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https://docs.suprsend.com/docs/getting-started#how-do-you-trigger-notifications | What is SuprSend? - SuprSend, Notification infrastructure for Product teams Skip to main content SuprSend, Notification infrastructure for Product teams home page Search... ⌘ K Community Trust Center Platform Status Postman Collection GETTING STARTED What is SuprSend? Quick Start Guide Best Practices Plan Your Integration Go-live checklist CORE CONCEPTS Templates Users Events Workflow Notification Categories Preferences Tenants Lists Broadcast Objects Translations DLT Guidelines Whatsapp Template Guidelines WORKFLOW BUILDER Design Workflow Node List Workflow Settings Trigger Workflow Validate Trigger Payload Tenant Workflows Notification Inbox Overview Multi Tabs React Javascript (Angular, Vuejs etc) React Native Flutter (Headless) PREFERENCE CENTRE Embedded Preference Centre Javascript Angular React VENDOR INTEGRATION GUIDE Overview Email Integrations SMS Integrations Android Push Whatsapp Integrations iOS Push Chat Integrations Vendor Fallback Tenant Vendor INTEGRATIONS Webhook Connectors MONITORING & DEBUGGING Logs Audit Logs Error Guides MANAGE YOUR ACCOUNT Authentication Methods Contact Us Get Started SuprSend, Notification infrastructure for Product teams home page Search... ⌘ K Ask AI Contact Us Get Started Get Started Search... Navigation GETTING STARTED What is SuprSend? Documentation API Reference Management API CLI Reference Developer Resources Changelog Documentation API Reference Management API CLI Reference Developer Resources Changelog GETTING STARTED What is SuprSend? OpenAI Open in ChatGPT Learn about SuprSend and how you can use it to power multi-channel product notifications. OpenAI Open in ChatGPT SuprSend has all the features set which enable you to send notifications in a reliable and scalable manner, as well as take care of end-user experience, thereby eliminating the need to build any notification service in-house. Benefits of using SuprSend as your notification stack: You do not have to do any vendor integrations for channels in your code. You can easily add/remove/prioritise vendors and channels from your SuprSend account, You can design powerful templates for all channels together and manage them from a single place, You can leverage powerful features to experiment fast with notifications as well as take care of end user experience without writing a single line of code. Introduction to Workflows Communications are made up of multiple components - trigger, logic, content, variables, target user, channels, vendors, etc. Typical communication solutions have one or more components intertwined with each other. SuprSend solves communications from a different and more powerful approach, which we call Workflows. At SuprSend, all the constituent components are decoupled from each other, making it modular in nature. The components can come from any source. All these components are configured as nodes in Workflows, where the processing happens for delivery and optimisation. This allows Workflows to handle any complexity possible in your communication use cases. How do you trigger notifications? You can trigger notifications in one of the two ways: Send events to SuprSend from your frontend clients (android app, website, etc) via SuprSend Client SDK, and create a Workflow on SuprSend platform to trigger notification on an event. Create workflow and trigger notification from your backend itself using an omni-channel HTTPS API method, or you can use our Backend SDK. All the other components (like vendors, templates, optimisation, scaling, etc.) are created and managed on SuprSend platform. You can check the ‘Core Concepts’ section that lists down the components used in the platform, so you can navigate the platform and use all the features with ease. SuprSend APIs You can try out SuprSend APIs from our Postman collection Was this page helpful? Yes No Suggest edits Raise issue Overview Start setting up your notifications with SuprSend by following quick start guides for one of the mentioned channels. Next ⌘ I x github linkedin youtube Powered by On this page Benefits of using SuprSend as your notification stack: Introduction to Workflows How do you trigger notifications? SuprSend APIs | 2026-01-13T08:49:46 |
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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 # soc Follow Hide Discussions related to Security Operations Centers, including tools, processes, and analyst life. Create Post Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu Splunk Basics Manoj Kumar Vemula Manoj Kumar Vemula Manoj Kumar Vemula Follow Dec 16 '25 Splunk Basics # splunk # soc # security # siem 1 reaction Comments Add Comment 4 min read SOC 1 vs SOC 2 vs SOC 3: What’s the Real Difference and Which One Do You Need? 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Yani A. Yani A. Follow Feb 19 '22 Single Responsibility vs Separation of Concerns # solid # oop # principles # soc 28 reactions Comments 1 comment 2 min read Security Information and Event Management (SIEM) using Microsoft Sentinel. 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https://tinyhack.com/2014/03/12/implementing-a-web-server-in-a-single-printf-call/#comments | Implementing a web server in a single printf() call – Tinyhack.com --> Skip to content Tinyhack.com A hacker does for love what others would not do for money. Implementing a web server in a single printf() call A guy just forwarded a joke that most of us will already know Jeff Dean Facts (also here and here ). Everytime I read that list, this part stands out: Jeff Dean once implemented a web server in a single printf() call. Other engineers added thousands of lines of explanatory comments but still don’t understand exactly how it works. Today that program is the front-end to Google Search. It is really possible to implement a web server using a single printf call, but I haven’t found anyone doing it. So this time after reading the list, I decided to implement it. So here is the code, a pure single printf call, without any extra variables or macros (don’t worry, I will explain how to this code works) #include <stdio.h> int main(int argc, char *argv[]) { printf("%*c%hn%*c%hn" "\xeb\x3d\x48\x54\x54\x50\x2f\x31\x2e\x30\x20\x32" "\x30\x30\x0d\x0a\x43\x6f\x6e\x74\x65\x6e\x74\x2d" "\x74\x79\x70\x65\x3a\x74\x65\x78\x74\x2f\x68\x74" "\x6d\x6c\x0d\x0a\x0d\x0a\x3c\x68\x31\x3e\x48\x65" "\x6c\x6c\x6f\x20\x57\x6f\x72\x6c\x64\x21\x3c\x2f" "\x68\x31\x3e\x4c\x8d\x2d\xbc\xff\xff\xff\x48\x89" "\xe3\x48\x83\xeb\x10\x48\x31\xc0\x50\x66\xb8\x1f" "\x90\xc1\xe0\x10\xb0\x02\x50\x31\xd2\x31\xf6\xff" "\xc6\x89\xf7\xff\xc7\x31\xc0\xb0\x29\x0f\x05\x49" "\x89\xc2\x31\xd2\xb2\x10\x48\x89\xde\x89\xc7\x31" "\xc0\xb0\x31\x0f\x05\x31\xc0\xb0\x05\x89\xc6\x4c" "\x89\xd0\x89\xc7\x31\xc0\xb0\x32\x0f\x05\x31\xd2" "\x31\xf6\x4c\x89\xd0\x89\xc7\x31\xc0\xb0\x2b\x0f" "\x05\x49\x89\xc4\x48\x31\xd2\xb2\x3d\x4c\x89\xee" "\x4c\x89\xe7\x31\xc0\xff\xc0\x0f\x05\x31\xf6\xff" "\xc6\xff\xc6\x4c\x89\xe7\x31\xc0\xb0\x30\x0f\x05" "\x4c\x89\xe7\x31\xc0\xb0\x03\x0f\x05\xeb\xc3", ((((unsigned long int)0x4005c8 + 12) >> 16) & 0xffff), 0, 0x00000000006007D8 + 2, (((unsigned long int)0x4005c8 + 12) & 0xffff)- ((((unsigned long int)0x4005c8 + 12) >> 16) & 0xffff), 0, 0x00000000006007D8 ); } This code only works on a Linux AMD64 bit system, with a particular compiler (gcc version 4.8.2 (Debian 4.8.2-16) ) And to compile it: gcc -g web1.c -O webserver As some of you may have guessed: I cheated by using a special format string . That code may not run on your machine because I have hardcoded two addresses. The following version is a little bit more user friendly (easier to change), but you are still going to need to change 2 values: FUNCTION_ADDR and DESTADDR which I will explain later: #include <stdio.h> #include <stdlib.h> #include <stdint.h> #define FUNCTION_ADDR ((uint64_t)0x4005c8 + 12) #define DESTADDR 0x00000000006007D8 #define a (FUNCTION_ADDR & 0xffff) #define b ((FUNCTION_ADDR >> 16) & 0xffff) int main(int argc, char *argv[]) { printf("%*c%hn%*c%hn" "\xeb\x3d\x48\x54\x54\x50\x2f\x31\x2e\x30\x20\x32" "\x30\x30\x0d\x0a\x43\x6f\x6e\x74\x65\x6e\x74\x2d" "\x74\x79\x70\x65\x3a\x74\x65\x78\x74\x2f\x68\x74" "\x6d\x6c\x0d\x0a\x0d\x0a\x3c\x68\x31\x3e\x48\x65" "\x6c\x6c\x6f\x20\x57\x6f\x72\x6c\x64\x21\x3c\x2f" "\x68\x31\x3e\x4c\x8d\x2d\xbc\xff\xff\xff\x48\x89" "\xe3\x48\x83\xeb\x10\x48\x31\xc0\x50\x66\xb8\x1f" "\x90\xc1\xe0\x10\xb0\x02\x50\x31\xd2\x31\xf6\xff" "\xc6\x89\xf7\xff\xc7\x31\xc0\xb0\x29\x0f\x05\x49" "\x89\xc2\x31\xd2\xb2\x10\x48\x89\xde\x89\xc7\x31" "\xc0\xb0\x31\x0f\x05\x31\xc0\xb0\x05\x89\xc6\x4c" "\x89\xd0\x89\xc7\x31\xc0\xb0\x32\x0f\x05\x31\xd2" "\x31\xf6\x4c\x89\xd0\x89\xc7\x31\xc0\xb0\x2b\x0f" "\x05\x49\x89\xc4\x48\x31\xd2\xb2\x3d\x4c\x89\xee" "\x4c\x89\xe7\x31\xc0\xff\xc0\x0f\x05\x31\xf6\xff" "\xc6\xff\xc6\x4c\x89\xe7\x31\xc0\xb0\x30\x0f\x05" "\x4c\x89\xe7\x31\xc0\xb0\x03\x0f\x05\xeb\xc3" , b, 0, DESTADDR + 2, a-b, 0, DESTADDR ); } I will explain how the code works through a series of short C codes. The first one is a code that will explain how that we can start another code without function call. See this simple code: #include <stdlib.h> #include <stdio.h> #define ADDR 0x00000000600720 void hello() { printf("hello world\n"); } int main(int argc, char *argv[]) { (*((unsigned long int*)ADDR))= (unsigned long int)hello; } You can compile it, but it many not run on your system. You need to do these steps: 1. Compile the code: gcc run-finalizer.c -o run-finalizer 2. Examine the address of fini_array objdump -h -j .fini_array run-finalizer And find the VMA of it: run-finalizer: file format elf64-x86-64 Sections: Idx Name Size VMA LMA File off Algn 18 .fini_array 00000008 0000000000600720 0000000000600720 00000720 2**3 CONTENTS, ALLOC, LOAD, DATA Note that you need a recent GCC to do this, older version of gcc uses different mechanism of storing finalizers. 3. Change the value of ADDR on the code to the correct address 4. Compile the code again 5. Run it and now you will see “hello world” printed to your screen. How does this work exactly?: According to Chapter 11 of Linux Standard Base Core Specification 3.1 .fini_array This section holds an array of function pointers that contributes to a single termination array for the executable or shared object containing the section. We are overwriting the array so that our hello function is called instead of the default handler. If you are trying to compile the webserver code, the value of ADDR is obtained the same way (using objdump). Ok, now we know how to execute a function by overriding a certain address, we need to know how we can overwrite an address using printf . You can find many tutorials on how to exploit format string bugs, but I will try give a short explanation. The printf function has this feature that enables us to know how many characters has been printed using the “%n” format: #include <stdio.h> int main(){ int count; printf("AB%n", &count); printf("\n%d characters printed\n", count); } You will see that the output is: AB 2 characters printed Of course we can put any address to the count pointer to overwrite that address. But to overide an address with a large value we need to print a large amount of text. Fortunately there is another format string “%hn” that works on short instead of int. We can overwrite the value 2 bytes at a time to form the 4 byte value that we want. Lets try to use two printf calls to put a¡ value that we want (in this case the pointer to function “hello”) to the fini_array: #include <stdio.h> #include <stdlib.h> #include <stdint.h> #define FUNCTION_ADDR ((uint64_t)hello) #define DESTADDR 0x0000000000600948 void hello() { printf("\n\n\n\nhello world\n\n"); } int main(int argc, char *argv[]) { short a= FUNCTION_ADDR & 0xffff; short b = (FUNCTION_ADDR >> 16) & 0xffff; printf("a = %04x b = %04x\n", a, b) uint64_t *p = (uint64_t*)DESTADDR; printf("before: %08lx\n", *p); printf("%*c%hn", b, 0, DESTADDR + 2 ); printf("after1: %08lx\n", *p); printf("%*c%hn", a, 0, DESTADDR); printf("after2: %08lx\n", *p); return 0; } The important lines are: short a= FUNCTION_ADDR & 0xffff; short b = (FUNCTION_ADDR >> 16) & 0xffff; printf("%*c%hn", b, 0, DESTADDR + 2 ); printf("%*c%hn", a, 0, DESTADDR); The a and b are just halves of the function address, we can construct a string of length a and b to be given to printf, but I chose to use the “%*” formatting which will control the length of the output through parameter. For example, this code: printf("%*c", 10, 'A'); Will print 9 spaces followed by A, so in total, 10 characters will be printed. If we want to use just one printf, we need to take account that b bytes have been printed, and we need to print another b-a bytes (the counter is accumulative). printf("%*c%hn%*c%hn", b, 0, DESTADDR + 2, b-a, 0, DESTADDR ); Currently we are using the “hello” function to call, but we can call any function (or any address). I have written a shellcode that acts as a web server that just prints “Hello world”. This is the shell code that I made: unsigned char hello[] = "\xeb\x3d\x48\x54\x54\x50\x2f\x31\x2e\x30\x20\x32" "\x30\x30\x0d\x0a\x43\x6f\x6e\x74\x65\x6e\x74\x2d" "\x74\x79\x70\x65\x3a\x74\x65\x78\x74\x2f\x68\x74" "\x6d\x6c\x0d\x0a\x0d\x0a\x3c\x68\x31\x3e\x48\x65" "\x6c\x6c\x6f\x20\x57\x6f\x72\x6c\x64\x21\x3c\x2f" "\x68\x31\x3e\x4c\x8d\x2d\xbc\xff\xff\xff\x48\x89" "\xe3\x48\x83\xeb\x10\x48\x31\xc0\x50\x66\xb8\x1f" "\x90\xc1\xe0\x10\xb0\x02\x50\x31\xd2\x31\xf6\xff" "\xc6\x89\xf7\xff\xc7\x31\xc0\xb0\x29\x0f\x05\x49" "\x89\xc2\x31\xd2\xb2\x10\x48\x89\xde\x89\xc7\x31" "\xc0\xb0\x31\x0f\x05\x31\xc0\xb0\x05\x89\xc6\x4c" "\x89\xd0\x89\xc7\x31\xc0\xb0\x32\x0f\x05\x31\xd2" "\x31\xf6\x4c\x89\xd0\x89\xc7\x31\xc0\xb0\x2b\x0f" "\x05\x49\x89\xc4\x48\x31\xd2\xb2\x3d\x4c\x89\xee" "\x4c\x89\xe7\x31\xc0\xff\xc0\x0f\x05\x31\xf6\xff" "\xc6\xff\xc6\x4c\x89\xe7\x31\xc0\xb0\x30\x0f\x05" "\x4c\x89\xe7\x31\xc0\xb0\x03\x0f\x05\xeb\xc3"; If we remove the function hello and insert that shell code, that code will be called. That code is just a string, so we can append it to the “%*c%hn%*c%hn” format string. This string is unnamed, so we will need to find the address after we compile it. To obtain the address, we need to compile the code, then disassemble it: objdump -d webserver 00000000004004fd <main>: 4004fd: 55 push %rbp 4004fe: 48 89 e5 mov %rsp,%rbp 400501: 48 83 ec 20 sub $0x20,%rsp 400505: 89 7d fc mov %edi,-0x4(%rbp) 400508: 48 89 75 f0 mov %rsi,-0x10(%rbp) 40050c: c7 04 24 d8 07 60 00 movl $0x6007d8,(%rsp) 400513: 41 b9 00 00 00 00 mov $0x0,%r9d 400519: 41 b8 94 05 00 00 mov $0x594,%r8d 40051f: b9 da 07 60 00 mov $0x6007da,%ecx 400524: ba 00 00 00 00 mov $0x0,%edx 400529: be 40 00 00 00 mov $0x40,%esi 40052e: bf c8 05 40 00 mov $0x4005c8,%edi 400533: b8 00 00 00 00 mov $0x0,%eax 400538: e8 a3 fe ff ff callq 4003e0 <printf@plt> 40053d: c9 leaveq 40053e: c3 retq 40053f: 90 nop We only need to care about this line: mov $0x4005c8,%edi That is the address that we need in: #define FUNCTION_ADDR ((uint64_t)0x4005c8 + 12) The +12 is needed because our shell code starts after the string “%*c%hn%*c%hn” which is 12 characters long. If you are curious about the shell code, it was created from the following C code. #include<stdio.h> #include<string.h> #include<stdlib.h> #include<unistd.h> #include<sys/types.h> #include<sys/stat.h> #include<sys/socket.h> #include<arpa/inet.h> #include<netdb.h> #include<signal.h> #include<fcntl.h> int main(int argc, char *argv[]) { int sockfd = socket(AF_INET, SOCK_STREAM, 0); struct sockaddr_in serv_addr; bzero((char *)&serv_addr, sizeof(serv_addr)); serv_addr.sin_family = AF_INET; serv_addr.sin_addr.s_addr = INADDR_ANY; serv_addr.sin_port = htons(8080); bind(sockfd, (struct sockaddr *)&serv_addr, sizeof(serv_addr)); listen(sockfd, 5); while (1) { int cfd = accept(sockfd, 0, 0); char *s = "HTTP/1.0 200\r\nContent-type:text/html\r\n\r\n<h1>Hello world!