin Sim Sabin Sim Sabin Sim Follow Jan 12 C#.NET - day 07 # programming # learning # csharp # career 1 reaction Comments Add Comment 3 min read My Journey Into Cybersecurity: A Beginner’s Guide The Duchess of Hackers The Duchess of Hackers The Duchess of Hackers Follow Jan 12 My Journey Into Cybersecurity: A Beginner’s Guide # cybersecurity # beginners # learning # mattermost 6 reactions Comments Add Comment 2 min read Why Learning Requires Patience Memory Rush Memory Rush Memory Rush Follow Jan 12 Why Learning Requires Patience # learning # mentalmodels # developers Comments Add Comment 3 min read Why I Build macOS Menu Bar Apps heocoi heocoi heocoi Follow Jan 12 Why I Build macOS Menu Bar Apps # beginners # learning 1 reaction Comments 1 comment 3 min read Multi-dimensional Arrays & Row-major Order: A Deep Dive ali ehab algmass ali ehab algmass ali ehab algmass Follow Jan 12 Multi-dimensional Arrays & Row-major Order: A Deep Dive # webdev # programming # computerscience # learning Comments Add Comment 5 min read I Thought I Understood Python Functions — Until One Line Returned None Emmimal Alexander Emmimal Alexander Emmimal Alexander Follow Jan 12 I Thought I Understood Python Functions — Until One Line Returned None # python # programming # learning # beginners Comments Add Comment 3 min read Inside Git: How It Works and the Role of the `.git` Folder Umar Hayat Umar Hayat Umar Hayat Follow Jan 12 Inside Git: How It Works and the Role of the `.git` Folder # git # beginners # tutorial # learning 1 reaction Comments Add Comment 4 min read CEED Mock Test Platform - Situation Report Ritik Jangir Ritik Jangir Ritik Jangir Follow Jan 12 CEED Mock Test Platform - Situation Report # webdev # sass # architecture # learning 1 reaction Comments Add Comment 2 min read Java Variables Kesavarthini Kesavarthini Kesavarthini Follow Jan 12 Java Variables # java # beginners # learning # programming Comments Add Comment 1 min read How Memory Organizes Information Memory Rush Memory Rush Memory Rush Follow Jan 12 How Memory Organizes Information # mentalmodels # learning # developers # development Comments Add Comment 3 min read I Built 97 Free Online Tools (and Games) While Learning to Ship Consistently Axonix Tools Axonix Tools Axonix Tools Follow Jan 12 I Built 97 Free Online Tools (and Games) While Learning to Ship Consistently # showdev # learning # productivity # webdev 3 reactions Comments 1 comment 2 min read An Introduction to Docker: Stop asking your stakeholders to install Postgres! 🚀 Francisco Luna Francisco Luna Francisco Luna Follow Jan 11 An Introduction to Docker: Stop asking your stakeholders to install Postgres! 🚀 # webdev # devops # productivity # learning 1 reaction Comments Add Comment 5 min read Electric Industry Operation GeunWooJeon GeunWooJeon GeunWooJeon Follow Jan 12 Electric Industry Operation # beginners # devjournal # learning Comments Add Comment 4 min read Starting My Learning Journey in Tech Hassan Olamide Hassan Olamide Hassan Olamide Follow Jan 12 Starting My Learning Journey in Tech # beginners # devjournal # learning # webdev 1 reaction Comments Add Comment 1 min read ReactJS Hook Pattern ~UseImperativeHandle~ Ogasawara Kakeru Ogasawara Kakeru Ogasawara Kakeru Follow Jan 12 ReactJS Hook Pattern ~UseImperativeHandle~ # programming # javascript # react # learning Comments Add Comment 1 min read First Calm the Eye, Then Clear the Vision Understanding Uveitis Cataract, A Guide for Patients and Doctors By Dr. Sonal Hinge Dr Sonal Hinge Dr Sonal Hinge Dr Sonal Hinge Follow Jan 12 First Calm the Eye, Then Clear the Vision Understanding Uveitis Cataract, A Guide for Patients and Doctors By Dr. Sonal Hinge # learning # resources # science 6 reactions Comments Add Comment 3 min read [Golang] Issues When Enabling Go Modules in Old Open Source Projects Evan Lin Evan Lin Evan Lin Follow Jan 11 [Golang] Issues When Enabling Go Modules in Old Open Source Projects # learning # tooling # go # opensource Comments Add Comment 5 min read TIL: Byzantine Generals Problem in Real-World Distributed Systems Evan Lin Evan Lin Evan Lin Follow Jan 11 TIL: Byzantine Generals Problem in Real-World Distributed Systems # computerscience # learning # systemdesign Comments Add Comment 3 min read loading... trending guides/resources DevOps From Scratch: Entry #01 DevOps From Scratch: A Student’s Diary (Entry #00) The Coursera–Udemy merger raises a bigger question: how do developers actually learn? Why Debugging Skills Matter More Than Writing New Code What happens when you type console.log()? 2025 Black Friday Developer Deals Exploring Extension Blocks in .NET 10 Python Registry Pattern: A Clean Alternative to Factory Classes CSS Shadows Mastery: Elevate Your Web Design with Box-Shadow & Text-Shadow Sync any Linux folder to Google drive using Rclone + systemd. The 3 GitHub Projects I Recommend to Every Prompt Writer Build Multi-Agent Systems Using the Agents as Tools Pattern When Should You Use Backblaze B2 and When Should You Use Cloudflare R2? 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https://blog.smartere.dk/category/planets/hal9k/ | blog.smartere » Hal9k blog.smartere // Ramblings of Mads Chr. Olesen jan 12 Floppy Disks: the best TV remote for kids Posted on mandag, januar 12, 2026 in Hal9k , Planet Ubuntu-DK , Planets Modern TVs are very poorly suited for kids. They require using complicated remotes or mobile phones, and navigating apps that continually try to lure you into watching something else than you intended to. The usual scenario ends up with the kid feeling disempowered and asking an adult to put something on. That something ends up on auto-play because then the adult is free to do other things and the kid ends up stranded powerless and comatose in front of the TV. Instead I wanted to build something for my 3-year old son that he could understand and use independently. It should empower him to make his own choices. It should be physical and tangible, i.e. it should be something he could touch and feel. It should also have some illusion that the actual media content was stored physically and not un-understandably in “the cloud”, meaning it should e.g. be destroyable — if you break the media there should be consequences. And there should be no auto-play: interact once and get one video. Floppy disks are awesome! And then I remembered the sound of a floppy disk. The mechanical click as you insert it, the whirr of the disk spinning, and the sound of the read-head moving. Floppy disks are the best storage media ever invented! Why else would the “save-icon” still be a floppy disk? Who hasn’t turned in a paper on a broken floppy disk, with the excuse ready that the floppy must have broken when the teacher asks a few days later? But kids these days have never used nor even seen a floppy disk, and I believe they deserve this experience! Building on the experience from the Big Red Fantus-Button , I already had a framework for controlling a Chromecast, and because of the netcat | bash shenanigans it was easily extendable. My first idea for datastorage was to use the shell of a floppy disk and floppy drive, and put in an RFID tag; this has been done a couple of times on the internet, such as RFIDisk or this RaspberryPi based RFID reader or this video covering how to embed an RFID tag in a floppy disk . But getting the floppy disk apart to put in an RFID tag and getting it back together was kinda wonky. When working on the project in Hal9k someone remarked: “Datastorage? The floppy disk can store data!”, and a quick prototype later this worked really, really , well. Formatting the disk and storing a single small file, “autoexec.sh”, means that all the data ends up in track 0 and is read more or less immediately. It also has the benefit that everything can be checked and edited with a USB floppy disk drive; and the major benefit that all the sounds are completely authentic: click, whirrr, brrr brrr. Autorun for floppy disks is not really a thing. The next problem to tackle was how to detect that a disk is inserted. The concept of AutoRun from Windows 95 was a beauty: insert a CD-ROM and it would automatically start whatever was on the media. Great for convenience, quite questionably for security. While in theory floppy disks are supported for AutoRun , it turns out that floppy drives basically don’t know if a disk is inserted until the operating system tries to access it! There is a pin 34 “Disk Change” that is supposed to give this information , but this is basically a lie. None of the drives in my possession had that pin connected to anything, and the internet mostly concurs. In the end I slightly modified the drive and added a simple rolling switch, that would engage when a disk was inserted. A floppy disk walks into a drive; the microcontroller says “hello!” The next challenge was to read the data on a microcontroller. Helpfully, there is the Arduino FDC Floppy library by dhansel, which I must say is most excellent. Overall, this meant that the part of the project that involved reading a file from the floppy disk FAT filesystem was basically the easiest part of all! A combined ATMega + ESP8266 UNO-like board. Not really recommended, but can be made to work. However, the Arduino FDC Floppy library is only compatible with the AVR-based Arduinos, not the ESP-based ones, because it needs to control the timing very precisely and therefore uses a healthy amount of inline assembler. This meant that I would need one AVR-based Arduino to control the floppy disk, but another ESP-based one to do the WiFi communication. Such combined boards do exist, and I ended up using such a board, but I’m not sure I would recommend it: the usage is really finagly, as you need to set the jumpers differently for programming the ATmega, or programming the ESP, or connecting the two boards serial ports together. A remote should be battery-powered A remote control should be portable, and this means battery-powered. Driving a floppy disk of of lithium batteries was interesting. There is a large spike in current draw when the disk needs to spin up of several amperes, while the power draw afterwards is more modest, a couple of hundred milliamperes. I wanted the batteries to be 18650s, because I have those in abundance. This meant a battery voltage of 3.7V nominally, up to 4.2V for a fully charged battery; 5V is needed to spin the floppy around, so a boost DC-DC converter was needed. I used an off the shelf XL6009 step-up converter board. At this point a lot of head-scratching occurred: that initial spin-up power draw would cause the microcontroller to reset. In the end a 1000uF capacitor at the microcontroller side seemed to help but not eliminate the problem. One crucial finding was that the ground side of the interface cable should absolutely not be connected to any grounds on the microcontroller side. I was using a relatively simple logic-level MOSFET, the IRLZ34N , to turn off the drive by disconnecting the ground side. If any ground is connected, the disk won’t turn off. But also: if any logic pin was being pulled to ground by the ATmega, that would also provide a path to ground. But since the ATmega cannot sink that much current this would lead to spurious resets! Obvious after the fact, but this took quite some headscratching. Setting all the logic pins to input, and thus high impedance , finally fixed the stability issues. After fixing the stability, the next challenge was how to make both of the microcontrollers sleep. Because the ATmega sleep modes are quite a lot easier to deal with, and because the initial trigger would be the floppy inserting, I decided to make the ATmega in charge overall. Then the ESP has a very simple function: when awoken, read serial in, when a newline is found then send off that complete line via WiFi, and after 30 seconds signal to the ATmega that we’re sleeping, and go back to sleep. The overall flow for the ATmega is then: A disk is inserted, this triggers a interrupt on the ATmega that wakes up. The ATmega resets the ESP, waking it from deep sleep. The ATmega sends a “diskin” message over serial to the ESP; the ESP transmits this over WiFi when available. The ATmega turns on the drive itself, and reads the disk contents, and just sends it over serial to the ESP. Spin down the disk, go to sleep. When the disk is ejected, send a “diskout” message over serial, resetting the ESP if needed. Go back to 1. The box itself is just lasercut from MDF-board. For full details see the FloppyDiskCast Git repository . Server-side handlers Responding to those commands is still the netcat | bash from the Big Red Fantus-Button , which was simply extended with a few more commands and capabilities. A few different disks to chose from, with custom printed labels. diskin always sends a “play” command to the Chromecast. diskout always sends a “pause” command to the Chromecast. Other commands like dad-music are handled in one of two ways: Play a random video from a set, if a video from that set is not already playing : e.g. dad-music will randomly play one of dad’s music tracks – gotta influence the youth! Play the next video from a list, if a video from the list is not already playing : e.g. fantus-maskinerne will play the next episode, and only the next episode. Common for both is that they should be idempotent actions, and the diskin shortcut will make the media resume without having to wait for the disk contents itself to be read and processed. This means that the “play/pause” disk just contains an empty file to work. Questionable idea meets real-world 3 year old user The little guy quickly caught on to the idea! Much fun was had just pausing and resuming music and his Fantus TV shows. He explored and prodded, and some disks were harmed in the process. One problem that I did solve was that the read head stayed on track 0 after having read everything: this means that when the remote with disk inside it is tumbled around, the disk gets damaged at track 0. To compensate for this, I move the head to track 20 after reading has finished: any damage is then done there, where we don’t store any data. As a bonus it also plays a little more mechanic melody. Comments (2) | apr 20 Upgrading the Olimex A20 LIME2 to 2GB RAM, by learning to BGA solder and deep diving into the U-Boot bootloader process Posted on søndag, april 20, 2025 in Hal9k , Planets As I’ve written about previously I have had the Olimex A20-OLinuXino-LIME2 in service for quite some time . But one thing that I’ve been curious about is why it’s only available with 1GB of RAM, when the A20 chip itself can support up to 2GB? Could it be upgraded to 2GB RAM by a simple swap in of a larger memory module? RAM part of the LIME2 schematic If you check the schematic the address lines are actually wired up: both A14 and A15 which are labelled NC (no-connect) on the chips are wired up on the address bus, meaning a full 2¹⁶ row addresses should be addressable. So this might actually work out! Detour: How do CPUs access memory? From a very high level the way a CPU accesses memory is the same all the way from a small microprocessor like the RP2040 up to a x86. There are a number of pins connecting the CPU and the RAM: A number of address lines, e.g. A0–A15 in our case. These are always driven by the CPU. A number of data lines, e.g. DQ0–DQ15. These are bi-directional and driven by the CPU for writes, but by the RAM for reads. A couple of signalling lines to control the communication, e.g. the shared clock, or the CPU signaling that the address lines are set with the address for a read, or the RAM signaling that the data lines are populated with the data read out. These can be quite complicated, as seen with DDR3 in this instance, where signalling talks about “banks”, “lower/upper byte data strobe”, “data masks” and “chip select”. The most crude form of using more than one RAM chip would be to use “chip select” as known from SPI or I2C communication. This is however not how it’s done on the LIME2: address, data and chip select lines are wired in parallel for the two chips. The only difference in wiring is on the “DMU”, “DML”, and “DQSU” and “DQSL” lines: these are used for lower and upper byte data strobes, meaning that the same address is setup for both chips, and then the chips are strobed one at a time – effectively allowing each chip to prepare the read in parallel. Finding compatible chips with 256Mx16 Luckily DDR chips are standardized, but it seems that the standardisation does not quite go all the way to the datasheets, in e.g. pin naming and concepts. But at least the density and organization are standardised: the 256M is the number of different addressable storage locations, and the x16 is how many bits are stored per location. Multiplying those gives the number of megabits stored, 4096 megabits in this case, so dividing by 8 gives the number of megabytes stored: 512MiB. Looking at the pinout for the specified chip ( K4B4G1646D-BYK0, a Samsung chip ): We can see it specifies only address lines A0–A14, which is enough for a 256M module. But the LIME2 schematic was helpful enough to hookup A15 to the JEDEC standard location , even if that pin is NC on all memory modules shipped. This might actually work! The last crucial parameter for selecting bigger RAM chips is the supply voltage. DDR3 comes in both standard and low-voltage (DDR3L) variants. The LIME2 schematic actually just specifies that “ When DDR3L is used, VDD&VDDQ are set to 1.35V!!! “, so to know which it is we would have to look at the particular board and measure the power supply line. But luckily, almost all DDR3L chips are backwards compatible to the 1.5V DDR3 level, so as long as we can find a DDR3L chip voltage shouldn’t be an issue. So in theory any 512Mx16 DDR3L chip should work. In practice I ended up trying two variants: Micron MT41K512M16 , which seems to be the only option on AliExpress, and cheap, but which (spoiler alert!) I did not get working ISSI IS46TR16512BL , which I did get working, but is more expensive to the point that the two needed RAM chips cost more than the LIME2 itself. Learning to BGA solder Finally, we can jump to the microscope soldering station, and learn to BGA solder. This was by far the longest part of this project. The chips come pre-balled, so in theory the job could have been as simple as desoldering the old chips and soldering on the new ones. Not so easy in practice. I ended up having to re-ball and re-solder chips , apply flux, solder-wick and ethanol in copious amount , re-attach SMD resistors that had taken a stroll under the heatgun, and battling a self-compiled U-Boot that I probably messed up badly. You get to see my frustration in a few nice pictures. I have a suspicion that I messed up U-Boot at one point, by trying to compile it with automatic impedance calibration, instead of leaving the LIME2 defaults DDR settings in. This might be the reason I couldn’t get the Micron MT41K512M16 chips to work, but I will have to investigate this more. I probably also messed up the first soldering on of a chip, by not using enough heat. My main piece of advice would be to not be too afraid to get the temperature of the chip up, if you spend more than about a minute trying to solder or desolder the chip, chances are you will be heating up the rest of the board much more than needed and the chip itself too little! The moment of seeing the board booting with 1GB from a single ISSI IS46TR16512BL was a great success though — soldering on the other ISSI chip was basically a walk in the park. Further U-Boot adventures of a curious character A serial terminal is absolutely essential for getting any kind of feedback on the early part of the boot process, and the first user-controlled software encountered on the LIME2 is U-Boot . U-Boot is the universal bootloader responsible for figuring out the basic hardware configuration (including RAM configuration), finding the (Linux) kernel and moving it into RAM and giving over control to the kernel for further booting. Curiously, U-Boot can run with absolutely no RAM chips (guess how I know!), because the SunXi early boot process happens entirely in on-chip ROM and a small on-chip SRAM . But how does U-Boot actually determine how much memory is there? Well, remember that accessing a memory location is just putting an address on the address lines and pulling some signalling pins. So U-Boot simply tries and write to increasing addresses and see if the expected data can be read back . How is the memory size then communicated to the Linux kernel? By a bootarg parameter, e.g. mem=2048M . Does this mean we can try and trick the Linux kernel into thinking it has more memory than physically present? Yes, but with disastrous results if the non-existent memory is ever attempted to be used. I now possess a unique 2GB LIME2 Until told otherwise, I will happily claim that this is the only 2GB LIME2 in existence — but do let me know if you give the procedure a try! In the end the process was much simpler than I thought: the tricky part was definitely getting the hang of BGA soldering. Don’t be afraid of raising the temperature! Peeking into the innards of U-Boot was also fascinating: there is definitely a layer below of pretty dark bit-setting magic, but the overall process is really well structured! A unique 2GB LIME2 That actually boots! Comments (3) | jan 6 Making a too cheap LED lamp safe to use Posted on mandag, januar 6, 2025 in Hal9k , Planets This could happen to you: A really cool LED lamp was found online, on a Danish and well-written homepage. Unfortunately, when the lamp arrives it is a cheap Chinese production, of questionable quality and safety. This is a non-rational quest to make such a cheap LED lamp safe to use. From the outset the wires are tiny. The wires are connected with wire nuts *gasp*! (Wire nuts are basically unheard of in Europe). The LED driver itself that converts the 230V AC into DC has absolutely no separation, and as we will see later, absolutely no safety features. It did have a cool feature of changing light color temperature by turning the lamp on and off a couple of times, though. Short-circuited 300mA Unloaded 118V. Sparky! But happily going to 300mA when shorted, going up to 118V unloaded, and full willingness to spark away, is a deal-breaker. This abomination was not being powered on in this house! It should be possible to replace the unsafe parts with safer (and more expensive) parts. The first step was understanding the mess of wires. This took quite some pondering to figure out that all the LEDs were basically in series, and that it was wired with a “common positive”, with either the white or the black wire (or both) acting as ground depending on the wanted color temperature. In the end the entire schematic was reverse engineered. That LED driver was going nowhere but the electronic garbage bin, so a replacement of decent quality had to be acquired: a constant-current LED driver (configurable from 200mA–350mA) was purchased from a reputable source. That gave the next problem: an LED driver of quality was at least double the size of the unsafe one, and did not fit in the original round enclosure. 3D-printing to the rescue, and a new bigger round enclosure was printed. Now everything should be able to fit and work! Instead of that illogical wiring of putting the LEDs in series, why not just put the two parts in parallel? Well, that won’t work. Only the path of least-resistance would light up, in this case the dome LEDs. So, back to the original wiring in series. Unfortunately, the next problem was that the new LED driver was unwilling to drive LEDs as originally wired, that seemed to require somewhere above 45V, out of spec for the new driver. More stuff had to change. Looking at the schematic, the long strip in the circle could be cut in half, and the two half put in parallel instead. This should reduce the power going to those LEDs, and thus also the light output, but should also help to decrease the required voltage. But first I had to learn again the hard way that putting LEDs in parallel they need to match quite closely: the original LED strip had 11 segments, and dividing into 6 and 5 gave lights only in the one part. Reducing to 5 and 5 segments worked really well! Finally, the total voltage of putting the two parts of the lamp in series was below what the new LED driver would supply. The only task remaining was to fit everything back into the enclosure, and add copious amounts of Kapton tape and hot glue. And finally, the spaceman could go star-fishing – safely. Comments (0) | okt 21 Giv mig nu bare elprisen.somjson.dk! (en historie om det måske værste datasæt i åbne energidata) Posted on mandag, oktober 21, 2024 in Danish , Hal9k , Planets Der findes rigtig meget åbent data om det danske energi system hos Energi Data Service , f.x. spot prisen på elektricitet og CO2 prognoser per kWh . Det er dog overordentligt svært at finde den samlede pris man betaler som forbruger per kWh, pga. det uigennemskuelige datasæt over tariffer og priser . I frustration kom udbruddet: “Giv mig nu bare elprisen.somjson.dk ” der nemt summerer alle priser og afgiter per elselskab, er open source og uden yderligere dikke-darer. Hvad koster strøm i Danmark? For en forbruger i Danmark er strømprisen en sum af forskellige priser og afgifter, nogle faste, nogle dynamiske: El-afgiften fastsat ved lov til 0,761 kr per kWh. Energinet’s eltariffer : Nettarif på 0,074 kr per kWh (år 2024), og systemtarif på 0,051 kr per kWh (år 2024). Netselskabstarif fra forsyningsselskabet ( N1 , Radius , etc.): denne varierer per time og per sæson for at forsøge at incentivere til at udligne forbruget så der ikke skal investeres i nye og større elkabler, og er indkodet i datasættet over tariffer og priser . Private forbrugere betaler C-tarif. Spot-prisen : er den anden variable, og denne varierer ud fra udbud og efterspørgsel. Moms: 25% lagt til summen af ovenstående Dette er alle de uundgåelige priser og afgifter, der kan regnes ud udelukkende fra adressen. Derudover kommer så det “frie elmarked”, hvor der skal betales til et elselskab: typisk månedsabonnement og et tillæg til spot-prisen. Tariffer og priser – det værste åbne datasæt? Som om det ikke er uoverskueligt nok i sig selv, bliver vi nødt til at snakke om datasættet Datahub Price List . Der er flere åbenlyse problemer med det: Der er flere felter man burde filtrere efter, men hvor der ikke findes en udtømmende liste over værdier, f.x. netselskab “ChargeOwner”. Det bedste man kan gøre er at downloade, hvor man så løber ind i at download kun giver 100.000 rækker – og datasættet er fuldt på over 300.000 rækker. ChargeTypeCode er per selskab – og uden systematik. Så for hvert enkelt selskab skal man finde ud af hvilken priskode de bruger for C-tariffen. Og hvad når det ændrer sig? ValidTo kan være udeladt og dermed et open ended interval, og prisen gælder så indtil data retroaktivt ændres. Det betyder også at man ikke kan filtrere på datoer, da prisen på 1. april kan være en række der har en ValidFrom 1. januar (eller tidligere). Price1-24: dette er selve timetarif-priserne. Hvis en pris ikke er udfyldt gælder Price1 – hvorfor I alverden dog tilføje den ekstra kompleksitet!?!?! For ikke at tale om tidszoner: man må antage (det er ikke dokumenteret) at alle datoer og timetal er angivet i hvad end tid der er gældende i Danmark på pågældende dato. Dette giver så problemer ved skift fra sommer-/normal-tid hvor en time gentages eller udelades: hvilken timesats bør bruges i et døgn der har 23 eller 25 timer? Giv mig nu bare elprisen.somjson.dk ! Efter at have regnet de fleste af de ovenstående problemer ud, skrev jeg en API-proxy der udstiller det API man i virkeligheden vil have: givet en dato, og et elselskab (eller en adresse), returnerer den prisen time for time som et JSON dokument . Prisen er typisk tilgængelig fra kl. 13 dagen før. Som bonus får man også CO2 udledningen med, hvis den er tilgængelig (typisk kl. 15 dagen før). Det er implementeret som en ren API proxy, dvs. det er ren omskrivning af input og data og ikke andet. Det hele er open source, men der kører en version på elprisen.somjson.dk som frit kan benyttes. Alternativer Der findes andre API’er der opfylder forskellige use-cases: Min Strøm API er rigtig modent og har egen forecast model der kan forecaste 7 dage frem, før priserne er låst på Energi Data Service. Kræver en API nøgle og er uden kildekode HomeAssistant energidataservice virker kun med Home Assistant, men fungerer på samme måde mod Energi Data Service. Strømligning API kan bruges til at udregne priser baseret på historisk forbrugsdata. Kan dog også bruges til at hente de forecastede priser. Med rate limiting, og uden kildekode. Carnot har også et åbent API og egen forecast model. Kræver API nøgle, og er uden kildekode. Billigkwh.dk har et åbent API til elpriser der også inkluderer de forskellige elselskabers abonnement. Comments (0) | okt 9 World’s Longest Multi-Cutter Blade: 30 cm Posted on onsdag, oktober 9, 2024 in Hal9k , Planets , Woodworking I had a need for an extra-extra long multi-cutter blade, so we made one in Hal9k . Until proven otherwise, we hereby claim it to be the world’s longest, at about 30 cm from rotation point to the cutting edge. Converting Starlock-MAX to Starlock-Plus Initially I thought I could get away with just a 80mm long Bosch MAIZ 32 APB which seems to be the longest commercially available. First problem was that my multi-cutter was only “Starlock-Plus” and this blade is Starlock-MAX. Turns out, you can easily get around that: just drill up the hole to 10mm, and it fits like a glove, at least on the Starlock-Plus Bosch GOP 18V-28 . World record time But as it turns out, I needed more length, and anything worth doing is worth overkilling! So sacrificing an old worn-out blade by welding on some 2mm steel plate provided a good base that would still attach to the multi-cutter. First attempt was just attaching the blade with two 2mm screws, as these are the largest that will fit in the star’s spikes and thereby prevent rotation. Initial testing: So next solution was to beef up with a central 8mm bolt instead. This worked much better if torqued enough (read: all you possibly can!), test-run went great after the initial oscillations: And ultimately the cut in the tight corner was made, one-handedly in order to be able to film: Great success! This should not be considered safe, and several warranties were probably voided, but it got the job done. Comments (2) | feb 15 Reparation af Nordlux IP S12 badeværelseslampe der ikke lyser længere Posted on torsdag, februar 15, 2024 in Danish , Hal9k , Planets Denne badeværelseslampe er udgået af produktion, og pga. monteringen og at man ofte har mere end én er det noget træls at skulle udskifte – det giver ihvertfald en del skrot uden grund. Heldigvis er konstruktionen super simpel: det er udelukkende en LED driver (230V AC til 24V DC) og en LED. Lad os starte med det nemme: LED-driveren er direkte tilgængelig bagfra, og med lidt forsigtighed kan spændingen udmåles. I dette tilfælde var der ca. 24V DC, og det er jo fint indenfor specifikationen. Selve LED’en er lidt sværere at komme til: fronten af glasset skal drejes af via de to huller deri. Jeg brugte en låseringstang af ca. korrekt dimension, med lidt forsigtighed. Lidt ridser gør nok ikke det store når lyset skinner. LED’en kan nu loddes af. En ny LED kan købes for ca. 10 kr, f.x. på AliExpress. Det rigtige søgterm er måske “Bridgelux 2020 COB LED”, jeg endte med en 7W i Warm White (3000 Kelvin). Efter lidt fidlen og lodden er den nye LED monteret, og kan testes. Stor succes! Comments (0) | okt 28 Fantus-button part 2: the physical button build and the network communication Posted on lørdag, oktober 28, 2023 in Hal9k , Planets First part of this series is here, covering the reverse engineering of the DRTV Chromecast App. I wanted the physical appearance to be extremely minimalistic, with slight references to various cubes from videogames. Because it is a remote control, it of course has to be wireless and battery-powered. The box is lasercut from 6 mm MDF , and with a giant red arcade button on top with a red LED inside. The electronics inside is a battery-powered Wemos D1 , along with 4 x 18650 Lithium battery cells. After some experimentation on the response time, which is primarily dominated by the time it takes to reconnect to the WiFi network, I initially only used “light sleep”. This resulted in a battery time of just over a week, which is okay, but not great. In order to preserve battery deep sleep would be really nice. The problem is deep sleep on the Wemos can only be interrupted by a reset. The idea was to use a MOSFET (in this case an N-channel logic level mosfet, IRFZ44N ) for the Wemos to be able to select whether a press of the button should reset it, or it should just register on a pin as normal. This circuit allows RST to be pulled low by the button, as long as D0 is high. Luckily, D0 is high during deep sleep , so as long as the Arduino code keeps D0 low button presses will not reset — but can still be registered by reading pin D1. This works out “responsively enough” because the initial start has some delay due to the Chromecast initializing the app and loading media. Any subsequent button presses within the 30 seconds the Arduino stays awake are instant though. With this setup the battery life is not a problem – I’ve only had to charge it once. As a bonus feature/bug whenever the battery gets low the Wemos will trigger a bit sporadically: this causes “Fantus-bombing” where Fantus will just randomly start; quite quickly thereafter the Fantus-button is being charged 😉 The Wemos itself is not powerful enough to do all the pyChromecast communication needed , so I setup a small Raspberry Pi to handle that part. Since I didn’t want to spend too much time and effort setting up the communication between them, I ended up using a trick from my youth: UDP broadcasting. Because UDP is datagram-oriented you can send a UDP packet to the broadcast address ( 255.255.255.255 ) and then it will be received by all hosts on the local area network: no configuration needed. In Arduino code it looks like: Udp.begin(31337); Udp.beginPacket("255.255.255.255", 31337); Udp.write("emergency-button\n"); Udp.endPacket(); ( Full Arduino code available here .) At this point I had a UDP packet that I could receive on the Raspberry Pi, and it was just a matter of writing a small server program to listen, receive and process those UDP commands. However, at this point a thought entered my mind, that derailed the project for a while: netcat | bash Why write my own server to parse and execute commands, when Bash is already fully capable of doing exactly that with more flexibility than I could ever dream of? And netcat is perfectly capable of receiving UDP packets? This is a UNIX system , after all, and UNIX is all about combining simple commands in pipelines — each doing one thing well. The diabolical simplicity of just executing commands directly from the network was a bit too insecure though. This is where Bash Restricted mode enters the project: I wouldn’t rely on it for high security (since it is trying to “ enumerate badness “), but by locking down the PATH of commands that are allowed to execute it should be relatively safe from most of the common bypass techniques : netcat -u -k -l 31337 | PATH=./handlers/ /bin/bash -r The project was now fully working: press the button, Fantus starts. Press it while Fantus is playing: Fantus pauses. Press it while Fantus is paused: Fantus resumes. The little human was delighted about his new powers over the world, and pressed the button to his hearts content (and his parents slight annoyance at times). ( Full code for handler available here .) But wouldn’t it be cool if the little human had a (limited) choice in what to view?… Comment (1) | jul 18 Fantus-button part 1: Reverse engineering the DRTV Chromecast App Posted on tirsdag, juli 18, 2023 in Hal9k , Planets I want to build a physical giant red button, that when pressed instantly starts a children’s TV-show, in my case Fantus on DRTV using a Chromecast. The first part of the build is figuring out how to remotely start a specific video on a Chromecast. Initially I thought this would be pretty simple to do from an Arduino, because back in the day you could start a video just using a HTTP request . Very much not so anymore: the Chromecast protocol has evolved into some monster using JSON inside Protobuf over TLS/TCP, with multicast DNS for discovery . Chance of getting that working on a microcontroller is near-zero. But remote control is possible using e.g. pychromecast which has support for not only the usual app of YouTube, but also a couple of custom ones like BBC. Let’s try and add support for DRTV to pychromecast, starting at the hints given on adding a new app . Using the netlog-viewer to decode the captured net-export from Chrome, and looking at the unencrypted socket communication, the appId of the DRTV app is easily found. However, one of the subsequent commands has a lot more customData than I expected, since it should more or less just be the contentId that is needed: { "items": [ { "autoplay": true, "customData": { "accountToken": { "expirationDate": "2022-07-02T00:48:35.391Z", "geoLocation": "dk", "isCountryVerified": false, "isDeviceAbroad": false, "isFallbackToken": false, "isOptedOut": false, "profileId": "c4e0...f3e", "refreshable": true, "scope": "Catalog", "type": "UserAccount", "value": "eyJ0eX...Dh8kXg" }, "chainPlayCountdown": 10, "profileToken": { "expirationDate": "2022-07-02T00:48:35.389Z", "geoLocation": "dk", "isCountryVerified": false, "isDeviceAbroad": false, "isFallbackToken": false, "isOptedOut": false, "profileId": "c4e0a...f3e", "refreshable": true, "scope": "Catalog", "type": "UserProfile", "value": "eyJ0eXAi...IkWOU5TA" }, "senderAppVersion": "2.211.33", "senderDeviceType": "web_browser", "sessionId": "cd84eb44-bce0-495b-ab6a-41ef125b945d", "showDebugOverlay": false, "userId": "" }, "media": { "contentId": " 278091 ", "contentType": "video/hls", "customData": { "accessService": "StandardVideo" }, "streamType": "BUFFERED" }, "preloadTime": 0, "startTime": 0 } ], "repeatMode": "REPEAT_OFF", "requestId": 202, "sessionId": "81bdf716-f28a-485b-8dc3-ac4881346f79", "startIndex": 0, "type": "QUEUE_LOAD" } Here I spent a long time trying without any customData , and just using the appId and contentId . Initially it seemed to work! However, it turned out it only worked if the DRTV Chromecast app was already launched from another device. If launched directly from pychromecast the app would load, show a spinner, and then go back to idle. Here much frustration was spent; I guess the customData is actually needed. And indeed, putting that in works! But where do these tokens come from, and how do we get those tokens from Python? Using Chrome’s developer tools (F12) on the DRTV page, and then searching globally (CTRL-SHIFT-f) for various terms (“expirationDate”, “customData”, “profileToken”, “accountToken” etc.) revealed some interesting code, that was as semi-readable as any pretty-printed minifyed Javascript. Eventually I found the tokens in local storage: Using these tokens work really well, and allows starting playback! Some further exploration proceeded: using the showDebugOverlay flag reveals that the DRTV player is just a rebranded Shaka Player . The autoplay functionality can be disabled by setting chainPlayCountdown to -1 , which is honestly a real oversight that it cannot be disabled officially, to not have to rush to stop the playback of the item before the next autoplays. With all the puzzle pieces ready, I prepared a pull request (still open) to add support for DRTV to pychromecast . Fantus-button part 2 will follow, detailing the hardware build and network integration with the support from pychromecast. Comment (1) | feb 20 Floating Solid Wood Alcove Shelves Posted on mandag, februar 20, 2023 in Hal9k , Planets , Woodworking I have an alcove where I wanted to put in some floating shelves. I wanted to use some solid wood I had lying around, to match the rest of the interior; this ruled out most of the methods described online: (i) building up the shelf around a bracket , and (ii) using hidden mounting hardware would be hard to get precise and would not provide support on the sides. So inspired by some of the options instead I tried to get by with just brackets on the three sides, in a solid wood shelf. I ended up with 12mm brackets of plywood in a 26mm solid wood shelf, and that was plenty sturdy. Step 1 was to cut out the rough shelves, with plenty of extra width, and rough fitting the plywood bracket pieces. It makes sense to leave as much on the top of the slit as possible, as this will be the failure point if overloaded. The excellent wood workshop at Hal9k came in very handy! Step 2 was to mount the plywood brackets in the alcove. Pretty easy to do using a laser level, biggest problem was getting the rawplugs in precise enough for the level to be kept. Step 3 was fitting the shelves individually, accounting for the crookedness of the 3 walls. The scribing method used by Rag’n’Bone Brown was pretty useful , just doing it in multiple steps to make sure not to cut off too much. Finally, all the shelves in final mounting. Getting them in took a bit of persuasion with a hammer, and minor adjustments with a knife to the plywood brackets, as it was a tight fit. The key again was small adjustments. One concern with such a tight fit would be wood movement; however most of the wood movement is “across the grain” which in this application means “in and out” from the alcove, where the wood is basically free to move as the shelves are not fastened to the brackets in any way. Another concern would be if the relatively small brackets (12x12mm) can handle the load of the relatively wide shelves (60cm wide, 35cm deep, and 2.6cm high). There are two failure scenarios: (i) the wood could split above the slit, (ii) or the bracket could deform or be pulled out. Neither seems likely as (i) applying a static (or even dynamic) load large enough to split the wood seems implausible, even at the weakest point in the middle of the front, and (ii) the tight fit counteracts the brackets ability to be pulled out since pulling out in one side would have the shelf hitting the wall on the opposite side. All in all a very satisfying project to work on and complete! Comments (0) | dec 15 Quick and dirty guide to Lithium battery-powered Wemos D1 Mini Posted on torsdag, december 15, 2022 in Hal9k The Wemos D1 Mini is an ESP8266 based prototyping board with WiFi connectivity and countless applications. It becomes even more useful in battery-powered applications, where with the proper setup, it can run low-powered for months at a time — or only hours if done incorrectly. This is the quick and dirty guide to running a Wemos D1 Mini powered by Lithium-Ion batteries: We will be blatantly ignoring several design specifications, so double check everything before using in a critical project. Several things will vary, and since there is plenty of clones of the board some boards will work better than others. Warning: Lithium-Ion batteries always command healthy respect, due to the energy they store! Do not use bad cells, and do not leave batteries unattended in places where a fire can develop, especially while charging. That being said, the setup given here should be as safe as most other Lithium-Ion battery projects. Why run off a battery? You chose a Wemos D1 because you want to do some WiFi connectivity. This narrows down the useful modes from the overwhelming large table of possibilities . The approach will be slightly different depending on why you want to run off a battery. There are 3 main usecases: Periodically wake up on a timer, do some work, connect to WiFi, and go back to sleep. Here we can utilize the deep sleep mode of the ESP8266, and get lifetimes in months. Wake up based on an external pin trigger, do some work, connect to WiFi, and go back to sleep. Here we can also utilize deep sleep , and get lifetimes in weeks/months. React with low latency to an external pin, do some work, and go to sleep while still connected to WiFi. Here we can utilize light sleep , but only get lifetimes in hours/days. Hardware setup The hardware needed is: Wemos D1 Mini TP4056 module with “discharge protection” , most modules with more than one chip has this, but be careful! Lithium-Ion battery, e.g. a 18650 cell, and probably a holder for the battery What you don’t want is anything resembling a power bank or battery shield with a regulated output (5V or 3V). These are practically useless, simply a more expensive battery holder! Two reasons: poorly built (I have several where standby is prevented by pulling 100 mA through a resistor!), and you don’t want a switching mode power supply. The keyword here is “quiescent current”: an SMPS can easily consume 5-10 mA continuously, which could very likely be the majority of the current draw. Wiring diagram. Waking on a timer – deep sleep Full code example for deep sleeping on a timer. To start deep sleep for a specified period of time: //Sleep for some time; when waking everything will be reset and setup() will run again ESP.deepSleep(30 * MICROSECONDS_PER_SEC); Note that you can’t safely sleep for more than approximately 3 hours . Power usage is approx 0.3–0.4mA when deep sleeping. Keep in mind that after waking from the timer the chip will be reset, meaning no state is available, and WiFi will have to reconnect. Reconnecting to WiFi can be anything from 3–10 seconds or even longer, meaning that will be a delay before the program can resume. Waking on an pin trigger (reset) Full code example for deep sleeping waiting for a pin trigger. The code is exactly the same as waking on a timer, with one exception: //Sleep until RESET pin is triggered ESP.deepSleep(0); The chip will be effectively comatose, sleeping until a RESET is triggered. Same caveats apply: waking up the program is restarted, and reconnecting to WiFi will be a delay. Stay connected – low latency Full code example for light sleeping connected to WiFi waiting for a pin trigger. Note that the button should be connected to D3 for this example, not RST. The key parts are: void setup() { ... WiFi.setSleepMode(WIFI_LIGHT_SLEEP, 3); // Automatic Light Sleep } void loop() { ... delay(350); // Any value between 100--500 will work, higher value more power savings // but also slower wakeup! } Simply delaying will bring power savings — simple and easy! When awake power consumption is around 75mA. Average power consumption when light sleeping with delay(200) is around 45 mA, with delay(350) and larger is around 30–40mA. Measuring battery depletion The ESP can measure it’s internal VCC supply voltage, and because the battery will start dropping below the rated 3.3V before it is depleted, this allows to get an warning when the battery starts to deplete. ADC_MODE(ADC_VCC); void loop() { if (ESP.getVcc() < 2800) { //Do something to warn of low battery } } In my experience the Vcc reading will drop below 2800 when the battery starts to be depleted. ADC readings vs. battery voltage Note that measuring the VCC while connected with USB is not possible, as the USB connection will pull up the battery and the 5V rail to 5V! Calculating battery life Here is a quick calculator for how long your Wemos D1 Mini can stay powered Number of batteries (assuming 2000 mAh capacity): Capacity (mAh): Deep sleep Waking up every (minutes): (conservatively assumes base load 1mA, 10 secs burst of 100mA for every wakeup), resulting in Average Consumption (mA): – Light sleep Average Consumption (mA): – Of course the consumption can be brought even lower: some chips are unused but partly connected and will have some leakage (LEDs, USB chip on the Wemos). Making it even leaner is outside the scope of quick and dirty. Comments (12) | « Previous Posts Categories Danish Hal9k Ikke kategoriseret Planet Ubuntu-DK Planets Sysadmin'ing Ubuntu University Woodworking © blog.smartere . All Rights Reserved. WordPress Theme designed by Chris Wallace | 2026-01-13T08:48:58 |
https://dev.to/shree_abhijeet/ai-augmented-cloud-operations-4c3p | AI-Augmented Cloud Operations - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse Abhijeet Yadav Posted on Jan 7 AI-Augmented Cloud Operations # aws # serverless # aiops # automation I've spent the last year buried in AWS stuff. You know, chasing CloudWatch alerts, digging through logs, hunting weird cost spikes, and sorting random errors that pop up right when you want to call it a day. Cloud-ops isn't that smooth Afterall. Actually, it's getting way louder with alarms going off nonstop. Think about it. Monday rolls around and RDS CPU spikes so high for no reason. Tuesday hits with a Lambda retrying over and over in some endless loop. Come Wednesday, a cost alert keeps beeping because that Staging(testing) EC2 server never got shut down or just like me when I forgot to stop the policy of AMI & Snapshots. (It actually burnt my 262$ when I ignored the Alerts.) If you've messed with AWS a bit, you totally get the routine. Then it hit me hard. Most of our work, close to 70 percent, boils down to the same grind. We analyze logs. Recap the chaos. Pinpoint what failed. Guess the real culprit. Wash, rinse, repeat every week. Things shifted when I troubleshot a client's Lambda glitch using CloudWatch and Bedrock. I stumbled into a setup where the AI ripped through a huge log file. It summed everything up and zeroed in on the problem within seconds. Way quicker than me pounding coffee over a screen. That's the aha moment. AI won't take over jobs. Instead, it acts like that reliable buddy who stays up all night. It catches patterns we overlook and lets us tackle bigger challenges. I kept experimenting after that. Linked Bedrock with CloudWatch, Lambda, Code-Commit for code trails, Cost Explorer data, plus Slack alerts. Suddenly the whole thing locked into place. AWS lays it all out ready to go. Logs, metrics, events, billing details, repos, old incident records, models that actually reason through stuff. Observing It smartly and we can build an AI helper that runs around the clock like a solid junior dev. No futuristic talk. This runs right now in real accounts. How I assembled it step by step, using actual services and headaches I fixed, with code anyone can fire up. But not like any dry tutorials, this is just my numerous Attempts and trying different ways until I get the solution and hit the spot. I didn’t plan any of this properly. It sort of came together while handling a random RDS CPU alert. The alarm fired (again), and instead of going through the usual drill, I thought I’d quickly put something in place to save myself the back-and-forth. So the first thing I did was open the CloudWatch alarm to check the settings, mainly to confirm the threshold and the evaluation period. Since this is part of the story anyway. After confirming the alarm settings, I jumped into the logs. I wanted Lambda to automatically pick up a small window of logs, so I opened the RDS log group to see what format and timestamps I’d be dealing with. Once I saw the structure, I created a simple Lambda function. Nothing fancy Python, default runtime, one file. The idea was: Setting Up Slack and Wiring the Notifications Once I had the basic flow in my head, the next thing I needed was a clean way to get alerts somewhere I actually check. Email works sometimes, but Slack is where most of us live anyway. So I created a small Slack app just for this setup. The moment you open the Slack developer page, it looks something like this. All I had to do was enable incoming webhooks for the workspace. Then Slack asked me where exactly I wanted the messages to appear. I picked a fresh channel I made only for this experiment, mostly so I could keep the noise separate from everything else. After approving it, Slack generated the webhook URL. This is the only thing Lambda needs to trigger messages into that channel. I didn’t want to hardcode this webhook into Lambda though. Storing secrets in code is a recipe for embarrassment later. So I opened Secrets Manager and created a new secret for the webhook. With that done, the notification path was ready. Slack would receive the message. Secrets Manager would hold the sensitive piece. And Lambda would glue the two together. Alarm fires → Lambda gets event → fetch 10 mins logs → send to Bedrock. Wiring Slack into the Flow Once the idea was clear, I needed a place where all this noise could land. Slack was the obvious choice. I created a small Slack app just for this project. Nothing fancy, just a name, a workspace, and a clean slate. Then I enabled incoming webhooks so external services could post messages into a channel . After that, Slack asked which channel should receive the alerts. I created a fresh channel named #ai-ops and approved the app. Once approved, Slack generated the webhook URL. That tiny URL is the bridge between AWS and my phone lighting up at 2 AM. Hiding the Webhook Where It Belongs Hardcoding the webhook into Lambda felt wrong, so I pushed it into Secrets Manager. Setting Up Secrets and Notifications Once the basic pieces started forming, I observed that I needed somewhere to store the Slack webhook properly. I could not do Hardcoding into Lambda, it felt messy and also slightly dangerous, so I moved it into Secrets Manager. It took just a minute but instantly made the whole thing feel cleaner. Almost like, ok fine, now this setup looks more aligned. After saving, the secret was sitting quietly in AWS, invisible to anyone who doesn’t have permission. This one step instantly made the setup feel less hacky and more production-ish. The Lambda That Holds Everything Together Now came the dispatcher. I created a new Lambda function using Python. No layers, no frameworks, just a single file. Then I added environment variables so Lambda would know: which bucket to write to where the Slack secret lives which region it is running in After saving, the configuration finally looked complete. At this point, the plumbing was done. Pressing Run and Watching It Come Alive I triggered the Lambda manually using a small test payload: Within seconds, Slack pinged. Not a test message, A real alert from something I just built. Capturing the Full Story in S3 Every execution drops a JSON file into S3. That file contains the logs, timestamps, event data and whatever analysis is produced. And when I opened the results folder, the structure was clean and traceable. How Everything Is Actually Connected This is the entire setup I have running today. No Bedrock yet. No heavy ML. Just automation that removes one painful step from my daily cloud routine. What This Actually Changed I didn’t build this system because I wanted to “do AI in the cloud”. I built it because I was tired of reacting blindly. Before this, every alert meant the same ritual. Open CloudWatch. Scroll through logs. Guess which 3 lines out of 50,000 actually mattered. Hope I didn’t miss the real problem. Now the flow is different. An alarm fires. A message hits Slack. A full execution trace lands in S3. By the time I even open the console, the context is already waiting for me. That changes the entire mental state. You don’t start from confusion anymore. You start from evidence. What surprised me most is how small the system is. 1. One Lambda. 2. One secret. 3. One S3 folder. 4. One Slack channel. That’s enough to cut out a painful slice of daily cloud work. And the future part isn’t some wild AI promise. It’s extremely practical. This same pattern can listen to cost anomalies. It can watch WAF logs. It can monitor security events. It can summarise incidents before anyone joins the bridge call. Not replacing engineers. Not auto-fixing production blindly. Just making sure the first thing you see is signal, not noise. That’s the kind of automation I actually want in my career. Quiet, Helpful And already working in my account today. Top comments (0) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse Abhijeet Yadav Follow AWS Community Builder | Skilled in multi-platform solutions, currently in Windows Enterprise Team managing Windows workloads, AD, and AWS services for secure, scalable environments Location Kolkata,India Work Associate Cloud Engineer Joined Apr 6, 2025 Trending on DEV Community Hot How I Built an AI Terraform Review Agent on Serverless AWS # aws # terraform # serverless # devops I Am 38, I Am a Nurse, and I Have Always Wanted to Learn Coding # career # learning # beginners # coding Prompt Engineering Won’t Fix Your Architecture # discuss # career # ai # programming 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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https://dev.to/aspire-softserv | Aspire Softserv - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Follow User actions Aspire Softserv Aspiresoftserv is a leading IT services and consulting company delivering innovative, scalable, and cost-effective digital solutions. Location Dover, Delaware USA, Joined Joined on Aug 4, 2023 Personal website https://www.aspiresoftserv.com More info about @aspire-softserv Badges Two Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least two years. Got it Close One Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least one year. Got it Close Writing Debut Awarded for writing and sharing your first DEV post! Continue sharing your work to earn the 4 Week Writing Streak Badge. Got it Close Skills/Languages seo, content writing, digital marketing, lead generation, b2b marketing, branding Post 34 posts published Comment 0 comments written Tag 0 tags followed Why Product Roadmaps Break Down When Business and Engineering Teams Aren't Aligned Aspire Softserv Aspire Softserv Aspire Softserv Follow Jan 12 Why Product Roadmaps Break Down When Business and Engineering Teams Aren't Aligned Comments Add Comment 5 min read Cloud Cost Optimization: Engineering-Led Strategy to Reduce AWS & GCP Spend by 30-50% Aspire Softserv Aspire Softserv Aspire Softserv Follow Jan 12 Cloud Cost Optimization: Engineering-Led Strategy to Reduce AWS & GCP Spend by 30-50% # aws # cloud # devops Comments Add Comment 5 min read Improve Product Traceability and Quality in Manufacturing with Odoo ERP Aspire Softserv Aspire Softserv Aspire Softserv Follow Jan 9 Improve Product Traceability and Quality in Manufacturing with Odoo ERP Comments Add Comment 4 min read Prevent Production Downtime with Odoo ERP Software Development Aspire Softserv Aspire Softserv Aspire Softserv Follow Jan 8 Prevent Production Downtime with Odoo ERP Software Development Comments Add Comment 4 min read Why Minimum Viable Products Fail and What High-Growth Teams Do Differently Aspire Softserv Aspire Softserv Aspire Softserv Follow Jan 5 Why Minimum Viable Products Fail and What High-Growth Teams Do Differently # leadership # product # productivity # startup Comments Add Comment 6 min read Ensure Manufacturing Compliance with Odoo ERP Software Development Aspire Softserv Aspire Softserv Aspire Softserv Follow Dec 30 '25 Ensure Manufacturing Compliance with Odoo ERP Software Development Comments Add Comment 5 min read Post-Migration Best Practices to Maximize Odoo ERP Benefits Aspire Softserv Aspire Softserv Aspire Softserv Follow Dec 25 '25 Post-Migration Best Practices to Maximize Odoo ERP Benefits Comments Add Comment 5 min read How to Accelerate Release Cycles Without Hiring More Engineers Aspire Softserv Aspire Softserv Aspire Softserv Follow Dec 22 '25 How to Accelerate Release Cycles Without Hiring More Engineers # automation # cicd # productivity # devops Comments Add Comment 8 min read Odoo Migration Challenges and How to Overcome Them Aspire Softserv Aspire Softserv Aspire Softserv Follow Dec 22 '25 Odoo Migration Challenges and How to Overcome Them # odoo # odoomigrationservices # odooerpdevelopment Comments Add Comment 5 min read Your 2026 Automation Roadmap: A Practical Guide for Teams with Limited Engineering Capacity Aspire Softserv Aspire Softserv Aspire Softserv Follow Dec 18 '25 Your 2026 Automation Roadmap: A Practical Guide for Teams with Limited Engineering Capacity Comments Add Comment 5 min read Product Feature ROI: ROI Signals to Check Before Funding Your Next Feature Aspire Softserv Aspire Softserv Aspire Softserv Follow Dec 17 '25 Product Feature ROI: ROI Signals to Check Before Funding Your Next Feature # roi # softwarefeatureroi # productengineeringservices Comments Add Comment 5 min read Step-by-Step Overview of the Odoo Migration Process Aspire Softserv Aspire Softserv Aspire Softserv Follow Dec 17 '25 Step-by-Step Overview of the Odoo Migration Process # odoomigrationservices # odoo # migration # odoodevelopment Comments Add Comment 5 min read Why Your Business Should Upgrade to the Latest Odoo Version? Aspire Softserv Aspire Softserv Aspire Softserv Follow Dec 12 '25 Why Your Business Should Upgrade to the Latest Odoo Version? 1 reaction Comments Add Comment 5 min read Why Manufacturers Choose Odoo ERP for Real-Time Inventory Control? Aspire Softserv Aspire Softserv Aspire Softserv Follow Dec 12 '25 Why Manufacturers Choose Odoo ERP for Real-Time Inventory Control? 1 reaction Comments Add Comment 5 min read How Healthcare Firms Automate HIPAA Compliance with Product Engineering Services Aspire Softserv Aspire Softserv Aspire Softserv Follow Dec 9 '25 How Healthcare Firms Automate HIPAA Compliance with Product Engineering Services Comments Add Comment 5 min read Automation-First Automation-First Engineering: Removing Manual Bottlenecks with CI/CD & IaC Aspire Softserv Aspire Softserv Aspire Softserv Follow Dec 8 '25 Automation-First Automation-First Engineering: Removing Manual Bottlenecks with CI/CD & IaC Comments Add Comment 7 min read Selecting the Right Product Engineering Partner: 8 Questions CEOs Should Ask Aspire Softserv Aspire Softserv Aspire Softserv Follow Dec 8 '25 Selecting the Right Product Engineering Partner: 8 Questions CEOs Should Ask Comments Add Comment 6 min read Product Engineering for Fintech Startups: Accelerating Compliance and Growth Aspire Softserv Aspire Softserv Aspire Softserv Follow Dec 4 '25 Product Engineering for Fintech Startups: Accelerating Compliance and Growth # startup # product # security # architecture Comments Add Comment 4 min read Streamlining Quality Control in Manufacturing with Odoo ERP Implementation Aspire Softserv Aspire Softserv Aspire Softserv Follow Nov 20 '25 Streamlining Quality Control in Manufacturing with Odoo ERP Implementation Comments Add Comment 6 min read How HR Tech Products Use Product Engineering to Stay Compliant & Scalable Aspire Softserv Aspire Softserv Aspire Softserv Follow Nov 19 '25 How HR Tech Products Use Product Engineering to Stay Compliant & Scalable Comments Add Comment 4 min read From Prototype to Launch: How Mid-Market Firms Can Speed Time-to-Market by 40% Aspire Softserv Aspire Softserv Aspire Softserv Follow Nov 14 '25 From Prototype to Launch: How Mid-Market Firms Can Speed Time-to-Market by 40% Comments Add Comment 5 min read How Healthcare Companies Build Secure, Compliant Products with Product Engineering Aspire Softserv Aspire Softserv Aspire Softserv Follow Nov 12 '25 How Healthcare Companies Build Secure, Compliant Products with Product Engineering # healthcare # product # engineering # productengineering Comments Add Comment 5 min read Avoiding Hidden Costs: The True Price of Technical Debt in Growing Products Aspire Softserv Aspire Softserv Aspire Softserv Follow Nov 10 '25 Avoiding Hidden Costs: The True Price of Technical Debt in Growing Products # product # productengineeringservices # costcut Comments Add Comment 5 min read What Does Odoo Migration Really Cost? A Transparent Pricing Breakdown for 2025 Aspire Softserv Aspire Softserv Aspire Softserv Follow Nov 7 '25 What Does Odoo Migration Really Cost? A Transparent Pricing Breakdown for 2025 # management # opensource # resources 1 reaction Comments Add Comment 6 min read How Odoo ERP Development Solves Production Scheduling Challenges in Manufacturing? Aspire Softserv Aspire Softserv Aspire Softserv Follow Nov 6 '25 How Odoo ERP Development Solves Production Scheduling Challenges in Manufacturing? Comments Add Comment 5 min read Product Engineering Services for Finance: Compliance, Automation & AI Integration Aspire Softserv Aspire Softserv Aspire Softserv Follow Nov 6 '25 Product Engineering Services for Finance: Compliance, Automation & AI Integration Comments Add Comment 6 min read Product Engineering Services for HR Compliance: Building Secure and GDPR-Ready Digital Platforms Aspire Softserv Aspire Softserv Aspire Softserv Follow Nov 5 '25 Product Engineering Services for HR Compliance: Building Secure and GDPR-Ready Digital Platforms Comments Add Comment 6 min read Automation in Product Engineering: Cut Costs & Time Aspire Softserv Aspire Softserv Aspire Softserv Follow Nov 5 '25 Automation in Product Engineering: Cut Costs & Time # automation # productengineeringservices Comments Add Comment 5 min read 7 Signs You Need Digital Product Engineering Services to Stay Competitive Aspire Softserv Aspire Softserv Aspire Softserv Follow Nov 4 '25 7 Signs You Need Digital Product Engineering Services to Stay Competitive Comments Add Comment 5 min read How Healthcare Firms Automate HIPAA Compliance with Product Engineering Services Aspire Softserv Aspire Softserv Aspire Softserv Follow Oct 30 '25 How Healthcare Firms Automate HIPAA Compliance with Product Engineering Services 2 reactions Comments Add Comment 3 min read Top Key Features to Look for in an Odoo ERP Development Partner Aspire Softserv Aspire Softserv Aspire Softserv Follow Oct 3 '25 Top Key Features to Look for in an Odoo ERP Development Partner # odoo # odooerpdevelopment 1 reaction Comments Add Comment 4 min read Tackling Fraud Detection in Fintech with Machine Learning App Solutions Aspire Softserv Aspire Softserv Aspire Softserv Follow Sep 24 '25 Tackling Fraud Detection in Fintech with Machine Learning App Solutions Comments Add Comment 4 min read How Liferay is Reshaping Healthcare Digital Transformation in 2025? Aspire Softserv Aspire Softserv Aspire Softserv Follow Sep 10 '25 How Liferay is Reshaping Healthcare Digital Transformation in 2025? # liferay # healthcare # digitaltransformation Comments Add Comment 5 min read Overcoming Challenges in DevOps Implementation: Strategies for Success Aspire Softserv Aspire Softserv Aspire Softserv Follow Aug 31 '23 Overcoming Challenges in DevOps Implementation: Strategies for Success Comments Add Comment 2 min read loading... 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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Integrations Integrations Overview Amplitude Integration ClickUp Integration Discord Integration Electron Support Front Integration GitHub Integration Grafana Integration Overview Setup Dashboards Alerts Height Integration Intercom Integration Jira Integration LaunchDarkly Integration Linear Integration Mixpanel Integration Nuxt Integration Pendo Integration Segment Integration Slack Integration Vercel Integration WordPress Plugin Highlight.io Changelog Overview Changelog 12 (02/17) Changelog 13 (02/24) Changelog 14 (03/03) Changelog 15 (03/11) Changelog 16 (03/19) Changelog 17 (04/07) Changelog 18 (04/26) Changelog 19 (05/22) Changelog 20 (06/06) Changelog 21 (06/21) Changelog 22 (08/07) Changelog 23 (08/22) Changelog 24 (09/11) Changelog 25 (10/03) Changelog 26 (11/08) Changelog 27 (12/22) Changelog 28 (3/6) Changelog 29 (4/2) Getting Started Getting Started with Highlight Fullstack Mapping Browser React.js Next.js Remix Vue.js Angular Gatsby.js SvelteKit Electron highlight.run SDK Overview Canvas & WebGL Console Messages Content-Security-Policy Identifying Users iframe Recording Monkey Patches Browser OpenTelemetry Persistent Asset Storage Privacy Proxying Highlight React.js Error Boundary Recording Network Requests and Responses Recording WebSocket Events Salesforce Lightning Web Components (LWC) Data Export Sourcemap Configuration Tracking Events Troubleshooting Upgrading Highlight Versioning Sessions & Errors Other React Native (beta) Server Go Overview chi Echo Fiber Gin GORM gqlgen Logrus Manual Tracing gorilla mux JS Overview Apollo AWS Lambda Cloudflare Workers Express.js Firebase Hono Nest.js Next.js Node.js Pino tRPC Winston Python Overview AWS Lambda Azure Functions Django FastAPI Flask Google Cloud Functions Loguru Other Frameworks Python AI / LLM Libraries Python Libraries Ruby Overview Other Frameworks Ruby on Rails Rust Overview actix-web No Framework Hosting Providers Overview Metrics in AWS Logging in AWS Logging in Azure Fly.io NATS Log Shipper Logging in GCP Heroku Log Drain Render Log Stream Logging in Trigger.dev Vercel Log Drain Elixir Overview Elixir App Java: All Frameworks PHP: All Frameworks C# .NET ASP C# .NET 4 ASP Docker / Docker Compose File Fluent Forward curl OpenTelemetry Protocol (OTLP) Syslog RFC5424 Systemd / Journald Native OpenTelemetry Overview Error Monitoring Logging Tracing Browser Instrumentation Metrics Fullstack Frameworks Overview Next.js Fullstack Overview Next.js Page Router Guide Next.js App Router Guide Edge Runtime Advanced Config Remix Walkthrough Self Host & Local Dev Overview Development deployment guide. Integrations Microsoft Teams self-hosted Hobby deployment guide. Traefik SSL Proxying. Docs Home SDK Client SDK API Reference Cloudflare Worker SDK API Reference Go SDK API Reference Hono SDK API Reference Java SDK API Reference Next.JS SDK API Reference Node.JS SDK API Reference Python SDK API Reference Ruby SDK API Reference Rust SDK API Reference Docs / Getting Started / Server / Go / GORM Tracing Quick Start GORM Tracing Quick Start Learn how to set up auto-instrumented tracing for your database calls using the GORM library. 1 Configure client-side Highlight. (optional) If you're using Highlight on the frontend for your application, make sure you've initialized it correctly and followed the fullstack mapping guide . 2 Install the Highlight Go SDK. Install the highlight-go package with go get . go get -u github.com/highlight/highlight/sdk/highlight-go 3 Initialize the Highlight Go SDK. highlight.Start starts a goroutine for recording and sending backend traces and errors. Setting your project id lets Highlight record errors for background tasks and processes that aren't associated with a frontend session. import ( "github.com/highlight/highlight/sdk/highlight-go" ) func main() { // ... highlight.SetProjectID("<YOUR_PROJECT_ID>") highlight.Start( highlight.WithServiceName("my-app"), highlight.WithServiceVersion("git-sha"), ) defer highlight.Stop() // ... } 4 Initialize the GORM library with the Highlight hooks Import the Highlight GORM library and call the SetupGORMOTel hook with any attributes wanted for context. import ( "github.com/highlight/highlight/sdk/highlight-go" htrace "github.com/highlight/highlight/sdk/highlight-go/trace" "go.opentelemetry.io/otel/attribute" ) DB, err = gorm.Open(<DB_SETTINGS>) if err := htrace.SetupGORMOTel(DB, highlight.GetProjectID()); err != nil { highlight.RecordError(ctx, err) } 5 Call GORM with the trace context When making any database calls with GORM, attach a WithContext hook to provide more data about the trace. DB.WithContext(ctx).Find(&user) 6 Verify your backend traces are being recorded. Visit the highlight traces portal and check that backend traces are coming in. Gin Quick Start Go gqlgen Quick Start [object Object] | 2026-01-13T08:48:58 |
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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Artificial Intelligence Follow Hide Artificial intelligence leverages computers and machines to mimic the problem-solving and decision-making capabilities found in humans and in nature. Create Post submission guidelines Posts about artificial intelligence. Older #ai posts 7 8 9 10 11 12 13 14 15 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu 📊 2026-01-11 - Daily Intelligence Recap - Top 9 Signals Agent_Asof Agent_Asof Agent_Asof Follow Jan 11 📊 2026-01-11 - Daily Intelligence Recap - Top 9 Signals # tech # programming # startup # ai Comments Add Comment 4 min read # What Is CORS and a Preflight Request? Explained for Developers sudip khatiwada sudip khatiwada sudip khatiwada Follow Jan 11 # What Is CORS and a Preflight Request? Explained for Developers # webdev # programming # ai # javascript Comments Add Comment 3 min read I made a free webapp for learning piano notes Daniel Lefanov Daniel Lefanov Daniel Lefanov Follow Jan 11 I made a free webapp for learning piano notes # webdev # ai # opensource # music Comments Add Comment 1 min read MCP Token Limits: The Hidden Cost of Tool Overload Piotr Hajdas Piotr Hajdas Piotr Hajdas Follow Jan 11 MCP Token Limits: The Hidden Cost of Tool Overload # mcp # devops # ai # opensource Comments Add Comment 5 min read AI: A Child in the Digital Age – Shaping Its Future with Data and Ethics. Kaushik Patil Kaushik Patil Kaushik Patil Follow Jan 10 AI: A Child in the Digital Age – Shaping Its Future with Data and Ethics. # discuss # ai # data # machinelearning Comments Add Comment 3 min read Building Cryptographic Audit Trails for AI Trading Systems: A Deep Dive into RFC 6962-Based Verification VeritasChain Standards Organization (VSO) VeritasChain Standards Organization (VSO) VeritasChain Standards Organization (VSO) Follow Jan 11 Building Cryptographic Audit Trails for AI Trading Systems: A Deep Dive into RFC 6962-Based Verification # ai # regtech Comments Add Comment 15 min read The Irreplaceable Human in the Age of Smart Systems New Riders Labs New Riders Labs New Riders Labs Follow Jan 11 The Irreplaceable Human in the Age of Smart Systems # ai # workflows # humans # future Comments Add Comment 4 min read Quantum Computing Explained in Simple Terms: Part 1 Adnan Arif Adnan Arif Adnan Arif Follow Jan 11 Quantum Computing Explained in Simple Terms: Part 1 # ai # machinelearning # quantumcomputing Comments Add Comment 4 min read Turning Database Schemas into Diagrams & Docs — Open for Early Feedback Rushikesh Bodakhe Rushikesh Bodakhe Rushikesh Bodakhe Follow Jan 11 Turning Database Schemas into Diagrams & Docs — Open for Early Feedback # webdev # programming # ai # beginners 1 reaction Comments Add Comment 1 min read Build something at your own Vishal Thakkar Vishal Thakkar Vishal Thakkar Follow Jan 12 Build something at your own # startup # ai # cloudnative Comments Add Comment 1 min read Can AI Translate Technical Content into Indian Languages? 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https://tinyhack.com/ | Tinyhack.com – A hacker does for love what others would not do for money. --> Skip to content Tinyhack.com A hacker does for love what others would not do for money. CVE-2025-31931 Arbitrary Shared Library Loading in Intel ITT API on Android (affects OpenCV <= 4.10) Intel® Instrumentation and Tracing Technology (ITT) is a profiling API that developers use to analyze performance. The ITT library is available for many platforms. It used by many Android applications, either directly, or indirectly (e.g: via precompiled OpenCV library for Android officially downloaded from OpenCV website). Intel advisory is here: https://www.intel.com/content/www/us/en/security-center/advisory/intel-sa-01337.html A bug was found that allows ITT to load arbitrary shared library. This shared library can do anything (executing arbitrary code, exfiltrating data, etc). Fortunately the exploitation is not that easy (requires adb access either via PC or Shizuku app, so remote exploitation should not be possible). POC is available on my github, but read on to understand this bug. OpenCV copies all ITT API files verbatim to their 3rdparty/ittnotify directory. ITT is always built for Android platform (can’t be disabled via CMake config): OCV_OPTION(BUILD_ITT "Build Intel ITT from source" (NOT MINGW OR OPENCV_FORCE_3RDPARTY_BUILD) IF (X86_64 OR X86 OR ARM OR AARCH64 OR PPC64 OR PPC64LE) AND NOT WINRT AND NOT APPLE_FRAMEWORK ) Any Android application using OpenCV up until 4.10 is affected, 4.11 and later are safe. There is no warning about this CVE in OpenCV because they were released before this CVE was published and they have accidentally fixed the bug (see this ) because someone wants to support OpenBSD (“ 3rdparty/ittnotify had not been updated until 9 years. To support OpenBSD, I suggest to update to latest release version v3.25.4 “) Continue reading “CVE-2025-31931 Arbitrary Shared Library Loading in Intel ITT API on Android (affects OpenCV <= 4.10)” Author admin Posted on November 9, 2025 November 11, 2025 Categories android , mobile , reverse-engineering , security , writeup Tags include Leave a comment on CVE-2025-31931 Arbitrary Shared Library Loading in Intel ITT API on Android (affects OpenCV <= 4.10) Decrypting Encrypted files from Akira Ransomware (Linux/ESXI variant 2024) using a bunch of GPUs I recently helped a company recover their data from the Akira ransomware without paying the ransom. I’m sharing how I did it, along with the full source code. Update: since this article was written, a new version of Akira ransomware has appeared that can’t be decrypted with this method The code is here: https://github.com/yohanes/akira-bruteforce To clarify, multiple ransomware variants have been named Akira over the years, and several versions are currently circulating. The variant I encountered has been active from late 2023 to the present (the company was breached this year). There was an earlier version (before mid-2023) that contained a bug, allowing Avast to create a decryptor. However, once this was published, the attackers updated their encryption. I expect they will change their encryption again after I publish this. https://decoded.avast.io/threatresearch/decrypted-akira-ransomware You can find various Akira malware sample hashes at the following URL: https://github.com/rivitna/Malware/blob/main/Akira/Akira_samples.txt The sample that matches my client’s case is: bcae978c17bcddc0bf6419ae978e3471197801c36f73cff2fc88cecbe3d88d1a It is listed under the version: Linux V3 . The sample can be found on virus.exchange (just paste the hash to search). Note that the ransom message and the private/public keys will differ. We do this not because it is easy, but because we thought it would be easy I usually decline requests to assist with ransomware cases. However, when my friend showed me this particular case, a quick check made me think it was solvable. Continue reading “Decrypting Encrypted files from Akira Ransomware (Linux/ESXI variant 2024) using a bunch of GPUs” Author admin Posted on March 13, 2025 November 7, 2025 Categories hacks , reverse-engineering , security Tags define , Final 76 Comments on Decrypting Encrypted files from Akira Ransomware (Linux/ESXI variant 2024) using a bunch of GPUs Patching .so files of an installed Android App If we installed an Android APK and we have a root access, we can modify the .so (native) filesof that app without altering the signature. This is true even if extractNativeLibs is set to false in AndroidManifest.xml . We can also patch the AOT compiled file (ODEX/VDEX) without changing the package signature, but that’s another story, I am just going to focus on the native code. native libraries are stored uncompressed and page aligned As a note: this is not a vulnerability, it requires root access. This method was discussed in the Mystique exploit presentation (2022). I just want to show that this is useful for pentest purpose, with an extra tip of how to write binary patch in C. Background I was doing a pentest on an Android app with a complex RASP. There are many challenges: If I unpack the APK file and repack it, it can detect the signature change If I use Frida, it can detect Frida in memory, even when I change the name using fridare It can detect Zygisk, so all injection methods that use Zygisk are detected It can detect hooks on any function, not just PLT. It seems that it is done by scanning the prologue of functions to see if it jumps to a location outside the binary; the app developer needs to call this check manually (this is quite an expensive operation), which is usually done before it performs some critical scenario. The RASP uses a native library, which is obfuscated Given enough time, I am sure it is possible to trace and patch everything, but we are time-limited, and I was only asked to check a specific functionality. When looking at that particular functionality, I can see that it is implemented natively in a non-obfuscated library. In this specific case, If I can patch the native code without altering the signature, I don’t need to deal with all the anti-frida, anti-hook, etc. Continue reading “Patching .so files of an installed Android App” Author admin Posted on November 18, 2024 February 12, 2025 Categories android , mobile , reverse-engineering Tags include 2 Comments on Patching .so files of an installed Android App Extracting WhatsApp Database (or any app data) from Android 12/13 using CVE-2024-0044 I want to make a WhatsApp message backup from a non-rooted Android 12 Phone. A few years ago, I used Whatsapp-Chat-Exporter to convert the backup to HTML, but first, I had to extract the database from the phone. The method pointed out by Whatsapp-Chat-Exporter to extract from non-root has remained the same for many years: downgrade to an old version of WhatsApp that allows backup, then create an Android backup that contains the WhatsApp database. This doesn’t work for WhatsApp for Business because there was no version that allowed backup. Depending on your use case, you might be able to move WhatsApp to a new device that can be rooted and then extract the files there (very easy when you have root access). When looking at the new Zygote Bug by Meta Red Team X (CVE-2024-31317), I thought it could be used to perform backup extraction, but then I saw the previous entry on that blog (CVE-2024-0044), which is much easier to use (but only works in Android 12 and 13 that has not received Marh 2024 security update). CVE-2023-0044 This exploit can work for any non-system app, not just for extracting data from WhatsApp/WhatsApp business. For an expert, the explanation for the exploit is very obvious. I am writing here for end users or beginners who need a step-by-step guide to extracting their WA database. Continue reading “Extracting WhatsApp Database (or any app data) from Android 12/13 using CVE-2024-0044” Author admin Posted on June 7, 2024 June 7, 2024 Categories android , mobile , security 9 Comments on Extracting WhatsApp Database (or any app data) from Android 12/13 using CVE-2024-0044 Zygisk-based reFlutter I developed a Zygisk module for rooted Android phones with Magisk (and Zygisk enabled). This module allows you to “reFlutter” your Flutter App at runtime, simplifying the testing and reverse engineering processes. If you don’t want to read the detail, the release is available at: https://github.com/yohanes/zygisk-reflutter Continue reading “Zygisk-based reFlutter” Author admin Posted on April 9, 2024 April 9, 2024 Categories android , mobile , reverse-engineering 1 Comment on Zygisk-based reFlutter Using U-Boot to extract Boot Image from Pritom P7 This is a guide to extract the boot image from a cheap Android tablet based on Allwinner A133 using U-Boot (accessed via UART). The original firmware was not found on the internet. With the boot image and Magisk, you can root your Android tablet to make it more useful. Pritom P7 is a very cheap Android tablet. I bought it for 33 USD from AliExpress, but it can be found for as low as 27 USD. This is a Google GMS-certified device (it passes Play Integrity, no malware was found when I received it), and it uses 32-bit Android Go. I am only using this to test some 32-bit Android app compatibility. I bought it for 32.75 USD They may have several variants of this model with different specifications. Mine is: Alwinner A133, 1.5GB RAM (advertised as 2GB, and shown as 2GB in the Android info), 32 GB ROM, only 2.4 GHz WIFI, no GPS. Unlockable Bootloader Luckily, we are allowed to unlock the bootloader of this device using the developer menu, adb reboot bootloader then using fastboot oem unlock . Some cheap Android devices don’t allow unlocking (for example, the ones that are based on recent Unisoc SOC). I can allow bootloader unlock using the OEM Unlocking option The product ID of my tablet is P7_EEA (Android 11) with kernel version Linux localhost 5.4.180-svn33409-ab20220924-092422 #28 SMP PREEMPT Sun Aug 20 19:13:45 CST 2023 armv8l . The build number is PRITOM_P7_EEA_20230820 . I did not find any Android exploit for this device, and I also didn’t find any backdoors. From my experience, some of these cheap Android devices have hidden su backdoors. Unable to find an exploit, I gave up trying to extract boot image from user space. With some SOC, you can easily read/dump/extract the flash using PC software. I didn’t find any software for this Allwinner