</h1>"; if (fork()==0) { write(cfd, s, strlen(s)); shutdown(cfd, SHUT_RDWR); close(cfd); } } return 0; } I have done an extra effort (although it is not really necessary in this case) to remove all NUL character from the shell code (since I couldn’t find one for X86-64 in the Shellcodes database ). Jeff Dean once implemented a web server in a single printf() call. Other engineers added thousands of lines of explanatory comments but still don’t understand exactly how it works. Today that program is the front-end to Google Search . It is left as an exercise for the reader to scale the web server to able to handle Google search load. Source codes for this post is available at https://github.com/yohanes/printf-webserver For people who thinks that this is useless: yes it is useless. I just happen to like this challenge, and it has refreshed my memory and knowledge for the following topics: shell code writing (haven’t done this in years), AMD64 assembly (calling convention, preserved registers, etc), syscalls, objdump, fini_array (last time I checked, gcc still used .dtors), printf format exploiting, gdb tricks (like writing memory block to file), and low level socket code (I have been using boost’s for the past few years). Update : Ubuntu adds a security feature that provides a read-only relocation table area in the final ELF. To be able to run the examples in ubuntu, add this in the command line when compiling -Wl,-z,norelro e.g: gcc -Wl,-z,norelro test.c Author admin Posted on March 12, 2014 April 28, 2017 Categories hacks 18 thoughts on “Implementing a web server in a single printf() call” dodi says: March 12, 2014 at 2:04 pm eh buset, serius nih lu ? 🙂 Reply priyo says: March 13, 2014 at 5:07 am scroll up… scroll down… scroll up… scroll down… 100x *gagal paham* Reply terminalcommand says: March 13, 2014 at 5:19 am Thank you! Very interesting article. I also didn’t know about the one line webserver at google. Although this is a hard topic, you’ve made a great work simplifying it. Reply Basun says: March 13, 2014 at 10:02 am The one line webserver bit is a joke about Jeff Dean, who works at Google. Its not real. 🙂 Reply Cees Timmerman says: April 20, 2016 at 4:12 pm There are real webserver oneliners: https://gist.github.com/willurd/5720255 Reply anonim says: March 13, 2014 at 5:29 am Diskusinya di https://news.ycombinator.com/item?id=7389623 Reply Neil says: March 13, 2014 at 12:38 pm Shouldn’t there be an exit() somewhere in the fork==0 branch? Otherwise every time there is a request the new child process will become a server too and start accepting requests, right? I think the parent leaks its copy of the file descriptor too. Maybe the fork is a bit redundant. I don’t think the write or close will block with such a small amount of data. Cool post though! I’m not really sure why I’m nitpicking in the shell code. Sorry. Reply admin says: March 14, 2014 at 1:58 am Ah yes, there is an exit from the loop on the assembly code (myhttp.s) but it got removed from http.c when I removed the comment and debug code. And you are also right about the fork, it is unnecessary in this case. At first I was going to write the HTTP headers and then exec some external command. I changed my mind and didn’t bother deleting the fork call. Reply Kyle Ross says: March 13, 2014 at 11:02 pm This is really interesting, but I’m having trouble following whats actually happening. Could you explain how you reduced that C code with includes and methods into a string containing hex codes and how that is turned back into some sort of executable code? Thanks Reply admin says: March 14, 2014 at 2:01 am I think it is beyond the scope of this article to explain about shell code writing. There are many books and tutorials that you can read (just search for “buffer overflow” or “shell code writing”). Reply TTK Ciar says: March 14, 2014 at 1:05 am Alternatively: $ perl -Mojo -E ‘a({inline => “%= `uptime`”})->start’ daemon & Server available at http://127.0.0.1:3000 . $ lynx -dump -nolist http://127.0.0.1:3000/ 17:57:56 up 66 days, 6:45, 108 users, load average: 0.10, 0.12, 0.07 though, perl by definition is cheating. Reply Evan Danaher says: March 14, 2014 at 2:54 pm I’m not sure why you used finalizers instead of just changing the return address on the stack; this may be the first time I’ve ever said this, but stack smashing is much more portable. I’ve made a variant that I’d expect to work on any gcc 4.4-4.7 on x86_64 Linux, and have some ideas which, if they work out, may make it actually “portable” to any x86/x86_64 Unix running a reasonable compiler. https://github.com/edanaher/printf-webserver Reply admin says: March 17, 2014 at 3:02 pm Yes using the stack is also possible, but on most modern system, GCC is compiled with stack protection turned on (and needs to be disabled using -fno-stack-protector). Reply Pingback: Implementing a web server in a single printf() call « adafruit industries blog Itzik Kotler says: March 15, 2014 at 4:35 pm Pretty neat. I did something similar (all though simpler) back in the days. See: http://www.exploit-db.com/papers/13233/ Reply Pingback: Saving the world, one cpu cycle at a time | Dav's bit o the web programath says: April 22, 2014 at 1:18 pm printf(“%*c%hn%*c%hn”, b, 0, DESTADDR + 2, b-a, 0, DESTADDR ); ————————————————— i think the fourth parameter should be ‘a-b’, not ‘b-a’, because a == b + (a – b) Reply Pingback: New top story on Hacker News: Implementing a web server in a single printf call (2014) – Latest news Leave a Reply Cancel reply Your email address will not be published. Required fields are marked * Comment * Name * Email * Website Save my name, email, and website in this browser for the next time I comment. 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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 Aviral Srivastava Posted on Oct 1, 2025 Using Podman as a Docker alternative # docker # containers # security # devops Podman: A Docker Alternative for Container Management Introduction Containers have revolutionized software development and deployment, offering portability, isolation, and resource efficiency. Docker has long been the dominant player in the containerization landscape, but alternatives have emerged, providing different approaches and addressing specific concerns. Podman, short for "POD MANager," is a popular, open-source container engine that offers a compelling alternative to Docker. Podman distinguishes itself by being daemonless and rootless by default, addressing some of the security concerns associated with Docker's daemon architecture. This article provides an in-depth look at Podman, covering its prerequisites, advantages, disadvantages, key features, and how it compares to Docker, empowering you to make informed decisions about your containerization strategy. Prerequisites Before diving into Podman, ensure you have the following prerequisites: Operating System: Podman primarily targets Linux-based systems, and is included in major distributions such as Red Hat Enterprise Linux (RHEL), Fedora, CentOS, Ubuntu and Debian. MacOS is also available as a client. System Requirements: Podman is lightweight and has minimal resource requirements. Any modern Linux system capable of running containers should suffice. Installation: Installation methods vary depending on your Linux distribution. Here's how to install Podman on some common distributions: Fedora/CentOS/RHEL: sudo dnf install podman Ubuntu/Debian: sudo apt update sudo apt install podman Root access (initially): While Podman aims for rootless execution, installation might require root privileges for installing the package and configuring system settings. Advantages of Podman Podman offers