chip. An example of a SOC that allows flash reading is Unisoc (formerly Spreadtrum), but on the other hand, the bootloader on phones and tablets with the latest SOCs from Unisoc (that I know of) is not unlockable. UART Fortunately, this device is easy to open, and a UART pin is on the top left near the camera. UART + FEL pad on top, near the camera Continue reading “Using U-Boot to extract Boot Image from Pritom P7” Author admin Posted on January 18, 2024 January 19, 2024 Categories android , hacks , hardware , mobile , phone Tags 28 26 Comments on Using U-Boot to extract Boot Image from Pritom P7 Reverse Engineering RG35XX Stock Firmware A friend gave me an Anbernic RG35XX to hack. This is a retro gaming device (it just means that it is designed to emulate old consoles). It comes with two OS: Stock OS and Garlic OS. Stock OS is closed source, and Garlic OS is open source, except for the kernel part (all are closed source). You can switch from one OS to another via a menu. Stock OS starting my custom binary. In my opinion, the stock OS is fast and quite user-friendly but is not customizable, although many people like Garlic OS more because it can emulate more systems. Kernel part Anbernic won’t release the source for ATM7039S, and no datasheet is found for this SOC. The stock RG35XX OS uses a slightly different kernel compared to the Garlic OS. Someone was able to compile the kernel from an old S500 device and have the GPU to work . Koriki for RG35XX was based on this kernel, but from the information in Discord, the latest Koriki release uses a stock kernel. There is no serial port accessible and no debug interface available, so trying to hack the kernel will be a painful experience. Stock RG35XX boot sequence The kernel is stored as a uImage file on the first partition (FAT32). The built-in bootloader (u-boot) will boot load this file, and it will mount ramdisk.img . Inside ramdisk.img , we can find: /init , /init.rc , loadapp.sh . The kernel will start /init , which is based on Android init (it uses bionic libc). /init will load /init.rc , and on the last lines, it contains instructions to start loadapp.sh service loadapp /system/bin/logwrapper /loadapp.sh class core loadapp.sh will load /system/dmenu/dmenu_ln . The dmenu_ln can be found on the second partition (ext4), and this is just a shell script that will start /mnt/vendor/bin/dmenu.bin that can also be found on the second partition. dmenu.bin is the main shell for the OS. This is written in C using SDL1.2, but it uses custom input handling instead of using SDL_WaitEvent . Custom Input Handling Some people swear that the input handling in the Stock RG35XX OS is faster than the other alternative OS. I can’t feel it, but the Stock OS does process input events manually. To reverse engineer how it works, I use Ghidra. Since this is not security-related software, there is no protection or obfuscation so the code can be decompiled quite cleanly. Reverse engineering It starts by opening /dev/input/ to find a device that has a name: gpio-keys-polled (this name is obtained using ioctl call with request EVIOCGNAME ). Then, it will start a thread (using pthread) to poll this device. The power button is a separate device from all other buttons, and the reset button (under the power button) is hardwired to reset the console. Emulator modification Inside appres/bin/game on the second partition, we can see several binaries for each emulator. All of them have been modified by Anbernic: They use custom error handling The menu button is set to display the menu (so all emulators have the same interface) Added Video filter effect (such as dot-matrix) implemented in C (not using GPU) Compiling for RG35XX stock OS Usually, we will need an SDK to compile an app, but since we know the target architecture, calling convention, and the libraries used, we can work around this problem. To compile a simple SDL app that will run on the Stock OS, we will need a compiler, header files, and some libraries. For the compiler, download Linaro toolchain 4.7 (closest to existing binaries on the system) from here (choose gnueabihf): https://releases.linaro.org/archive/12.11/components/toolchain/binaries/ For the headers, download the latest SDL1.2 and use the default SDL config. And for the libraries, we can use files from /lib on the second partition. Remove libc.so and libm.so , these two are bionic files and will cause errors. Then, add files from usr/local/lib/arm-linux-gnueabihf (also from the second partition). Then, you should be able just to compile everything manually. Outputs to stdout/stderr will not be visible, so use dup2 to redirect these to files. Small Demo App In this repository, you can see my small demo app. I included all the libraries to make it easy for anyone to start (please change CC path in Makefile to your installation directory). https://github.com/yohanes/rg35xx-stock-sdl-demo This is a very simple app to replace dmenu.bin (please rename the original dmenu.bin to orig.bin ), it only provides three functions: Testing key events Starting ADB (useful for transferring files and debugging), I Included my own ADB_ON.sh which needs to be copied to the same location as dmenu.bin Starting the original launcher (now named orig.bin ) I am not planning to develop this. Maybe someone can make a better launcher based on this. Author admin Posted on December 31, 2023 December 31, 2023 Categories hardware , reverse-engineering Leave a comment on Reverse Engineering RG35XX Stock Firmware When you deleted /lib on Linux while still connected via ssh Let’s first not talk about why this can happen, but deleting /lib , /usr/lib , or some other essential runtime files happens quite a lot (as you can see: here , here , here , and here ). In this post, I will only discuss what happens when you delete /lib on Linux and how to recover from that. The easy solution for everything is to replace the missing files, but this can be difficult if /lib is deleted because we won’t have ld-linux , which is needed to run any dynamic executable. When you deleted /lib , all non-static executable (such as ls , cat , etc , will output): No such file or directory You will also be unable to open any new connection using ssh, or open a new tmux window/pane if you are using tmux. So you can only rely on your current shell built in, and some static executables that you have on the system. If you have a static busybox installed, then it can be your rescue. You can use wget from busybox to download libraries from a clean system. For your information: Debian has busybox installed by default, but the default is not the static version. Minimal Debian install If you are worried that this kind of problem might happen to you in the future: Install the static version of the busybox binary, and confirm that it is the correct version. Installing static busybox Continue reading “When you deleted /lib on Linux while still connected via ssh” Author admin Posted on September 16, 2022 September 16, 2022 Categories debian , hacks , linux 1 Comment on When you deleted /lib on Linux while still connected via ssh Reverse Engineering a Flutter app by recompiling Flutter Engine It is not easy to reverse engineer a release version of a flutter app because the tooling is not available and the flutter engine itself changes rapidly. As of now, if you are lucky, you can dump the classes and method names of a flutter app using darter or Doldrums if the app was built with a specific version of Flutter SDK. If you are extremely lucky, which is what happened to me the first time I needed to test a Flutter App: you don’t even need to reverse engineer the app. If the app is very simple and uses a simple HTTPS connection, you can test all the functionalities using intercepting proxies such as Burp or Zed Attack Proxy. The app that I just tested uses an extra layer of encryption on top of HTTPS, and that’s the reason that I need to do actual reverse engineering. In this post, I will only give examples for the Android platform, but everything written here is generic and applicable to other platforms. The TLDR is: instead of updating or creating a snapshot parser, we just recompile the flutter engine and replace it in the app that we targeted. Flutter compiled app Currently several articles and repositories that I found regarding Flutter reverse engineering are: Reverse engineering Flutter for Android (explains the basic of snapshot format, introduces, Doldrums, as of this writing only supports snapshot version 8ee4ef7a67df9845fba331734198a953) Reverse engineering Flutter apps (Part 1) a very good article explaining Dart internals, unfortunately, no code is provided and part 2 is not yet available as of this writing darter: Dart snapshot parser a tool to dump snapshot version c8562f0ee0ebc38ba217c7955956d1cb The main code consists of two libraries libflutter.so (the flutter engine) and libapp.so (your code). You may wonder: what actually happens if you try to open a libapp.so (Dart code that is AOT compiled) using a standard disassembler. It’s just native code, right? If you use IDA, initially, you will only see this bunch of bytes. If you use other tools, such as binary ninja which will try to do some linear sweep, you can see a lot of methods. All of them are unnamed, and there are no string references that you can find. There is also no reference to external functions (either libc or other libraries), and there is no syscall that directly calls the kernel (like Go).. With a tool like Darter dan Doldrums, you can dump the class names and method names, and you can find the address of where the function is implemented. Here is an example of a dump using Doldrums. This helps tremendously in reversing the app. You can also use Frida to hook at these addresses to dump memory or method parameters. The snapshot format problem The reason that a specific tool can only dump a specific version of the snapshot is: the snapshot format is not stable, and it is designed to be run by a specific version of the runtime. Unlike some other formats where you can skip unknown or unsupported format, the snapshot format is very unforgiving. If you can’t parse a part, you can parse the next part. Basically, the snapshot format is something like this: <tag> <data bytes> <tag> <data bytes> … There is no explicit length given for each chunk, and there is no particular format for the header of the tag (so you can’t just do a pattern match and expect to know the start of a chunk). Everything is just numbers. There is no documentation of this snapshot, except for the source code itself. In fact, there is not even a version number of this format. The format is identified by a snapshot version string. The version string is generated from hashing the source code of snapshot-related files . It is assumed that if the files are changed, then the format is changed. This is true in most cases, but not always (e.g: if you edit a comment, the snapshot version string will change). My first thought was just to modify Doldrums or Darter to the version that I needed by looking at the diff of Dart sources code. But it turns out that it is not easy: enums are sometimes inserted in the middle (meaning that I need to shift all constants by a number). And dart also uses extensive bit manipulation using C++ template. For example, when I look at Doldums code, I saw something like this: def decodeTypeBits(value): return value & 0x7f I thought I can quickly check this constant in the code (whether it has changed or not in the new version), the type turns out to be not a simple integer. class ObjectPool : public Object { using TypeBits = compiler::ObjectPoolBuilderEntry::TypeBits; } struct ObjectPoolBuilderEntry { using TypeBits = BitField<uint8_t, EntryType, 0, 7>; } You can see that this Bitfield is implemented as BitField template class . This particular bit is easy to read, but if you see kNextBit , you need to look back at all previous bit definitions. I know it’s not that hard to follow for seasoned C++ developers, but still: to track these changes between versions, you need to do a lot of manual checks. My conclusion was: I don’t want to maintain the Python code, the next time the app is updated for retesting, they could have used a newer version of Flutter SDK, with another snapshot version. And for the specific work that I am doing: I need to test two apps with two different Flutter versions: one for something that is already released in the app store and some other app that is going to be released. Rebuilding Flutter Engine The flutter engine ( libflutter.so ) is a separate library from libapp.so (the main app logic code), on iOS, this is a separate framework. The idea is very simple: Download the engine version that we want Modify it to print Class names, Methods, etc instead of writing our own snapshot parser Replace the original libflutter.so library with our patched version Profit The first step is already difficult: how can we find the corresponding snapshot version? This table from darter helps, but is not updated with the latest version. For other versions, we need to hunt and test if it has matching snapshot numbers. The instruction for recompiling the Flutter engine is here , but there are some hiccups in the compilation and we need to modify the python script for the snapshot version. And also: the Dart internal itself is not that easy to work with. Most older versions that I tested can’t be compiled correctly. You need to edit the DEPS file to get it to compile. In my case: the diff is small but I need to scour the web to find this. Somehow the specific commit was not available and I need to use a different version. Note: don’t apply this patch blindly, basically check these two things: If a commit is not available, find nearest one from the release date If something refers to a _internal you probably should remove the _internal part. diff --git a/DEPS b/DEPS index e173af55a..54ee961ec 100644 --- a/DEPS +++ b/DEPS @@ -196,7 +196,7 @@ deps = { Var('dart_git') + '/dartdoc.git@b039e21a7226b61ca2de7bd6c7a07fc77d4f64a9', 'src/third_party/dart/third_party/pkg/ffi': - Var('dart_git') + '/ffi.git@454ab0f9ea6bd06942a983238d8a6818b1357edb', + Var('dart_git') + '/ffi.git@5a3b3f64b30c3eaf293a06ddd967f86fd60cb0f6', 'src/third_party/dart/third_party/pkg/fixnum': Var('dart_git') + '/fixnum.git@16d3890c6dc82ca629659da1934e412292508bba', @@ -468,7 +468,7 @@ deps = { 'src/third_party/android_tools/sdk/licenses': { 'packages': [ { - 'package': 'flutter_internal/android/sdk/licenses', + 'package': 'flutter/android/sdk/licenses', 'version': 'latest', } ], Now we can start editing the snapshot files to learn about how it works. But as mentioned early: if we modify the snapshot file: the snapshot hash will change, so we need to fix that by returning a static version number in third_party/dart/tools/make_version.py . If you touch any of these files in VM_SNAPSHOT_FILES , change the line snapshot_hash = MakeSnapshotHashString() with a static string to your specific version. What happens if we don’t patch the version? the app won’t start. So after patching (just start by printing a hello world) using OS::PrintErr("Hello World") and recompiling the code, we can test to replace the .so file, and run it. I made a lot of experiments (such as trying to FORCE_INCLUDE_DISASSEMBLER ), so I don’t have a clean modification to share but I can provide some hints of things to modify: in runtime/vm/clustered_snapshot.cc we can modify Deserializer::ReadProgramSnapshot(ObjectStore* object_store) to print the class table isolate->class_table()->Print() in runtime/vm/class_table.cc we can modify void ClassTable::Print() to print more informations For example, to print function names: const Array& funcs = Array::Handle(cls.functions()); for (intptr_t j = 0; j < funcs.Length(); j++) { Function& func = Function::Handle(); func = cls.FunctionFromIndex(j); OS::PrintErr("Function: %s", func.ToCString()); } Sidenote: SSL certificates Another problem with Flutter app is: it won’t trust a user installed root cert . This a problem for pentesting, and someone made a note on how to patch the binary (either directly or using Frida) to workaround this problem. Quoting TLDR of this blog post : Flutter uses Dart, which doesn’t use the system CA store Dart uses a list of CA’s that’s compiled into the application Dart is not proxy aware on Android, so use ProxyDroid with iptables Hook the session_verify_cert_chain function in x509.cc to disable chain validation By recompiling the Flutter engine, this can be done easily. We just modify the source code as-is ( third_party/boringssl/src/ssl/handshake.cc ), without needing to find assembly byte patterns in the compiled code. Obfuscating Flutter It is possible to obfuscate Flutter/Dart apps using the instructions provided here. This will make reversing to be a bit harder. Note that only the names are obfuscated, there is no advanced control flow obfuscation performed. Conclusion I am lazy, and recompiling the flutter engine is the shortcut that I take instead of writing a proper snapshot parser. Of course, others have similar ideas of hacking the runtime engine when reversing other technologies, for example, to reverse engineer an obfuscated PHP script, you can hook eval using a PHP module. Author admin Posted on March 7, 2021 March 8, 2021 Categories mobile , reverse-engineering , security 3 Comments on Reverse Engineering a Flutter app by recompiling Flutter Engine Dissecting a MediaTek BootROM exploit A bricked Xiaomi phone led me to discover a project in Github that uses a MediaTek BootROM exploit that was undocumented. The exploit was found by Xyz , and implemented by Chaosmaster . The initial exploit was already available for quite a while . Since I have managed to revive my phone, I am documenting my journey to revive it and also explains how the exploit works. This exploit allows unsigned code execution, which in turn allows us to read/write any data from our phone. For professionals: you can just skip to how the BootROM exploit works (spoiler: it is very simple). This guide will try to guide beginners so they can add support for their own phones. I want to show everything but it will violate MediaTek copyright, so I will only snippets of decompilation of the boot ROM. Bricking my Phone and understanding SP Flash Tool I like to use Xiaomi phones because it’s relatively cheap, has an easy way to unlock the bootloader, and the phone is easy to find here in Thailand. With an unlocked bootloader, I have never got into an unrecoverable boot loop, because I can usually boot into fastboot mode and just reflash with the original ROM. I usually buy a phone with Qualcomm SOC, but this time I bought Redmi 10X Pro 5G with MediaTek SOC (MT6873 also known as Dimensity 800). But it turns out: you can get bricked without the possibility to enter fastboot mode. A few years ago, it was easy to reflash a Mediatek phone: enter BROM mode (usually by holding the volume up button and plugging the USB when the phone is off), and use SP Flash Tool to overwrite everything (including boot/recovery partition). It works this way: we enter BROM mode, the SP Flash Tool will upload DA (download agent) to the phone, and SP Flash Tool will communicate with the DA to perform actions (erase flash, format data, write data, etc). But they have added more security now: when I tried flashing my phone, it displays an authentication dialog. It turns out that this is not your ordinary Mi Account dialog, but you need to be an Authorized Mi Account holder (usually from a service center). It turns out that just flashing a Mediatek phone may enter a boot loop without the possibility of entering fastboot mode. Quoting from an XDA article : The developers who have been developing for the Redmi Note 8 Pro have found that the device tends to get bricked for a fair few reasons. Some have had their phone bricked when they were flashing to the recovery partition from within the recovery, while others have found that installing a stock ROM through fastboot on an unlocked bootloader also bricks the device Xiaomi needs a better way to unbrick its devices instead of Authorized Mi Accounts I found one of the ROM modders that had to deal with a shady person on the Internet using remote Team Viewer to revive his phone. He has some explanation about the MTK BootROM security. To summarize: BROM can have SLA (Serial Link Authorization), DAA (Download Agent Authorization), or both. SLA prevents loading DA if we are not authorized. And DA can present another type of authentication. Using custom DA, we can bypass the DA security, assuming we can bypass SLA to allow loading the DA. When I read those article I decided to give up. I was ready to let go of my data. MTK Bypass By a stroke of luck, I found a bypass for various MTK devices was published just two days after I bricked my Phone. Unfortunately: MT6873 is not yet supported. To support a device, you just need to edit one file ( device.c ), which contains some addresses. Some of these addresses can be found from external sources (such as from the published Linux kernel for that SOC), but most can’t be found without access to the BootROM itself. I tried reading as much as possible about the BROM protocol. Some of the documentation that I found: MediaTek details: SoC startup : has a link to BROM documentation Support for Mediatek Devices in Oxygen Forensic® Detective (Explains about BROM protection) Another luck came in a few days later: Chaosmaster published a generic payload to dump the BootROM. I got lucky: the generic payload works immediately on the first try on my phone and I got my Boot ROM dump. Now we need to figure out what addresses to fill in. At this point, I don’t have another ROM to compare, so I need to be clever in figuring out these addresses. We need to find the following: send_usb_response usbdl_put_dword usbdl_put_data usbdl_get_data uart_reg0 uart_reg1 sla_passed skip_auth_1 skip_auth_2 From the main file that uses those addresses we can see that: uart_reg0 and uart_reg1 are required for proper handshake to work. These addresses can be found on public Linux kernel sources. usbdl_put_dword and usbdl_put_data is used to send data to our computer usbdl_get_data is used to read data from computer sla_passed , skip_auth_1 and skip_auth_2 , are the main variables that we need to overwrite so we can bypass the authentication We can start disassembling the firmware that we obtain fro the generic dumper. We need to load this to address 0x0. Not many strings are available to cross-reference so we need to get creative. Somehow generic_dump_payload can find the address for usb_put_data to send dumped bytes to the Python script. How does it know that? The source for generic_dump_payload is is available in ChaosMaster’s repository . But I didn’t find that information sooner so I just disassembled the file. This is a small binary, so we can reverse engineer it easily using binary ninja. It turns out that it does some pattern matching to find the prolog of the function: 2d e9 f8 4f 80 46 8a 46 . Actually, it searches for the second function that has that prolog. Pattern finder in generic_dump_payload Now that we find the send_word function we can see how sending works. It turns out that it sends a 32-bit value by sending it one byte at a time. Note: I tried continuing with Binary Ninja, but it was not easy to find cross-references to memory addresses on a raw binary, so I switched to Ghidra. After cleaning up the code a bit, it will look something like this: What generic_dump_payload found Now we just need to find the reference to function_pointers and we can find the real address for sendbyte . By looking at related functions I was able to find the addresses for: usbdl_put_dword , usbdl_put_data , usbdl_get_data . Note that the exploit can be simplified a bit, by replacing usbdl_put_dword by a call to usbdl_put_data so we get 1 less address to worry about. The hardest part for me was to find send_usb_response to prevent a timeout. From the main file , I know that it takes 3 numeric parameters (not pointers), and this must be called somewhere before we send data via USB. This narrows it down quite a lot and I can find the correct function. Now to the global variables: sla_passed , skip_auth_1 , and skip_auth_2 . When we look at the main exploit in Python, one of the first things that it does is to read the status of the current configuration. This is done by doing a handshake then retrieve the target config . Target config There must be a big “switch” statement in the boot ROM that handles all of these commands. We can find the handshake bytes ( A0 0A 50 05 ) to find the reference to the handshake routine (actually found two of them, one for USB and one for UART). From there we can find the reference to the big switch statement. The handshake You should be able to find something like this: after handshake it starts to handle commands And the big switch should be clearly visible. Switch to handle various commands Now that we found the switch, we can find the handler for command 0xd8 (get target config). Notice in python, the code is like this : Notice the bit mask By looking at the bitmask, we can conclude the name of the functions that construct the value of the config. E.g: we can name the function that sets the secure boot to is bit_is_secure_boot . Knowing this, we can inspect each bit_is_sla and bit_is_daa we can name the functions from the bit that it sets For SLA: we need to find cross-references that call bit_is_sla , and we can see that another variable is always consulted. If SLA is not set, or SLA is already passed, we are allowed to perform the next action. finding sla_passed Now we need to find two more variables for passing DAA. Looking at bit_is_daa , we found that at the end of this function, it calls a routine that checks if we have passed it. These are the last two variables that we are looking for. How the BootROM Exploit Works The exploit turns out very simple. We are allowed to upload data to a certain memory space The handler for USB control transfer blindly index a function pointer table Basically it something like this: handler_array[value*13](); But there are actually some problems: The value for this array is unknown, but we know that most devices will have 0x100a00 as one of the elements We can brute force the value for USB control transfer to invoke the payload We may also need to experiment with different addresses (since not all device has 0x100a00 as an element that can be used) Another payload is also provided to just restart the device. This will make it easy to find the correct address and control value. Closing Remarks Although I was very upset when my phone got bricked, the experience in solving this problem has been very exciting. Thank you to Xyz for finding this exploit, and ChaosMaster for implementing it, simplifying it, and also for answering my questions and reviewing this post. Author admin Posted on January 31, 2021 March 7, 2021 Categories hacks , hardware , reverse-engineering , security , writeup 18 Comments on Dissecting a MediaTek BootROM exploit Posts pagination Page 1 Page 2 … Page 10 Next page Pages About Archive Search for: Search Follow x.com/yohanes Mastodon Recent Posts CVE-2025-31931 Arbitrary Shared Library Loading in Intel ITT API on Android (affects OpenCV <= 4.10) Decrypting Encrypted files from Akira Ransomware (Linux/ESXI variant 2024) using a bunch of GPUs Patching .so files of an installed Android App Extracting WhatsApp Database (or any app data) from Android 12/13 using CVE-2024-0044 Zygisk-based reFlutter Recent Comments Eitan Porat on About admin on Using U-Boot to extract Boot Image from Pritom P7 lpt2007 on Using U-Boot to extract Boot Image from Pritom P7 admin on Using U-Boot to extract Boot Image from Pritom P7 lpt2007 on Using U-Boot to extract Boot Image from Pritom P7 Archives November 2025 March 2025 November 2024 June 2024 April 2024 January 2024 December 2023 September 2022 March 2021 January 2021 May 2019 January 2019 November 2018 July 2018 May 2018 February 2018 October 2017 September 2017 March 2017 November 2016 November 2015 July 2014 March 2014 February 2014 June 2013 January 2013 November 2011 March 2011 February 2011 July 2010 April 2010 January 2010 December 2009 September 2009 August 2009 June 2009 May 2009 April 2009 March 2009 February 2009 January 2009 December 2008 October 2008 September 2008 August 2008 July 2008 June 2008 May 2008 March 2008 February 2008 October 2007 June 2007 February 2007 January 2007 December 2006 Categories agestar android blog ctf debian flareon flex freebsd google hacks hardware hostmonster linux mac os x misc mobile opensource phone raspberry reverse-engineering sdr security Uncategorized wii writeup Meta Log in Entries feed Comments feed WordPress.org Tinyhack.com Proudly powered by WordPress | 2026-01-13T08:48:58 |
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https://www.fsf.org/jobs | Free software jobs — Free Software Foundation — Working together for free software ​ Push freedom ahead! The free software community has always thwarted the toughest challenges facing freedom in technology. This winter season, we want to thank the many individuals and projects that have helped us get where we are today: a world where a growing number of users are able to do their computing in full freedom. Our work isn't over. We have so much more to do. Help us reach our stretch New Year's membership goal of 100 new associate members by January 16, 2026, and keep the FSF strong and independent. Join | Read more Join Renew Donate Skip to content , sitemap or skip to search . Personal tools Log in Help! 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Skip sitemap or skip to licensing items About Staff and Board Contact Us Press Information Jobs Volunteering and Internships History Privacy Policy JavaScript Licenses Hardware Database Free Software Directory Free Software Resources Copyright Infringement Notification Skip to general items Campaigns Freedom Ladder Fight to Repair Free JavaScript High Priority Free Software Projects Secure Boot vs Restricted Boot Surveillance Upgrade from Windows Working Together for Free Software GNU Operating System Defective by Design End Software Patents OpenDocument Free BIOS Connect with free software users Skip to philosophical items Licensing Education Licenses GNU GPL GNU AGPL GNU LGPL GNU FDL Licensing FAQ Compliance How to use GNU licenses for your own software Latest News Upcoming Events FSF Blogs Skip list Donate to the FSF Join the FSF Patrons Associate Members My Account Working Together for Free Software Fund Philosophy The Free Software Definition Copyleft: Pragmatic Idealism Free Software and Free Manuals Selling Free Software Motives for Writing Free Software The Right To Read Why Open Source Misses the Point of Free Software Complete Sitemap fsf.org is powered by: Plone Zope Python CiviCRM HTML5 Arabic Belarussian Bulgarian Catalan Chinese Cornish Czech Danish English French German Greek Hebrew Hindi Italian Japanese Korean Norwegian Polish Portuguese Portuguese (Brazil) Romanian Russian Slovak Spanish Swedish Turkish Urdu Welsh Send your feedback on our translations and new translations of pages to campaigns@fsf.org . | 2026-01-13T08:48:58 |
https://www.highlight.io/docs/getting-started/browser/replay-configuration/upgrading-highlight | Upgrading Highlight Star us on GitHub Star Docs Sign in Sign up Getting Started Getting Started with Highlight Fullstack Mapping Browser React.js Next.js Remix Vue.js Angular Gatsby.js SvelteKit Electron highlight.run SDK Overview Canvas & WebGL Console Messages Content-Security-Policy Identifying Users iframe Recording Monkey Patches Browser OpenTelemetry Persistent Asset Storage Privacy Proxying Highlight React.js Error Boundary Recording Network Requests and Responses Recording WebSocket Events Salesforce Lightning Web Components (LWC) Data Export Sourcemap Configuration Tracking Events Troubleshooting Upgrading Highlight Versioning Sessions & Errors Other React Native (beta) Server Go Overview chi Echo Fiber Gin GORM gqlgen Logrus Manual Tracing gorilla mux JS Overview Apollo AWS Lambda Cloudflare Workers Express.js Firebase Hono Nest.js Next.js Node.js Pino tRPC Winston Python Overview AWS Lambda Azure Functions Django FastAPI Flask Google Cloud Functions Loguru Other Frameworks Python AI / LLM Libraries Python Libraries Ruby Overview Other Frameworks Ruby on Rails Rust Overview actix-web No Framework Hosting Providers Overview Metrics in AWS Logging in AWS Logging in Azure Fly.io NATS Log Shipper Logging in GCP Heroku Log Drain Render Log Stream Logging in Trigger.dev Vercel Log Drain Elixir Overview Elixir App Java: All Frameworks PHP: All Frameworks C# .NET ASP C# .NET 4 ASP Docker / Docker Compose File Fluent Forward curl OpenTelemetry Protocol (OTLP) Syslog RFC5424 Systemd / Journald Native OpenTelemetry Overview Error Monitoring Logging Tracing Browser Instrumentation Metrics Fullstack Frameworks Overview Next.js Fullstack Overview Next.js Page Router Guide Next.js App Router Guide Edge Runtime Advanced Config Remix Walkthrough Self Host & Local Dev Overview Development deployment guide. Integrations Microsoft Teams self-hosted Hobby deployment guide. Traefik SSL Proxying. Menu Highlight Docs Welcome to highlight.io Get Started Roadmap Company Values Compliance & Security Open Source Contributing Overview GraphQL Backend Frontend (app.highlight.io) Landing Site (highlight.io) Documentation End to End SDK Example Apps Adding an SDK Application Architecture GitHub Code Spaces Code Style Good First Issues Self-hosting Self-hosted [Dev] Self-hosted [Hobby] Self-hosted [Enterprise] Telemetry Our Competitors Product Philosophy Product Features Session Replay Overview Canvas & Iframe Dev-tool Window Recording Tracking Users & Recording Events Filtering Sessions GraphQL Live Mode Performance Impact Player Session Caching Rage Clicks Request Proxying Session Search Extracting the Session URL Session Search Deep Linking Shadow Dom + Web Components Error Monitoring Overview Enhancing Errors with GitHub Error Search Filtering Errors Grouping Errors Managing Errors Manually Reporting Errors Sourcemaps General Features Overview Alerts Comments Digests Environments Search Segments Services Webhooks Logging Overview Log Alerts Log Search Tracing Overview Trace Search Dashboards Overview Dashboard Management Metrics Tutorials Service Latency Web Vitals & Page Speed User Engagement User Analytics Graphing Drilldown Event Search Dashboard Variables SQL Editor Metrics (beta) Overview Frequently Asked Questions. Integrations Integrations Overview Amplitude Integration ClickUp Integration Discord Integration Electron Support Front Integration GitHub Integration Grafana Integration Overview Setup Dashboards Alerts Height Integration Intercom Integration Jira Integration LaunchDarkly Integration Linear Integration Mixpanel Integration Nuxt Integration Pendo Integration Segment Integration Slack Integration Vercel Integration WordPress Plugin Highlight.io Changelog Overview Changelog 12 (02/17) Changelog 13 (02/24) Changelog 14 (03/03) Changelog 15 (03/11) Changelog 16 (03/19) Changelog 17 (04/07) Changelog 18 (04/26) Changelog 19 (05/22) Changelog 20 (06/06) Changelog 21 (06/21) Changelog 22 (08/07) Changelog 23 (08/22) Changelog 24 (09/11) Changelog 25 (10/03) Changelog 26 (11/08) Changelog 27 (12/22) Changelog 28 (3/6) Changelog 29 (4/2) Getting Started Getting Started with Highlight Fullstack Mapping Browser React.js Next.js Remix Vue.js Angular Gatsby.js SvelteKit Electron highlight.run SDK Overview Canvas & WebGL Console Messages Content-Security-Policy Identifying Users iframe Recording Monkey Patches Browser OpenTelemetry Persistent Asset Storage Privacy Proxying Highlight React.js Error Boundary Recording Network Requests and Responses Recording WebSocket Events Salesforce Lightning Web Components (LWC) Data Export Sourcemap Configuration Tracking Events Troubleshooting Upgrading Highlight Versioning Sessions & Errors Other React Native (beta) Server Go Overview chi Echo Fiber Gin GORM gqlgen Logrus Manual Tracing gorilla mux JS Overview Apollo AWS Lambda Cloudflare Workers Express.js Firebase Hono Nest.js Next.js Node.js Pino tRPC Winston Python Overview AWS Lambda Azure Functions Django FastAPI Flask Google Cloud Functions Loguru Other Frameworks Python AI / LLM Libraries Python Libraries Ruby Overview Other Frameworks Ruby on Rails Rust Overview actix-web No Framework Hosting Providers Overview Metrics in AWS Logging in AWS Logging in Azure Fly.io NATS Log Shipper Logging in GCP Heroku Log Drain Render Log Stream Logging in Trigger.dev Vercel Log Drain Elixir Overview Elixir App Java: All Frameworks PHP: All Frameworks C# .NET ASP C# .NET 4 ASP Docker / Docker Compose File Fluent Forward curl OpenTelemetry Protocol (OTLP) Syslog RFC5424 Systemd / Journald Native OpenTelemetry Overview Error Monitoring Logging Tracing Browser Instrumentation Metrics Fullstack Frameworks Overview Next.js Fullstack Overview Next.js Page Router Guide Next.js App Router Guide Edge Runtime Advanced Config Remix Walkthrough Self Host & Local Dev Overview Development deployment guide. Integrations Microsoft Teams self-hosted Hobby deployment guide. Traefik SSL Proxying. Docs Home SDK Client SDK API Reference Cloudflare Worker SDK API Reference Go SDK API Reference Hono SDK API Reference Java SDK API Reference Next.JS SDK API Reference Node.JS SDK API Reference Python SDK API Reference Ruby SDK API Reference Rust SDK API Reference Docs / Getting Started / Browser / highlight.run SDK / Upgrading Highlight Upgrading Highlight Highlight is shipping improvements multiple times a day. Non-breaking changes will automatically be applied to your applications without any action needed by you. If Highlight ships a breaking change (new feature, security fix, etc.), we'll need your help to upgrade Highlight in your application. We aim to give 2 weeks notice in the event this happens. We recognize that there will be clients still using older versions of Highlight so we make sure all of our changes are backwards compatible. Using a Package Manager # with npm npm install highlight.run@latest # with yarn yarn upgrade highlight.run@latest HTML/CDN Replace the Highlight snippet in your index.html with the one on https://app.highlight.io/setup . Changelog To see if a new version has any breaking changes, see Changelog . Troubleshooting Versioning Sessions & Errors Community / Support Suggest Edits? Follow us! [object Object] | 2026-01-13T08:48:58 |
https://www.highlight.io/docs/general/product-features/session-replay/filtering-sessions | Filtering Sessions Star us on GitHub Star Docs Sign in Sign up General Docs Welcome to highlight.io Get Started Roadmap Company Values Compliance & Security Open Source Contributing Overview GraphQL Backend Frontend (app.highlight.io) Landing Site (highlight.io) Documentation End to End SDK Example Apps Adding an SDK Application Architecture GitHub Code Spaces Code Style Good First Issues Self-hosting Self-hosted [Dev] Self-hosted [Hobby] Self-hosted [Enterprise] Telemetry Our Competitors Product Philosophy Product Features Session Replay Overview Canvas & Iframe Dev-tool Window Recording Tracking Users & Recording Events Filtering Sessions GraphQL Live Mode Performance Impact Player Session Caching Rage Clicks Request Proxying Session Search Extracting the Session URL Session Search Deep Linking Shadow Dom + Web Components Error Monitoring Overview Enhancing Errors with GitHub Error Search Filtering Errors Grouping Errors Managing Errors Manually Reporting Errors Sourcemaps General Features Overview Alerts Comments Digests Environments Search Segments Services Webhooks Logging Overview Log Alerts Log Search Tracing Overview Trace Search Dashboards Overview Dashboard Management Metrics Tutorials Service Latency Web Vitals & Page Speed User Engagement User Analytics Graphing Drilldown Event Search Dashboard Variables SQL Editor Metrics (beta) Overview Frequently Asked Questions. Integrations Integrations Overview Amplitude Integration ClickUp Integration Discord Integration Electron Support Front Integration GitHub Integration Grafana Integration Overview Setup Dashboards Alerts Height Integration Intercom Integration Jira Integration LaunchDarkly Integration Linear Integration Mixpanel Integration Nuxt Integration Pendo Integration Segment Integration Slack Integration Vercel Integration WordPress Plugin Highlight.io Changelog Overview Changelog 12 (02/17) Changelog 13 (02/24) Changelog 14 (03/03) Changelog 15 (03/11) Changelog 16 (03/19) Changelog 17 (04/07) Changelog 18 (04/26) Changelog 19 (05/22) Changelog 20 (06/06) Changelog 21 (06/21) Changelog 22 (08/07) Changelog 23 (08/22) Changelog 24 (09/11) Changelog 25 (10/03) Changelog 26 (11/08) Changelog 27 (12/22) Changelog 28 (3/6) Changelog 29 (4/2) Menu Highlight Docs Welcome to highlight.io Get Started Roadmap Company Values Compliance & Security Open Source Contributing Overview GraphQL Backend Frontend (app.highlight.io) Landing Site (highlight.io) Documentation End to End SDK Example Apps Adding an SDK Application Architecture GitHub Code Spaces Code Style Good First Issues Self-hosting Self-hosted [Dev] Self-hosted [Hobby] Self-hosted [Enterprise] Telemetry Our Competitors Product Philosophy Product Features Session Replay Overview Canvas & Iframe Dev-tool Window Recording Tracking Users & Recording Events Filtering Sessions GraphQL Live Mode Performance Impact Player Session Caching Rage Clicks Request Proxying Session Search Extracting the Session URL Session Search Deep Linking Shadow Dom + Web Components Error Monitoring Overview Enhancing Errors with GitHub Error Search Filtering Errors Grouping Errors Managing Errors Manually Reporting Errors Sourcemaps General Features Overview Alerts Comments Digests Environments Search Segments Services Webhooks Logging Overview Log Alerts Log Search Tracing Overview Trace Search Dashboards Overview Dashboard Management Metrics Tutorials Service Latency Web Vitals & Page Speed User Engagement User Analytics Graphing Drilldown Event Search Dashboard Variables SQL Editor Metrics (beta) Overview Frequently Asked Questions. Integrations Integrations Overview Amplitude Integration ClickUp Integration Discord Integration Electron Support Front Integration GitHub Integration Grafana Integration Overview Setup Dashboards Alerts Height Integration Intercom Integration Jira Integration LaunchDarkly Integration Linear Integration Mixpanel Integration Nuxt Integration Pendo Integration Segment Integration Slack Integration Vercel Integration WordPress Plugin Highlight.io Changelog Overview Changelog 12 (02/17) Changelog 13 (02/24) Changelog 14 (03/03) Changelog 15 (03/11) Changelog 16 (03/19) Changelog 17 (04/07) Changelog 18 (04/26) Changelog 19 (05/22) Changelog 20 (06/06) Changelog 21 (06/21) Changelog 22 (08/07) Changelog 23 (08/22) Changelog 24 (09/11) Changelog 25 (10/03) Changelog 26 (11/08) Changelog 27 (12/22) Changelog 28 (3/6) Changelog 29 (4/2) Getting Started Getting Started with Highlight Fullstack Mapping Browser React.js Next.js Remix Vue.js Angular Gatsby.js SvelteKit Electron highlight.run SDK Overview Canvas & WebGL Console Messages Content-Security-Policy Identifying Users iframe Recording Monkey Patches Browser OpenTelemetry Persistent Asset Storage Privacy Proxying Highlight React.js Error Boundary Recording Network Requests and Responses Recording WebSocket Events Salesforce Lightning Web Components (LWC) Data Export Sourcemap Configuration Tracking Events Troubleshooting Upgrading Highlight Versioning Sessions & Errors Other React Native (beta) Server Go Overview chi Echo Fiber Gin GORM gqlgen Logrus Manual Tracing gorilla mux JS Overview Apollo AWS Lambda Cloudflare Workers Express.js Firebase Hono Nest.js Next.js Node.js Pino tRPC Winston Python Overview AWS Lambda Azure Functions Django FastAPI Flask Google Cloud Functions Loguru Other Frameworks Python AI / LLM Libraries Python Libraries Ruby Overview Other Frameworks Ruby on Rails Rust Overview actix-web No Framework Hosting Providers Overview Metrics in AWS Logging in AWS Logging in Azure Fly.io NATS Log Shipper Logging in GCP Heroku Log Drain Render Log Stream Logging in Trigger.dev Vercel Log Drain Elixir Overview Elixir App Java: All Frameworks PHP: All Frameworks C# .NET ASP C# .NET 4 ASP Docker / Docker Compose File Fluent Forward curl OpenTelemetry Protocol (OTLP) Syslog RFC5424 Systemd / Journald Native OpenTelemetry Overview Error Monitoring Logging Tracing Browser Instrumentation Metrics Fullstack Frameworks Overview Next.js Fullstack Overview Next.js Page Router Guide Next.js App Router Guide Edge Runtime Advanced Config Remix Walkthrough Self Host & Local Dev Overview Development deployment guide. Integrations Microsoft Teams self-hosted Hobby deployment guide. Traefik SSL Proxying. Docs Home SDK Client SDK API Reference Cloudflare Worker SDK API Reference Go SDK API Reference Hono SDK API Reference Java SDK API Reference Next.JS SDK API Reference Node.JS SDK API Reference Python SDK API Reference Ruby SDK API Reference Rust SDK API Reference Docs / Highlight Docs / Product Features / Session Replay / Filtering Sessions Filtering Sessions highlight.io allows you to filter sessions that you don't want to see in your session feed. This is useful for sessions that you know are not relevant to your application, or that are not actionable. Filtered sessions do not count towards your billing quota. Set up ingestion filters You can set up ingestion filters by product to limit the number of data points recorded. You can filter sessions, errors, logs, or traces in the following ways: Sample a percentage of all data. For example, you may configure ingestion of 1% of all sessions. For each session we receive, we will make a randomized decision that will result in storing only 1% of those. The random decision is based on the identifier of that product model for consistency. With traces, the Trace ID is used to make sure all children of the same trace are also ingested. Rate limit the maximum number of data points ingested in a 1 minute window. For example, you may configure a rate limit of 100 sessions per minute. This will allow you to limit the number of sessions recorded in case of a significant spike in usage of your product. Set up an exclusion query. For example, you may configure an exclusion query of environment: development . This will avoid ingesting all sessions tagged with the development environment. With these filters, we will only bill you for data actually retained. For instance, setting up ingestion of only 1% of all sessions will mean that you will be billed only for 1% of all sessions (as measured by our definition of a session ). You can configure the filters on your project settings page in highlight . Filter sessions by user identifier In some cases, you may want to filter sessions from a specific user. You can do this by adding the user identifier to the "Filtered Sessions" input under the "Session Replay" tab in your project settings . Please note that we use the identifier (or first argument) sent in your H.identify method to filter against (SDK docs here ). Filtering sessions without an error If you're using Highlight mostly for error monitoring, customize the ingest filters in your project settings to only record sessions with an error by setting the Has Error: false filter. Filtering sessions using custom logic If you'd like to filter sessions based on custom logic (e.g. filtering sessions from users who have not logged in), use the manualStart flag in your H.init configuration. This will allow you to start and stop a session at your discretion. H.init({ manualStart: true, // ... other options }) Then you can manually start a session by calling H.start : useEffect(() => { if (userIsLoggedIn) { H.start() } }, [userIsLoggedIn]) Disable all session recording If you're interested in using Highlight for the error monitoring or logging products without session replay, use the follow setting: import { H } from 'highlight.run'; H.init('<YOUR_PROJECT_ID>', { disableSessionRecording: true, // ... }); Want to filter something else? If you'd like an easier way to filter specific types of sessions, we're open to feedback. Please reach out to us in our discord community . Tracking Users & Recording Events GraphQL Community / Support Suggest Edits? Follow us! [object Object] | 2026-01-13T08:48:58 |
https://libreplanet.org?pk_campaign=fsfhome | LibrePlanet Navigation menu Toggle navigation About About LibrePlanet Mission Statement Founding documents Support this Community Code of Conduct Anti-harassment policy Teams Activists Wiki Helpers LibrePlanet Artists FSF Community Team Local & Student Teams Conferences LibrePlanet Conference Non-official Get involved Participate Discussion channels Events Login From LibrePlanet Jump to: navigation , search Welcome to LibrePlanet , the free software wiki that anyone can edit. We have 1,743 articles in English . All Pages (Group names) About LibrePlanet Conference Participate FSF resources FSF community Support LibrePlanet LibrePlanet activists Wiki helpers Meet the team Contents 1 Welcome aboard to LibrePlanet! 1.1 Join or start a Team 1.2 Join our Discussion channels 1.3 FSF Resources and Campaigns 1.4 1.5 1.6 1.7 1.8 This month's featured resource 1.9 Media links 1.10 Events 2 Important Topics Welcome aboard to LibrePlanet! Join or start a Team Meet the teams that are part of LibrePlanet and participate... Join our Discussion channels Get to know our channels of interaction with the community, campaigns... FSF Resources and Campaigns Collaborate with the FSF team, help out with resources and translations... The LibrePlanet project is a global network of free software activists and teams working together to help further the ideals of software freedom by advocating and contributing to free software. Help us reach our fundraising goal of $400,000 USD by January 1, 2026. We can't protect and continue the hard work of our predecessors without your help. This month's featured resource Remote_Communication For this month, we are highlighting Remote Communication. Most of us communicate with family, friends, coworkers, and other activists through some kind of digital format. Let's work together to make sure we're respecting our freedom while staying in touch by using free software. On this page, you can find almost one hundred free software methods of communication. You are invited to help update, adopt, spread, and improve this important resource. See our list of past featured resources here . Do you have a suggestion for next month's featured resource? Let us know at campaigns@fsf.org. Media links AI in a closing world Software enshittification or freedom? It's not a hard choice! Gaming on a Talos II: How I avoid using Steam Steadfast self-hosting Events Free Software Directory meeting on IRC: Friday, January 16, starting at 12:00 EST (17:00 UTC) Join the FSF and friends on Friday, January 16 from 12:00 to 15:00 EST (17:00 to 20:00 UTC) to help improve the Free Software Directory. 2026-01-09 17:24:40 Important Topics End Software Patents Fight to Repair Open Document Format Nonfree Software Blacklist In other languages : česky dansk Deutsch español euskara فارسی suomi français Galego Magyar Bahasa Indonesia Italiano بهاس ملايو Vlaams Norsk polski Português română slovenčina svenska Türkçe Tiếng Việt 中文 (Zhōngwén) Main_Page en en Retrieved from " https://libreplanet.org/wiki?title=Main_Page&oldid=72276 " Categories : Pages with RSS feeds Top-level categories Pages in English The Free Software Foundation (FSF) is a nonprofit with a worldwide mission to promote computer user freedom. We defend the rights of all software users. ( Read more ) Campaigns High Priority Free Software Projects Free JavaScript Secure Boot vs Restricted Boot GNU Operating System Defective by Design See all campaigns Get Involved Contact Send your feedback on our translations and new translations of pages to campaigns@fsf.org . Copyright © 2013–2023 Free Software Foundation , Inc. Privacy Policy , JavaScript license information ​ Push freedom ahead! The free software community has always thwarted the toughest challenges facing freedom in technology. This winter season, we want to thank the many individuals and projects that have helped us get where we are today: a world where a growing number of users are able to do their computing in full freedom. Our work isn't over. We have so much more to do. Help us reach our stretch New Year's membership goal of 100 new associate members by January 16, 2026, and keep the FSF strong and independent. Join | Read more Join Renew Donate | 2026-01-13T08:48:58 |
https://www.highlight.io/docs/getting-started/server/ruby/rails | Using highlight.io with Ruby on Rails Star us on GitHub Star Docs Sign in Sign up Getting Started Getting Started with Highlight Fullstack Mapping Browser React.js Next.js Remix Vue.js Angular Gatsby.js SvelteKit Electron highlight.run SDK Overview Canvas & WebGL Console Messages Content-Security-Policy Identifying Users iframe Recording Monkey Patches Browser OpenTelemetry Persistent Asset Storage Privacy Proxying Highlight React.js Error Boundary Recording Network Requests and Responses Recording WebSocket Events Salesforce Lightning Web Components (LWC) Data Export Sourcemap Configuration Tracking Events Troubleshooting Upgrading Highlight Versioning Sessions & Errors Other React Native (beta) Server Go Overview chi Echo Fiber Gin GORM gqlgen Logrus Manual Tracing gorilla mux JS Overview Apollo AWS Lambda Cloudflare Workers Express.js Firebase Hono Nest.js Next.js Node.js Pino tRPC Winston Python Overview AWS Lambda Azure Functions Django FastAPI Flask Google Cloud Functions Loguru Other Frameworks Python AI / LLM Libraries Python Libraries Ruby Overview Other Frameworks Ruby on Rails Rust Overview actix-web No Framework Hosting Providers Overview Metrics in AWS Logging in AWS Logging in Azure Fly.io NATS Log Shipper Logging in GCP Heroku Log Drain Render Log Stream Logging in Trigger.dev Vercel Log Drain Elixir Overview Elixir App Java: All Frameworks PHP: All Frameworks C# .NET ASP C# .NET 4 ASP Docker / Docker Compose File Fluent Forward curl OpenTelemetry Protocol (OTLP) Syslog RFC5424 Systemd / Journald Native OpenTelemetry Overview Error Monitoring Logging Tracing Browser Instrumentation Metrics Fullstack Frameworks Overview Next.js Fullstack Overview Next.js Page Router Guide Next.js App Router Guide Edge Runtime Advanced Config Remix Walkthrough Self Host & Local Dev Overview Development deployment guide. Integrations Microsoft Teams self-hosted Hobby deployment guide. Traefik SSL Proxying. Menu Highlight Docs Welcome to highlight.io Get Started Roadmap Company Values Compliance & Security Open Source Contributing Overview GraphQL Backend Frontend (app.highlight.io) Landing Site (highlight.io) Documentation End to End SDK Example Apps Adding an SDK Application Architecture GitHub Code Spaces Code Style Good First Issues Self-hosting Self-hosted [Dev] Self-hosted [Hobby] Self-hosted [Enterprise] Telemetry Our Competitors Product Philosophy Product Features Session Replay Overview Canvas & Iframe Dev-tool Window Recording Tracking Users & Recording Events Filtering Sessions GraphQL Live Mode Performance Impact Player Session Caching Rage Clicks Request Proxying Session Search Extracting the Session URL Session Search Deep Linking Shadow Dom + Web Components Error Monitoring Overview Enhancing Errors with GitHub Error Search Filtering Errors Grouping Errors Managing Errors Manually Reporting Errors Sourcemaps General Features Overview Alerts Comments Digests Environments Search Segments Services Webhooks Logging Overview Log Alerts Log Search Tracing Overview Trace Search Dashboards Overview Dashboard Management Metrics Tutorials Service Latency Web Vitals & Page Speed User Engagement User Analytics Graphing Drilldown Event Search Dashboard Variables SQL Editor Metrics (beta) Overview Frequently Asked Questions. Integrations Integrations Overview Amplitude Integration ClickUp Integration Discord Integration Electron Support Front Integration GitHub Integration Grafana Integration Overview Setup Dashboards Alerts Height Integration Intercom Integration Jira Integration LaunchDarkly Integration Linear Integration Mixpanel Integration Nuxt Integration Pendo Integration Segment Integration Slack Integration Vercel Integration WordPress Plugin Highlight.io Changelog Overview Changelog 12 (02/17) Changelog 13 (02/24) Changelog 14 (03/03) Changelog 15 (03/11) Changelog 16 (03/19) Changelog 17 (04/07) Changelog 18 (04/26) Changelog 19 (05/22) Changelog 20 (06/06) Changelog 21 (06/21) Changelog 22 (08/07) Changelog 23 (08/22) Changelog 24 (09/11) Changelog 25 (10/03) Changelog 26 (11/08) Changelog 27 (12/22) Changelog 28 (3/6) Changelog 29 (4/2) Getting Started Getting Started with Highlight Fullstack Mapping Browser React.js Next.js Remix Vue.js Angular Gatsby.js SvelteKit Electron highlight.run SDK Overview Canvas & WebGL Console Messages Content-Security-Policy Identifying Users iframe Recording Monkey Patches Browser OpenTelemetry Persistent Asset Storage Privacy Proxying Highlight React.js Error Boundary Recording Network Requests and Responses Recording WebSocket Events Salesforce Lightning Web Components (LWC) Data Export Sourcemap Configuration Tracking Events Troubleshooting Upgrading Highlight Versioning Sessions & Errors Other React Native (beta) Server Go Overview chi Echo Fiber Gin GORM gqlgen Logrus Manual Tracing gorilla mux JS Overview Apollo AWS Lambda Cloudflare Workers Express.js Firebase Hono Nest.js Next.js Node.js Pino tRPC Winston Python Overview AWS Lambda Azure Functions Django FastAPI Flask Google Cloud Functions Loguru Other Frameworks Python AI / LLM Libraries Python Libraries Ruby Overview Other Frameworks Ruby on Rails Rust Overview actix-web No Framework Hosting Providers Overview Metrics in AWS Logging in AWS Logging in Azure Fly.io NATS Log Shipper Logging in GCP Heroku Log Drain Render Log Stream Logging in Trigger.dev Vercel Log Drain Elixir Overview Elixir App Java: All Frameworks PHP: All Frameworks C# .NET ASP C# .NET 4 ASP Docker / Docker Compose File Fluent Forward curl OpenTelemetry Protocol (OTLP) Syslog RFC5424 Systemd / Journald Native OpenTelemetry Overview Error Monitoring Logging Tracing Browser Instrumentation Metrics Fullstack Frameworks Overview Next.js Fullstack Overview Next.js Page Router Guide Next.js App Router Guide Edge Runtime Advanced Config Remix Walkthrough Self Host & Local Dev Overview Development deployment guide. Integrations Microsoft Teams self-hosted Hobby deployment guide. Traefik SSL Proxying. Docs Home SDK Client SDK API Reference Cloudflare Worker SDK API Reference Go SDK API Reference Hono SDK API Reference Java SDK API Reference Next.JS SDK API Reference Node.JS SDK API Reference Python SDK API Reference Ruby SDK API Reference Rust SDK API Reference Docs / Getting Started / Server / Ruby / Using highlight.io with Ruby on Rails Using highlight.io with Ruby on Rails Learn how to set up highlight.io on your Rails backend. 1 Configure client-side Highlight. (optional) If you're using Highlight on the frontend for your application, make sure you've initialized it correctly and followed the fullstack mapping guide . 2 Install the Highlight Ruby SDK. Add Highlight to your Gemfile and install with Bundler. gem "highlight_io" bundle install 3 Initialize the Highlight Ruby SDK. Highlight.init initializes the SDK. Setting your project ID also lets Highlight record errors for background tasks and processes that aren't associated with a frontend session. require "highlight" Highlight.init("<YOUR_PROJECT_ID>", environment: "production") do |c| c.service_name = "my-app" c.service_version = "1.0.0" end 4 Verify your errors are being recorded. Now that you've set up the Middleware, you can verify that the backend error handling works by throwing an error in a controller. Visit the highlight errors page and check that backend errors are coming in. class ArticlesController < ApplicationController def index 1/0 end end 5 Record custom errors. (optional) If you want to explicitly send an error to Highlight, you can use the error method within traced code. Highlight.exception(e) 6 Set up the Highlight Logger. In a Rails initializer, you can replace or extend your logger with the Highlight Logger. require "highlight" Highlight.init("<YOUR_PROJECT_ID>", environment: "production") do |c| c.service_name = "my-rails-app" c.service_version = "git-sha" end # you can replace the Rails.logger with Highlight's Rails.logger = Highlight::Logger.new(STDOUT) # or broadcast logs to Highlight's logger highlight_logger = Highlight::Logger.new(nil) Rails.logger.broadcast_to(highlight_logger) # or if using an older version of Rails, you can extend the logger Rails.logger.extend(ActiveSupport::Logger.broadcast(highlight_logger)) 7 Verify your errors are being recorded. Now that you've set up the Middleware, verify that the backend error handling works by consuming an error from traced code. 8 Verify your backend logs are being recorded. Visit the highlight logs portal and check that backend logs are coming in. 9 Record custom traces. (optional) If you want to explicitly send a trace to Highlight, you can use the start_span method to wrap any code you want to trace. Highlight.start_span('my-span') do |span| # ... end 10 Verify your backend traces are being recorded. Visit the highlight traces portal and check that backend traces are coming in. Using highlight.io with Other Ruby Frameworks Rust [object Object] | 2026-01-13T08:48:58 |
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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close # devsecops Follow Hide Integrating security practices into the DevOps lifecycle. Create Post Older #devsecops posts 4 5 6 7 8 9 10 11 12 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu DevOps vs. DevSecOps: What’s the Difference and Why It Matters? Koti Vellanki Koti Vellanki Koti Vellanki Follow Dec 21 '24 DevOps vs. DevSecOps: What’s the Difference and Why It Matters? # devops # devsecops # cloudcomputing # kubernetes 1 reaction Comments Add Comment 5 min read Understanding DevSecOps Principles Vivesh Vivesh Vivesh Follow Dec 19 '24 Understanding DevSecOps Principles # devops # security # cloud # devsecops 29 reactions Comments Add Comment 6 min read From Paper to Code: Why Security is Now a Business Imperative for Developers Sulav Dahal Sulav Dahal Sulav Dahal Follow Dec 14 '24 From Paper to Code: Why Security is Now a Business Imperative for Developers # cybersecurity # devops # softwaredevelopment # devsecops 1 reaction Comments Add Comment 3 min read Ensuring Security and Compliance with a DevSecOps Pipeline BuzzGK BuzzGK BuzzGK Follow Nov 10 '24 Ensuring Security and Compliance with a DevSecOps Pipeline # devsecops Comments Add Comment 5 min read Threat Modeling for Non-Security Experts Nikola Popov Nikola Popov Nikola Popov Follow Nov 9 '24 Threat Modeling for Non-Security Experts # security # devsecops # threatmanagement # productivity Comments Add Comment 5 min read KUBERNETICS Kaviyashree Tamilarasan Kaviyashree Tamilarasan Kaviyashree Tamilarasan Follow Nov 7 '24 KUBERNETICS # devops # devsecops # cloudnative Comments Add Comment 4 min read Top 10 Challenges of DevSecOps Implementation in 2024 Emma Wags Emma Wags Emma Wags Follow Nov 19 '24 Top 10 Challenges of DevSecOps Implementation in 2024 # devops # devsecops # cloud Comments Add Comment 3 min read Vulnerability-Free C and C++ Development in Automotive Manufacturing and Software Defined Vehicles (SDV) SnykSec SnykSec SnykSec Follow for Snyk Oct 24 '24 Vulnerability-Free C and C++ Development in Automotive Manufacturing and Software Defined Vehicles (SDV) # codesecurity # devsecops # ccpp Comments Add Comment 6 min read Day 02 of learning DevOps: OSI Model MasterHermit MasterHermit MasterHermit Follow Oct 21 '24 Day 02 of learning DevOps: OSI Model # devops # devsecops # networking # osi 1 reaction Comments Add Comment 1 min read How to Become a DevSecOps from Zero: A Practical Guide duouser duouser duouser Follow Oct 17 '24 How to Become a DevSecOps from Zero: A Practical Guide # devops # devsecops # beginners Comments Add Comment 9 min read Reimagining cybersecurity for developers Tide Foundation Tide Foundation Tide Foundation Follow Nov 19 '24 Reimagining cybersecurity for developers # security # opensource # devsecops # cybersecurity 1 reaction Comments Add Comment 7 min read Understanding command injection vulnerabilities in Go SnykSec SnykSec SnykSec Follow for Snyk Nov 15 '24 Understanding command injection vulnerabilities in Go # engineering # devsecops # opensourcesecurity # go 13 reactions Comments 2 comments 8 min read Implementing Blue-Green Deployment in Kubernetes with TLS Encryption Using Cert-Manager and Nginx Ingress George Ezejiofor George Ezejiofor George Ezejiofor Follow Nov 15 '24 Implementing Blue-Green Deployment in Kubernetes with TLS Encryption Using Cert-Manager and Nginx Ingress # devops # kubernetes # devsecops # microservices 3 reactions Comments Add Comment 6 min read Tricentis Tosca: A Powerful Tool for Continuous Testing Tharunika L Tharunika L Tharunika L Follow Nov 7 '24 Tricentis Tosca: A Powerful Tool for Continuous Testing # devops # devsecops # cicd # git 2 reactions Comments Add Comment 3 min read Advanced Container Security Techniques for DevSecOps Pipelines Bellevue Publishers Bellevue Publishers Bellevue Publishers Follow Oct 22 '24 Advanced Container Security Techniques for DevSecOps Pipelines # devops # container # security # devsecops 1 reaction Comments Add Comment 6 min read 7 Kubernetes Security Best Practices in 2024 Shubham Shubham Shubham Follow Oct 29 '24 7 Kubernetes Security Best Practices in 2024 # devops # devsecops # sre # kubernetes 6 reactions Comments Add Comment 3 min read Latest DevOps Tools and Trends: A Comprehensive Guide Subhash Bohra Subhash Bohra Subhash Bohra Follow Oct 23 '24 Latest DevOps Tools and Trends: A Comprehensive Guide # devops # aws # learning # devsecops 1 reaction Comments Add Comment 5 min read Dive into AI and LLM learning with the new Snyk Learn learning path SnykSec SnykSec SnykSec Follow for Snyk Sep 19 '24 Dive into AI and LLM learning with the new Snyk Learn learning path # ai # devsecops # engineering Comments Add Comment 2 min read Demystifying DevOps vs DevSecOps Tarunbalaji Tarunbalaji Tarunbalaji Follow Sep 16 '24 Demystifying DevOps vs DevSecOps # devops # devsecops # cloud # learning Comments Add Comment 3 min read The Future of DevSecOps: Enhancing Your Software Security Development with NIST Guidelines andre aliaman andre aliaman andre aliaman Follow Sep 21 '24 The Future of DevSecOps: Enhancing Your Software Security Development with NIST Guidelines # cicd # cybersecurity # devsecops # productivity 3 reactions Comments Add Comment 4 min read The State of DevOps Threats Report – GitProtect.io’s Study Highlights The Major Cyber Risks and Security Best Practices GitProtect Team GitProtect Team GitProtect Team Follow for GitProtect Sep 6 '24 The State of DevOps Threats Report – GitProtect.io’s Study Highlights The Major Cyber Risks and Security Best Practices # devsecops # devops # cybersecurity # developer Comments Add Comment 6 min read DevSecops Tools in CICD Pipeline akhil mittal akhil mittal akhil mittal Follow Oct 9 '24 DevSecops Tools in CICD Pipeline # devsecops # security # cicd # vulnerabilities 1 reaction Comments Add Comment 4 min read DevSecOps Fundamentals: Security in the Jenkins Pipeline Soumya Soumya Soumya Follow Oct 6 '24 DevSecOps Fundamentals: Security in the Jenkins Pipeline # jenkins # sast # dast # devsecops 9 reactions Comments Add Comment 5 min read DevSecOps 2024: The Game-Changing Trends in AI, Automation, and Cloud Tech Jeffrey Boyle Jeffrey Boyle Jeffrey Boyle Follow Oct 3 '24 DevSecOps 2024: The Game-Changing Trends in AI, Automation, and Cloud Tech # devsecops # cloud # tech 1 reaction Comments Add Comment 4 min read Automate Uploading Security Scan Results to DefectDojo Salaudeen O. Abdulrasaq Salaudeen O. Abdulrasaq Salaudeen O. Abdulrasaq Follow Sep 15 '24 Automate Uploading Security Scan Results to DefectDojo # devsecops # gitlab # defectdojo # python 13 reactions Comments Add Comment 5 min read loading... 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . DEV Community © 2016 - 2026. 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https://dev.to/jwebsite-go/readiness-probe-3co0#%D0%B2-kubernetes-%D1%87%D1%82%D0%BE-%D0%BF%D1%80%D0%BE%D0%B8%D1%81%D1%85%D0%BE%D0%B4%D0%B8%D1%82 | Readiness probe - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse Khadijah (Dana Ordalina) Posted on Jan 13 Readiness probe # devops # aws # kubernetes # beginners Readiness probe ** — это **проверка “готово ли приложение принимать трафик” . Проще говоря: “Ты уже готов работать с пользователями или ещё нет?” Чаще всего это термин из Kubernetes . Простыми словами 👇 Представь кафе: Кафе открыто , но повар ещё не готов, кухня не прогрелась, продукты не разложены. Readiness probe — это как вопрос официанту: 👉 «Можно уже пускать клиентов?» Если ответ “нет” — клиенты не заходят. Если “да” — клиентов начинают пускать. В Kubernetes что происходит Kubernetes регулярно проверяет приложение (например, по HTTP-запросу или команде). Если readiness probe успешен ✅ → pod получает трафик (его добавляют в Service / Load Balancer). Если неуспешен ❌ → pod жив , но трафик к нему не идёт . ⚠️ Важно: Readiness probe не убивает pod , он просто временно “выводится из оборота”. Чем отличается от liveness probe Коротко: Liveness probe — “Ты вообще жив?” ❌ нет → pod перезапускают Readiness probe — “Ты готов обслуживать запросы?” ❌ нет → pod живёт, но без трафика Когда readiness probe особенно нужен приложение долго стартует подключается к БД делает миграции временно перегружено зависит от внешних сервисов Погнали, наглядно и без заумных слов 😄 Реальный YAML-пример с readiness + liveness + startup apiVersion : v1 kind : Pod metadata : name : demo-app spec : containers : - name : app image : my-app:1.0 ports : - containerPort : 8080 # 1️⃣ Startup probe — ждём, пока приложение ВООБЩЕ запустится startupProbe : httpGet : path : /health/startup port : 8080 failureThreshold : 30 periodSeconds : 5 # → даём до 150 секунд на старт # 2️⃣ Readiness probe — готово ли принимать трафик readinessProbe : httpGet : path : /health/ready port : 8080 initialDelaySeconds : 5 periodSeconds : 5 failureThreshold : 3 # 3️⃣ Liveness probe — не зависло ли livenessProbe : httpGet : path : /health/live port : 8080 periodSeconds : 10 failureThreshold : 3 Enter fullscreen mode Exit fullscreen mode Что здесь происходит по шагам 🟦 Startup probe Вопрос: «Ты уже ЗАПУСТИЛСЯ?» Kubernetes не запускает readiness и liveness , пока startup probe не станет OK если не стал OK за лимит → pod перезапускают 💡 Нужен для: Java / Spring приложений с миграциями долгого старта 🟩 Readiness probe Вопрос: «Ты ГОТОВ принимать запросы?» если ❌ → pod убирают из Service pod не перезапускают когда снова ✅ → трафик возвращается 💡 Типично проверяют: подключение к БД доступность зависимостей перегрузку 🟥 Liveness probe Вопрос: «Ты вообще ЖИВ?» если ❌ → pod перезапускают 💡 Проверяет: deadlock зависшие потоки утечки памяти Сравнение: startup vs readiness (очень коротко) Probe Когда Если FAIL Для чего startup только при старте pod перезапуск долгий запуск readiness всё время убрать трафик временно не готов liveness всё время pod перезапуск приложение зависло Жизненный пример Приложение стартует так: запускается JVM (40 сек) миграции БД (30 сек) готово принимать запросы 👉 startup probe ждёт шаги 1–2 👉 readiness probe включает трафик только после шага 3 👉 liveness probe следит, чтобы всё не зависло через час Top comments (0) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse Khadijah (Dana Ordalina) Follow DevOps Engineer. AWS, Terraform, Docker and CI/CD. Building real projects and sharing my DevOps journey. Location United States Work DevOps Engineer Joined Dec 20, 2025 More from Khadijah (Dana Ordalina) Сине-зеленое развертывание на EKS # eks # aws # bluegreen # programming Kubernetes #1 # kubernetes # nginx # docker # programming 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . DEV Community © 2016 - 2026. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Artificial Intelligence Follow Hide Artificial intelligence leverages computers and machines to mimic the problem-solving and decision-making capabilities found in humans and in nature. Create Post submission guidelines Posts about artificial intelligence. Older #ai posts 11 12 13 14 15 16 17 18 19 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu COST EFFECTIVE AI IN GCP Aparna Pradhan Aparna Pradhan Aparna Pradhan Follow Jan 10 COST EFFECTIVE AI IN GCP # ai # cloudcomputing # gemini # serverless Comments Add Comment 2 min read vLLM Quickstart: High-Performance LLM Serving Rost Rost Rost Follow Jan 10 vLLM Quickstart: High-Performance LLM Serving # llm # ai # python # docker Comments Add Comment 18 min read Stop Manually Booking Doctors: Build an Autonomous Health Agent with LangGraph & Playwright Beck_Moulton Beck_Moulton Beck_Moulton Follow Jan 10 Stop Manually Booking Doctors: Build an Autonomous Health Agent with LangGraph & Playwright # ai # python # machinelearning # opensource Comments Add Comment 3 min read Building Kiddomato: How We Designed an AI Picture Book Platform That Puts Children First Kiddomato Kiddomato Kiddomato Follow Jan 10 Building Kiddomato: How We Designed an AI Picture Book Platform That Puts Children First # ai # webdev 1 reaction Comments Add Comment 3 min read Met and fixed(not sure) a issue where hires_fix paramaters saved wrongly when using dynamic prompts ragnaDolphin ragnaDolphin ragnaDolphin Follow Jan 10 Met and fixed(not sure) a issue where hires_fix paramaters saved wrongly when using dynamic prompts # ai # python # beginners Comments Add Comment 1 min read Why I built an "Anti-Node" for the Deep Web Ayush Gairola Ayush Gairola Ayush Gairola Follow Jan 10 Why I built an "Anti-Node" for the Deep Web # programming # saas # ai # algorithms Comments Add Comment 2 min read I built TuneKit to escape fine-tuning hell (trending #19 on Product Hunt today) Riyanshi Bohra Riyanshi Bohra Riyanshi Bohra Follow Jan 9 I built TuneKit to escape fine-tuning hell (trending #19 on Product Hunt today) # machinelearning # ai # opensource # webdev Comments Add Comment 2 min read Vibe Coding vs AI-Driven Development: The Contracts Problem (and GS-TDD) Dennis Schmock Dennis Schmock Dennis Schmock Follow Jan 9 Vibe Coding vs AI-Driven Development: The Contracts Problem (and GS-TDD) # ai # testing # tdd # reliability Comments Add Comment 4 min read The Missing Link in AI Engineering: Why TypeScript + Zod is Better Than Python Python Programming Series Python Programming Series Python Programming Series Follow Jan 9 The Missing Link in AI Engineering: Why TypeScript + Zod is Better Than Python # javascript # typescript # ai Comments Add Comment 5 min read The Grok Scandal Proves AI Needs Cryptographic Audit Trails—Not Just Content Moderation VeritasChain Standards Organization (VSO) VeritasChain Standards Organization (VSO) VeritasChain Standards Organization (VSO) Follow Jan 10 The Grok Scandal Proves AI Needs Cryptographic Audit Trails—Not Just Content Moderation # ai # security # opensource Comments Add Comment 4 min read Prompt Routing & Context Engineering: Letting the System Decide What It Needs Parth Sarthi Sharma Parth Sarthi Sharma Parth Sarthi Sharma Follow Jan 9 Prompt Routing & Context Engineering: Letting the System Decide What It Needs # ai # promptengineering # vectordatabase # rag Comments Add Comment 3 min read Building an Autonomous Legal Contract Auditor with Python Aniket Hingane Aniket Hingane Aniket Hingane Follow Jan 10 Building an Autonomous Legal Contract Auditor with Python # python # ai # programming # productivity Comments Add Comment 4 min read What Business Owners Thought AI Would Be, Why It Didn’t Work, And Why the Canonical Intelligence Layer (CIL) Changes Everything Michal Harcej Michal Harcej Michal Harcej Follow Jan 10 What Business Owners Thought AI Would Be, Why It Didn’t Work, And Why the Canonical Intelligence Layer (CIL) Changes Everything # inteligencelayer # ai # enterprise # tauguard Comments Add Comment 3 min read A Tier List for Company AI Strategies. Michael Landry Michael Landry Michael Landry Follow Jan 12 A Tier List for Company AI Strategies. # ai # leadership 2 reactions Comments 1 comment 3 min read Network Communication Protocols and Artificial Intelligence Enhancement in IoT Environmental Monitoring Systems rachmad andri atmoko rachmad andri atmoko rachmad andri atmoko Follow Jan 10 Network Communication Protocols and Artificial Intelligence Enhancement in IoT Environmental Monitoring Systems # ai # iot # networking # systemdesign Comments Add Comment 29 min read How I Bypassed Google's Broken Python SDK to Build an AI Pipeline in Docker Shashank Chakraborty Shashank Chakraborty Shashank Chakraborty Follow Jan 9 How I Bypassed Google's Broken Python SDK to Build an AI Pipeline in Docker # ai # docker # google # python Comments 1 comment 3 min read Can AI Really Build Your App From Just a Vibe? Max aka Mosheh Max aka Mosheh Max aka Mosheh Follow Jan 10 Can AI Really Build Your App From Just a Vibe? # ai # productivity # security Comments Add Comment 1 min read I Abused AI to Build Products. Here’s What It Cost Me. ItsMadeByDani ItsMadeByDani ItsMadeByDani Follow Jan 11 I Abused AI to Build Products. Here’s What It Cost Me. # ai # vibecoding # entrepreneurship # programming Comments Add Comment 3 min read What is cyber security and why is it important in today’s digital world? Ridhima Ridhima Ridhima Follow Jan 9 What is cyber security and why is it important in today’s digital world? # cybersecurity # webdev # ai # security Comments Add Comment 1 min read Building an Autonomous Template Business, kind of. Sang Song Sang Song Sang Song Follow Jan 9 Building an Autonomous Template Business, kind of. # agents # antigravity # programming # ai Comments Add Comment 4 min read Visionary - Photo Of the Day Browser Extension Senthil Kumaran Senthil Kumaran Senthil Kumaran Follow Jan 10 Visionary - Photo Of the Day Browser Extension # ai # extensions # browser # picture Comments Add Comment 1 min read Project Review: AI-Powered Oil Spill Detection Using Deep Learning Kenechukwu Anoliefo Kenechukwu Anoliefo Kenechukwu Anoliefo Follow Jan 9 Project Review: AI-Powered Oil Spill Detection Using Deep Learning # mlzoomcamp # deeplearning # ai Comments Add Comment 3 min read When Everyone Runs a Factory Chris Korhonen Chris Korhonen Chris Korhonen Follow Jan 11 When Everyone Runs a Factory # ai # agents # management 7 reactions Comments 3 comments 10 min read When AI Is the Programmer, the Language Has to Change Mark Edmondson Mark Edmondson Mark Edmondson Follow Jan 9 When AI Is the Programmer, the Language Has to Change # ai # coding # programming # go Comments Add Comment 2 min read 🧠✂️ Neural Network Lobotomy: Removed 7 Layers from an LLM — It Became 30% Faster Artyom Molchanov Artyom Molchanov Artyom Molchanov Follow Jan 9 🧠✂️ Neural Network Lobotomy: Removed 7 Layers from an LLM — It Became 30% Faster # machinelearning # ai Comments Add Comment 6 min read loading... 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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https://dev.to/jwebsite-go/readiness-probe-3co0#liveness-probe | Readiness probe - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. DUMB DEV Community Follow Memes and software development shitposting Design Community Follow Web design, graphic design and everything in-between Security Forem Follow Your central hub for all things security. From ethical hacking and CTFs to GRC and career development, for beginners and pros alike Golf Forem Follow A community of golfers and golfing enthusiasts Crypto Forem Follow A collaborative community for all things Crypto—from Bitcoin to protocol development and DeFi to NFTs and market analysis. Parenting Follow A place for parents to the share the joys, challenges, and wisdom that come from raising kids. We're here for them and for each other. Forem Core Follow Discussing the core forem open source software project — features, bugs, performance, self-hosting. Maker Forem Follow A community for makers, hobbyists, and professionals to discuss Arduino, Raspberry Pi, 3D printing, and much more. HMPL.js Forem Follow For developers using HMPL.js to build fast, lightweight web apps. A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse Khadijah (Dana Ordalina) Posted on Jan 13 Readiness probe # devops # aws # kubernetes # beginners Readiness probe ** — это **проверка “готово ли приложение принимать трафик” . Проще говоря: “Ты уже готов работать с пользователями или ещё нет?” Чаще всего это термин из Kubernetes . Простыми словами 👇 Представь кафе: Кафе открыто , но повар ещё не готов, кухня не прогрелась, продукты не разложены. Readiness probe — это как вопрос официанту: 👉 «Можно уже пускать клиентов?» Если ответ “нет” — клиенты не заходят. Если “да” — клиентов начинают пускать. В Kubernetes что происходит Kubernetes регулярно проверяет приложение (например, по HTTP-запросу или команде). Если readiness probe успешен ✅ → pod получает трафик (его добавляют в Service / Load Balancer). Если неуспешен ❌ → pod жив , но трафик к нему не идёт . ⚠️ Важно: Readiness probe не убивает pod , он просто временно “выводится из оборота”. Чем отличается от liveness probe Коротко: Liveness probe — “Ты вообще жив?” ❌ нет → pod перезапускают Readiness probe — “Ты готов обслуживать запросы?” ❌ нет → pod живёт, но без трафика Когда readiness probe особенно нужен приложение долго стартует подключается к БД делает миграции временно перегружено зависит от внешних сервисов Погнали, наглядно и без заумных слов 😄 Реальный YAML-пример с readiness + liveness + startup apiVersion : v1 kind : Pod metadata : name : demo-app spec : containers : - name : app image : my-app:1.0 ports : - containerPort : 8080 # 1️⃣ Startup probe — ждём, пока приложение ВООБЩЕ запустится startupProbe : httpGet : path : /health/startup port : 8080 failureThreshold : 30 periodSeconds : 5 # → даём до 150 секунд на старт # 2️⃣ Readiness probe — готово ли принимать трафик readinessProbe : httpGet : path : /health/ready port : 8080 initialDelaySeconds : 5 periodSeconds : 5 failureThreshold : 3 # 3️⃣ Liveness probe — не зависло ли livenessProbe : httpGet : path : /health/live port : 8080 periodSeconds : 10 failureThreshold : 3 Enter fullscreen mode Exit fullscreen mode Что здесь происходит по шагам 🟦 Startup probe Вопрос: «Ты уже ЗАПУСТИЛСЯ?» Kubernetes не запускает readiness и liveness , пока startup probe не станет OK если не стал OK за лимит → pod перезапускают 💡 Нужен для: Java / Spring приложений с миграциями долгого старта 🟩 Readiness probe Вопрос: «Ты ГОТОВ принимать запросы?» если ❌ → pod убирают из Service pod не перезапускают когда снова ✅ → трафик возвращается 💡 Типично проверяют: подключение к БД доступность зависимостей перегрузку 🟥 Liveness probe Вопрос: «Ты вообще ЖИВ?» если ❌ → pod перезапускают 💡 Проверяет: deadlock зависшие потоки утечки памяти Сравнение: startup vs readiness (очень коротко) Probe Когда Если FAIL Для чего startup только при старте pod перезапуск долгий запуск readiness всё время убрать трафик временно не готов liveness всё время pod перезапуск приложение зависло Жизненный пример Приложение стартует так: запускается JVM (40 сек) миграции БД (30 сек) готово принимать запросы 👉 startup probe ждёт шаги 1–2 👉 readiness probe включает трафик только после шага 3 👉 liveness probe следит, чтобы всё не зависло через час Top comments (0) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse Khadijah (Dana Ordalina) Follow DevOps Engineer. AWS, Terraform, Docker and CI/CD. Building real projects and sharing my DevOps journey. Location United States Work DevOps Engineer Joined Dec 20, 2025 More from Khadijah (Dana Ordalina) Сине-зеленое развертывание на EKS # eks # aws # bluegreen # programming Kubernetes #1 # kubernetes # nginx # docker # programming 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . DEV Community © 2016 - 2026. 