several advantages over Docker: Daemonless Architecture: Unlike Docker, Podman doesn't rely on a central daemon to manage containers. Instead, containers are launched as child processes of the user, eliminating the single point of failure and potential security risks associated with a privileged daemon. This daemonless design improves stability and security. Rootless by Default: Podman prioritizes security by enabling rootless container execution by default. This means containers run under the user's context without requiring root privileges, significantly reducing the attack surface. Rootless containers limit the potential damage an attacker can inflict if they compromise a container. Enhanced Security: The combination of a daemonless architecture and rootless capabilities strengthens security posture. Without a central daemon, there's no single privileged process to target. Rootless containers prevent privilege escalation within the container, further limiting potential exploits. OCI Compliance: Podman is compliant with the Open Container Initiative (OCI) standards for container images and runtimes. This ensures interoperability with other OCI-compliant tools and technologies, preventing vendor lock-in and promoting portability. Integration with Systemd: Podman seamlessly integrates with systemd, allowing you to manage containers as systemd services. This provides a robust and familiar mechanism for starting, stopping, restarting, and monitoring containers. Familiar CLI: Podman offers a command-line interface (CLI) that is mostly compatible with Docker's CLI. This makes it easier for Docker users to transition to Podman with minimal learning curve. Most Docker commands have a direct equivalent in Podman. Pod Management: Podman excels at managing pods, which are groups of containers sharing network and storage resources, enabling multi-container applications with enhanced isolation. Disadvantages of Podman While Podman has numerous advantages, it's important to acknowledge its limitations: GUI Support: Docker has extensive GUI tools available for visual container management. Podman lacks the same level of mature GUI support, although projects like Cockpit are improving the graphical management experience. Remote API: Podman's remote API is not as mature or comprehensive as Docker's. This can limit integration with some existing tools and workflows that rely heavily on Docker's API. While podman system service provides a REST API, its adoption is not yet widespread. Windows and MacOS Support: While Podman has excellent support for Linux, its support for Windows and MacOS is less mature and typically relies on virtualization or remote access to a Linux environment. Docker has native support for both Windows and MacOS. Network Driver Differences: Docker uses a different networking driver (usually bridge ) than Podman (default is CNI ). This can impact how containers are configured and communicate within a network. It can cause compatibility problems when migrating docker-compose files. Key Features of Podman Podman offers a range of features that make it a compelling containerization platform: Image Management: Podman can pull, build, tag, push, and manage container images from various registries like Docker Hub, Quay.io, and private registries. podman pull ubuntu:latest podman build -t my-app . podman push my-app Container Lifecycle Management: Podman provides commands for creating, starting, stopping, restarting, and deleting containers. podman create --name my-container ubuntu:latest podman start my-container podman stop my-container podman rm my-container Pod Management: Podman allows you to create and manage pods, grouping containers together with shared resources. podman pod create --name my-pod podman run --pod my-pod -d --name container1 ubuntu:latest sleep infinity podman run --pod my-pod -d --name container2 nginx podman pod ps Networking: Podman integrates with CNI (Container Network Interface) plugins for configuring container networking. Volume Management: Podman supports persistent volumes for storing data outside of containers. podman volume create my-volume podman run -v my-volume:/data ubuntu:latest Rootless Container Execution: Podman allows containers to be run without root privileges, enhancing security. podman run --user $( id -u ) : $( id -g ) ubuntu:latest Systemd Integration: Podman can generate systemd unit files for managing containers as system services. podman generate systemd --new --files my-container sudo mv container-my-container.service /etc/systemd/system/ sudo systemctl daemon-reload sudo systemctl enable container-my-container.service sudo systemctl start container-my-container.service Docker Compose Compatibility: Podman can use podman-compose to manage multi-container applications defined using Docker Compose files (although some compatibility issues might arise depending on the file). Requires installation of pip install podman-compose . podman-compose up -d Podman vs. Docker: A Comparison Feature Podman Docker Architecture Daemonless Daemon-based Security Rootless by default Requires root privileges for the daemon CLI Mostly Docker-compatible Standard CLI OCI Compliance Yes Yes Systemd Support Native Requires additional configuration GUI Support Limited Mature and extensive Remote API Less mature Well-established Windows/MacOS Via VM/Remote Native Compose Support podman-compose (some compatibility issues) Native via docker-compose Conclusion Podman presents a compelling alternative to Docker, particularly for security-conscious environments. Its daemonless architecture, rootless execution, and integration with systemd offer significant advantages. While it may lack some of Docker's mature features, like extensive GUI support, Podman's focus on security and OCI compliance makes it a valuable tool in the containerization ecosystem. The choice between Podman and Docker depends on your specific needs and priorities. If security and minimal privilege are paramount, Podman is an excellent choice. If you require native Windows/MacOS support, extensive GUI tools, and a more mature remote API, Docker may be a better fit. In many cases, organizations can even use both tools, leveraging Docker for development and Podman for secure production deployments. As Podman continues to mature, it is likely to gain even wider adoption as a robust and secure container management solution. 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 Aviral Srivastava Follow Hi! I am a student currently pursuing my Undergraduate degree in Computer Science and Engineering in India. 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https://news.ycombinator.com/item?id=7389623#7390232 | Implementing a web server in a single printf() call | Hacker News Hacker News new | past | comments | ask | show | jobs | submit login Implementing a web server in a single printf() call ( tinyhack.com ) 181 points by pdq on March 13, 2014 | hide | past | favorite | 39 comments goldenkey on March 13, 2014 | next [–] It's called Shellcode. These kids these days with their exclusive Ruby on Rails knowledge. "Shell what? Oh you mean that new band that you probably never heard of?" joebo on March 13, 2014 | parent | next [–] I don't see ruby mentioned anywhere and the article mentions shellcode. I thought it was informative and interesting and I am well aware of shellcode. Your comment is unnecessarily condescending and may discourage posts like this. pessimizer on March 13, 2014 | root | parent | next [–] >may discourage posts like this. That may be goldenkey's goal, and shouldn't be discouraged either. Someone's opinion that something is awful and doesn't belong here is just as legitimate as your opinion that something is informative and interesting. Your comment is unnecessarily condescending and may discourage comments like this. scott_s on March 13, 2014 | root | parent | next [–] I disagree. Most opinions that state "I already knew this, and you should too" are banal and do not lead to interesting discussion. And the moderation system of this site is set up to promote interesting discussion. goldenkey on March 20, 2014 | root | parent | next [–] True but my comment was more directed at the disenfranchising nature of 'using printf.' Printf has nothing to do with shellcode, and is just a silent mockdrop of BS to entice those who would probably click onto the next article of a real explanation of shellcode were had. I prefer frankness to BS even if the frank explanation intimidates most. ethikal on March 13, 2014 | parent | prev | next [–] "Machine code? What's that?" negamax on March 13, 2014 | root | parent | next [–] "Javascript is assembly". ROFL! austinz on March 13, 2014 | prev | next [–] If you want to read more about shellcode/C vulnerabilities you can check out the Phrack and other links at Stanford's CS155 web site: https://courseware.stanford.edu/pg/assignments/view/280907/b... The Buffer Overflow #1 and #2 projects might also be worth checking out. You can download the project description, starter code, and VM image, and see if you can write code to get the root shell. voltagex_ on March 13, 2014 | parent | next [–] The requested URL /cs155/hw_and_proj/pp1/boxes-2.3.tar.bz2 was not found on this server. From https://crypto.stanford.edu/cs155/hw_and_proj/pp1/boxes-2.3.... which is the VM image link. Anyone got any contacts at Stanford? austinz on March 13, 2014 | root | parent | next [–] If you change https to http, it works for me (and I'm not logged in or privileged in any way). j_m_b on March 13, 2014 | parent | prev | next [–] Oldie but relevant: http://www.phrack.org/issues.html?issue=49&id=14#article DanielRibeiro on March 13, 2014 | parent | prev | next [–] Thanks for the course info! Quick link for those that missed how to use printf to call arbitrary functions: http://stackoverflow.com/a/7459758/113507 coldpie on March 13, 2014 | parent | prev | next [–] Along the same lines, I would also recommend "Hacking" by Jon Erickson. nostrademons on March 13, 2014 | prev | next [–] I did something like this in Haskell a few years ago, largely as an entertaining practical joke: http://pastebin.com/6kfwTsB0 sedev on March 13, 2014 | parent | next [–] I admire that feat at the same time as I have an overwhelming urge to take a cheap shot about which Haskell projects are entertaining practical jokes. JetSpiegel on March 13, 2014 | parent | prev | next [–] Minor lacerations detected. userbinator on March 13, 2014 | prev | next [–] When I read the title I thought it was going to be a printf("HTTP/1.1 200 OK..."); sort of thing, but I was pleasantly surprised. zobzu on March 13, 2014 | prev | next [–] if you're going to insert a shell code into printf, then well... you can implement anything in printf... or in memcpy.. or in strcat.. or whatever really. yalue on March 13, 2014 | parent | next [–] Heck, why not just title it "a web server with no library function calls" and call an array of bytes as a function? Then everybody would be able to see what it really is, which is an unremarkable shellcode embedded directly in a C program. I feel like the "printf" was only included so that people would have something to recognize in the title. anon4 on March 14, 2014 | root | parent | next [–] By that logic you could just execve httpd with shellcode. Or ruby. Or a ruby program that generates a perl script that compiles a Prolog program to shellcode that looks like it prints hello world, but actually does execve httpd. kang on March 13, 2014 | parent | prev | next [–] Yes, he mentions that. kentuckyduck on March 13, 2014 | prev | next [–] I got segmentation fault trying out his hello world example (after changing VMA address). Then again, isn't that the supposed behavior? Not every memory page can be written to, if I remember correctly. evandrix on March 13, 2014 | parent | next [–] Yes, segfault for me too after i changed ADDR preprocessor directive to the VMA address from objdump, as the instruction says. I'm on Ubuntu Linux 13.10 x64. yohanes on March 13, 2014 | root | parent | next [–] Ubuntu adds a security feature that provides a read-only relocation table area in the final ELF. To be able to run the examples in ubuntu, add this in the command line when compiling -Wl,-z,norelro e.g: gcc -Wl,-z,norelro test.c evandrix on March 13, 2014 | root | parent | next [–] ok, now it compiles, thanks for that. However, I'm getting an incomplete response "<h1>hello world</h1" without the trailing closing angled bracket. And when I try to run final.c after setting the FUNCTION_ADDR and ADDR as per your tutorial, I get some stray HTTP/1.0 200 and Content-type text/html being displayed on stdout as I start the program final.c (compiled to a.out by default) yohanes on March 13, 2014 | root | parent | next [–] Ah, you have found a bug in my code (I made an error in computing the string length, and didn't notice it because it displayed fine on Chrome). I have fixed my code in git and the blog post. As for the stray output displayed on the stdout: it is to be expected. The %n format outputs the numbers of character that is written by printf, so it must have written something to the stdout. evandrix on March 13, 2014 | root | parent | next [–] Ah! that explains so much (and also why i've wasted a whole hour figuring out why what I observed was happening) I'm a CLI curl guy, rather than relying on these browsers which randomly would add a 0x0d 0x0a to my form submissions, for example. I also noticed that compiling (assembling-linking) the .S to execute it would not print anything (just hang there like a normal webserver), but I was getting stuff written to stdout with the final.c/webserver.c version using its shellcode. mvirkkunen on March 13, 2014 | root | parent | next [–] Did you also post this reply using curl? Morgawr on March 13, 2014 | prev | next [–] Really nice, it's so weird that format strings support %n, it's such a massive security vulnerability that I don't really know what was going on in the mind of the guy that decided to implement this. But alas, it's always fun to see. Here's an excellent article on format string vulnerabilities, an amazing read: http://crypto.stanford.edu/cs155/papers/formatstring-1.2.pdf userbinator on March 13, 2014 | parent | next [–] It's only a vulnerability if the user can control the format string. Otherwise it's a useful way of getting the lengths of things; but ironically it's not paying attention to lengths that also causes buffer overflow vulnerabilities... psionski on March 13, 2014 | parent | prev | next [–] C was designed way before security was a concern. If somebody exploited your program, you could just slap them because they'd be sitting at a terminal in the same room with you - no need for fancy ASLR or controlling how many characters you write to a buffer when physical violence was a viable option :) pjmlp on March 13, 2014 | root | parent | next [–] Except security was already a concern in other operating systems that had Lisp, Cedar, Modula-2, Algol as system languages among others. C designers just decided to ignored it. kjs3 on March 13, 2014 | root | parent | prev | next [–] This isn't even remotely true. Computer security was a concern and an area of study long before C/Unix showed up. Unix (and by extension C) descended directly from the Multics project, which from its start in 1964 made security a central priority. Kernighan and Ritche were important members of the Multics project. Further, the idea that everyone who used the computers of that era were "in the same room" is also patently absurd. psionski on March 14, 2014 | root | parent | next [–] I like my fantasy about how things were back then better, thankyouverymuch. At least this way I can believe they didn't unleash the flood of pwnage on the world while knowing better. kang on March 13, 2014 | prev | next [–] I wish for a forum/site with links only like these! Pure code hacking. kreeben on March 13, 2014 | parent | next [–] Seems to be available: purecodehacking.com. Do it! DateK on March 13, 2014 | prev [–] maintenance nightmare tonyarkles on March 13, 2014 | parent | next [–] Understatement of the year! chii on March 13, 2014 | parent | prev [–] it doesn't need maintenance - it works as advertised! If a client asks for a change, write a new program! Guidelines | FAQ | Lists | API | Security | Legal | Apply to YC | Contact Search: | 2026-01-13T08:49:46 |