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https://dev.to/ben/meme-monday-2if1#comment-33h5c | Meme Monday - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse Ben Halpern Posted on Jan 12 Meme Monday # jokes # watercooler # discuss Meme Monday! Today's cover image comes from last week's thread . DEV is an inclusive space! Humor in poor taste will be downvoted by mods. Top comments (18) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Collapse Expand bingkahu bingkahu bingkahu Follow Full-stack developer focused on decentralized communication and privacy-centric web applications. Lead maintainer of CodeChat, an open-source peer-to-peer messaging platform built on WebRTC and PeerJS Education School Work Student Joined Jan 11, 2026 • Jan 12 Dropdown menu Copy link Hide Finally, a UI that doesn't make me check my phone for a code. This is the peak user experience we should all strive for. 10/10 security. Like comment: Like comment: 4 likes Like Comment button Reply Collapse Expand Ben Halpern Ben Halpern Ben Halpern Follow A Canadian software developer who thinks he’s funny. Email ben@forem.com Location NY Education Mount Allison University Pronouns He/him Work Co-founder at Forem Joined Dec 27, 2015 • Jan 12 Dropdown menu Copy link Hide haha Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Ben Halpern Ben Halpern Ben Halpern Follow A Canadian software developer who thinks he’s funny. Email ben@forem.com Location NY Education Mount Allison University Pronouns He/him Work Co-founder at Forem Joined Dec 27, 2015 • Jan 12 Dropdown menu Copy link Hide Today's AI comedy showdown based on the joke from the cover Gemini ChatGPT Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Ben Halpern Ben Halpern Ben Halpern Follow A Canadian software developer who thinks he’s funny. Email ben@forem.com Location NY Education Mount Allison University Pronouns He/him Work Co-founder at Forem Joined Dec 27, 2015 • Jan 12 • Edited on Jan 12 • Edited Dropdown menu Copy link Hide These are both complicated and not great but I think Gemini is a bit funnier here Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Reid Burton Reid Burton Reid Burton Follow I am an amateur programmer. I program in more languages than I care to remember. Location string Location = null; Education Homeschooled Pronouns He/Him Work Ceo of unemployment. Joined Nov 7, 2024 • Jan 12 Dropdown menu Copy link Hide Tru dat. Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Best Codes Best Codes Best Codes Follow I love coding, 3D designing, and listening to music. I'm currently a fanatic about Rust, TypeScript, and Next.js. Christian, Coder, Creator Email bestcodes.official+devto@gmail.com Location Earth Education Self-taught Work Freelance Programmer | Fullstack Dev Joined Oct 24, 2023 • Jan 13 Dropdown menu Copy link Hide It's hard to tell which one is “funnier” because they're both so bad 💀 Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand heckno heckno heckno Follow Joined Sep 4, 2025 • Jan 12 Dropdown menu Copy link Hide Like comment: Like comment: 9 likes Like Comment button Reply Collapse Expand Aryan Choudhary Aryan Choudhary Aryan Choudhary Follow Level up 10x faster Email aryanc1240@gmail.com Location Pune, India Pronouns He/Him Work SDE 1 Joined Nov 5, 2024 • Jan 13 Dropdown menu Copy link Hide Haha I'm gonna use this term Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand heckno heckno heckno Follow Joined Sep 4, 2025 • Jan 12 • Edited on Jan 12 • Edited Dropdown menu Copy link Hide Like comment: Like comment: 10 likes Like Comment button Reply Collapse Expand bingkahu bingkahu bingkahu Follow Full-stack developer focused on decentralized communication and privacy-centric web applications. Lead maintainer of CodeChat, an open-source peer-to-peer messaging platform built on WebRTC and PeerJS Education School Work Student Joined Jan 11, 2026 • Jan 12 Dropdown menu Copy link Hide 😂 Like comment: Like comment: 3 likes Like Comment button Reply Collapse Expand Ben Halpern Ben Halpern Ben Halpern Follow A Canadian software developer who thinks he’s funny. Email ben@forem.com Location NY Education Mount Allison University Pronouns He/him Work Co-founder at Forem Joined Dec 27, 2015 • Jan 12 Dropdown menu Copy link Hide lol Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand Best Codes Best Codes Best Codes Follow I love coding, 3D designing, and listening to music. I'm currently a fanatic about Rust, TypeScript, and Next.js. Christian, Coder, Creator Email bestcodes.official+devto@gmail.com Location Earth Education Self-taught Work Freelance Programmer | Fullstack Dev Joined Oct 24, 2023 • Jan 13 Dropdown menu Copy link Hide Like comment: Like comment: 3 likes Like Comment button Reply Collapse Expand Aryan Choudhary Aryan Choudhary Aryan Choudhary Follow Level up 10x faster Email aryanc1240@gmail.com Location Pune, India Pronouns He/Him Work SDE 1 Joined Nov 5, 2024 • Jan 13 Dropdown menu Copy link Hide Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Brian Zavala Brian Zavala Brian Zavala Follow CS Student & Dad. I build privacy-first apps on Arch Linux (btw). Turning caffeine into code. Location Texas Education Bachelor of science in computer science Pronouns He/Him Work Founder & Lead Dev Joined Sep 2, 2024 • Jan 13 Dropdown menu Copy link Hide When someone asks me about my side-project Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Timm David Timm David Timm David Follow Joined Dec 10, 2025 • Jan 13 Dropdown menu Copy link Hide hahaha great. Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand Hadil Ben Abdallah Hadil Ben Abdallah Hadil Ben Abdallah Follow Software Engineer • Technical Content Writer • LinkedIn Content Creator Email hadilbenabdallah111@gmail.com Location Tunisia Education ENET'COM Pronouns she/her Work Content Writer & Social Media Manager Joined Nov 13, 2023 • Jan 13 Dropdown menu Copy link Hide Like comment: Like comment: 1 like Like Comment button Reply View full discussion (18 comments) Some comments may only be visible to logged-in visitors. Sign in to view all comments. Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse Ben Halpern Follow A Canadian software developer who thinks he’s funny. Location NY Education Mount Allison University Pronouns He/him Work Co-founder at Forem Joined Dec 27, 2015 More from Ben Halpern Meme Monday # discuss # jokes # watercooler Meme Monday # discuss # watercooler # jokes Meme Monday # discuss # watercooler # jokes 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . DEV Community © 2016 - 2026. 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https://dev.to/whykislay/the-limitations-of-text-embeddings-in-rag-applications-a-deep-engineering-dive-3ohh#comments | The Limitations of Text Embeddings in RAG Applications: A Deep Engineering Dive - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse Kumar Kislay Posted on Jan 12 The Limitations of Text Embeddings in RAG Applications: A Deep Engineering Dive # productivity # sre # rag # machinelearning TL;DR We have all been there. You follow the tutorial, spin up a vector database, ingest your documentation, and for a moment, it feels like magic. You ask a question, and the LLM answers. But then you push to production. Suddenly, searching for "error 500" returns "500 days of summer," asking for "code without bugs" returns buggy code, and asking "what happened last week?" results in a blank stare from your system. This report is a comprehensive, 15,000-word deep dive into why naive RAG fails. We explore the mathematical limitations of cosine similarity, the "curse of dimensionality," and the inability of embeddings to handle negation, temporal context, and structured engineering data. We will also cover how to fix it using Hybrid Search (BM25), Re-ranking (ColBERT), and Knowledge Graphs (GraphRAG), with real-world examples from our engineering journey at SyncAlly. Part I: The Honeymoon Phase and the Inevitable Crash If you are reading this, you are likely standing somewhere in the "Trough of Disillusionment" regarding Retrieval Augmented Generation (RAG). The initial promise was intoxicating. We were told that by simply chunking our data, running it through an embedding model perhaps OpenAI's text-embedding-3-small or an open-source champion from Hugging Face and storing it in a vector database, we could give our LLMs "long-term memory." It felt like we had solved the context window problem forever. You could turn paragraphs of dense technical text into lists of floating-point numbers (vectors), plot them in a high-dimensional hyperspace, and mathematically calculate "semantic similarity." It was elegant. It was modern. It was supposed to work. Then, you gave it to your users. Or worse, you gave it to your own engineering team. The complaints started rolling in immediately. A developer searches for "payment gateway timeout" and gets fifty documents about "payment success" because the vectors for "success" and "timeout" are suspiciously close in the high-dimensional space of financial transaction contexts.1 Another engineer asks, "Who changed the auth service configuration last Tuesday?" and the system retrieves a generic Wiki page about 'Authentication Best Practices' written in 2021, completely ignoring the temporal constraint of "last Tuesday". Someone else tries to find a specific error code, 0x80040115, and the system retrieves a marketing blog post about "115 ways to improve customer satisfaction" because the embedding model treated the hexadecimal code as noise and latched onto the number 115. Why does this happen? Why does a technology labeled "Artificial Intelligence" fail at basic keyword matching, boolean logic, and time perception? The answer lies deep in the fundamental architecture of dense vector retrieval. While embeddings are incredible at capturing general semantic vibes matching "car" to "automobile" or "happy" to "joyful" they are mathematically ill-equipped to handle the precision, structure, and temporal context required for complex engineering workflows. They are fuzzy matching engines in a domain that demands absolute precision. At SyncAlly, we are obsessed with developer productivity. We are building an all-in-one workspace that connects tasks, meetings, code, and calendars to stop the context-switching madness that kills engineering flow. We faced these exact issues when we tried to build our own "brain" for engineering teams. We wanted engineers to be able to ask, "Why did we decide to use PostgreSQL?" and get an answer that synthesized context from a Slack debate, a Jira ticket description, and a transcript from a Zoom sprint planning meeting. We quickly learned that a simple vector store couldn't do this. It couldn't connect the dots between the decision (Slack) and the implementation (Code) because they didn't share enough lexical overlap for a vector model to consider them "close". In this report, we are going to dissect the failures of text embeddings with surgical precision. We are not just going to complain; we are going to look at the math, the linguistics, and the operational headaches. Then, we are going to build the solutions. We will explore why Hybrid Search is non-negotiable, why Re-ranking is the secret sauce of accuracy, and why the industry is inevitably moving toward GraphRAG to solve the complex reasoning problems that vectors simply cannot touch. Part II: The Mathematical Failures of Dense Embeddings To understand why your RAG system fails, you have to understand what it is actually doing under the hood. It is compressing the infinite complexity of human language into a fixed-size vector, typically 768, 1536, or 3072 dimensions. This compression is lossy. It discards syntax, precise negation, and structural hierarchy in favor of a generalized semantic position. The Curse of Dimensionality and the Meaning of "Distance" Vector retrieval relies on K-Nearest Neighbors (KNN) or, more commonly in production, Approximate Nearest Neighbors (ANN) algorithms like Hierarchical Navigable Small World (HNSW) graphs. The core operation is measuring the distance between the user's query vector and your document vectors. The industry standard metric for this is Cosine Similarity. It measures the cosine of the angle between two vectors in a multi-dimensional space. If the vectors point in the exact same direction, the similarity is 1. If they are orthogonal (90 degrees apart), the similarity is 0. If they point in opposite directions, it is -1. Here is the problem: In very high-dimensional spaces, the concept of "distance" starts to lose its intuitive meaning. This is known as the Curse of Dimensionality.6 As the number of dimensions increases, the volume of the space increases exponentially, and the data becomes incredibly sparse. In these high-dimensional hypercubes, all points tend to become equidistant from each other. The contrast between the "nearest" neighbor and the "farthest" neighbor diminishes, making it difficult for the algorithm to distinguish between a highly relevant document and a marginally relevant one. Furthermore, recent research has highlighted that cosine similarity has significant blind spots. Crucially, it ignores the magnitude (length) of the vector. Vector A: (Small magnitude) Vector B: (Large magnitude) Cosine similarity says these two vectors are identical (Similarity = 1.0). They point in the exact same direction. But in semantic space, magnitude often correlates with specificity, information density, or confidence. A short, vague sentence ("The system crashed.") and a long, detailed technical post-mortem ("The system crashed due to a null pointer exception in the payment microservice…") might end up with identical directionality in the vector space. If your retrieval system is based solely on cosine similarity, it might retrieve the vague chunk because it is "closer" or just as close as the detailed one, simply because the noise in the detailed chunk pulls its vector slightly off-axis. This phenomenon leads to "retrieval instability," where short, noisy text outranks high-quality, information-dense text. The "Mizan" balance function has been proposed as an alternative to weight magnitude back into the equation, but most off-the-shelf vector databases (Pinecone, Weaviate, Milvus) default to cosine similarity or dot product (which requires normalized vectors, making it mathematically equivalent to cosine similarity). The Anisotropy Problem Theoretical vector spaces are isotropic meaning space is uniform in all directions. Real-world language model embedding spaces are highly anisotropic. This means that embeddings tend to occupy a narrow cone in the vector space rather than being distributed evenly. Why does this matter to you as a developer? It means that "similarity" is not uniform. Two documents might be very different semantically but still have a high cosine similarity score (e.g., 0.85) simply because all documents in that embedding model cluster together. This makes setting a "similarity threshold" for your RAG system a nightmare. You might set a threshold of 0.7 to filter out irrelevant docs, only to find that totally irrelevant noise scores a 0.75 because of the "collapsing" nature of the embedding space. This anisotropy also exacerbates the Hubness Problem, where certain vectors (hubs) appear as nearest neighbors to a disproportionately large number of other vectors, regardless of actual semantic relevance. If your query hits a "hub," you get generic garbage results. The "Exact Match" & Lexical Gap Vectors are "dense" representations. They smear the meaning of a word across hundreds of dimensions. This is a feature, not a bug, when you want to match "car" to "automobile." It allows for fuzzy matching and synonym detection. However, it is a catastrophic bug when you need lexical exactness. In engineering contexts, we often search for specific, non-negotiable identifiers: Error Codes: 0xDEADBEEF, E_ACCESSDENIED Product SKUs: SKU-9928-X Variable Names: getUserById vs getUserByName Version Numbers: v2.1.4 vs v2.1.5 Trace IDs: a1b2-c3d4-e5f6 To a vector model, v2.1.4 and v2.1.5 are nearly identical. They appear in identical linguistic contexts (e.g., "upgraded to version X"). They share similar character n-grams. They likely map to almost the same point in vector space. However, to a developer debugging a breaking change, the difference between .4 and .5 is the difference between a working system and a production outage. Case Study: The "ID" Problem We ran an experiment internally at SyncAlly where we tried to retrieve specific Jira tickets using only dense vector search. Query: "Show me ticket ENG-342" Result: The system retrieved tickets ENG-341, ENG-343, and ENG-345. Analysis: The model (OpenAI text-embedding-ada-002 at the time) effectively treated the "ENG-" prefix as the semantic anchor and the numbers as minor noise. Since the descriptions of these tickets were all related to similar engineering tasks, the vector distance between them was negligible. The specific integer "342" did not have enough semantic weight to differentiate itself from "341". This is known as the Lexical Gap. Embeddings capture meaning, but they lose surface form. In many technical domains, the surface form (the exact spelling, the exact number) is the meaning. If you are building a tool for developers, you simply cannot rely on vectors alone to handle unique identifiers. Part III: The Linguistic Failures (Logic is Hard) If math is the engine of RAG failures, linguistics is the fuel. Text embeddings are fundamentally statistical correlations of word co-occurrences. They do not "understand" logic, negation, or compositionality in the way a human or a symbolic logic system does. The Negation Blind Spot One of the most embarrassing and persistent failures of vector search is negation. Query: "Find recipes with no peanuts." Result: Retrieves recipes with peanuts. Query: "Show me functions that are not deprecated." Result: Retrieves a list of deprecated functions. Why does this happen? Consider the sentences "The function is deprecated" and "The function is not deprecated." They share almost all the same words ("The", "function", "is", "deprecated"). In a bag-of-words model, they are nearly identical. Even in sophisticated transformer models like BERT or CLIP, the token "not" acts as a modifier, but it often does not have enough "gravitational pull" to flip the vector to the opposite side of the semantic hyperspace. The vector for the sentence is still dominated by the strong semantic content of "function" and "deprecated". Recent studies on Vision-Language Models (VLMs) and text embeddings have formalized this as a "Negation Blindness." These models frequently interpret negated text pairs as semantically similar because the training data (e.g., Common Crawl) contains far fewer examples of explicit negation compared to affirmative statements. The models learn to associate "deprecated" with the concept of deprecation, but they fail to learn that "not" is a logical operator that inverts that concept. For a developer tool like SyncAlly, this is critical. If a CTO asks, "Which projects are not on track?", and the system retrieves updates about projects that are on track because they contain the words "project" and "track," the trust in the tool evaporates instantly. Polysemy and "Context Flattening" Polysemy refers to words that have multiple meanings depending on context. "Apple" (fruit) vs. "Apple" (company). "Java" (island) vs. "Java" (language). "Driver" (golf) vs. "Driver" (software) vs. "Driver" (car). Modern embeddings like BERT are contextual, meaning they look at surrounding words to determine the specific embedding for a token. So, theoretically, they should handle this. However, RAG pipelines often introduce a failure mode during the chunking phase known as Context Flattening. The Chunking Problem: To fit documents into a vector database, we must chop them into chunks (e.g., 500 tokens). Chunk 1: "…the driver failed to load during the initialization sequence…" Chunk 2: "…causing the application to crash and burn." If you search for "database driver issues," Chunk 1 might be retrieved. But what if the document was actually about a printer driver? Or a JDBC driver? Or a golf simulation game? If the chunk itself doesn't contain the clarifying context (e.g., the words "printer" or "JDBC" appeared in the previous paragraph), the embedding for Chunk 1 becomes ambiguous. The vector represents a generic "driver failure," which might match a query about a totally different type of driver. At SyncAlly, we deal with "Tasks." A "Task" in an engineering context (a Jira ticket) is very different from a "Task" in a generic To-Do app or a "Task" in an operating system process scheduler. If our RAG pipeline treats them as generic English words, we lose domain specificity. The embedding model "flattens" the rich, hierarchical context of the document into a single, flat vector for the chunk, discarding the surrounding knowledge that defines what the chunk actually means. The "Bag of Words" Legacy Despite the advancements of Transformers, embeddings often still behave somewhat like "Bag of Words" models. They struggle with compositionality understanding how the order of words changes meaning. Sentence A: "The dog bit the man." Sentence B: "The man bit the dog." These sentences contain identical words. A simple averaging of word vectors would yield identical sentence embeddings. While modern models (like OpenAI's) use attention mechanisms to capture order, they are still prone to confusion when sentences become complex or when the distinguishing information is subtle. In code search, this is fatal. A.calls(B) is fundamentally different from B.calls(A), yet embeddings often struggle to distinguish the directionality of the relationship. Part IV: The Engineering Failures (Code & Structure) You are building a RAG for developers. Naturally, you want to index code. This is where text embeddings fail spectacularly. Code is not natural language. It is a formal language with strict syntax, hierarchy, and dependency structures that text embedding models simply do not comprehend. Code is Logic, Not Prose Standard embedding models (like OpenAI's text-embedding-3 or ada-002) are trained primarily on massive corpora of natural language text (Wikipedia, Reddit, Common Crawl). They treat code like it is weirdly punctuated English. But code is highly structured logic. The Indentation Failure: In languages like Python, indentation determines the logic and control flow. Snippet A if user.is_admin: delete_database() vs Snippet B if user.is_admin: pass delete_database() To a text embedding model, these two snippets are 99% similar. They share the exact same tokens in almost the same order. But functionally, one is safe (admin only) and the other is catastrophic (deletes database for everyone). A vector search for "safe database deletion" might retrieve the catastrophic code because it matches the keywords "database" and "delete" and "admin," completely missing the semantic significance of the indentation change. The Dependency Disconnect Code does not live in isolation. A function process_payment() in payment.ts depends on UserSchema in models.ts and StripeConfig in config.ts. If you chunk payment.ts and embed it, you lose the connection to UserSchema. Query: "How is the user address validated during payment?" RAG Result: It retrieves process_payment() because it matches "payment." However, the answer-the validation logic-is inside the UserSchema file. The UserSchema file doesn't mention "payment" explicitly; it only mentions "address" and "validation." Therefore, the vector search fails to retrieve the dependency, and the LLM cannot answer the question. This is a failure of retrieval scope. Text embeddings look at files (or chunks) as independent islands. Software engineering is a graph of dependencies. When you ask a question about a function, you often need the context of the functions it calls, the classes it inherits from, and the interfaces it implements. Vectors flatten this graph into a list of disconnected point The Insight: Code retrieval requires Code-Specific Embeddings (like jina-embeddings-v2-code or Salesforce's SFR-Embedding-Code) that have been trained on Abstract Syntax Trees (ASTs) or data flow graphs. Better yet, it requires a Graph-based approach where the dependencies are explicitly modeled as edges in a database, allowing the retrieval system to "walk" from the payment function to the user schema. The "Stale Code" Problem Code changes. Fast. A function that was valid yesterday might be deprecated today. If your RAG pipeline ingests code and documentation, it faces a massive synchronization challenge. Scenario: You refactor auth.ts and rename login() to authenticate(). RAG State: Your vector database still contains the old chunk for login(). Query: "How do I log in?" Failure: The system retrieves the old, hallucinated code snippet for login(). The developer tries it, it fails, and they curse the AI. Keeping a vector index in sync with a high-velocity codebase (Git repo) is an immense engineering challenge. You cannot just "update" a vector easily; you often have to re-chunk and re-embed the file. If you use a sliding window chunking strategy, changing one line of code might shift all the window boundaries, requiring you to re-embed the entire file or even the entire module. Part V: The Context Gap (SyncAlly's Specialty) This section highlights the specific pain point we solve at SyncAlly: The Temporal and Relational Context Gap. This is where "general purpose" RAG tools fail to deliver value for engineering teams. The "Last Week" Problem Time is relative. Humans use relative time constantly. Query: "What was discussed in last week's sprint planning?" Query: "Show me the latest error logs." A vector database stores static chunks of text. It does not natively understand that "last week" is dynamic relative to NOW(). If you indexed a meeting note from 2023 that says "Next week we ship v2," and you search for "shipping v2," that note is retrieved forever, even if v2 shipped years ago. Metadata Filtering is Not Enough: You might think, "I'll just filter by date > NOW() - 7 days." Sure, if the user explicitly asks for a date range and your system is smart enough to parse "last week" into a timestamp. But users are vague. They ask, "What's the status of the new UI?" They implicitly mean "the status as of today." Vector search will retrieve the project kickoff doc from 6 months ago (high semantic match, lots of keywords about "new UI") instead of the Slack update from this morning (lower semantic match because it's short, informal, and says "UI is looking good"). Traditional RAG systems struggle with Temporal Reasoning. They treat all facts as equally valid, regardless of when they were generated. In engineering, facts decay. The "truth" about the system architecture in 2022 is a "lie" in 2024. Unless your retrieval system explicitly prioritizes recency or models the evolution of documents (e.g., using a Versioned Knowledge Graph), you will constantly serve outdated information. The Context Switching Nightmare Engineers switch tools constantly. A typical workflow spans Jira, GitHub, Slack, Notion, and Zoom. The Scenario: A decision is made in a Slack thread ("Let's use Redis for caching"). A ticket is created in Jira ("Implement Cache"). Code is written in GitHub (import redis). The RAG Failure: If you ask "Why are we using Redis?", a vector search might find the import redis code or the Jira ticket. But it likely won't find the reasoning. The reasoning is buried in a Slack thread that doesn't mention the ticket ID or the specific file name. The Slack thread might say: "MySQL is choking on the session data. We need something faster." The code says: const cache = new Redis(); There is no semantic overlap between "MySQL is choking" and new Redis(). A vector search cannot bridge this gap. This is the core value proposition of SyncAlly. We don't just embed text; we map the relationships. "You know that feeling when you can't find where a decision was made? We fixed that." We realized that to answer "Why?", you need to traverse the graph: Code -> Linked Ticket -> Linked Conversation -> Decision. Vectors cannot traverse. They can only match. Without this relational graph, your RAG system is just a glorified Ctrl+F that hallucinates. Part VI: The Solutions (Building a Better RAG) Enough about why it breaks. Let's talk about how to fix it. If you are building a serious RAG application for engineering data, you need to move beyond "Naive RAG" (Chunk -> Embed -> Retrieve). You need a sophisticated, multi-stage retrieval pipeline. Solution 1: Hybrid Search (BM25 + Vectors) This is the single most effective "quick win" for engineering RAG systems. It involves combining the semantic understanding of dense vectors with the keyword precision of BM25 (Best Matching 25). What is BM25? BM25 is the evolution of TF-IDF. It is a probabilistic retrieval algorithm that ranks documents based on the frequency of query terms in the document, relative to their frequency in the entire corpus. Crucially, it handles exact matches perfectly. If you search for 0x80040115, BM25 will find the document that contains that exact string, even if the vector model thinks it's noise. How Hybrid Search Works: Dense Retrieval: Run the query through your vector database to find semantically similar documents (e.g., "authentication error"). Sparse Retrieval: Run the query through a BM25 index to find keyword matches (e.g., "E_AUTH_FAIL"). Reciprocal Rank Fusion (RRF): Combine the two lists of results. RRF works by taking the rank of a document in each list and calculating a new score: $$Score(d) = \sum_{r \in R} \frac{1}{k + rank(d, r)}$$ Where $rank(d, r)$ is the position of document $d$ in result list $r$, and $k$ is a constant (usually 60). This ensures that a document that appears in both lists gets a huge boost, while a document that is a perfect exact match (BM25 #1) but a poor semantic match still bubbles up to the top. Implementation Snippet (Python): from rank_bm25 import BM25Okapi from langchain_community.vectorstores import FAISS from langchain_openai import OpenAIEmbeddings 1. Setup BM25 (Sparse Index) In production, use a library like Elasticsearch or MeiliSearch for this tokenized_corpus = [doc.page_content.split() for doc in documents] bm25 = BM25Okapi(tokenized_corpus) 2. Setup Vector Search (Dense Index) vector_store = FAISS.from_documents(documents, OpenAIEmbeddings()) def hybrid_search(query, k=5): # Get BM25 scores bm25_scores = bm25.get_scores(query.split()) # Get indices of top k BM25 results top_bm25_indices = sorted(range(len(bm25_scores)), key=lambda i: bm25_scores[i], reverse=True)[:k] # Get Vector results # Returns (Document, score) tuples vector_docs = vector_store.similarity_search_with_score(query, k=k) # Fuse (Simplified RRF Logic) # In a real app, you would map vector_docs back to IDs and calculate RRF scores combined_results = deduplicate_and_fuse(top_bm25_indices, vector_docs) return combined_results Enter fullscreen mode Exit fullscreen mode Why developers love this: It solves the "SKU problem," the "Error Code problem," and the "ID problem" instantly. It makes the search feel "smart" (semantic) but "reliable" (exact). Solution 2: Late Interaction & Re-ranking (ColBERT) Sometimes, Hybrid search isn't enough. You need the model to look at the query and the document together to understand nuance. Standard embeddings (Bi-Encoders) compress the query and document independently. This causes information loss. Cross-Encoders (Re-ranking): Instead of just trusting the vector DB, you retrieve a broad set of candidates (e.g., top 50), and then pass them through a Cross-Encoder (like ms-marco-MiniLM-L-6-v2 or Cohere's Rerank API). This model takes (Query, Document) as a single input pair and outputs a relevance score (0 to 1). It can "see" how the specific words in the query interact with the words in the document. Pros: Drastically improves accuracy. Cons: Very slow. You cannot run a Cross-Encoder on your entire database; only on the top N results. ColBERT (Late Interaction): ColBERT (Contextualized Late Interaction over BERT) is a fascinating middle ground. Instead of compressing a document into one vector, it keeps vectors for every token in the document. When you search, it performs "late interaction," matching every query token vector to every document token vector using a "MaxSim" operation. This preserves fine-grained details that usually get lost in a single vector. If your query is "bug in the payment retry logic," ColBERT can explicitly match "payment," "retry," and "logic" to the corresponding parts of the document, rather than hoping a single vector captures the whole idea.24 Trade-off: ColBERT is storage-intensive. Your index size will balloon because you are storing a vector for every single word in your corpus. But for "needle in a haystack" engineering queries, it is often necessary. Solution 3: GraphRAG (The Knowledge Graph Approach) This is the endgame. This is where SyncAlly focuses its R&D. GraphRAG combines Knowledge Graphs (KG) with LLMs. Instead of just chunking text, you use an LLM to extract entities and relationships during ingestion. Extraction Phase: An LLM scans your documents and identifies: Entities: PostgreSQL, Kislay (Founder), AuthService, Ticket-123. Relationships: Kislay CREATED AuthService. AuthService USES PostgreSQL. Ticket-123 MODIFIES AuthService. Querying Phase: When you ask "What databases does Kislay use?", the system doesn't just look for text similarity. It traverses the graph: Kislay -> CREATED -> AuthService -> USES -> PostgreSQL. Why GraphRAG Wins: Multi-hop Reasoning: It can connect dots across different documents. It can link a Slack message to a Jira ticket to a GitHub commit, answering "Why did we change this code?". Global Summarization: It can answer high-level questions like "What are the main themes in our sprint retrospectives?" by aggregating "communities" of nodes in the graph (e.g., detecting a cluster of nodes related to "database latency"). Explainability: It can show you the path it took to get the answer. "I found this answer because Kislay is linked to AuthService which is linked to Postgres." The Cost: Building a Knowledge Graph is hard. It requires maintaining a schema (ontology), performing entity resolution (knowing that "Phil" and "Philip" are the same person), and paying for expensive LLM calls to perform the extraction. At SyncAlly, we handle this complexity for you. We automatically build the Knowledge Graph from your connected tools, identifying entities like Tickets, PRs, and Meetings, and linking them based on mentions and timestamps. This gives you the power of GraphRAG without needing to write Cypher queries or manage a Neo4j instance. Part VII: Real-World Engineering Costs (The Horror Stories) Before you go and build your own custom RAG pipeline using open-source tools, let's talk about the hidden costs that the tutorials conveniently skip. "Building a RAG demo takes a weekend. Building a production RAG takes a year." The Maintenance Tax & Data Cleaning You will spend 80% of your time on Data Cleaning and Chunking Strategies, not on AI. PDF Parsing: Have you tried parsing a two-column PDF with tables? It is a nightmare. The text comes out garbled ("Column 1 Row 1 Column 2 Row 1…"), and your embeddings turn to trash. If the input text is garbage, the vector is garbage. Stale Data: Your documentation changes every day. How do you update the vectors? If you delete a Confluence page, do you remember to delete the vector? If you update a single paragraph, do you re-embed the whole document? This synchronization logic is painful and prone to bugs. Legacy Pipelines: As your data grows, your ingestion pipeline becomes a complex distributed system. You need queues (Kafka/RabbitMQ), retry logic for failed embeddings, and monitoring for API rate limits. Debugging Hallucinations When your RAG lies, how do you debug it? Was the retrieval bad? (Did we find the wrong docs?) Was the context window too small? (Did we cut off the answer?) Did the LLM just make it up? You need sophisticated Observability tools (like LangSmith, Arize Phoenix, or custom logging) to trace the exact chunks retrieved for every query. You need to curate "Negative Examples" queries that should return "I don't know" to test if your system hallucinates an answer when no relevant data exists. Case Study: The Silent Failure We once saw a RAG system that failed silently because a "knowledge base source" went offline. The system didn't throw an error; it just retrieved documents from the remaining sources (which were irrelevant) and the LLM confidently hallucinated an answer based on them. We had to implement "Guardrails" that check for source health before generating an answer. The "Not My Job" Problem Who owns the RAG pipeline? The AI Team? They build the prototype but don't want to carry the pager for the vector database. The Platform Team? They don't know how to optimize chunking strategies or debug embedding drift. The DevOps Team? They don't want to manage a new stateful infrastructure component (Vector DB like Milvus or Weaviate) alongside their Postgres and Redis instances. It usually falls into a black hole of ownership, leading to "Tech Debt" that accumulates rapidly. This is why we built SyncAlly. We believe developers shouldn't have to be RAG engineers just to get answers from their own data. We abstract away the vector stores, the graph construction, the embedding pipelines, and the synchronization logic. You just connect your GitHub and Slack, and it works. We handle the "plumbing" so you can focus on shipping code. Conclusion: The Future is Hybrid and Structured Text embeddings are a powerful tool, but they are not a silver bullet. They are "fuzzy" matching engines in a domain (software engineering) that demands precision, logic, and structure. Relying on them exclusively is a recipe for frustration. If you are building RAG applications today, you must follow these principles: Don't rely on vectors alone. Implement Hybrid Search (BM25 + Vectors) to capture exact keyword matches and identifiers. Respect structure. If you have metadata (dates, authors, tags), use it! Filter by metadata before or during your search to handle temporal and categorical queries. Consider the Graph. For complex, multi-hop questions ("Why did we do X?" or "How does A impact B?"), vectors will fail. You need a Knowledge Graph to model relationships. And if you don't want to build all of this yourself if you just want to stop searching through 50 browser tabs to find that one API key or design decision give SyncAlly a look. We've done the hard work of fusing GraphRAG, Vector Search, and Hybrid Retrieval into a unified workspace that actually understands your engineering context. We turn your scattered tools into a coherent knowledge base. Stop context switching. Start shipping. Discussion Devs, be honest: How many times has your "AI Search" returned completely irrelevant results because of a keyword mismatch? Have you tried implementing Hybrid Search yet? Or are you sticking with Ctrl+F? Drop your war stories (and your horror stories) in the comments below! 👇 Top comments (0) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse Kumar Kislay Follow Joined Nov 12, 2025 More from Kumar Kislay How do you keep engineering context alive when requirements change? Post: # discuss # documentation # productivity Anyone else feel like they spend more time finding information than writing code? # documentation # discuss # career # productivity I spent 4 months building features nobody wanted. Here's how I fixed my process. # learning # productivity # startup 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV Forem — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . Forem © 2016 - 2026. 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https://blog.smartere.dk/category/woodworking/ | blog.smartere » Woodworking blog.smartere // Ramblings of Mads Chr. Olesen okt 9 World’s Longest Multi-Cutter Blade: 30 cm Posted on onsdag, oktober 9, 2024 in Hal9k , Planets , Woodworking I had a need for an extra-extra long multi-cutter blade, so we made one in Hal9k . Until proven otherwise, we hereby claim it to be the world’s longest, at about 30 cm from rotation point to the cutting edge. Converting Starlock-MAX to Starlock-Plus Initially I thought I could get away with just a 80mm long Bosch MAIZ 32 APB which seems to be the longest commercially available. First problem was that my multi-cutter was only “Starlock-Plus” and this blade is Starlock-MAX. Turns out, you can easily get around that: just drill up the hole to 10mm, and it fits like a glove, at least on the Starlock-Plus Bosch GOP 18V-28 . World record time But as it turns out, I needed more length, and anything worth doing is worth overkilling! So sacrificing an old worn-out blade by welding on some 2mm steel plate provided a good base that would still attach to the multi-cutter. First attempt was just attaching the blade with two 2mm screws, as these are the largest that will fit in the star’s spikes and thereby prevent rotation. Initial testing: So next solution was to beef up with a central 8mm bolt instead. This worked much better if torqued enough (read: all you possibly can!), test-run went great after the initial oscillations: And ultimately the cut in the tight corner was made, one-handedly in order to be able to film: Great success! This should not be considered safe, and several warranties were probably voided, but it got the job done. Comments (2) | feb 20 Floating Solid Wood Alcove Shelves Posted on mandag, februar 20, 2023 in Hal9k , Planets , Woodworking I have an alcove where I wanted to put in some floating shelves. I wanted to use some solid wood I had lying around, to match the rest of the interior; this ruled out most of the methods described online: (i) building up the shelf around a bracket , and (ii) using hidden mounting hardware would be hard to get precise and would not provide support on the sides. So inspired by some of the options instead I tried to get by with just brackets on the three sides, in a solid wood shelf. I ended up with 12mm brackets of plywood in a 26mm solid wood shelf, and that was plenty sturdy. Step 1 was to cut out the rough shelves, with plenty of extra width, and rough fitting the plywood bracket pieces. It makes sense to leave as much on the top of the slit as possible, as this will be the failure point if overloaded. The excellent wood workshop at Hal9k came in very handy! Step 2 was to mount the plywood brackets in the alcove. Pretty easy to do using a laser level, biggest problem was getting the rawplugs in precise enough for the level to be kept. Step 3 was fitting the shelves individually, accounting for the crookedness of the 3 walls. The scribing method used by Rag’n’Bone Brown was pretty useful , just doing it in multiple steps to make sure not to cut off too much. Finally, all the shelves in final mounting. Getting them in took a bit of persuasion with a hammer, and minor adjustments with a knife to the plywood brackets, as it was a tight fit. The key again was small adjustments. One concern with such a tight fit would be wood movement; however most of the wood movement is “across the grain” which in this application means “in and out” from the alcove, where the wood is basically free to move as the shelves are not fastened to the brackets in any way. Another concern would be if the relatively small brackets (12x12mm) can handle the load of the relatively wide shelves (60cm wide, 35cm deep, and 2.6cm high). There are two failure scenarios: (i) the wood could split above the slit, (ii) or the bracket could deform or be pulled out. Neither seems likely as (i) applying a static (or even dynamic) load large enough to split the wood seems implausible, even at the weakest point in the middle of the front, and (ii) the tight fit counteracts the brackets ability to be pulled out since pulling out in one side would have the shelf hitting the wall on the opposite side. All in all a very satisfying project to work on and complete! Comments (0) | Categories Danish Hal9k Ikke kategoriseret Planet Ubuntu-DK Planets Sysadmin'ing Ubuntu University Woodworking © blog.smartere . All Rights Reserved. WordPress Theme designed by Chris Wallace | 2026-01-13T08:48:58 |