https://docs.suprsend.com/reference/cli-schema-generate-types | Generate Types - SuprSend, Notification infrastructure for Product teams Skip to main content SuprSend, Notification infrastructure for Product teams home page Search... ⌘ K Community Trust Center Platform Status Postman Collection Versioning Versioning and Support Policy CLI Changelog Getting Started with CLI CLI Overview BETA Quickstart Installation Authentication Enable Autocompletion Global Flags Profile Commands and Flags Add Profile Use Profile List Profile Modify Profile Remove Profile Sync Sync Assets Workflow Commands and Flags List Workflows Pull Workflows Push Workflows Enable Workflow Disable Workflow Schema Commands and Flags List Schemas Pull Schemas Push Schemas Commit Schema Generate Types Event Commands and Flags List Events Pull Events Push Events Preference Category Commands and Flags List Categories Pull Categories Push Categories Commit Categories List Category Translations Pull Category Translations Push Category Translations Translation Commands and Flags List Translations Pull Translations Push Translations Commit Translations Contact Us Get Started SuprSend, Notification infrastructure for Product teams home page Search... ⌘ K Ask AI Contact Us Get Started Get Started Search... Navigation Schema Generate Types Documentation API Reference Management API CLI Reference Developer Resources Changelog Documentation API Reference Management API CLI Reference Developer Resources Changelog Schema Generate Types OpenAI Open in ChatGPT Generate type definitions from all enabled SuprSend schemas in a workspace. OpenAI Open in ChatGPT The generate-types command creates type definition files in a given language for all enabled SuprSend schemas from a specified workspace. Syntax Copy Ask AI suprsend generate-types < languag e > --output-file < output-fil e > [flags] Arguments: Argument Description <language> The programming language to generate types for. Supported languages - typescript , go , python , java , kotlin , swift , dart --output-file Path to the output file where types will be generated (required) Flags Flag Description Default -h, --help Show help for the command – --output-file string Output file for generated types – --build-flags string Flags to generate types in a certain way (e.g. --zod for TypeScript) – --mode string Mode of schema to fetch (draft, live) live --workspace string Workspace to get schemas from staging Example python typescript go java kotlin swift dart Copy Ask AI # Generate TypeScript types from all enabled schemas in staging workspace suprsend generate-types python --output-file suprsend-types.py # Generate Python types with Pydantic in production workspace suprsend generate-types python --pydantic --workspace production Was this page helpful? Yes No Suggest edits Raise issue Previous Commands and Flags Reference for managing events in the SuprSend CLI. Next ⌘ I x github linkedin youtube Powered by On this page Syntax Flags Example | 2026-01-13T08:49:46 |
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https://docs.suprsend.com/reference/create-update-category | Create or Update Preference Category - SuprSend, Notification infrastructure for Product teams Skip to main content SuprSend, Notification infrastructure for Product teams home page Search... ⌘ K Community Trust Center Platform Status Postman Collection API Reference Overview Authentication Errors WORKFLOWS POST Create/Update Workflow PATCH Commit Workflow GET Get Workflow GET List Workflows PATCH Enable/Disable Workflow DEL Delete Workflow SCHEMAS POST Create/Update Schema PATCH Commit Schema GET List Schemas GET Get Schema EVENTS POST Create Event PATCH Update Event GET List Events GET Get Event Details GET Get Linked Workflows PATCH Delink Schema from Event CATEGORIES GET Get Category POST Create/Update Category PATCH Commit Category GET List Translation GET Get Translation POST Add Translation DEL Delete Translation TRANSLATIONS POST Add Translation PATCH Commit Translation GET Get Translation GET List Translations GET Get Translation History POST Rollback Translation DEL Delete Translation Contact Us Get Started SuprSend, Notification infrastructure for Product teams home page Search... ⌘ K Ask AI Contact Us Get Started Get Started Search... Navigation CATEGORIES Create or Update Preference Category Documentation API Reference Management API CLI Reference Developer Resources Changelog Documentation API Reference Management API CLI Reference Developer Resources Changelog CATEGORIES Create or Update Preference Category OpenAI Open in ChatGPT Use this API to set preference categories to be used in workflow or to show on user preference page. OpenAI Open in ChatGPT POST / v1 / {workspace} / preference_category Try it Create/Update Category cURL Copy Ask AI curl -X POST "https://management-api.suprsend.com/v1/{workspace}/preference_category/?commit=false" \ --header "Authorization: ServiceToken {token}" \ --header "Content-Type: application/json" \ --data '{ "root_categories": [ { "root_category": "system" }, { "root_category": "transactional", "sections": [ { "name": "Task Updates", "categories": [ { "category": "tagged-to-me", "name": "Tagged to Me", "description": "Status Update or mentions on tasks assigned by me or tagged to me", "default_preference": "opt_in" } ] } ] }, { "root_category": "promotional", "sections": [ { "name": "Product Updates", "categories": [ { "category": "newsletter", "name": "Newsletter", "default_preference": "opt_out" } ] } ] } ] }' 200 401 404 Copy Ask AI { "$schema" : "https://schema.suprsend.com/preference_category/v1/schema.json" , "root_categories" : [ { "root_category" : "system" , "sections" : [] }, { "root_category" : "transactional" , "sections" : [ { "name" : "Task Updates" , "description" : null , "tags" : null , "categories" : [ { "category" : "tagged-to-me" , "name" : "Tagged to Me" , "description" : "Status Update or mentions on tasks assigned by me or tagged to me" , "default_preference" : "opt_in" , "default_mandatory_channels" : null , "default_opt_in_channels" : null , "tags" : null } ] } ] }, { "root_category" : "promotional" , "sections" : [ { "name" : "Product Updates" , "description" : null , "tags" : null , "categories" : [ { "category" : "newsletter" , "name" : "Newsletter" , "description" : null , "default_preference" : "opt_out" , "default_mandatory_channels" : null , "default_opt_in_channels" : null , "tags" : null } ] } ] } ], "version_no" : 3 , "status" : "draft" , "commit_message" : null , "committed_at" : null , "validation_result" : { "is_valid" : true } } ⚠️ This API call will override existing categories with whatever is passed in the request body. Recommended approach is to first fetch the current categories using GET method , modify the response as needed, and then send it back in the request body. You can read more about preference categories here . Note: Changes will only be pushed if "validation_result":{"is_valid":true} in the response. General reasons for validation failure are: There are multiple categories with the same slug Some subcategories have been deleted in this version, on which active workflows are configured You’ve not passed all three categories in the request body - system, transactional, promotional