https://blog.smartere.dk/category/danish/ | blog.smartere » Danish blog.smartere // Ramblings of Mads Chr. Olesen okt 21 Giv mig nu bare elprisen.somjson.dk! (en historie om det måske værste datasæt i åbne energidata) Posted on mandag, oktober 21, 2024 in Danish , Hal9k , Planets Der findes rigtig meget åbent data om det danske energi system hos Energi Data Service , f.x. spot prisen på elektricitet og CO2 prognoser per kWh . Det er dog overordentligt svært at finde den samlede pris man betaler som forbruger per kWh, pga. det uigennemskuelige datasæt over tariffer og priser . I frustration kom udbruddet: “Giv mig nu bare elprisen.somjson.dk ” der nemt summerer alle priser og afgiter per elselskab, er open source og uden yderligere dikke-darer. Hvad koster strøm i Danmark? For en forbruger i Danmark er strømprisen en sum af forskellige priser og afgifter, nogle faste, nogle dynamiske: El-afgiften fastsat ved lov til 0,761 kr per kWh. Energinet’s eltariffer : Nettarif på 0,074 kr per kWh (år 2024), og systemtarif på 0,051 kr per kWh (år 2024). Netselskabstarif fra forsyningsselskabet ( N1 , Radius , etc.): denne varierer per time og per sæson for at forsøge at incentivere til at udligne forbruget så der ikke skal investeres i nye og større elkabler, og er indkodet i datasættet over tariffer og priser . Private forbrugere betaler C-tarif. Spot-prisen : er den anden variable, og denne varierer ud fra udbud og efterspørgsel. Moms: 25% lagt til summen af ovenstående Dette er alle de uundgåelige priser og afgifter, der kan regnes ud udelukkende fra adressen. Derudover kommer så det “frie elmarked”, hvor der skal betales til et elselskab: typisk månedsabonnement og et tillæg til spot-prisen. Tariffer og priser – det værste åbne datasæt? Som om det ikke er uoverskueligt nok i sig selv, bliver vi nødt til at snakke om datasættet Datahub Price List . Der er flere åbenlyse problemer med det: Der er flere felter man burde filtrere efter, men hvor der ikke findes en udtømmende liste over værdier, f.x. netselskab “ChargeOwner”. Det bedste man kan gøre er at downloade, hvor man så løber ind i at download kun giver 100.000 rækker – og datasættet er fuldt på over 300.000 rækker. ChargeTypeCode er per selskab – og uden systematik. Så for hvert enkelt selskab skal man finde ud af hvilken priskode de bruger for C-tariffen. Og hvad når det ændrer sig? ValidTo kan være udeladt og dermed et open ended interval, og prisen gælder så indtil data retroaktivt ændres. Det betyder også at man ikke kan filtrere på datoer, da prisen på 1. april kan være en række der har en ValidFrom 1. januar (eller tidligere). Price1-24: dette er selve timetarif-priserne. Hvis en pris ikke er udfyldt gælder Price1 – hvorfor I alverden dog tilføje den ekstra kompleksitet!?!?! For ikke at tale om tidszoner: man må antage (det er ikke dokumenteret) at alle datoer og timetal er angivet i hvad end tid der er gældende i Danmark på pågældende dato. Dette giver så problemer ved skift fra sommer-/normal-tid hvor en time gentages eller udelades: hvilken timesats bør bruges i et døgn der har 23 eller 25 timer? Giv mig nu bare elprisen.somjson.dk ! Efter at have regnet de fleste af de ovenstående problemer ud, skrev jeg en API-proxy der udstiller det API man i virkeligheden vil have: givet en dato, og et elselskab (eller en adresse), returnerer den prisen time for time som et JSON dokument . Prisen er typisk tilgængelig fra kl. 13 dagen før. Som bonus får man også CO2 udledningen med, hvis den er tilgængelig (typisk kl. 15 dagen før). Det er implementeret som en ren API proxy, dvs. det er ren omskrivning af input og data og ikke andet. Det hele er open source, men der kører en version på elprisen.somjson.dk som frit kan benyttes. Alternativer Der findes andre API’er der opfylder forskellige use-cases: Min Strøm API er rigtig modent og har egen forecast model der kan forecaste 7 dage frem, før priserne er låst på Energi Data Service. Kræver en API nøgle og er uden kildekode HomeAssistant energidataservice virker kun med Home Assistant, men fungerer på samme måde mod Energi Data Service. Strømligning API kan bruges til at udregne priser baseret på historisk forbrugsdata. Kan dog også bruges til at hente de forecastede priser. Med rate limiting, og uden kildekode. Carnot har også et åbent API og egen forecast model. Kræver API nøgle, og er uden kildekode. Billigkwh.dk har et åbent API til elpriser der også inkluderer de forskellige elselskabers abonnement. Comments (0) | feb 15 Reparation af Nordlux IP S12 badeværelseslampe der ikke lyser længere Posted on torsdag, februar 15, 2024 in Danish , Hal9k , Planets Denne badeværelseslampe er udgået af produktion, og pga. monteringen og at man ofte har mere end én er det noget træls at skulle udskifte – det giver ihvertfald en del skrot uden grund. Heldigvis er konstruktionen super simpel: det er udelukkende en LED driver (230V AC til 24V DC) og en LED. Lad os starte med det nemme: LED-driveren er direkte tilgængelig bagfra, og med lidt forsigtighed kan spændingen udmåles. I dette tilfælde var der ca. 24V DC, og det er jo fint indenfor specifikationen. Selve LED’en er lidt sværere at komme til: fronten af glasset skal drejes af via de to huller deri. Jeg brugte en låseringstang af ca. korrekt dimension, med lidt forsigtighed. Lidt ridser gør nok ikke det store når lyset skinner. LED’en kan nu loddes af. En ny LED kan købes for ca. 10 kr, f.x. på AliExpress. Det rigtige søgterm er måske “Bridgelux 2020 COB LED”, jeg endte med en 7W i Warm White (3000 Kelvin). Efter lidt fidlen og lodden er den nye LED monteret, og kan testes. Stor succes! Comments (0) | aug 29 Grundfos Alpha 2 pumpe går i stykker og flimrer: reparer den med en kondensator til nogle få kr Posted on mandag, august 29, 2022 in Danish , Hal9k , Planets Som med så mange andre huse fulgte der en Grundfos Alpha 2 cirkulationspumpe med da vi købte et hus. Den pumpede og pumpede, indtil den var blevet 13 år gammel: så begyndte den at flimre når den skulle starte op. Det er jo som sådan en rimelig hæderlig levetid, men også lidt mistænkeligt at det ikke virkede til at være et mekanisk problem. Flimmer, men ingen pumpning. Symptomerne er: Pumpen kan køre fint i længere tid Ved længere tids stop kan den ikke starte; nogen gange starter den efter noget tid Ved opvarmning starter pumpen, f.x. med en varmepistol Det sidste punkt har gjort at der flere steder bliver spekuleret i at der er “kondens” i pumpen . Det er dog ikke problemet. Problemet er en lille kondensator der holder strøm til lavspændingselektronikken: 47 uF 16 V kondensatoren er problemet. I Hal9k eksperimenterede vi en smule for at verificere: hvis man køler den ned med f.x. sprit opstår problemet med det samme. Hvis man varmer den op starter pumpen med det samme. For en udførlig vejledning i hvordan pumpen skilles ad og kondensatoren skiftes har Simon lavet en video: Men hvad er kilden til problemet så? Kondensatoren får over tid en alt for stor indre modstand, og spændingstabet bliver for stort. Her et par målinger uden og med lidt sprit til ekstra afkøling: Med sprit En helt ny kondensator måler under 1 ohms modstand, altså 100 gange så lille indre modstand: En ny kondensator kan findes ved at søge på “47 uf 16 v smd electrolytic capacitor”, f.x. TME.eu , eller endnu mere lokalt fra el-supply.dk . Efter erstatning pumper pumpen lystigt. Så hvad kan man lære af hele denne historie? Grundfos laver mekanisk gode pumper, men sparer på deres elektronik. Det er trist at tænke på hvor mange pumper der mon er smidt ud lang tid før tid. Man kan nok ikke beskylde Grundfos for “ planned obsolence ” efter 13 år, men man kunne dog ønske at produktet fejlede i en mere brugbar konfiguration: f.x. at pumpen kører ved et minimum hvis elektronikken fejler. Comments (0) | jan 31 Reparation af Aduro-tronic II Posted on søndag, januar 31, 2021 in Danish , Hal9k Vi har en Aduro 1-2 brændeovn med Aduro-tronic , som vi generelt er rigtig glade for. Den har nu været i drift i 5 år, og har haft omkring 4500 optændinger. Generelt er designet rigtig fornuftigt, og med Aduro-tronic og Smart Response er det rigtig nemt at fyre korrekt. Den eneste anke må være at vi nu 2 gange har oplevet at Aduro-tronic stemplet har givet op: Første gang købte jeg et nyt, men det viste sig at være ret nemt at reparere. Så da problemet opstod igen reparerede jeg bare det gamle stempel. Aduro-tronic er basalt set en utæt luftcylinder med en fjeder. Stemplet trykkes ind, fjederen bliver spændt og som lufter langsomt trækker ud af cylinderen kører stemplet op igen. Hvor utæt cylinderen er justeres med den lille skrue, og dette sætter således tiden spjældet holdes åbent. Problemet opstår når aske, støv og lignende sætter sig inde i cylinderen, og over tid får foringen til at blive utæt. Derved er stemplet for utæt. Løsningen er simpel: Tag forsigtigt fjederen af ved at trykke holderpladen ned og dreje den 90 grader. Den øverste plade kan forsigtig tages ud. Jeg brugte en spidstang, og lidt vrikken fra side til side. Derefter kan selve stemplet med gummi-foring tages ud. Rengør nu cylinderen, og smør stempel og cylinder med en lille smule silikone-spray der hjælper med at forsegle. Saml hele mekanikken igen, tryk stemplet ned og check at det nu bliver nede af sig selv. Når mekanikken igen er monteret på brændeovnen skal tiden nok indstilles forfra. Comments (0) | feb 1 Dør jeg af partikelforurening fra min moderne brændeovn? Posted on fredag, februar 1, 2019 in Danish , Hal9k , Planets Vi har en fin moderne brændeovn derhjemme (en Aduro 1-2), som vi bruger ret intensivt til opvarmning af vores gamle stuehus. Et meget relevant spørgsmål er derfor: hvor meget bidrager sådan en moderne brændeovn til partikelforureningen i vores stue? Partikelforurening er små partikler af støv og sod, der bl.a. fremkommer ved afbrænding af fossile brændsler, som olie og træ. De kan forårsage forskellige slags sundhedsproblemer, bl.a. kræft. På et interaktivt partikelkort kan man se hvilke niveauer der (beregnet) var i Danmark i 2012, og f.x. forskellen mellem land og by; årsgennemsnittet for PM2.5 lå på 5.3 – 11.9 μg/m 3 . Det er et ganske egoistisk projekt jeg har gang i: jeg har ingen data for hvor stor partikelforureningen er udenfor huset, men kun inde i selve stuen. Der er en del kilder til partikelforurening som jeg kender til, eller har observeret: Vi har et pillefyr, der står i nærheden, der også kører i den kolde tid Vi bor i kort afstand fra en lettere befærdet vej Madlavning, specielt med en gammel emhætte, kan bidrage betydeligt Den generelle baggrundsvariation kan være betydelig For at undersøge det har jeg opsat en partikel sensor (en Honeywell HPMA-1150S0 ) i stuen, ca. 3 m fra brændeovnen. Samtidig registrerer jeg brændeovnens temperatur, via en Aduro Smart Response sensor . Dette har jeg nu gjort i lidt over et år, og kan dermed lave en data analyse på et års data. Til brug for analysen er der registreret PM10 og PM2.5 værdier, ifølge databladet i μg/m 3 . Sensoren skulle desuden være “fully calibrated”, og kunne køre i mindst 20.000 timer, så et års data burde man kunne stole på. Usikkerheden er dog angivet til +/- 15 μg/m 3 , eller +/-15% alt efter målingen; i praksis virker den dog til at være ret stabil i værdierne. Sensoren beregner PM10 værdier ud fra PM2.5 værdier, så jeg vil primært fokusere på analyse af PM2.5 værdierne. Data er optaget med et interval på 5 minutter, men med sensor læsninger ca. hvert 6 sekund der så er aggregeret ved gennemsnit (Der er brugt HPMA-1150S0 sensorens “auto-send”). Sensoren opfanger partikler mindre end 2.5 μg med en laser. Brændeovnens temperatur er målt som foreskrevet af Aduro Smart Response, dvs. i den øvre del af brændkammeret på vej mod røgrøret. Aduro sensoren sender data i ca. 4 timer. Jeg har defineret at brændeovnen er i brug, hvis temperaturen er registreret, dvs. afkøling også er talt med. Data der er opsamlet er bl.a. PM10, PM2.5, brændeovnens temperatur, og strømforbrug på de 3 faser. Vi bruger vores brændeovn en hel del i de kolde måneder. Faktisk helt op til halvdelen af tiden: Det passer meget godt med at vi bruger brændeovnen næsten alt tid vi er hjemme, i de kolde måneder. Vi tænder op efter forskrifterne og bedste evne; genindfyring sker typisk ved 175C eller 150C ved at lægge 2-3 stykker brænde ind, og åbne spjældet (der så ved Adurotronic lukker over ca. 6 minutter). Der er naturligvis stor variation i præcis hvornår der lige bliver genindfyret. Og en sjælden gang imellem glipper optændingen, og giver røg i stuen. Men generelt opleves fyringen som ganske uproblematisk. Gennem året har jeg lavet lidt observationer, og min subjektive vurdering for partikelforureningen er ca.: Der er normalt meget lille partikelforurening, 2-3 μg/m 3 Ved god optænding stiger forureningen med 1-2 μg/m 3 I nogle perioder er baggrundsforureningen højere, lige under 20 μg/m 3 Ved uheldig opførsel stiger partikelforureningen drastisk – helt op til 900 μg/m 3 ; det kan f.x. være ved dårlig optænding, eller ved madlavning. Uheldig optænding. Uheldig baconstegning. Målinger PM2.5 koncentrationer, ifht. årets måneder. Som det kan ses er der en del variation imellem månederne. Der er også en hel del outliers, der trækker gennemsnittet op, mens medianen for alle måneder ligger under 5 μg/m 3 . PM2.5 koncentrationer, ifht. brændeovnens temperatur; røde cirkler angiver gennemsnit, rød linje angiver kubisk tendenslinje. Mere interessant er det om partikelforureningen påvirkes af brændeovnens temperatur, og dermed dens brug. Det ser det bestemt ud til! Selvom median værdierne ikke stiger meget stiger specielt 3. kvartil. Gennemsnitsværdierne stiger også, helt op til 12.37 μg/m 3 for intervallet [250, 300). En tolkning af dette kunne være at der normalt (median) ikke er ret meget mere partikelforurening, men det sker hyppigere at der er store koncentrationer til stede. Det bør noteres at der ikke er særlig mange målinger over 350C, som det kan ses af histogrammet for hvilke brændeovnstemperaturer der er registreret: Fejlkilder Der er et par fejlkilder i målingerne: Der mangler en uges data i september, hvor en strømforsyning stod af mens vi var på ferie. Partikelsensoren giver nogle meget højere målinger i et enkelt punkt, engang imellem. Checksummen fra sensoren ser ud til at passe, så hvad præcist problemet er ved jeg ikke. Jeg har først filtreret åbenlyst forkerte målinger (<0 eller >1000) fra i databehandlingen, men pga. gennemsnittet over de 5 min kan nogle åbenlyst forkerte målinger stadig være talt med. Brændeovnssensor har nok manglet batteri en dag eller to, det kan jeg ikke helt huske. Analyse PM2.5 Årligt gennemsnit 5.44 μg/m 3 – Årligt gennemsnit, brændeovn i brug 9.28 μg/m 3 – Årligt gennemsnit, brændeovn ikke i brug 4.49 μg/m 3 Alle værdier er under EU’s grænseværdi , på 25 μg/m 3 PM2.5. Hvis vi antager at målingerne mens brændeovnen ikke er i brug er repræsentative for hele året, så har brændeovnen bidraget med 0.95 μg/m 3 PM2.5 til års gennemsnittet . Hvor farligt er det så? Et studie fra 2013 af sammenhængen mellem partikelforurening og lungekræft fandt (eftersigende, jeg har ikke adgang til artiklen men kun til resuméet på Videnskab.dk ) at selv små stigninger i partikelforurening giver øget risiko for lungekræft. For småkornet luftforurening [PM2.5] stiger risikoen for lungekræft med 18 procent per fem ekstra mikrogram svævestøv, men det resultat var ikke statistisk signifikant. Det var alle resultaterne for risikostigning under det tilladte niveau heller ikke. Videnskab.dk: Små mængder forurening øger faren for kræft Hvis vi antager at det resultat holder, og at virkningen er lineær, vil den øgede forurening på 0.95 μg/m 3 PM2.5 øge risikoen for lungekræft med 3.42%. Enkeltstående tilfælde Et andet problem kunne være hvis enkeltstående tilfælde af høj luftforurening var specielt sundhedsskadeligt, som indikeret af at EU for PM10 også har en daglig grænseværdi (50 μg/m 3 ), og et antal tilladte overskridelser per år (35). Der er 0 dage hvor den daglige PM10 grænseværdi har været overskredet. Jeg har alligevel analyseret de 35 dage med det højeste gennemsnit, og forsøgt at klassificere de årsager (primær og sekundære) til de høje værdier. Det har jeg gjort ved at kigge på brændeovnstemperaturen, strømforbruget, tidspunket på dagen, osv. Disse tal må derfor siges at være min subjektive vurdering. Primær årsag Sekundær årsag Madlavning 19 3 Baggrund 11 1 Brændeovn 3 15 Ukendt 2 0 De primære årsager til høje målinger ser ud til at være madlaving og baggrund, mens brændeovnen bidrager til halvdelen af de høje dagsgennemsnit. Konklusion Vores moderne brændeovn bidrager med 0.95 μg/m 3 PM2.5 til års gennemsnittet, og øger dermed vores risiko for lungekræft med 3.42%. Hvis vi f.x. flyttede til en større by som København ville vi opleve en væsentlig højere forøgelse til måske 10 μg/m 3 , ifølge modelberegningen , hvilket ville øge risikoen for lungekræft med 16%. Hvis man ser på PM2.5 koncentrationer ifht. brændeovnens temperatur, ser det ud til at brændeovnen for det meste (målt på medianen) ikke udleder ret mange partikler, men bidrager til at høje forureningskoncentrationer optræder oftere (som set på de øgede gennemsnitsværdier, og forøgede 3. kvartil). Brændeovnen bidrager til 18 af de 35 højeste dagsmålinger, mens de primære årsager til høje dagsmålinger er madlavning og baggrundsforurening. Comments (0) | okt 17 Reparation af DUKA/PAX Passad 30 Ventilator der kører uregelmæssigt Posted on tirsdag, oktober 17, 2017 in Danish , Hal9k , Planets Vores Duka Passad 30 ventilator var begyndt at køre noget uregelmæssigt. Ventilatoren er ellers ret smart styret af fugtighed og IR-bevægelse, men vi bruger den kun fugtighedsstyret. Den var imidlertid begyndt ikke at kunne starte ordentligt: den reagerede fint på fugt, men motoren stoppede efter få sekunder, for straks derefter at starte igen. Der var jo ikke andet for end at prøve at åbne den og reparere den; en ny ventilator er relativt dyr, og den kunne jo ikke gå mere i stykker end den allerede var. Bladene kan hives af direkte ved at hive op i dem, og tragten kan tages af ved at dreje til siden. Der gemmer sig en enkelt skrue under mærkaten på bagsiden. Inden i er et relativt simpelt printkort: Den eneste chip er desværre en micro-controller af en art, så hvis den er i stykker er der ikke rigtig noget at gøre. Jeg fik en hel del hjælp i Hal9k til at måle på printet, og det viste sig at strømforsyningen ikke var særlig stabil; ca. når problemet opstod steg spændingen. Vi endte med at lodde en ledning på microcontrollerens GND-ben, og kunne så se at VCC-benet faktisk lå ret lavt ved ca. 3V, og at spændingen der faldt når problemet opstod. Ved at måle tilbage i kredsløbet derfra endte vi helt tilbage ved den store kondensator (0,33 uF) der er næsten først i kredsløbet. Det er dog ikke så nemt at måle kapacitet med kondensatoren i kredsløbet, men alligevel et forsøg værd: målingen var et godt stykke fra 0,33 uF. Med kondensatoren som hovedmistænkt blev den loddet af, og målt alene: værdien var nærmere et antal nF! Altså var kondensatoren gået i stykker. En erstatning blev fundet i en kaffemaskine fra Hal9k’s Limbo hylde, dog en 0,47 uF, men det burde virke: Den nye kondensator blev loddet i, og problemet var nu væk! Spændingen ved micro-controlleren lå også stabilt, lige omkring 4,8V. Så var der kun tilbage at samle det hele igen, og sætte ventilatoren til, med lidt penge sparet, og en ventilator reddet fra skrotpladsen. Den eneste forskel synes at være at fugtigheds indstillingen nu skal stå lidt anderledes, men om det er pga. en lidt anden spænding eller bare er tilfældigt er jeg ikke sikker på. Comment (1) | feb 19 Hvorfor korrelerer min DC-spænding med solen? Posted on fredag, februar 19, 2016 in Danish , Hal9k I mit home-monitoring setup har jeg en AC-DC strømforsyning der laver DC-strøm og lader UPS-batterierne. Denne spænding overvåger jeg, som beskrevet i sidste blogindlæg . Grafen set for en typisk dag ser ud som ovenover. Der er en tydelig stigning i spændingen om morgenen og et tydeligt fald sidst på eftermiddagen. Det korrelerer forbavsende godt med hvornår solen står og og går ned. Her er data for 3 forskellige dage, overlagt med sol op-/ned-tidspunkt : 6. september – ufiltreret 26. oktober – filtreret 21. december – filtreret Der er ikke noget forbundet til DC-forsyningen der trækker væsentlig forskellig strøm efter belastning (det der er forbundet er switche, router og Arduinoer), og intet der tænder/slukker efter tidspunktet. Temperaturen varierer ikke væsentligt i rack-skabet, og korrelerer ikke med spændingen: Temperatur og spænding, hele oktober. Spænding (grøn) på højre akse. Temperatur og spænding, 26. oktober. Spænding (grøn) på højre akse. Så det store spørgsmål er: Hvorfor korrelerer min DC-spænding med solen? Er det pga. solceller i nabolaget? Er det pga. gadebelysning der tænder/slukker? Gode bud modtages 🙂 Comments (0) | feb 15 Et lille slag for ytringsfriheden Posted on søndag, februar 15, 2009 in Danish , Planet Ubuntu-DK Som de fleste ved har nogle danske internet-udbydere spærret for adgangen til The Pirate Bay , bl.a. TDC. Dermed er det også blevet gjort umuligt at følge med i den nærtstående retssag mod nogle af folkene bag The Pirate Bay, hvor nyheder set fra deres synspunkt bliver publiceret på trial.thepiratebay.org . Dette synes jeg er helt uholdbart i et rets-samfund som det danske! Tænk hvis det bliver kutyme at anklagede ikke kan forsvare sig i medierne! Derfor har jeg sat et mirror af bloggen , på http://tpbtrial.smartere.dk/ så folk der har en mindre friheds-elskende internet-udbyder også kan følge med i begge sider af retssagen. Den opdaterer én gang i timen. Bemærk! Der findes ingen links til ophavsrettigt beskyttet materiale på den side jeg laver et mirror af! Det er nok det bedste eksempel på censur vi har i Danmark pt.: En side der ikke overtræder nogen som helst love, men som blot udtrykker en mening, er blevet spærret! Comments (0) | Categories Danish Hal9k Ikke kategoriseret Planet Ubuntu-DK Planets Sysadmin'ing Ubuntu University Woodworking © blog.smartere . All Rights Reserved. WordPress Theme designed by Chris Wallace | 2026-01-13T08:48:58 |
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Report Abuse Evan Lin Posted on Jan 11 • Originally published at evanlin.com on Jan 11 LINE Taiwan DevRel: 2020 Review and 2021 Community Plans (Part 3: Technical Branding and Hiring) # devjournal # community # marketing # career title: [LINE DevRel] LINE Taiwan Developer Relations 2020 Review and 2020 Developer Community Plan Report (part 3: Technical Branding and Hiring) published: false date: 2021-02-03 00:00:00 UTC tags: canonical_url: http://www.evanlin.com/devrel-2020-3/ Enter fullscreen mode Exit fullscreen mode Preface Hello everyone, I am Evan Lin from the LINE Taiwan Developer Relations team. After more than a year of effort by LINE Developer Relations, I would like to summarize in this article what the entire team has done, and I also hope to make an annual report for the " LINE Developer Community Plan ". According to the original introduction article (Introducing Developer Relations team) written by LINE Developer Relations, the main goals of this team are clearly defined as follows: External Evangelism: Encouraging developers to use LINE's platform, APIs and SDKs to develop attractive and interesting application services. (Encouraging people to make attractive and interesting services using the APIs and the SDK by LINE) Internal Evangelism: Through some methods to enable engineers to grow and hone themselves (Doing whatever our engineers feel difficult to do themselves in making improvements at work) Technical Branding and Hiring: Letting more people know that being a LINER (LINE employees' self-proclaimed name) has many interesting and exciting things. (Letting people know how fun and exciting it is for engineers to work at LINE) The previous article has clearly defined External Evangelism , and the next step will be to further explain Technical Branding and Hiring . Article List: [LINE DevRel] LINE Taiwan Developer Relations 2020 Review and 2020 Developer Community Plan Report (part 1: External Evangelism) [LINE DevRel] LINE Taiwan Developer Relations 2020 Review and 2020 Developer Community Plan Report (part 2: Internal Evangelism) [LINE DevRel] LINE Taiwan Developer Relations 2020 Review and 2020 Developer Community Plan Report (part 3: **Technical Branding and Hiring) (This article) Technical Branding and Hiring: Letting more people know that being a LINER (LINE employees' self-proclaimed name) has many interesting and exciting things. As a technology-based technology company, LINE requires developers for many underlying architectures and services. However, the brand awareness of LINE's technology is an area that needs continuous effort, so another important task of Developer Relations is to let more developers understand that LINE Taiwan has a considerable number of developers, and there are many interesting job openings here that need the participation of experts from all sides. Summer Tech Fair We hope to create more opportunities for technical sharing and cross-border exchanges, and at the same time, continue to recruit outstanding talents to join the LINE Taiwan development engineering team! This is the first joint recruitment Taiwan technology job fair this year, hoping to let more student friends understand the student internship program brought by LINE. "LINE Tech Star Talent Program – LINE TECHFRERSH". Reference Articles: LINE Developer Community Plan: Summer Tech Fair Taiwan Technology Job Fair Community Event Co-hosting Invitation (Community Meetup) This year, LINE Taiwan not only holds community events by itself, but also welcomes various technical communities to hold community gatherings at the LINE Taiwan office. In addition to hoping to have more exchanges with the community, it will also provide LINE internal developers to share relevant development experiences with everyone. As a developer, do you know that LINE also actively participates in welcoming various communities to apply and exchange? Due to the epidemic, the events in the first half of the year were postponed. In the second half of the year, 5 open source technology community gatherings were held at the LINE office, and we cooperated with many communities, and allowed many communities to understand that LINE also has related development technology engineers, and each colleague has an open attitude and is willing to share. Related Articles: You are also welcome to refer to the following articles to learn more about the exciting community event content: LINE Developer Community Plan: 2020/10/21 TWJUG@LINE LINE Developer Community Plan: Golang #54 Community Gathering Experience LINE Developer Community Plan: Vue.js Taiwan 006 Gathering Highlights Sharing LINE Developer Community Plan: 20200707 Test Corner #26 Gathering Experience 2020 June LINE Platform Update Summary and LINE Group/Room Chatbot Demonstration LINE Taiwan Security Meetup – BECKS #6 LINE Taiwan Security Meetup – BECKS #5 LINE Annual Developer Recruitment Conference LINE Developer Recruitment Day LINE Taiwan Developers Recruitment Day is a public recruitment event for developers. We invite outstanding candidates who have passed the online preliminary test to participate in the interview. In addition, we have also planned a full day of product and service introductions, and welcome the developers invited to the interview to come and learn together. Through this event, more developers can also understand that LINE Taiwan has a considerable number of development positions waiting for experts from all sides to join. Related Articles 2020 LINE Taiwan Developers Recruitment Day LINE UIT Introduction LINE SHOPPING Introduction LINE QA Introduction LINE TODAY Introduction LINE Pay Introduction Technical Seminars (COSCUP, DataCon, JCConf, JSDC) Regarding the technical seminars, the LINE Developer Relations department also participated in JCConf this year, and set up a booth for LINE Taiwan engineers to communicate and discuss with everyone. We also found that in each exchange, each interaction, in addition to feeling the enthusiasm of LINER sharing, we can also feel the love and curiosity of every developer for LINE services. Everyone wants to explore the technical architecture content of the services they use every day, and the enthusiasm of the engineers' exchanges was also felt in the four seminars. Related Articles: LINE Taiwan x Java Annual Event: JCConf 2020 A trip to JCConf 2020 JCConf 2020 Conference Experience Sharing – RSocket Revolution, a High-Efficiency Communication Protocol Born for Reactive Programming Information Security Community in South Korea, Japan and Taiwan - BECKS Information security has always been one of the most important aspects of LINE. In addition to actively promoting various information security enhancement strategies, starting this year (2019), it has regularly held BECKS.IO – Security Meetup jointly in South Korea, Japan, and Taiwan, inviting information security researchers from various countries to participate, allowing information security researchers from all over the world to have more exchanges through this gathering. In 2019, a total of five BECKS gatherings were held, and we also hope that more participants can join us. Related Articles: BECKS Community Event Registration Website LINE Taiwan Security Meetup – BECKS #6 LINE Taiwan Security Meetup – BECKS #5 LINE Taiwan Annual Developer Event - LINE TECHPULSE 2020 LINE TAIWAN TECHPULSE 2020 was held on 2020/12/18 at Nangang Exhibition Center Hall 2. I don't know if you all participated in this carefully arranged event this year. As one of the organizers, we always hope that every idea and thought can be shared with every guest. We hope that through this article, regardless of whether you are present or not, you can feel the team's dedication. In addition to the new venue this year, the working team has also carefully prepared the following items to welcome everyone to learn more: LINE CLOVA venue experience The first dual-track agenda, a perfect combination of technology and business applications Interactive booth: giving you the opportunity to know the gods Display rack (Poster): Face-to-face discussion of architecture with LINE Taiwan service engineers Related Articles: LINE TAIWAN TECHPULSE 2020 Agenda Content Sharing Behind the Scenes of LINE TAIWAN TECHPULSE 2020 Event Arrangements TECHPULSE 2020 Youth Main Stage – TECH FRESH Agenda and Booth Introduction LINE TAIWAN TECHPULSE 2020 Annual Event You Can't Miss Conclusion This is the last article summarizing the results of LINE Developer Relations in 2020. Thank you for watching. Developer Relations is never an easy road. Developers, due to their own desire for technical exchanges, are still willing to use their free time after work to participate in technical communities to get to know more like-minded people and hone their skills. Therefore, the staff of Developer Relations and Technical Promotion Department (Developer Relations) need more enthusiasm to plan in-depth and meaningful activities to make every hard-working developer have a fulfilling harvest and let everyone exchange happily. 2020 has passed, how many LINE Developer Relations events have you participated in? Let's meet again in 2020. Join the "LINE Developer Official Community" official account immediately, and you can receive push notifications of the latest Meetup events or the latest news related to the developer plan. ▼ "LINE Developer Official Community" Official Account ID: @line_tw_dev About "LINE Developer Community Plan" Join the "LINE Developer Official Community" official account immediately, and you can receive push notifications of the latest Meetup events or the latest news related to the developer plan. ▼ "LINE Developer Official Community" Official Account ID: @line_tw_dev About "LINE Developer Community Plan" LINE launched the "LINE Developer Community Plan" in Taiwan at the beginning of this year, and will invest manpower and resources in Taiwan for a long time to hold developer community gatherings, recruitment days, developer conferences, etc., both internally and externally, online and offline, and is expected to hold more than 30 events throughout the year. Readers are welcome to continue to check back for the latest updates. For details, please see: LINE Taiwan Developer Relations 2019 Review and 2019 Developer Community Plan Report 2019 LINE Developer Community Plan Event Schedule 2020 LINE Developer Community Plan Event Schedule 2021 LINE Developer Community Plan Event Schedule (continuously updated) Enter fullscreen mode Exit fullscreen mode Top comments (1) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Some comments may only be visible to logged-in visitors. Sign in to view all comments. Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse Evan Lin Follow Attitude is Everything. @golangtw Co-Organizer / LINE Taiwan Technology Evangelist. Golang GDE. Location Taipei Work Technology Evangelist at LINE Corp. Joined Jun 16, 2020 More from Evan Lin Steve Jobs: The Biography (Updated Edition) # career # leadership # motivation # product 2020: Review and Outlook # career # devjournal # productivity [TIL] Golang community discussion about PTT BBS # community # backend # discuss # go 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV Forem — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . Forem © 2016 - 2026. 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https://dev.to/missamarakay | Amara Graham - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Follow User actions Amara Graham Enabling developers Location Austin, TX Joined Joined on Jan 4, 2017 github website twitter website Education BS Computer Science from Trinity University Work Developer Advocate at Kestra Eight Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least eight years. Got it Close Writing Debut Awarded for writing and sharing your first DEV post! Continue sharing your work to earn the 4 Week Writing Streak Badge. Got it Close Seven Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least seven years. Got it Close Tag Moderator 2022 Awarded for being a tag moderator in 2022. 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Got it Close Show all 17 badges More info about @missamarakay GitHub Repositories Unity-AI-AR Code for a corresponding Medium tutorial for an AI AR iOS App C# • 9 stars Starter-AR-Project A complete Unity project using Watson SDK and Vuforia. C# • 3 stars Skills/Languages JavaScript, Node.js, C#, Unity3d, AR/VR, developer experience (DX) Currently learning BPMN (relearning), process automation Currently hacking on all things documentation Available for AI, beginner AR/VR, live video streaming, beginner game dev, cooking, baking, video games, developer experience, DevRel, documentation Post 49 posts published Comment 247 comments written Tag 13 tags followed Pin Pinned Bing Webmaster Tools De-indexed My Docs Site and Increased My Cognitive Load Amara Graham Amara Graham Amara Graham Follow Nov 1 '22 Bing Webmaster Tools De-indexed My Docs Site and Increased My Cognitive Load # webdev # seo # documentation 8 reactions Comments 3 comments 3 min read What is this Developer Experience thing? Amara Graham Amara Graham Amara Graham Follow Jan 31 '22 What is this Developer Experience thing? # devrel # dx 75 reactions Comments 15 comments 5 min read Measuring Successful Documentation Amara Graham Amara Graham Amara Graham Follow Mar 18 '21 Measuring Successful Documentation # devrel # documentation 190 reactions Comments 16 comments 6 min read What is cURL and why is it all over API docs? Amara Graham Amara Graham Amara Graham Follow for IBM Developer Feb 19 '19 What is cURL and why is it all over API docs? # documentation # api # coding # webdev 118 reactions Comments 12 comments 5 min read My First Flow with Kestra.io Amara Graham Amara Graham Amara Graham Follow Jan 2 My First Flow with Kestra.io # orchestration # automation # opensource # gettingstarted 2 reactions Comments 1 comment 6 min read Want to connect with Amara Graham? Create an account to connect with Amara Graham. You can also sign in below to proceed if you already have an account. Create Account Already have an account? Sign in Get started with me & Kestra.io Amara Graham Amara Graham Amara Graham Follow Dec 26 '25 Get started with me & Kestra.io # orchestration # automation # gettingstarted # opensource 18 reactions Comments 9 comments 4 min read Is this thing on? Amara Graham Amara Graham Amara Graham Follow Dec 18 '25 Is this thing on? # watercooler # community # devjournal 2 reactions Comments Add Comment 1 min read Moving Config Docs From YAML to Markdown Amara Graham Amara Graham Amara Graham Follow May 3 '23 Moving Config Docs From YAML to Markdown # documentation # yaml # markdown 8 reactions Comments Add Comment 2 min read Moving DevEx from DevRel to Engineering Amara Graham Amara Graham Amara Graham Follow Mar 30 '23 Moving DevEx from DevRel to Engineering # devrel # devex # engineering # reorg 10 reactions Comments Add Comment 2 min read Software Development and Transformational Leadership Amara Graham Amara Graham Amara Graham Follow Feb 24 '23 Software Development and Transformational Leadership 10 reactions Comments 3 comments 4 min read How do you approach a new API? Amara Graham Amara Graham Amara Graham Follow Jan 18 '23 How do you approach a new API? # discuss # api 6 reactions Comments 12 comments 1 min read How are you preparing for the new year? Amara Graham Amara Graham Amara Graham Follow Dec 16 '22 How are you preparing for the new year? # discuss 10 reactions Comments 13 comments 1 min read What is your favorite way to learn? Amara Graham Amara Graham Amara Graham Follow Nov 28 '22 What is your favorite way to learn? # discuss 28 reactions Comments 27 comments 1 min read Developer Enablement Requires Thoughtful Community Building Amara Graham Amara Graham Amara Graham Follow Aug 30 '22 Developer Enablement Requires Thoughtful Community Building # devrel # dx # community 5 reactions Comments Add Comment 3 min read A question about developer product emails Amara Graham Amara Graham Amara Graham Follow Jul 18 '22 A question about developer product emails # watercooler # discuss 6 reactions Comments 8 comments 1 min read Achieving a Docs Vision Amara Graham Amara Graham Amara Graham Follow Jul 6 '22 Achieving a Docs Vision # documentation 7 reactions Comments Add Comment 5 min read Do you use git status? Amara Graham Amara Graham Amara Graham Follow Mar 23 '22 Do you use git status? 5 reactions Comments 9 comments 1 min read How My Approach to IWD Has Changed Amara Graham Amara Graham Amara Graham Follow Mar 7 '22 How My Approach to IWD Has Changed # wecoded 23 reactions Comments 1 comment 2 min read 3 Most Important Focus Areas for Developer Experience Amara Graham Amara Graham Amara Graham Follow Feb 16 '22 3 Most Important Focus Areas for Developer Experience # devrel # dx 21 reactions Comments 2 comments 4 min read The Power of Online Networking Amara Graham Amara Graham Amara Graham Follow Jan 25 '22 The Power of Online Networking 17 reactions Comments 7 comments 4 min read I collect and prioritize tech debt for a living Amara Graham Amara Graham Amara Graham Follow Dec 15 '21 I collect and prioritize tech debt for a living # devrel # dx 24 reactions Comments 3 comments 4 min read My Docusaurus Pros and Cons List Amara Graham Amara Graham Amara Graham Follow Sep 1 '21 My Docusaurus Pros and Cons List # documentation # devrel 17 reactions Comments 4 comments 6 min read How much assumed knowledge is enough? Amara Graham Amara Graham Amara Graham Follow Aug 26 '21 How much assumed knowledge is enough? # documentation # devrel 28 reactions Comments 1 comment 5 min read Why I Love Zero Result Search as a Metric and You Should Too! Amara Graham Amara Graham Amara Graham Follow Apr 9 '21 Why I Love Zero Result Search as a Metric and You Should Too! # documentation # devrel 27 reactions Comments 7 comments 4 min read Iterating on Your Personas Amara Graham Amara Graham Amara Graham Follow Oct 29 '20 Iterating on Your Personas # ux # devrel 14 reactions Comments 1 comment 4 min read I work for a live video streaming company, ask me anything! Amara Graham Amara Graham Amara Graham Follow Apr 16 '20 I work for a live video streaming company, ask me anything! # ama # livestreaming # video # streaming 15 reactions Comments 24 comments 1 min read YAML vs. XML vs. JSON for Configuration Amara Graham Amara Graham Amara Graham Follow Apr 6 '20 YAML vs. XML vs. JSON for Configuration # discuss 23 reactions Comments 20 comments 1 min read She Coded! But she tired from the week. Amara Graham Amara Graham Amara Graham Follow Mar 6 '20 She Coded! But she tired from the week. # wecoded 63 reactions Comments 13 comments 1 min read GraphQL For Consumers Who Don't Want to Use Libraries Amara Graham Amara Graham Amara Graham Follow Feb 20 '20 GraphQL For Consumers Who Don't Want to Use Libraries # graphql 21 reactions Comments Add Comment 4 min read What are your thoughts on 'Silent Installations'? 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Amara Graham Amara Graham Amara Graham Follow Apr 19 '19 I've Been Mojaved. # unity3d # osx # devtips # tips 7 reactions Comments Add Comment 2 min read Capturing Audio in the Browser For “Wake Words” Amara Graham Amara Graham Amara Graham Follow for IBM Developer Apr 17 '19 Capturing Audio in the Browser For “Wake Words” # javascript # audio # node # chatbot 17 reactions Comments Add Comment 8 min read Nevertheless, Amara Graham Coded Amara Graham Amara Graham Amara Graham Follow Mar 7 '19 Nevertheless, Amara Graham Coded # wecoded 13 reactions Comments 1 comment 3 min read A Few of My Favorite (Dev) Things Amara Graham Amara Graham Amara Graham Follow Mar 4 '19 A Few of My Favorite (Dev) Things # github # programming # softwaredevelopment 14 reactions Comments Add Comment 3 min read My Experience On Your Site Amara Graham Amara Graham Amara Graham Follow Jan 25 '19 My Experience On Your Site # ux # webdev 42 reactions Comments 9 comments 1 min read Screenshot for Mac! 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Amara Graham Amara Graham Amara Graham Follow Jan 15 '19 Where did the Watson Assets go? # ibmwatson # unity3d # sdk # programming 6 reactions Comments 2 comments 2 min read Building Your Internal Army — DevRelCon London Follow Up Amara Graham Amara Graham Amara Graham Follow Jan 3 '19 Building Your Internal Army — DevRelCon London Follow Up # developerrelations # personaldevelopment # developeradvocacy 6 reactions Comments Add Comment 6 min read Hi, I'm Amara Keller Amara Graham Amara Graham Amara Graham Follow Jan 4 '17 Hi, I'm Amara Keller # introduction 4 reactions Comments 1 comment 1 min read loading... 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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https://www.highlight.io/docs/getting-started/server/python/aws-lambda | AWS Lambda Python Star us on GitHub Star Docs Sign in Sign up Getting Started Getting Started with Highlight Fullstack Mapping Browser React.js Next.js Remix Vue.js Angular Gatsby.js SvelteKit Electron highlight.run SDK Overview Canvas & WebGL Console Messages Content-Security-Policy Identifying Users iframe Recording Monkey Patches Browser OpenTelemetry Persistent Asset Storage Privacy Proxying Highlight React.js Error Boundary Recording Network Requests and Responses Recording WebSocket Events Salesforce Lightning Web Components (LWC) Data Export Sourcemap Configuration Tracking Events Troubleshooting Upgrading Highlight Versioning Sessions & Errors Other React Native (beta) Server Go Overview chi Echo Fiber Gin GORM gqlgen Logrus Manual Tracing gorilla mux JS Overview Apollo AWS Lambda Cloudflare Workers Express.js Firebase Hono Nest.js Next.js Node.js Pino tRPC Winston Python Overview AWS Lambda Azure Functions Django FastAPI Flask Google Cloud Functions Loguru Other Frameworks Python AI / LLM Libraries Python Libraries Ruby Overview Other Frameworks Ruby on Rails Rust Overview actix-web No Framework Hosting Providers Overview Metrics in AWS Logging in AWS Logging in Azure Fly.io NATS Log Shipper Logging in GCP Heroku Log Drain Render Log Stream Logging in Trigger.dev Vercel Log Drain Elixir Overview Elixir App Java: All Frameworks PHP: All Frameworks C# .NET ASP C# .NET 4 ASP Docker / Docker Compose File Fluent Forward curl OpenTelemetry Protocol (OTLP) Syslog RFC5424 Systemd / Journald Native OpenTelemetry Overview Error Monitoring Logging Tracing Browser Instrumentation Metrics Fullstack Frameworks Overview Next.js Fullstack Overview Next.js Page Router Guide Next.js App Router Guide Edge Runtime Advanced Config Remix Walkthrough Self Host & Local Dev Overview Development deployment guide. Integrations Microsoft Teams self-hosted Hobby deployment guide. Traefik SSL Proxying. Menu Highlight Docs Welcome to highlight.io Get Started Roadmap Company Values Compliance & Security Open Source Contributing Overview GraphQL Backend Frontend (app.highlight.io) Landing Site (highlight.io) Documentation End to End SDK Example Apps Adding an SDK Application Architecture GitHub Code Spaces Code Style Good First Issues Self-hosting Self-hosted [Dev] Self-hosted [Hobby] Self-hosted [Enterprise] Telemetry Our Competitors Product Philosophy Product Features Session Replay Overview Canvas & Iframe Dev-tool Window Recording Tracking Users & Recording Events Filtering Sessions GraphQL Live Mode Performance Impact Player Session Caching Rage Clicks Request Proxying Session Search Extracting the Session URL Session Search Deep Linking Shadow Dom + Web Components Error Monitoring Overview Enhancing Errors with GitHub Error Search Filtering Errors Grouping Errors Managing Errors Manually Reporting Errors Sourcemaps General Features Overview Alerts Comments Digests Environments Search Segments Services Webhooks Logging Overview Log Alerts Log Search Tracing Overview Trace Search Dashboards Overview Dashboard Management Metrics Tutorials Service Latency Web Vitals & Page Speed User Engagement User Analytics Graphing Drilldown Event Search Dashboard Variables SQL Editor Metrics (beta) Overview Frequently Asked Questions. Integrations Integrations Overview Amplitude Integration ClickUp Integration Discord Integration Electron Support Front Integration GitHub Integration Grafana Integration Overview Setup Dashboards Alerts Height Integration Intercom Integration Jira Integration LaunchDarkly Integration Linear Integration Mixpanel Integration Nuxt Integration Pendo Integration Segment Integration Slack Integration Vercel Integration WordPress Plugin Highlight.io Changelog Overview Changelog 12 (02/17) Changelog 13 (02/24) Changelog 14 (03/03) Changelog 15 (03/11) Changelog 16 (03/19) Changelog 17 (04/07) Changelog 18 (04/26) Changelog 19 (05/22) Changelog 20 (06/06) Changelog 21 (06/21) Changelog 22 (08/07) Changelog 23 (08/22) Changelog 24 (09/11) Changelog 25 (10/03) Changelog 26 (11/08) Changelog 27 (12/22) Changelog 28 (3/6) Changelog 29 (4/2) Getting Started Getting Started with Highlight Fullstack Mapping Browser React.js Next.js Remix Vue.js Angular Gatsby.js SvelteKit Electron highlight.run SDK Overview Canvas & WebGL Console Messages Content-Security-Policy Identifying Users iframe Recording Monkey Patches Browser OpenTelemetry Persistent Asset Storage Privacy Proxying Highlight React.js Error Boundary Recording Network Requests and Responses Recording WebSocket Events Salesforce Lightning Web Components (LWC) Data Export Sourcemap Configuration Tracking Events Troubleshooting Upgrading Highlight Versioning Sessions & Errors Other React Native (beta) Server Go Overview chi Echo Fiber Gin GORM gqlgen Logrus Manual Tracing gorilla mux JS Overview Apollo AWS Lambda Cloudflare Workers Express.js Firebase Hono Nest.js Next.js Node.js Pino tRPC Winston Python Overview AWS Lambda Azure Functions Django FastAPI Flask Google Cloud Functions Loguru Other Frameworks Python AI / LLM Libraries Python Libraries Ruby Overview Other Frameworks Ruby on Rails Rust Overview actix-web No Framework Hosting Providers Overview Metrics in AWS Logging in AWS Logging in Azure Fly.io NATS Log Shipper Logging in GCP Heroku Log Drain Render Log Stream Logging in Trigger.dev Vercel Log Drain Elixir Overview Elixir App Java: All Frameworks PHP: All Frameworks C# .NET ASP C# .NET 4 ASP Docker / Docker Compose File Fluent Forward curl OpenTelemetry Protocol (OTLP) Syslog RFC5424 Systemd / Journald Native OpenTelemetry Overview Error Monitoring Logging Tracing Browser Instrumentation Metrics Fullstack Frameworks Overview Next.js Fullstack Overview Next.js Page Router Guide Next.js App Router Guide Edge Runtime Advanced Config Remix Walkthrough Self Host & Local Dev Overview Development deployment guide. Integrations Microsoft Teams self-hosted Hobby deployment guide. Traefik SSL Proxying. Docs Home SDK Client SDK API Reference Cloudflare Worker SDK API Reference Go SDK API Reference Hono SDK API Reference Java SDK API Reference Next.JS SDK API Reference Node.JS SDK API Reference Python SDK API Reference Ruby SDK API Reference Rust SDK API Reference Docs / Getting Started / Server / Python / AWS Lambda Python Using highlight.io with Python on AWS Lambda Learn how to set up highlight.io on AWS Lambda. 1 Configure client-side Highlight. (optional) If you're using Highlight on the frontend for your application, make sure you've initialized it correctly and followed the fullstack mapping guide . 2 Add the ARN layer. Add the ARN layer to your Lambda function. Click on the "Layers" tab in the Lambda console and click "Add layer". You can find the most recent instrumentation release URLs in their releases . arn:aws:lambda:<region>:184161586896:layer:opentelemetry-<language>-<version> 3 Set the ENV vars. Set the ENV vars to connect your Lambda to Highlight. For more details on setting up the OTeL Lambda autoinstrumentation and some language-specific details, see their documentation . AWS_LAMBDA_EXEC_WRAPPER=/opt/otel-instrument OTEL_EXPORTER_OTLP_ENDPOINT=https://otel.highlight.io:4318 OTEL_RESOURCE_ATTRIBUTES=highlight.project_id=<project_id>,service.name=<service_name> 4 Test your Lambda function. Hit your Lambda function by testing it from the AWS console or sending an HTTP request to it. 5 Verify your backend traces are being recorded. Visit the highlight traces portal and check that backend traces are coming in. 6 Install the highlight-io python package. Download the package from pypi and save it to your requirements. If you use a zip or s3 file upload to publish your function, you will want to make sure highlight-io is part of the build. poetry add highlight-io # or with pip pip install highlight-io 7 Initialize the Highlight SDK. Setup the SDK. Add the @observe_handler decorator to your lambdas. import highlight_io from highlight_io.integrations.aws import observe_handler # `instrument_logging=True` sets up logging instrumentation. # if you do not want to send logs or are using `loguru`, pass `instrument_logging=False` H = highlight_io.H( "<YOUR_PROJECT_ID>", instrument_logging=True, service_name="my-app", service_version="git-sha", environment="production", ) @observe_handler def lambda_handler(event, context): return { "statusCode": 200, "body": f"Hello, {name}. This HTTP triggered function executed successfully.", } 8 Verify your installation. Check that your installation is valid by throwing an error. Add an operation that raises an exception to your lambda handler. Setup an HTTP trigger and visit your lambda on the internet. You should see a DivideByZero error in the Highlight errors page within a few moments. import highlight_io from highlight_io.integrations.aws import observe_handler # `instrument_logging=True` sets up logging instrumentation. # if you do not want to send logs or are using `loguru`, pass `instrument_logging=False` H = highlight_io.H( "<YOUR_PROJECT_ID>", instrument_logging=True, service_name="my-app", service_version="git-sha", environment="production", ) @observe_handler def lambda_handler(event, context): return { "body": f"Returning this is a bad idea: {5 / 0}.", } 9 Verify your backend logs are being recorded. Visit the highlight logs portal and check that backend logs are coming in. 10 Verify your backend traces are being recorded. Visit the highlight traces portal and check that backend traces are coming in. Highlight Integration in Python Azure Functions [object Object] | 2026-01-13T08:48:58 |
https://blog.smartere.dk/category/ikke-kategoriseret/ | blog.smartere » Ikke kategoriseret blog.smartere // Ramblings of Mads Chr. Olesen aug 31 Measuring high DC supply voltage with an Arduino Posted on mandag, august 31, 2015 in Hal9k , Ikke kategoriseret , Planets For my home-monitoring setup I would like an Arduino to measure the supply voltage it is getting from a DC battery UPS (Uninteruptible Power Supply). Unfortunately (actually by design, but that’s another story), the power supply is 24V, which means it will put out anywhere from 21.3V-29.8V (according to the manufacturer), which is far too much to measure with the Arduino’s 0-5V input range. For simplicity’s sake, lets assume we want to measure a 20-30V voltage. The immediate answer is to use a voltage divider , which will bring a voltage in the 0-30V range into the 0-5V range. The general formula for the resistor divider is: We want to give , so Now, just as a sanity check we should calculate the current of the resistor divider, to make sure we’re not converting too much electricity into heat. Ohm’s law gives us which in this cases gives No problems there. This works okay, but we lose a lot of precision, as only ~1/3 of the Arduino’s range is actually used: the Arduino’s ADC has 1024 different readings between 0-5V, so when reading the 0-30V range the precision is just about over the range. If only we could move the lower bound, so that 20V would map to 0V on the Arduino. A wild Zener Diode appears! One use of a Zener diode is as a voltage shifter . Zener diode voltage shifter The closest Zener diode I could find was an 18V of the BZX79 series . This resulted in the following circuit: which I hacked into my Arduino box. Now, theoretically the formula for translating an voltage at the Arduino to the supply voltage should be: I then did some quick measurements of various input voltages and the resulting voltage at the Arduino pin: Input voltage Arduino pin 18V 0.32V 20V 1.16V 26V 3.60V 28V 4.41V 29V 4.81V Plot it into a spreadsheet, create a graph and add a linear regression gives: Now, this formula is a bit different compared to the theoretical one, mainly in the Zener diode drop. However, the datasheet for the BZX79 actually has the 18V C-type ( ) as between 16.8-19.1V, so this is well within spec. Since this is just a one-off, I’m happy to just use the measured formula, as this will be more accurate. The final precision should be . The current should be around , which again is ok. Comment (1) | Categories Danish Hal9k Ikke kategoriseret Planet Ubuntu-DK Planets Sysadmin'ing Ubuntu University Woodworking © blog.smartere . All Rights Reserved. WordPress Theme designed by Chris Wallace | 2026-01-13T08:48:58 |
https://core.forem.com/t/seo/page/4 | Seo Page 4 - Forem Core Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. DUMB DEV Community Follow Memes and software development shitposting Design Community Follow Web design, graphic design and everything in-between Security Forem Follow Your central hub for all things security. From ethical hacking and CTFs to GRC and career development, for beginners and pros alike Golf Forem Follow A community of golfers and golfing enthusiasts Crypto Forem Follow A collaborative community for all things Crypto—from Bitcoin to protocol development and DeFi to NFTs and market analysis. Parenting Follow A place for parents to the share the joys, challenges, and wisdom that come from raising kids. We're here for them and for each other. Forem Core Follow Discussing the core forem open source software project — features, bugs, performance, self-hosting. Maker Forem Follow A community for makers, hobbyists, and professionals to discuss Arduino, Raspberry Pi, 3D printing, and much more. HMPL.js Forem Follow For developers using HMPL.js to build fast, lightweight web apps. A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account Forem Core Close # seo Follow Hide Search-engine optimization topics Create Post Older #seo posts 1 2 3 4 5 6 7 8 9 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu loading... 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV Forem Core — Discussing the core forem open source software project — features, bugs, performance, self-hosting. Home About Contact Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . Forem Core © 2016 - 2026. Community building community Log in Create account | 2026-01-13T08:48:58 |
https://dev.to/dmuraco3/when-to-user-server-side-rendering-vs-static-generation-in-nextjs-8ab#comment-26dh1 | When to Use Server-Side rendering vs Static Generation in Next.js - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. DUMB DEV Community Follow Memes and software development shitposting Design Community Follow Web design, graphic design and everything in-between Security Forem Follow Your central hub for all things security. From ethical hacking and CTFs to GRC and career development, for beginners and pros alike Golf Forem Follow A community of golfers and golfing enthusiasts Crypto Forem Follow A collaborative community for all things Crypto—from Bitcoin to protocol development and DeFi to NFTs and market analysis. Parenting Follow A place for parents to the share the joys, challenges, and wisdom that come from raising kids. We're here for them and for each other. Forem Core Follow Discussing the core forem open source software project — features, bugs, performance, self-hosting. Maker Forem Follow A community for makers, hobbyists, and professionals to discuss Arduino, Raspberry Pi, 3D printing, and much more. HMPL.js Forem Follow For developers using HMPL.js to build fast, lightweight web apps. A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse Dylan Muraco Posted on Dec 30, 2021 When to Use Server-Side rendering vs Static Generation in Next.js Pre-rendering your pages has multiple benefits such as better performance and better SEO. But choosing whether to statically generate your pages or render them on the server side can be confusing. Let's first take a look at Server-Side rendering getServerSideProps The main difference between getServerSideProps and getStaticProps is when they are ran. getServerSideProps is ran when every new request is made to the page. export async function getServerSideProps ( context ) { const { userId } = context . params const user = await getUser ( userId ) return { props : { user } } } export default function User ({ user }) { return ( < div > < h1 > { user . name } < /h1 > < /div > ) } Enter fullscreen mode Exit fullscreen mode In this example we are getting the userId from a dynamic route , getting the information about the user, then using that data to build the user page. Note that we have access to the request through params now lets take a look at getStaticProps getStaticProps We saw that getServerSideProps gets ran every time a new request is made so what about getStaticProps. getStaticProps is ran at build time, meaning that whenever you run npm run build this is when your static pages are built. export async function getStaticProps () { const blogPosts = await getBlogPosts () return { props : { blogPosts } } } export default function Home ({ blogPosts }) { return ( < div > { blogPosts . map ( post => ( < h1 > { post . name } < /h1 > ))} < /div > ) } Enter fullscreen mode Exit fullscreen mode this function is getting a list of blog posts and rendering them on a page. Because we know what we want before hand we can statically render the page whereas in our server side rendering example we don't know before the request is made what the user wants. So when to user getServerSideProps? Good for when you don't know what the user wants before they make a request Still want good SEO When to use getStaticProps? When we know what the user wants at build time Really fast performance and SEO This was just a quick dive into static generation vs server-side generation. If you want to learn more please let me know. As always thanks for reading. Top comments (8) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Collapse Expand Martin Krause Martin Krause Martin Krause Follow “It’s only work if somebody makes you do it.” • craft code • creative ideas • cutting edge • author • senior front end architect • professional scuba diver • adventures above and below the sea level Location Germany Work Senior Front End Architect, Full Stack Engineer, Creative Technologist and Scuba Diving Professional Joined May 19, 2019 • Dec 30 '21 • Edited on Dec 30 • Edited Dropdown menu Copy link Hide Hey! Great explanation! Back in summer I took e deep dive into the different types of pre-rendering with next.js - take a look if you like! Cheers! Like comment: Like comment: 4 likes Like Comment button Reply Collapse Expand Aimee Aimee Aimee Follow I'm a passionate front end developer with experience in HTML5, CSS3, Javascript, React, Typescript, GraphQL, Styled Components, MUI. Location UK Work web developer Joined May 18, 2019 • Jan 12 '23 Dropdown menu Copy link Hide hey nice blog post, which one should I use then, getByStaticProps, I'm fetching some data from a CMS I set up which stores my projects in then I'm wanting to display this data in my portfolio, I was using getByServerSideProps but I'm thinking I should use the other as it's not rarely going to change unless I go into the CMS and add a new project. Thanks Like comment: Like comment: Like Comment button Reply Collapse Expand coder-pixel coder-pixel coder-pixel Follow Work Student Joined Jan 23, 2023 • May 3 '23 Dropdown menu Copy link Hide I think in that case you should go for 'getStaticProps' option, as your data is ll static in general most of the time. Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Ryan-Mambou Ryan-Mambou Ryan-Mambou Follow Joined Mar 28, 2022 • Sep 20 '22 Dropdown menu Copy link Hide Excellent article man. Thanks a lot! Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand Emeka Orji Emeka Orji Emeka Orji Follow Email emekapraiseo@gmail.com Location Lagos, Nigeria Pronouns He/Him Work Engineering Joined Jun 25, 2020 • Jul 25 '22 Dropdown menu Copy link Hide Amazing Explanation!!👍👍 Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand Stelios Papoutsakis Stelios Papoutsakis Stelios Papoutsakis Follow I started as a full stack junior web developer in 2018, became a team leader and I am trying to level up my game. Joined Jun 15, 2024 • Jun 15 '24 Dropdown menu Copy link Hide good one. can we use both in a next.js project? Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand Shuvo Koiri Shuvo Koiri Shuvo Koiri Follow Joined Jun 30, 2022 • Jun 30 '22 Dropdown menu Copy link Hide Ok,,,,Can you tell me wahich one should I use in index.js for my Blogging website>>>??? Like comment: Like comment: Like Comment button Reply Collapse Expand Md Ohidul Islam Md Ohidul Islam Md Ohidul Islam Follow Joined Jul 1, 2022 • Jul 1 '22 Dropdown menu Copy link Hide Hello Shuvo Koiri, I am assuming that your index.js page is responsible for showing a list of blog posts, which we can assume doesn't change so frequently (e.g: Multiple-times in an hour). Therefore you can use getStaticProps with the property revalidate: 10 . By doing that Next.js will re-generate only the index.js page at most once every 10 seconds. See the code snapshot below, this is from the official Next.js documentation. export async function getStaticProps () { const res = await fetch ( ' https://.../posts ' ) const posts = await res . json () return { props : { posts , }, // Next.js will attempt to re-generate the page: // - When a request comes in // - At most once every 10 seconds revalidate : 10 , // In seconds } } ``` Enter fullscreen mode Exit fullscreen mode Like comment: Like comment: 4 likes Like Comment button Reply Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse Dylan Muraco Follow I like coding cool stuff Location Mars Joined Dec 21, 2021 More from Dylan Muraco Guide to Adding Info Text in Sanity Studio # sanity # webdev # react # typescript How to Create a Local RAG Agent with Ollama and LangChain # rag # tutorial # ai # python Authenticate in React with Firebase Auth # react # firebase # authentication 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close # iot Follow Hide Security challenges and solutions for Internet of Things and embedded devices. Create Post Older #iot posts 6 7 8 9 10 11 12 13 14 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu Interfacing 2.4" SSD1309 SPI OLED Display With ESP8266 İbrahim Gündüz İbrahim Gündüz İbrahim Gündüz Follow Oct 10 '25 Interfacing 2.4" SSD1309 SPI OLED Display With ESP8266 # iot # programming # electronics # esp8266 Comments Add Comment 2 min read A Reproducible Way to Size Ultra-Thin Solid-State Film Batteries for GPT48-X / GPT50 applekoiot applekoiot applekoiot Follow Oct 10 '25 A Reproducible Way to Size Ultra-Thin Solid-State Film Batteries for GPT48-X / GPT50 # iot # embedded # hardware # battery 1 reaction Comments Add Comment 3 min read Getting RGB LED Working on ESP32-C3 DevKitM-1 / Rust-1 John Ajera John Ajera John Ajera Follow Sep 19 '25 Getting RGB LED Working on ESP32-C3 DevKitM-1 / Rust-1 # esp32 # arduino # iot # rgb Comments Add Comment 2 min read Why Default Passwords Are Still a Massive Problem in 2025 GuardingPearSoftware GuardingPearSoftware GuardingPearSoftware Follow Oct 10 '25 Why Default Passwords Are Still a Massive Problem in 2025 # cybersecurity # networking # security # iot 1 reaction Comments Add Comment 5 min read Cyberspace Visibility and Privacy: Why Your Router Might Appear in ZoomEye sqlmap sqlmap sqlmap Follow Sep 18 '25 Cyberspace Visibility and Privacy: Why Your Router Might Appear in ZoomEye # privacy # iot # cybersecurity # tooling 1 reaction Comments Add Comment 2 min read How I safely tested a TurnKey CCTV appliance (lab workflow + mitigation playbook) Seif Eldien Ahmad Mohammad Seif Eldien Ahmad Mohammad Seif Eldien Ahmad Mohammad Follow Oct 9 '25 How I safely tested a TurnKey CCTV appliance (lab workflow + mitigation playbook) # security # devops # iot # infosec 1 reaction Comments Add Comment 2 min read Basic Signals in MATLAB for IoT and AI Md Sajib Pramanic Md Sajib Pramanic Md Sajib Pramanic Follow Sep 17 '25 Basic Signals in MATLAB for IoT and AI # ai # iot # matlab Comments Add Comment 2 min read Predictive Maintenance: AI That Hears Whispers of Impending Machine Failure Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Oct 20 '25 Predictive Maintenance: AI That Hears Whispers of Impending Machine Failure # machinelearning # iot # datascience # engineering Comments Add Comment 2 min read What is IOT? Ank Ank Ank Follow Sep 18 '25 What is IOT? # webdev # beginners # basic # iot Comments Add Comment 2 min read Preparing Your IoT Fleet for T-Mobile’s LTE Phase-Out applekoiot applekoiot applekoiot Follow Oct 9 '25 Preparing Your IoT Fleet for T-Mobile’s LTE Phase-Out # lte # 5g # iot # tmobile 5 reactions Comments Add Comment 2 min read Urban Skies: Navigating Drone Delivery Regulations Lori Spatt Lori Spatt Lori Spatt Follow Sep 16 '25 Urban Skies: Navigating Drone Delivery Regulations # automation # iot # productivity Comments Add Comment 4 min read The Hidden Challenges Nobody Tells You About IoT Apps CHILLICODE CHILLICODE CHILLICODE Follow Sep 15 '25 The Hidden Challenges Nobody Tells You About IoT Apps # appdev # development # mobile # iot Comments Add Comment 2 min read 💻 MicroPython on a $3 Board: Real-Time IoT Dashboard with Zero Cloud Costs! Yevhen Kozachenko 🇺🇦 Yevhen Kozachenko 🇺🇦 Yevhen Kozachenko 🇺🇦 Follow Oct 16 '25 💻 MicroPython on a $3 Board: Real-Time IoT Dashboard with Zero Cloud Costs! # micropython # iot # embeddedprogramming # webdev 1 reaction Comments Add Comment 3 min read Designing Years-Long Asset Trackers on LTE-M/NB-IoT: nRF9160, GNSS, and Real-Time Wake applekoiot applekoiot applekoiot Follow Oct 16 '25 Designing Years-Long Asset Trackers on LTE-M/NB-IoT: nRF9160, GNSS, and Real-Time Wake # hardware # iot # embedded # lowpower 1 reaction Comments Add Comment 7 min read 💡Idea: Using VPN-Type Virtual Links for Secure IoT Data Flow Hassam Fathe Muhammad Hassam Fathe Muhammad Hassam Fathe Muhammad Follow Oct 14 '25 💡Idea: Using VPN-Type Virtual Links for Secure IoT Data Flow # iot # cloudsecurity # edgecomputing # researchreflection 11 reactions Comments Add Comment 2 min read OpenMQTT Gateway for Infrared Signals Sebastian Sebastian Sebastian Follow Sep 15 '25 OpenMQTT Gateway for Infrared Signals # iot # esp32 # mqtt # infrared 1 reaction Comments 1 comment 6 min read Disposable Doesn't Have to Mean Disastrous: Smarter Design for 'Smart' Packaging Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 11 '25 Disposable Doesn't Have to Mean Disastrous: Smarter Design for 'Smart' Packaging # iot # sustainability # embedded # hardware 1 reaction Comments Add Comment 2 min read Lifespan Thinking: How to Build IoT that Learns Forever Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 11 '25 Lifespan Thinking: How to Build IoT that Learns Forever # iot # machinelearning # embedded # sustainability 1 reaction Comments Add Comment 2 min read Building High-Performance Time-Series Applications with tsink: A Rust Embedded Database h2337 h2337 h2337 Follow Sep 14 '25 Building High-Performance Time-Series Applications with tsink: A Rust Embedded Database # rust # database # timeseries # iot 1 reaction Comments Add Comment 4 min read From Trash to Treasure: A Developer's Guide to Smart Waste Management JennyThomas498 JennyThomas498 JennyThomas498 Follow Oct 14 '25 From Trash to Treasure: A Developer's Guide to Smart Waste Management # bigdata # datascience # iot 3 reactions Comments Add Comment 8 min read The Self-Aware Gadget: Predictive Lifespan Design for IoT Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 11 '25 The Self-Aware Gadget: Predictive Lifespan Design for IoT # iot # embedded # ai # design 1 reaction Comments Add Comment 2 min read Drips to Data Streams: Hacking Water Scarcity with IoT & Big Data Laetitia Perraut Laetitia Perraut Laetitia Perraut Follow Oct 13 '25 Drips to Data Streams: Hacking Water Scarcity with IoT & Big Data # iot # bigdata # sustainability Comments Add Comment 6 min read CanKit: a unified c# API for CAN bus (looking for testers & feedback) Pkuyo Pkuyo Pkuyo Follow Oct 13 '25 CanKit: a unified c# API for CAN bus (looking for testers & feedback) # showdev # csharp # iot # automotive 4 reactions Comments Add Comment 2 min read Building a Reliable USB-to-UART Bridge for Your Embedded Projects with FT232HQ-REEL xecor xecor xecor Follow Oct 13 '25 Building a Reliable USB-to-UART Bridge for Your Embedded Projects with FT232HQ-REEL # iot # usb # twiliohackathon 1 reaction Comments Add Comment 3 min read The 64 KB Challenge: Teaching a Tiny Neural Network to Play Pong Ruben Ghafadaryan Ruben Ghafadaryan Ruben Ghafadaryan Follow Oct 12 '25 The 64 KB Challenge: Teaching a Tiny Neural Network to Play Pong # python # neural # pytorch # iot 1 reaction Comments Add Comment 9 min read loading... 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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https://www.highlight.io/docs/getting-started/server/js/hono | Hono Quick Start Star us on GitHub Star Docs Sign in Sign up Getting Started Getting Started with Highlight Fullstack Mapping Browser React.js Next.js Remix Vue.js Angular Gatsby.js SvelteKit Electron highlight.run SDK Overview Canvas & WebGL Console Messages Content-Security-Policy Identifying Users iframe Recording Monkey Patches Browser OpenTelemetry Persistent Asset Storage Privacy Proxying Highlight React.js Error Boundary Recording Network Requests and Responses Recording WebSocket Events Salesforce Lightning Web Components (LWC) Data Export Sourcemap Configuration Tracking Events Troubleshooting Upgrading Highlight Versioning Sessions & Errors Other React Native (beta) Server Go Overview chi Echo Fiber Gin GORM gqlgen Logrus Manual Tracing gorilla mux JS Overview Apollo AWS Lambda Cloudflare Workers Express.js Firebase Hono Nest.js Next.js Node.js Pino tRPC Winston Python Overview AWS Lambda Azure Functions Django FastAPI Flask Google Cloud Functions Loguru Other Frameworks Python AI / LLM Libraries Python Libraries Ruby Overview Other Frameworks Ruby on Rails Rust Overview actix-web No Framework Hosting Providers Overview Metrics in AWS Logging in AWS Logging in Azure Fly.io NATS Log Shipper Logging in GCP Heroku Log Drain Render Log Stream Logging in Trigger.dev Vercel Log Drain Elixir Overview Elixir App Java: All Frameworks PHP: All Frameworks C# .NET ASP C# .NET 4 ASP Docker / Docker Compose File Fluent Forward curl OpenTelemetry Protocol (OTLP) Syslog RFC5424 Systemd / Journald Native OpenTelemetry Overview Error Monitoring Logging Tracing Browser Instrumentation Metrics Fullstack Frameworks Overview Next.js Fullstack Overview Next.js Page Router Guide Next.js App Router Guide Edge Runtime Advanced Config Remix Walkthrough Self Host & Local Dev Overview Development deployment guide. 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Menu Highlight Docs Welcome to highlight.io Get Started Roadmap Company Values Compliance & Security Open Source Contributing Overview GraphQL Backend Frontend (app.highlight.io) Landing Site (highlight.io) Documentation End to End SDK Example Apps Adding an SDK Application Architecture GitHub Code Spaces Code Style Good First Issues Self-hosting Self-hosted [Dev] Self-hosted [Hobby] Self-hosted [Enterprise] Telemetry Our Competitors Product Philosophy Product Features Session Replay Overview Canvas & Iframe Dev-tool Window Recording Tracking Users & Recording Events Filtering Sessions GraphQL Live Mode Performance Impact Player Session Caching Rage Clicks Request Proxying Session Search Extracting the Session URL Session Search Deep Linking Shadow Dom + Web Components Error Monitoring Overview Enhancing Errors with GitHub Error Search Filtering Errors Grouping Errors Managing Errors Manually Reporting Errors Sourcemaps General Features Overview Alerts Comments Digests Environments Search Segments Services Webhooks Logging Overview Log Alerts Log Search Tracing Overview Trace Search Dashboards Overview Dashboard Management Metrics Tutorials Service Latency Web Vitals & Page Speed User Engagement User Analytics Graphing Drilldown Event Search Dashboard Variables SQL Editor Metrics (beta) Overview Frequently Asked Questions. Integrations Integrations Overview Amplitude Integration ClickUp Integration Discord Integration Electron Support Front Integration GitHub Integration Grafana Integration Overview Setup Dashboards Alerts Height Integration Intercom Integration Jira Integration LaunchDarkly Integration Linear Integration Mixpanel Integration Nuxt Integration Pendo Integration Segment Integration Slack Integration Vercel Integration WordPress Plugin Highlight.io Changelog Overview Changelog 12 (02/17) Changelog 13 (02/24) Changelog 14 (03/03) Changelog 15 (03/11) Changelog 16 (03/19) Changelog 17 (04/07) Changelog 18 (04/26) Changelog 19 (05/22) Changelog 20 (06/06) Changelog 21 (06/21) Changelog 22 (08/07) Changelog 23 (08/22) Changelog 24 (09/11) Changelog 25 (10/03) Changelog 26 (11/08) Changelog 27 (12/22) Changelog 28 (3/6) Changelog 29 (4/2) Getting Started Getting Started with Highlight Fullstack Mapping Browser React.js Next.js Remix Vue.js Angular Gatsby.js SvelteKit Electron highlight.run SDK Overview Canvas & WebGL Console Messages Content-Security-Policy Identifying Users iframe Recording Monkey Patches Browser OpenTelemetry Persistent Asset Storage Privacy Proxying Highlight React.js Error Boundary Recording Network Requests and Responses Recording WebSocket Events Salesforce Lightning Web Components (LWC) Data Export Sourcemap Configuration Tracking Events Troubleshooting Upgrading Highlight Versioning Sessions & Errors Other React Native (beta) Server Go Overview chi Echo Fiber Gin GORM gqlgen Logrus Manual Tracing gorilla mux JS Overview Apollo AWS Lambda Cloudflare Workers Express.js Firebase Hono Nest.js Next.js Node.js Pino tRPC Winston Python Overview AWS Lambda Azure Functions Django FastAPI Flask Google Cloud Functions Loguru Other Frameworks Python AI / LLM Libraries Python Libraries Ruby Overview Other Frameworks Ruby on Rails Rust Overview actix-web No Framework Hosting Providers Overview Metrics in AWS Logging in AWS Logging in Azure Fly.io NATS Log Shipper Logging in GCP Heroku Log Drain Render Log Stream Logging in Trigger.dev Vercel Log Drain Elixir Overview Elixir App Java: All Frameworks PHP: All Frameworks C# .NET ASP C# .NET 4 ASP Docker / Docker Compose File Fluent Forward curl OpenTelemetry Protocol (OTLP) Syslog RFC5424 Systemd / Journald Native OpenTelemetry Overview Error Monitoring Logging Tracing Browser Instrumentation Metrics Fullstack Frameworks Overview Next.js Fullstack Overview Next.js Page Router Guide Next.js App Router Guide Edge Runtime Advanced Config Remix Walkthrough Self Host & Local Dev Overview Development deployment guide. Integrations Microsoft Teams self-hosted Hobby deployment guide. Traefik SSL Proxying. Docs Home SDK Client SDK API Reference Cloudflare Worker SDK API Reference Go SDK API Reference Hono SDK API Reference Java SDK API Reference Next.JS SDK API Reference Node.JS SDK API Reference Python SDK API Reference Ruby SDK API Reference Rust SDK API Reference Docs / Getting Started / Server / JS / Hono Quick Start Hono Quick Start Learn how to set up highlight.io in your Hono application. 1 Configure client-side Highlight. (optional) If you're using Highlight on the frontend for your application, make sure you've initialized it correctly and followed the fullstack mapping guide . 2 Install the relevant Highlight SDK(s). Install @highlight-run/hono with your package manager. npm install --save @highlight-run/hono 3 Add the Hono Highlight middleware Use the Hono SDK in your response handler. The middleware automatically traces all requests, reports exceptions, and captures console logs to Highlight. It integrates seamlessly with Hono's middleware system for minimal configuration. import { Hono } from 'hono' import { highlightMiddleware } from '@highlight-run/hono' const app = new Hono() // Initialize the Highlight middleware app.use(highlightMiddleware({ projectID: '<YOUR_PROJECT_ID>' })) // Your routes app.get('/', (c) => c.text('Hello Hono!')) // Errors will be automatically caught and reported app.get('/error', (c) => { throw new Error('Example error!') return c.text('This will not be reached') }) export default app 4 Verify that your SDK is reporting errors. You'll want to throw an exception in one of your hono handlers. Access the API handler and make sure the error shows up in Highlight . const app = new Hono() app.use(highlightMiddleware({ projectID: '<YOUR_PROJECT_ID>' })) app.get('/error', (c) => { throw new Error('example error!') return c.text('Error route') }) 5 Verify your backend logs are being recorded. Visit the highlight logs portal and check that backend logs are coming in. 6 Verify your backend traces are being recorded. Visit the highlight traces portal and check that backend traces are coming in. Firebase Quick Start Nest.js Quick Start [object Object] | 2026-01-13T08:48:58 |
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https://piccalil.li/blog/ | Articles - Piccalilli Front-end education for the real world. Since 2018. — From set.studio Articles Links Courses Newsletter Merch Login Switch to Dark Theme RSS Articles Subscribe via RSS Date is out, Temporal is in Temporal is the Date system we always wanted in JavaScript. It's extremely close to being available so Mat Marquis thought it would be a good idea to explain exactly what is better about this new JavaScript date system. JavaScript By Mat “Wilto” Marquis 07 January 2026 Wrapping up 2025 We don't normally do one of these, but I think 2025 has been a stellar year for Piccalilli, so we wanted to get into what we've done and what we're planning for next year. Announcements By Andy Bell 18 December 2025 Why are my view transitions blinking? Miguel had been battling an annoying blinking with his view transitions and found the root cause. He’s sharing his learning in this article so you don’t fall into the same trap! CSS By Miguel Pimentel 11 December 2025 A view transitions fallback: DOMContentLoaded + requestAnimationFrame() Look, we get it, your boss wants everything to work the same in every browser. We're all about progressive enhancement here but we know a lot of organisations don’t like working like that, so Sunkanmi is here to help you navigate implementing view transitions with that in mind. CSS By Sunkanmi Fafowora 04 December 2025 A pragmatic guide to modern CSS colours - part two Kevin is back with the follow up to part one of this series. This time, Kevin goes deep on how functional the newer colour capabilities are in practice to hopefully, encourage more designers to use their browser more often. CSS By Kevin Powell 02 December 2025 A Q&A with Mindful Design author, Scott Riley To celebrate the launch of Mindful Design, we gathered some questions from the community for Scott to answer to give you some more insight into his background, why he wanted to do this course and how it can help you. Announcements By Scott Riley 27 November 2025 We made an email template to help convince your boss to pay for Mindful Design We recently launched Mindful Design, and plenty of people have mentioned that they don’t know how to approach their boss to ask them to pay for it. Here’s an email template for you to help with that. Advice By Andy Bell 26 November 2025 Perfecting Baseline After two years, it’s clear that awareness about Baseline is grown a lot. As one of the co-chair of the group that makes Baseline, Patrick wanted to take a pause and reflect on how Baseline is starting to show up in developer’s lives, but also how it can be perfected. Opinion By Patrick Brosset 13 November 2025 Programming principles for self taught front-end developers The majority of us are a bunch of self taught people with rather spotty knowledge and that's fine! Kilian (also self taught) is here to share some of the computer science fundamentals you probably are missing with the aim to improve your code in the long term. Advice By Kilian Valkhof 11 November 2025 Some practical examples of view transitions to elevate your UI Declan Chidlow here with some really practical uses of view transitions, along with some of the stuff that will trip you up, with guidance to help you navigate that. CSS By Declan Chidlow 06 November 2025 1 2 … 18 19 Next From set.studio About Code of Conduct Privacy and cookie policy Terms and conditions Contact Advertise Support us RSS | 2026-01-13T08:48:58 |