Authorizations ServiceToken <token> string header required You can get Service Token from SuprSend dashboard -> Account Settings -> Service Tokens section. Path Parameters workspace string required Workspace slug (staging, production, etc.) Query Parameters commit boolean Whether to commit changes immediately. Set to true to make changes live, false to save as draft. commit_message string Optional commit message describing the changes made. Required when commit=true. Body application/json root_categories object[] Array of root preference categories. Include all three root categories (system, transactional, promotional) even if empty. Show child attributes Response 200 application/json Successfully created/updated preference category $schema string JSON schema reference for preference category structure Example : "https://schema.suprsend.com/preference_category/v1/schema.json" root_categories object[] Array of root preference categories Show child attributes status enum<string> Current status of the preference category Available options : draft , active Example : "draft" version_no integer Version number of the preference category Example : 3 commit_message string Commit message describing the changes that were made Example : null committed_at string<date-time> Timestamp when the changes were committed Example : null validation_result object Result of validating the preference category Show child attributes Was this page helpful? Yes No Suggest edits Raise issue Previous Commit Category Commit draft changes to the preference category to make them live Next ⌘ I x github linkedin youtube Powered by Create/Update Category cURL Copy Ask AI curl -X POST "https://management-api.suprsend.com/v1/{workspace}/preference_category/?commit=false" \ --header "Authorization: ServiceToken {token}" \ --header "Content-Type: application/json" \ --data '{ "root_categories": [ { "root_category": "system" }, { "root_category": "transactional", "sections": [ { "name": "Task Updates", "categories": [ { "category": "tagged-to-me", "name": "Tagged to Me", "description": "Status Update or mentions on tasks assigned by me or tagged to me", "default_preference": "opt_in" } ] } ] }, { "root_category": "promotional", "sections": [ { "name": "Product Updates", "categories": [ { "category": "newsletter", "name": "Newsletter", "default_preference": "opt_out" } ] } ] } ] }' 200 401 404 Copy Ask AI { "$schema" : "https://schema.suprsend.com/preference_category/v1/schema.json" , "root_categories" : [ { "root_category" : "system" , "sections" : [] }, { "root_category" : "transactional" , "sections" : [ { "name" : "Task Updates" , "description" : null , "tags" : null , "categories" : [ { "category" : "tagged-to-me" , "name" : "Tagged to Me" , "description" : "Status Update or mentions on tasks assigned by me or tagged to me" , "default_preference" : "opt_in" , "default_mandatory_channels" : null , "default_opt_in_channels" : null , "tags" : null } ] } ] }, { "root_category" : "promotional" , "sections" : [ { "name" : "Product Updates" , "description" : null , "tags" : null , "categories" : [ { "category" : "newsletter" , "name" : "Newsletter" , "description" : null , "default_preference" : "opt_out" , "default_mandatory_channels" : null , "default_opt_in_channels" : null , "tags" : null } ] } ] } ], "version_no" : 3 , "status" : "draft" , "commit_message" : null , "committed_at" : null , "validation_result" : { "is_valid" : true } } | 2026-01-13T08:49:46 |
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https://opensource.org/blog/the-open-source-community-and-u-s-public-policy | The Open Source Community and U.S. Public Policy – 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 October 30, 2025 News Katie Steen-James The Open Source Community and U.S. Public Policy When I joined the Open Source Initiative (OSI) in February, the organization had been engaging in global standards and European policy discussions for seven years and had been working in the U.S. policy space on a part-time basis for the last two and a half years. Led in the U.S. by Deb Bryant, OSI informed public comment responses to requests for information from the Biden Administration on open weights in AI models and collaborated with like-minded organizations on a joint response and listening session. OSI also brought the Open Source community to key discussions on cybersecurity run by the Cybersecurity and Infrastructure Security Agency (CISA). These efforts were a recognition that the Open Source community should contribute to U.S. public policy discussions. Today, the evolution of Artificial Intelligence (AI) and the geopolitical landscape have made the Open Source community’s participation in U.S. public policy even more critical. As the full-time Senior U.S. Policy Manager, my role at OSI is to educate policymakers about the benefits of Open Source software, track policy developments at the state and federal level, and ultimately, ensure that Open Source developers can continue doing their work. Concerns of security in the software supply chain and the rise of AI have seeded policy proposals that have the potential to impact Open Source developers in new ways or in ways that are hard to predict. That’s why now, more than ever, the Open Source community should be at the table when these proposals are being discussed to make sure those developing the policy understand Open Source software development and its existence in the vast majority of technology. For example, let’s consider state legislation aimed at regulating AI systems that may cause harm. It is reasonable to set guardrails around technology that may harm consumers. However, AI systems that are used by a consumer may contain Open Source components from someone who created the code and openly licensed it but were not involved in deploying the AI system. Making code available for others is a core principle of Open Source. Open Source developers share code because they want others to build on it but it does not mean they endorse what is done with the code later on. Understanding the distinction is important so that policies do not inadvertently punish those sharing their software openly for the benefit of everyone (see our two-pager ). The good news is that the Open Source community has a plethora of expertise in Open Source software development and can educate policymakers about these distinctions as well as the general benefits of Open Source. A large part of educating policymakers is working with their staff. Legislative branch staff, either in the U.S. Congress or in state legislatures, are typically responsible for a range of different issues and only have the time to develop a general sense of a topic, but not deep expertise. On the other hand, executive branch staff at all levels of government are more likely to have deep expertise on one or two issues. It’s important for our community to remember that the knowledge base of policy staff varies significantly and we must meet people where they are at. Ultimately, U.S. technology policy will be made and the Open Source community can either be part of the discussion or a casual observer. In my mind, we should be proactive about speaking with policymakers instead of waiting for them to come to us. Further, we must be strategic about how we engage to ensure our message is clear and reaches the right people in government. Fresh off my first All Things Open conference earlier this month, I’m excited about what lies ahead and working with the community to build resilient structures for policy engagement. If you are a nonprofit organization that wants to learn more and participate in U.S. policy discussions, consider joining the Open Policy Alliance (OPA). The OPA brings together nonprofit public benefit organizations to educate and inform U.S policy decisions related to Open Source software, content, research, and education. It’s free to join! 