https://dev.to/vjnvisakh | Visakh Vijayan - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Follow User actions Visakh Vijayan There is nothing else in this world that gives as much happiness as coding Location Kolkata, West Bengal Joined Joined on Sep 2, 2018 Email address vjnvisakh@gmail.com Personal website https://github.com/visakhvjn github website twitter website Education MCA Pronouns he/him/his Work Full Stack Developer at JTC Seven Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least seven years. Got it Close Six Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least six years. Got it Close Writing Debut Awarded for writing and sharing your first DEV post! Continue sharing your work to earn the 4 Week Writing Streak Badge. Got it Close Five Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least five years. Got it Close 2 Week Community Wellness Streak Keep the community conversation going! Post at least 2 comments for 2 straight weeks and unlock the 4 Week Badge. Got it Close Four Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least four years. Got it Close 1 Week Community Wellness Streak For actively engaging with the community by posting at least 2 comments in a single week. Got it Close Three Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least three years. Got it Close 8 Week Writing Streak The streak continues! You've written at least one post per week for 8 consecutive weeks. Unlock the 16-week badge next! Got it Close 4 Week Writing Streak You've posted at least one post per week for 4 consecutive weeks! Got it Close Two Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least two years. Got it Close One Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least one year. Got it Close More info about @vjnvisakh Organizations Souparnika Skills/Languages NestJs, Flutter, ReactJs, Graphql, Mongo, Elastic-search, Docker Currently learning Gatsby Currently hacking on Fiverr Available for Collaboration :D Post 297 posts published Comment 122 comments written Tag 10 tags followed Unlocking the Power of Inheritance in Python Visakh Vijayan Visakh Vijayan Visakh Vijayan Follow Jan 12 Unlocking the Power of Inheritance in Python # beginners # programming # python # tutorial Comments Add Comment 2 min read Want to connect with Visakh Vijayan? Create an account to connect with Visakh Vijayan. You can also sign in below to proceed if you already have an account. Create Account Already have an account? Sign in Mastering Interview Body Language Techniques: A Guide to Non-Verbal Communication Visakh Vijayan Visakh Vijayan Visakh Vijayan Follow Jan 11 Mastering Interview Body Language Techniques: A Guide to Non-Verbal Communication # career # interview # tutorial Comments Add Comment 1 min read Navigating the Startup Landscape: Mastering Competitive Analysis Visakh Vijayan Visakh Vijayan Visakh Vijayan Follow Jan 10 Navigating the Startup Landscape: Mastering Competitive Analysis # analytics # management # startup Comments Add Comment 3 min read Mastering Loops in Python: A Journey Through Iteration Visakh Vijayan Visakh Vijayan Visakh Vijayan Follow Jan 9 Mastering Loops in Python: A Journey Through Iteration Comments Add Comment 1 min read Elevating Innovation: The Future of Cloud with Platform as a Service (PaaS) Visakh Vijayan Visakh Vijayan Visakh Vijayan Follow Jan 8 Elevating Innovation: The Future of Cloud with Platform as a Service (PaaS) # architecture # cloudcomputing # devops Comments Add Comment 3 min read Navigating the Future: Startup Financial Forecasting Strategies Visakh Vijayan Visakh Vijayan Visakh Vijayan Follow Jan 7 Navigating the Future: Startup Financial Forecasting Strategies # analytics # management # startup Comments Add Comment 1 min read Boosting Frontend Development Efficiency with Vite and Webpack Visakh Vijayan Visakh Vijayan Visakh Vijayan Follow Jan 6 Boosting Frontend Development Efficiency with Vite and Webpack # frontend # javascript # productivity # tooling Comments Add Comment 2 min read Unleashing the Power of Arrow Functions in JavaScript Visakh Vijayan Visakh Vijayan Visakh Vijayan Follow Jan 5 Unleashing the Power of Arrow Functions in JavaScript # beginners # javascript # tutorial Comments Add Comment 2 min read Revolutionizing Code Testing with JavaScript: A Comprehensive Guide Visakh Vijayan Visakh Vijayan Visakh Vijayan Follow Jan 4 Revolutionizing Code Testing with JavaScript: A Comprehensive Guide # codequality # javascript # testing Comments Add Comment 2 min read Unlocking TypeScript's Power: Mastering Type Guards for Safer, Smarter Code Visakh Vijayan Visakh Vijayan Visakh Vijayan Follow Jan 3 Unlocking TypeScript's Power: Mastering Type Guards for Safer, Smarter Code # javascript # tutorial # typescript Comments Add Comment 2 min read Elevate Your Cloud Game: Mastering Monitoring & Logging with CloudWatch and Stackdriver Visakh Vijayan Visakh Vijayan Visakh Vijayan Follow Jan 2 Elevate Your Cloud Game: Mastering Monitoring & Logging with CloudWatch and Stackdriver # google # monitoring # devops # aws Comments Add Comment 3 min read Unveiling the Power of Databases in the Realm of Big Data Visakh Vijayan Visakh Vijayan Visakh Vijayan Follow Jan 1 Unveiling the Power of Databases in the Realm of Big Data # database # dataengineering # performance Comments Add Comment 2 min read Mastering Reinforcement Learning: A Dive into Machine Learning's Next Frontier Visakh Vijayan Visakh Vijayan Visakh Vijayan Follow Dec 31 '25 Mastering Reinforcement Learning: A Dive into Machine Learning's Next Frontier # ai # datascience # machinelearning Comments Add Comment 2 min read Exploring the Power of Set & Map in JavaScript Visakh Vijayan Visakh Vijayan Visakh Vijayan Follow Dec 30 '25 Exploring the Power of Set & Map in JavaScript # algorithms # beginners # javascript 5 reactions Comments Add Comment 1 min read Unveiling the Threat of Clickjacking in Web Security Visakh Vijayan Visakh Vijayan Visakh Vijayan Follow Dec 29 '25 Unveiling the Threat of Clickjacking in Web Security # html # ui # security # webdev Comments Add Comment 2 min read Revolutionizing Scalability: Exploring Container Orchestration Solutions Visakh Vijayan Visakh Vijayan Visakh Vijayan Follow Dec 28 '25 Revolutionizing Scalability: Exploring Container Orchestration Solutions # systemdesign # architecture # kubernetes # devops Comments Add Comment 2 min read Revolutionizing Frontend Development with Design Systems Visakh Vijayan Visakh Vijayan Visakh Vijayan Follow Dec 27 '25 Revolutionizing Frontend Development with Design Systems # architecture # frontend # ui # design 1 reaction Comments Add Comment 2 min read Unleashing the Power of DOM Manipulation in Frontend Development Visakh Vijayan Visakh Vijayan Visakh Vijayan Follow Dec 25 '25 Unleashing the Power of DOM Manipulation in Frontend Development # 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https://dev.to/om_shree_0709/cognee-building-the-next-generation-of-memory-for-ai-agents-oss-3jm1 | Cognee: Building the Next Generation of Memory for AI Agents (OSS) - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse Om Shree Posted on Oct 17, 2025 Cognee: Building the Next Generation of Memory for AI Agents (OSS) # ai # tutorial # beginners # discuss I. Moving Beyond Simple Search: The RAG Challenge If you've built applications using Large Language Models (LLMs) , you've likely used Retrieval-Augmented Generation (RAG) . RAG is essentially giving the LLM context from your documents so it doesn't hallucinate. It works like this: when a user asks a question, the system finds the most semantically similar chunks of text in your data (using vectors) and passes those chunks to the LLM for an answer. However, standard RAG has a massive limitation: it has no structural memory . It can tell you what a document says, but it can't understand how different concepts are related across multiple documents. It can’t perform "multi-hop" reasoning (e.g., "Find the manager of the person who approved Project X"). For AI agents, this is a major problem. They need to remember context, link facts, and build on past interactions to act intelligently. RAG can’t do that, it only retrieves information in isolation. A good memory gives agents continuity and understanding, letting them connect ideas the way humans do. Cognee is designed to solve this. It’s an open-source ai memory that combines two powerful storage methods “ Vector Search and Knowledge Graphs ” to give your AI a truly structural and semantic memory, resulting in answers with up to 92.5% reported accuracy in complex scenarios. II. The Core Architecture: A Cognitive Blueprint Cognee's architecture is inspired by human cognition, separating its functionality into four distinct layers. This separation ensures modularity and clarity in the data flow. Layer Analogy Technical Function Ingestion Intake / Triage Ingests data (over 30 formats supported), normalizes it, and routes it to the processing pipelines ( cognify ). Memory Dynamic Memory Layers and Persistent Storage Cognifies and stores knowledge in three systems (Graph, Vector, Relational) for structural and semantic recall. Reasoning Analysis / Synthesis Retrieves context from the Memory Layer, analyzes relationships, and prepares the final prompt for the LLM. Action Output Takes the LLM's final response and delivers it to the user or executes an external task (e.g., an API call). For visualization and exploration, Cognee also has a built-in function that renders the generated knowledge graph directly. This is what a Cognee knowledge graph looks like, illustrating the complex web of interconnected entities and relationships it builds from your input data, forming the structural memory for AI agents. Cognee also offers a local UI that uses interactive notebooks to run cognee tasks, pipelines, and custom logic we will describe below.. III. The Triple-Store Secret: Why You Need Three Databases One of the core innovations of Cognee is its sophisticated storage system, which integrates three types of databases, each serving a critical, non-redundant function. 1. The Vector Store (Semantic Recall) Purpose : Stores data chunks as numerical representations (embeddings). What it provides : High-speed semantic similarity search. This lets the system find content based on meaning, even if the query uses different words. Supported Tech : Qdrant, Milvus, LanceDB, Redis and more. 2. The Graph Store (Structural Reasoning) Purpose : Stores entities (nodes) and their relationships (edges) extracted from the text. What it provides: Structural reasoning . This is the GraphRAG component. It allows the system to traverse non-linear relationships, essential for complex queries like organizational charts, causal chains, and dependencies. Supported Tech : Neo4j, Kuzu, FalkorDB, NetworkX and more. 3. The Relational Store (Source of Truth) Purpose : A traditional SQL-based system (using SQLAlchemy and Alembic). What it provides: Provenance and Auditability . It stores all metadata, tracks the original source of every data chunk, ensuring that any derived knowledge is explainable and verifiable. This is crucial for enterprise applications requiring data governance. The magic happens in Hybrid Search (part of the .search() operation), where the system queries the Vector Store for relevant content and the Graph Store for the contextual relationships simultaneously, resulting in a maximally rich and coherent prompt for the LLM. IV. The Developer Workflow: Operations and Data Modeling Cognee is primarily a Pythonic library (over Python codebase). It exposes a clean, asynchronous API defined by four core functional primitives. A. The Core Functional Operations (ECL Model) Operation Action Description .add() Ingestion (Extract) Takes your raw files (PDFs, code, databases) and performs initial cleaning and preparation. .cognify() Knowledge Generation (Cognify) The main processing step . It uses an LLM to automatically read the cleaned data, chunk it, extract all entities and relationships, and build the final Triple-Store Memory . .memify() Memory Refinement (New) Cognee's advanced pipeline that uses AI to infer implicit connections, rule patterns, and relationships that were not explicitly in the source data, significantly enriching reasoning capability. .search() Hybrid Retrieval Executes a query combining vector search and graph traversal to retrieve context or generate a high-quality RAG answer. Code Snippet Python: import cognee # 1. Add raw data (text, PDFs, etc.) await cognee.add("path_to_your_project_notes.pdf") # 2. Cognify it - Transform data into structured knowledge await cognee.cognify() #3. Memify it - Enhance memory await cognee.memify() # 4. Search semantically and using graph traversal results = await cognee.search("Who manages Project X?") print(results) Enter fullscreen mode Exit fullscreen mode B. The Atomic Unit of Knowledge: DataPoints (Pydantic Models) For developers, the DataPoint is the single most important conceptual unit. Think of it as the strongly-typed schema for all knowledge within Cognee. Pydantic Foundation: DataPoints are implemented as Pydantic models. This guarantees that all knowledge is structured, type-validated, and reliable as it moves through the asynchronous processing pipeline. Dual Role: A DataPoint can represent a document, a segmented chunk of text, a concept/entity, or even a relationship (edge) in the graph. Declarative Indexing: The most powerful feature is the metadata.index_fields key. This is a list that you, the developer, use to explicitly tell Cognee which specific fields should be converted to embeddings. Example: For a DocumentChunk object, you'd index the text field. For an Entity object, you might only index the name field to save cost and avoid semantic noise. This granular control over indexing significantly optimizes both embedding costs and search accuracy. C. The Advanced Search Engine: Optimizations and Awareness Cognee's .search() operation goes beyond hybrid retrieval through two advanced features: Temporal Awareness : By setting temporal_cognify=True during knowledge generation, the system constructs a time-aware graph. This allows for powerful queries that analyze trends, understand the evolution of concepts, and provide context based on historical development velocity. Continuous Feedback Loops : The system supports an auto-optimization feedback mechanism. By saving search interactions ( save_interaction=True ) and providing explicit feedback, the system incorporates user-validated relevance into the graph, ensuring that its memory continuously adapts to specific user preferences and needs over time. V. Primary Use Cases: Where Cognee Shines Cognee’s architecture makes it ideal for applications that demand high-quality, verifiable outputs: Deterministic AI Agents : By providing agents (e.g., those built with Agent Frameworks like LangGraph, CrewAI) with structured, semantic memory, you ensure their outputs are grounded in verifiable relationships, leading to more reliable, accurate results. The .memify() pipeline is key here, as it allows memory enrichment through custom logic for agent decision-making. Vertical AI Agents (For Business functions) : They are specialized systems for compliance, finance, or legal workflows. They require absolute accuracy and explainability. Cognee provides this through its knowledge graph, which encodes domain-specific rules and relationships, supports ontology for more structured data modeling. This structural memory enables the agent to perform multi-step workflow orchestration and make auditable, factual decisions, thus overcoming the limitations of standard, general-purpose RAG. Code Graph Generation : Cognee can ingest codebases and automatically map out dependencies, function calls, and structural relationships. This resulting Code Graph Context is necessary for building sophisticated code copilots that can reason over a large project's structure, not just its content. VI. Getting Started with Cognee For developers eager to try Cognee locally, here’s a quick setup guide to get started within minutes: Step 1 : Clone the repository git clone https://github.com/topoteretes/cognee.git cd cognee Enter fullscreen mode Exit fullscreen mode Step 2 : Set up the Environment uv sync Enter fullscreen mode Exit fullscreen mode Step 3 : Once dependencies are installed, you can activate the virtual environment and explore examples: source .venv/bin/activate cd examples Enter fullscreen mode Exit fullscreen mode Or you can start Cognee with: uv pip install cognee Enter fullscreen mode Exit fullscreen mode Step 4 : Add your OpenAI API key to your .env file: LLM_API_KEY="your_openai_api_key" Enter fullscreen mode Exit fullscreen mode Cognee uses OpenAI by default but you can configure other model providers following their guideline. This process initiates Cognee's local environment, loading all available modules, such as the ingestion, graph, and search layers. Step 5 : Explore the Core Workflow The following example illustrates how Cognee simplifies intricate memory systems into a clear, high-level API: import cognee # 1. Add raw data (text, PDFs, etc.) await cognee.add("meeting_notes.pdf") # 2. Cognify it - transform data into structured knowledge await cognee.cognify() # 3. Search semantically and using graph traversal results = await cognee.search("Who manages the data pipeline?") print(results) Enter fullscreen mode Exit fullscreen mode Cognee instantly constructs and organizes information from raw documents, enabling semantic queries without the need for a duct taped RAG pipeline. You can find an end to end notebook tutorial here . VII. Conclusion: The Shift from Retrieval to Reasoning Cognee represents a pivotal shift in how developers approach context engineering. It moves the focus from simple retrieval (finding keywords and similar vectors) to complex reasoning **(analyzing structured relationships) powered by dynamic memory layers. By providing a powerful, yet simple to use **Pythonic framework that incorporates graph-based memory, declarative data modeling via DataPoints , and robust observability tools, Cognee is a perfect toolkit for me and other devs for building production-grade AI systems. The latest features, including the advanced .memify() reasoning pipeline, Node Sets for organizing memory and search filtering, Temporal Awareness for evolutionary analysis, auto-optimization with feedback loops, and a local visualization UI, firmly position Cognee as the next generation of AI memory. For any developer building agents that need to operate with accuracy, context, and structural awareness in complex domains, exploring Cognee is an essential next step in moving beyond the limitations of first-generation RAG. Dive into the repository and start building AI systems that don't just recall information, but genuinely reason with it. Top comments (27) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Collapse Expand shemith mohanan shemith mohanan shemith mohanan Follow AI Startup Founder | Creator of BusinessAdBooster.pro — an AI-powered marketing tool that generates human-sounding, SEO, AEO & GEO-optimized content for small businesses and digital marketers. Helping Joined Oct 8, 2025 • Oct 18 '25 Dropdown menu Copy link Hide This is an incredible deep dive — Cognee feels like a genuine step forward from traditional RAG setups. The triple-store architecture (Vector + Graph + Relational) makes perfect sense for achieving both semantic recall and structural reasoning. The .memify() feature in particular stands out — it’s exactly what’s needed for AI agents to move from retrieval to real contextual understanding. Definitely going to explore this on GitHub. Like comment: Like comment: 3 likes Like Comment button Reply Collapse Expand Om Shree Om Shree Om Shree Follow Technical Evangelist | AI Researcher | Simplifying Complex AI & Agent Workflows for Developers Email omshree0709@gmail.com Location India Education Jaypee University Of Information Technology Pronouns He/Him Work Founder of Shreesozo Joined Feb 27, 2025 • Oct 18 '25 Dropdown menu Copy link Hide Thanks Sir, Glad you liked it!!! ❤️ Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand shemith mohanan shemith mohanan shemith mohanan Follow AI Startup Founder | Creator of BusinessAdBooster.pro — an AI-powered marketing tool that generates human-sounding, SEO, AEO & GEO-optimized content for small businesses and digital marketers. Helping Joined Oct 8, 2025 • Oct 18 '25 Dropdown menu Copy link Hide Thanks, Om! 🙌 Really appreciate the detailed write-up — the .memify() pipeline idea was especially insightful. Excited to see how Cognee evolves, this approach could set a new standard for AI memory systems 🔥 Like comment: Like comment: 2 likes Like Thread Thread Om Shree Om Shree Om Shree Follow Technical Evangelist | AI Researcher | Simplifying Complex AI & Agent Workflows for Developers Email omshree0709@gmail.com Location India Education Jaypee University Of Information Technology Pronouns He/Him Work Founder of Shreesozo Joined Feb 27, 2025 • Oct 18 '25 Dropdown menu Copy link Hide I'm excited tooooo Sir ❤️❤️❤️ Like comment: Like comment: 2 likes Like Thread Thread shemith mohanan shemith mohanan shemith mohanan Follow AI Startup Founder | Creator of BusinessAdBooster.pro — an AI-powered marketing tool that generates human-sounding, SEO, AEO & GEO-optimized content for small businesses and digital marketers. Helping Joined Oct 8, 2025 • Oct 19 '25 Dropdown menu Copy link Hide Haha awesome, Om! 😄 Can’t wait to see where you take this — really promising work 🚀 Like comment: Like comment: 2 likes Like Thread Thread Om Shree Om Shree Om Shree Follow Technical Evangelist | AI Researcher | Simplifying Complex AI & Agent Workflows for Developers Email omshree0709@gmail.com Location India Education Jaypee University Of Information Technology Pronouns He/Him Work Founder of Shreesozo Joined Feb 27, 2025 • Oct 19 '25 Dropdown menu Copy link Hide Thanks Sir, all credit goes to Cognee's team ❤️. Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Dylan Ashford Dylan Ashford Dylan Ashford Follow Marketing pro in dev tools & AI. Focused on positioning, GTM, and community growth. Exploring how open source + SDKs drive the future of AI. Location Campbell Joined Sep 26, 2025 • Oct 21 '25 Dropdown menu Copy link Hide That’s a solid approach. The combination of vector search with a knowledge graph feels like the missing piece for most RAG setups. I’ve seen similar issues where context gets lost between related documents or previous user sessions. In Vezlo, we’re testing something similar for SaaS knowledge bases — trying to link context across multiple data sources instead of just retrieving static chunks. Curious how Cognee handles updates when the underlying data changes — does the graph rebuild incrementally or from scratch? Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Om Shree Om Shree Om Shree Follow Technical Evangelist | AI Researcher | Simplifying Complex AI & Agent Workflows for Developers Email omshree0709@gmail.com Location India Education Jaypee University Of Information Technology Pronouns He/Him Work Founder of Shreesozo Joined Feb 27, 2025 • Oct 23 '25 Dropdown menu Copy link Hide Thank Sir, Glad you liked it! Cognee's approach is designed to be highly efficient. When the underlying data changes, the knowledge graph does not rebuild from scratch. Instead, it updates incrementally, allowing for real-time changes without the need for a full re-index. This is a core part of our architecture, ensuring that the system remains scalable and responsive, even with large and frequently updated datasets. It's interesting to hear about what you're building at Vezlo. Linking context across multiple data sources is a crucial challenge, and it sounds like you're tackling it head-on. I'd love to connect and share notes on our respective approaches. Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand Xion Apex Academy Xion Apex Academy Xion Apex Academy Follow On a mission to make building things easier, fairer, and more global. I share what I learn, ship what I can, and invite others to build with me. Location Randburg, South Africa Joined May 12, 2025 • Oct 22 '25 Dropdown menu Copy link Hide This is really awesome and opens many more ways to improve our AI agents. Very nice work! Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Om Shree Om Shree Om Shree Follow Technical Evangelist | AI Researcher | Simplifying Complex AI & Agent Workflows for Developers Email omshree0709@gmail.com Location India Education Jaypee University Of Information Technology Pronouns He/Him Work Founder of Shreesozo Joined Feb 27, 2025 • Oct 23 '25 Dropdown menu Copy link Hide Thanks Sir, Glad you liked it Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand Anna kowoski Anna kowoski Anna kowoski Follow Senior Software Engineer with 8+ years of experience building scalable backend systems. Currently at TechWave, she specializes in cloud infrastructure, optimizing AWS and Kubernetes deployments for hi Joined Jun 5, 2025 • Oct 17 '25 Dropdown menu Copy link Hide Nice Article Om!, I love the idea of using the Knowledge Graph for structural memory. Loved the visualization part. Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Om Shree Om Shree Om Shree Follow Technical Evangelist | AI Researcher | Simplifying Complex AI & Agent Workflows for Developers Email omshree0709@gmail.com Location India Education Jaypee University Of Information Technology Pronouns He/Him Work Founder of Shreesozo Joined Feb 27, 2025 • Oct 17 '25 Dropdown menu Copy link Hide Thanks Ma'am, Glad you liked it!!! Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand Mahua Vaidya Mahua Vaidya Mahua Vaidya Follow Just here to build reading as a habit Joined Sep 8, 2025 • Oct 17 '25 Dropdown menu Copy link Hide Loved it, but how does Cognee’s hybrid search differ from traditional RAG pipelines in practice? Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Om Shree Om Shree Om Shree Follow Technical Evangelist | AI Researcher | Simplifying Complex AI & Agent Workflows for Developers Email omshree0709@gmail.com Location India Education Jaypee University Of Information Technology Pronouns He/Him Work Founder of Shreesozo Joined Feb 27, 2025 • Oct 18 '25 Dropdown menu Copy link Hide Thanks ma'am!!! Cognee's hybrid search combines vector similarity (semantic context) with knowledge graph traversal (structural relationships) to enable complex, multi-hop reasoning that traditional RAG cannot perform. Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand Hande Kafkas Hande Kafkas Hande Kafkas Follow Joined Apr 24, 2025 • Oct 17 '25 Dropdown menu Copy link Hide great work Om, thank you for sharing! Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Om Shree Om Shree Om Shree Follow Technical Evangelist | AI Researcher | Simplifying Complex AI & Agent Workflows for Developers Email omshree0709@gmail.com Location India Education Jaypee University Of Information Technology Pronouns He/Him Work Founder of Shreesozo Joined Feb 27, 2025 • Oct 18 '25 Dropdown menu Copy link Hide Thanks ma'am, Glad you liked it!!! Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand cuongnp cuongnp cuongnp Follow I'm a software engineer. Location Tokyo, Japan Work Technical Lead Joined May 1, 2023 • Oct 19 '25 Dropdown menu Copy link Hide Love it! Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Om Shree Om Shree Om Shree Follow Technical Evangelist | AI Researcher | Simplifying Complex AI & Agent Workflows for Developers Email omshree0709@gmail.com Location India Education Jaypee University Of Information Technology Pronouns He/Him Work Founder of Shreesozo Joined Feb 27, 2025 • Oct 19 '25 Dropdown menu Copy link Hide Thanks Sir, Glad you liked it! Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand Nube Colectiva Nube Colectiva Nube Colectiva Follow We are a Programming and Technology community. Somos una comunidad de Programación y Tecnología. 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Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse Om Shree Follow Technical Evangelist | AI Researcher | Simplifying Complex AI & Agent Workflows for Developers Location India Education Jaypee University Of Information Technology Pronouns He/Him Work Founder of Shreesozo Joined Feb 27, 2025 More from Om Shree Bridging LLMs and Design Systems via MCP: Implementing a Community Figma MCP Server for Generative Design # mcp # ai # figma # design Orchestrating Intelligence: Simplifying Agentic Workflows with Model Context Protocol # discuss # ai # automation # mcp The $1 Takeover: How the U.S. Government "Nationalized" Anthropic # ai # anthropic # discuss # news 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Career Follow Hide This tag is for anything relating to careers! Job offers, workplace conflict, interviews, resumes, promotions, etc. Create Post submission guidelines All articles and discussions should relate to careers in some way. Pretty much everything on dev.to is about our careers in some way. Ideally, though, keep the tag related to getting, leaving, or maintaining a career or job. about #career A career is the field in which you work, while a job is a position held in that field. Related tags include #resume and #portfolio as resources to enhance your #career Older #career posts 75 76 77 78 79 80 81 82 83 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu Friender: Building Real Friendships in a World of Swipe Fatigue WLH Challenge: After the Hack Submission Faraz Faraz Faraz Follow Jul 24 '25 Friender: Building Real Friendships in a World of Swipe Fatigue # devchallenge # wlhchallenge # career # entrepreneurship 9 reactions Comments Add Comment 4 min read I've Shipped for Millions, But Can't Ship Myself Past ATS Philip John Basile Philip John Basile Philip John Basile Follow Jul 20 '25 I've Shipped for Millions, But Can't Ship Myself Past ATS # ai # webdev # gamedev # career 38 reactions Comments 26 comments 2 min read Could an AI Coach Actually Fix Rehab? Our Hackathon Experiment WLH Challenge: Building with Bolt Submission Luke Luke Luke Follow Jul 21 '25 Could an AI Coach Actually Fix Rehab? 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Ashfaq Jani Ashfaq Jani Ashfaq Jani Follow Jun 25 '25 🚀 I built HireME – A platform to track job applications, get job reminders, and collaborate with friends! # webdev # productivity # career 1 reaction Comments Add Comment 2 min read Yes, You Have to Play Office Politics - Because Your Team Can’t Afford for You Not To John Munn John Munn John Munn Follow Jun 25 '25 Yes, You Have to Play Office Politics - Because Your Team Can’t Afford for You Not To # leadership # career # management # devculture Comments Add Comment 4 min read Provide storage for a new company app Isaiah Izibili Isaiah Izibili Isaiah Izibili Follow Jul 24 '25 Provide storage for a new company app # devops # career # aws # cloud 6 reactions Comments Add Comment 8 min read The Latin Tech-Dreamer Manifesto 🔥🚀 Andrés Beltran Andrés Beltran Andrés Beltran Follow Jun 20 '25 The Latin Tech-Dreamer Manifesto 🔥🚀 # discuss # learning # beginners # career Comments Add Comment 5 min read The Art of Cyber Deception: Why Thinking Like a Liar Can Make You a Better Defender ahmed Awad (Nullc0d3) ahmed Awad (Nullc0d3) ahmed Awad (Nullc0d3) Follow Jul 14 '25 The Art of Cyber Deception: Why Thinking Like a Liar Can Make You a Better Defender # programming # tutorial # cybersecurity # career Comments Add Comment 2 min read 🎒 Friday Stack Pack: Tools, Toys & Side Quests for the Weekend Sumit Roy Sumit Roy Sumit Roy Follow Jun 20 '25 🎒 Friday Stack Pack: Tools, Toys & Side Quests for the Weekend # beginners # productivity # tutorial # career Comments Add Comment 2 min read Quebrei a barreira do 'medo' de contribuir em open source e criei uma ferramenta para te ajudar também André Timm André Timm André Timm Follow Jun 24 '25 Quebrei a barreira do 'medo' de contribuir em open source e criei uma ferramenta para te ajudar também # opensource # career # beginners 6 reactions Comments 2 comments 3 min read The Descent Is Harder Than the Climb: Lessons in Leadership from Mt. 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Fuji # leadership # career # management # productivity 7 reactions Comments 1 comment 6 min read If it Ain’t Broke… Fix it Until it is Ben Link Ben Link Ben Link Follow Jul 24 '25 If it Ain’t Broke… Fix it Until it is # leadership # management # workplace # career 1 reaction Comments Add Comment 5 min read The Hidden Depth of Skill: What Building Taught Me About Ego Numerous Oriabure Numerous Oriabure Numerous Oriabure Follow Jun 20 '25 The Hidden Depth of Skill: What Building Taught Me About Ego # career # learning # motivation # developers 2 reactions Comments 1 comment 3 min read Building the Future of Emotional AI: Looking for Passionate Co-Founders Facundo Facundo Facundo Follow Jul 3 '25 Building the Future of Emotional AI: Looking for Passionate Co-Founders # ai # react # career # codenewbie Comments Add Comment 3 min read We're Hiring: Full-Stack Developer (Nuxt.js + Nest.js) With Database Migration Expertise RPMAnetworks RPMAnetworks RPMAnetworks Follow Jun 24 '25 We're Hiring: Full-Stack Developer (Nuxt.js + Nest.js) With Database Migration Expertise # discuss # hiring # career # postgressql 5 reactions Comments 1 comment 1 min read Why Calm Developers Build Better Code: Stoic Strategies for Handling Chaos in Software Engineering Tony St Pierre Tony St Pierre Tony St Pierre Follow Jun 19 '25 Why Calm Developers Build Better Code: Stoic Strategies for Handling Chaos in Software Engineering # discuss # programming # career # learning Comments Add Comment 1 min read A Real-World UI Problem You Can’t Ignore” Nuro Design Nuro Design Nuro Design Follow Jun 20 '25 A Real-World UI Problem You Can’t Ignore” # beginners # ai # career # startup 1 reaction Comments Add Comment 1 min read ToDo Today - After the Hack WLH Challenge: After the Hack Submission Łukasz Modzelewski Łukasz Modzelewski Łukasz Modzelewski Follow Jul 23 '25 ToDo Today - After the Hack # devchallenge # wlhchallenge # career # entrepreneurship 3 reactions Comments 1 comment 1 min read The Enduring Power of the 12-Factor App: A Modern Playbook for Cloud-Native Excellence Pranav Gandhi Pranav Gandhi Pranav Gandhi Follow Jun 20 '25 The Enduring Power of the 12-Factor App: A Modern Playbook for Cloud-Native Excellence # cloudnative # softwaredevelopment # career # productivity Comments Add Comment 1 min read Developer Presence: The Underrated Skill for Focused & Resilient Code Tony St Pierre Tony St Pierre Tony St Pierre Follow Jun 21 '25 Developer Presence: The Underrated Skill for Focused & Resilient Code # discuss # programming # career # learning 1 reaction Comments Add Comment 1 min read My Journey as a Young Web Developer in a Fast-Changing Tech World Ogundimu Emmanuel oluseyi Ogundimu Emmanuel oluseyi Ogundimu Emmanuel oluseyi Follow Jun 20 '25 My Journey as a Young Web Developer in a Fast-Changing Tech World # codenewbie # fullstack # webdev # career Comments Add Comment 1 min read How Do You Collaborate in the US Dev World? Mike Mike Mike Follow Jun 20 '25 How Do You Collaborate in the US Dev World? # career # fullstack # typescript # laravel Comments Add Comment 1 min read Hello, I am a DevOps Engineer and I Broke Production Today Ogonna Nnamani Ogonna Nnamani Ogonna Nnamani Follow Jul 23 '25 Hello, I am a DevOps Engineer and I Broke Production Today # devops # career # failure # postmortem 2 reactions Comments Add Comment 5 min read Don’t Learn These Tech Skills in 2025 (Unless You Want to Stay Broke) Abdul Rehman Khan Abdul Rehman Khan Abdul Rehman Khan Follow Jul 12 '25 Don’t Learn These Tech Skills in 2025 (Unless You Want to Stay Broke) # tech # career # programming # ai 1 reaction Comments Add Comment 2 min read loading... 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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https://opensource.org/definition-annotated | The Open Source Definition (Annotated) – Open Source Initiative Skip to content Get involved About Licenses Open Source Definition Open Source AI Programs Blog Get involved About Licenses Open Source Definition Open Source AI Programs Blog Open Main Menu Home The Open Source Definition (Annotated) The Open Source Definition (Annotated) Page created on July 24, 2006 | Last modified on February 16, 2024 The sections below appear as annotations to the Open Source Definition (OSD) and are not a part of the OSD. A plain version of the OSD without annotations can be found here . Introduction Open source doesn’t just mean access to the source code. The distribution terms of open source software must comply with the following criteria: 1. Free Redistribution The license shall not restrict any party from selling or giving away the software as a component of an aggregate software distribution containing programs from several different sources. The license shall not require a royalty or other fee for such sale. Rationale: By constraining the license to require free redistribution, we eliminate the temptation for licensors to throw away many long-term gains to make short-term gains. If we didn’t do this, there would be lots of pressure for cooperators to defect. 2. Source Code The program must include source code, and must allow distribution in source code as well as compiled form. Where some form of a product is not distributed with source code, there must be a well-publicized means of obtaining the source code for no more than a reasonable reproduction cost, preferably downloading via the Internet without charge. The source code must be the preferred form in which a programmer would modify the program. Deliberately obfuscated source code is not allowed. Intermediate forms such as the output of a preprocessor or translator are not allowed. Rationale: We require access to un-obfuscated source code because you can’t evolve programs without modifying them. Since our purpose is to make evolution easy, we require that modification be made easy. 3. Derived Works The license must allow modifications and derived works, and must allow them to be distributed under the same terms as the license of the original software. Rationale: The mere ability to read source isn’t enough to support independent peer review and rapid evolutionary selection. For rapid evolution to happen, people need to be able to experiment with and redistribute modifications. 4. Integrity of The Author’s Source Code The license may restrict source-code from being distributed in modified form only if the license allows the distribution of “patch files” with the source code for the purpose of modifying the program at build time. The license must explicitly permit distribution of software built from modified source code. The license may require derived works to carry a different name or version number from the original software. Rationale: Encouraging lots of improvement is a good thing, but users have a right to know who is responsible for the software they are using. Authors and maintainers have reciprocal right to know what they’re being asked to support and protect their reputations. Accordingly, an open source license must guarantee that source be readily available, but may require that it be distributed as pristine base sources plus patches. In this way, “unofficial” changes can be made available but readily distinguished from the base source. 5. No Discrimination Against Persons or Groups The license must not discriminate against any person or group of persons. Rationale: In order to get the maximum benefit from the process, the maximum diversity of persons and groups should be equally eligible to contribute to open sources. Therefore we forbid any open source license from locking anybody out of the process. Some countries, including the United States, have export restrictions for certain types of software. An OSD-conformant license may warn licensees of applicable restrictions and remind them that they are obliged to obey the law; however, it may not incorporate such restrictions itself. 6. No Discrimination Against Fields of Endeavor The license must not restrict anyone from making use of the program in a specific field of endeavor. For example, it may not restrict the program from being used in a business, or from being used for genetic research. Rationale: The major intention of this clause is to prohibit license traps that prevent open source from being used commercially. We want commercial users to join our community, not feel excluded from it. 7. Distribution of License The rights attached to the program must apply to all to whom the program is redistributed without the need for execution of an additional license by those parties. Rationale: This clause is intended to forbid closing up software by indirect means such as requiring a non-disclosure agreement. 8. License Must Not Be Specific to a Product The rights attached to the program must not depend on the program’s being part of a particular software distribution. If the program is extracted from that distribution and used or distributed within the terms of the program’s license, all parties to whom the program is redistributed should have the same rights as those that are granted in conjunction with the original software distribution. Rationale: This clause forecloses yet another class of license traps. 9. License Must Not Restrict Other Software The license must not place restrictions on other software that is distributed along with the licensed software. For example, the license must not insist that all other programs distributed on the same medium must be open source software. Rationale: Distributors of open source software have the right to make their own choices about their own software. Yes, the GPL v2 and v3 are conformant with this requirement. Software linked with GPLed libraries only inherits the GPL if it forms a single work, not any software with which they are merely distributed. 10. License Must Be Technology-Neutral No provision of the license may be predicated on any individual technology or style of interface. Rationale: This provision is aimed specifically at licenses which require an explicit gesture of assent in order to establish a contract between licensor and licensee. Provisions mandating so-called “click-wrap” may conflict with important methods of software distribution such as FTP download, CD-ROM anthologies, and web mirroring; such provisions may also hinder code re-use. Conformant licenses must allow for the possibility that (a) redistribution of the software will take place over non-Web channels that do not support click-wrapping of the download, and that (b) the covered code (or re-used portions of covered code) may run in a non-GUI environment that cannot support popup dialogues. The Open Source Definition was originally derived from the Debian Free Software Guidelines (DFSG). 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