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https://dev.to/ikhwanal | Ikhwan A Latif - 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 Ikhwan A Latif 418 I'm a teapot Location Riau Islands, Batam Joined Joined on Aug 21, 2025 Email address ikhwanal235@gmail.com github website Education Batam State Polytechnic Pronouns He/him More info about @ikhwanal 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 Skills/Languages Go, JS, SQL, Performance, Architecture Currently learning Golang, Image Processing, Kubernetes, Docker, SQL, Currently hacking on Side Project That Involve Image Processing Right Now. Available for anytime no restrictions Post 4 posts published Comment 1 comment written Tag 0 tags followed Get Hit By Performance Bottleneck In Canvas Ikhwan A Latif Ikhwan A Latif Ikhwan A Latif Follow Jan 2 Get Hit By Performance Bottleneck In Canvas # learning # development # programming # performance Comments Add Comment 4 min read Want to connect with Ikhwan A Latif? Create an account to connect with Ikhwan A Latif. You can also sign in below to proceed if you already have an account. Create Account Already have an account? Sign in Quick To Spot API/System Slow Ikhwan A Latif Ikhwan A Latif Ikhwan A Latif Follow Sep 29 '25 Quick To Spot API/System Slow # performance # devjournal # database # javascript Comments Add Comment 10 min read Gaussian Blur Ikhwan A Latif Ikhwan A Latif Ikhwan A Latif Follow Sep 12 '25 Gaussian Blur # programming # learning # devjournal Comments Add Comment 8 min read Adventure Of DIP Ikhwan A Latif Ikhwan A Latif Ikhwan A Latif Follow Aug 22 '25 Adventure Of DIP # programming # learning # codenewbie # devjournal Comments Add Comment 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 | 2026-01-13T08:49:46 |
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https://dev.to/jitin_800e8b484929929663a | Jitin - 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 Forem Close Follow User actions Jitin 404 bio not found Joined Joined on Jan 2, 2026 More info about @jitin_800e8b484929929663a 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 Post 1 post published Comment 0 comments written Tag 0 tags followed The Command Pattern Simplified: How Modern Java (21–25) Makes It Elegant Jitin Jitin Jitin Follow Jan 8 The Command Pattern Simplified: How Modern Java (21–25) Makes It Elegant # architecture # java # tutorial 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 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 | 2026-01-13T08:49:46 |
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https://jsfiddle.net/coderfonts#send-to-jsfiddle | Coder Fonts by JSFiddle Coder Fonts by JSFiddle Input License Designed by David Jonathan Ross const DecodeHtmlEntity = ( string ) => { string.replace ( /&#(d+);/ g, (match, dec) => { if ( match === String ){ return String .fromCharCode ( dec ) } } ) } Use in JSFiddle Monoflow License Designed by Finaltype const DecodeHtmlEntity = ( string ) => { string.replace ( /&#(d+);/ g, (match, dec) => { if ( match === String ){ return String .fromCharCode ( dec ) } } ) } Use in JSFiddle Fira Code Designed by Nikita Prokopov (for Mozilla) const DecodeHtmlEntity = ( string ) => { string.replace ( /&#(d+);/ g, (match, dec) => { if ( match === String ){ return String .fromCharCode ( dec ) } } ) } Use in JSFiddle Source Code Pro Designed by Paul D. 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https://python-3-patterns-idioms-test.readthedocs.io/en/latest/ | Python 3 Patterns, Recipes and Idioms — Python 3 Patterns, Recipes and Idioms --> Python 3 Patterns, Recipes and Idioms latest Contributors ToDo List The remainder are from context, from the book. A Note To Readers Introduction Teaching Support Book Development Rules Developer Guide Part I: Foundations Python for Programmers Initialization and Cleanup Unit Testing & Test-Driven Development Python 3 Language Changes Decorators Metaprogramming Generators, Iterators, and Itertools Comprehensions Coroutines, Concurrency & Distributed Systems Jython Part II: Idioms Discovering the Details About Your Platform A Canonical Form for Command-Line Programs Messenger/Data Transfer Object Part III: Patterns The Pattern Concept The Singleton Building Application Frameworks Fronting for an Implementation StateMachine Decorator: Dynamic Type Selection Iterators: Decoupling Algorithms from Containers Factory: Encapsulating Object Creation Function Objects Changing the Interface Table-Driven Code: Configuration Flexibility Observer Multiple Dispatching Visitor Pattern Refactoring Projects Python 3 Patterns, Recipes and Idioms Docs » Python 3 Patterns, Recipes and Idioms Edit on Bitbucket Python 3 Patterns, Recipes and Idioms ¶ Contributors Thanks To ToDo List The remainder are from context, from the book. A Note To Readers Introduction A Team Effort Not an Introductory Book The License The Printed Book Translations My Motives Teaching Support Book Development Rules Contribute What You Can Don’t Get Attached Credit Mechanics Diagrams Developer Guide Getting Started: The Easiest Approach For Windows Users Installing Sphinx Getting the Development Branch of the Book Building the Book Building the PDF Setting up Mercurial Working with BitBucket and Mercurial A Simple Overview Of Editing and Merging Emacs for Editing Restructured Text Part I: Foundations Python for Programmers Scripting vs. Programming Built-In Containers Functions Strings Classes Inheritance Useful Techniques Further Reading Initialization and Cleanup Initialization Constructor Calls __new__() vs. __init__() Static Fields Cleanup Further Reading Unit Testing & Test-Driven Development Write Tests First Simple Python Testing A Very Simple Framework Writing Tests White-Box & Black-Box Tests Running tests Automatically Executing Tests Exercises Python 3 Language Changes Decorators Decorators vs. the Decorator Pattern History of Macros The Goal of Macros What Can You Do With Decorators? Function Decorators Slightly More Useful Using Functions as Decorators Review: Decorators without Arguments Decorators with Arguments Decorator Functions with Decorator Arguments Further Reading Metaprogramming Basic Metaprogramming The Metaclass Hook The Metaclass Hook in Python 3 Example: Self-Registration of Subclasses Using Class Decorators Using the inspect module Example: Making a Class “Final” Using __init__ vs. __new__ in Metaclasses Class Methods and Metamethods Intercepting Class Creation A Class Decorator Singleton The __prepare__() Metamethod Module-level __metaclass__ Assignment Metaclass Conflicts Further Reading Generators, Iterators, and Itertools Comprehensions List Comprehensions Nested Comprehensions Techniques A More Complex Example Set Comprehensions Dictionary Comprehensions Coroutines, Concurrency & Distributed Systems The GIL Multiprocessing Further Reading Jython Installation Getting the Trunk Scripting Interpreter Motivation Creating a Language Using Java libraries Inheriting from Java library Classes Controlling Java from Jython Inner Classes Controlling the Interpreter Putting Data In Getting Data Out Multiple Interpreters Creating Java classes with Jython Building Java Classes from Python Summary Exercises Part II: Idioms Discovering the Details About Your Platform A Canonical Form for Command-Line Programs Messenger/Data Transfer Object Part III: Patterns The Pattern Concept What is a Pattern? Classifying Patterns Pattern Taxonomy Design Structures Design Principles Further Reading The Singleton Exercises Building Application Frameworks Template Method Exercises Fronting for an Implementation Proxy State StateMachine Table-Driven State Machine The State Class Conditions for Transition Transition Actions The Table The Basic Machine Simple Vending Machine Testing the Machine Tools Exercises Decorator: Dynamic Type Selection Basic Decorator Structure A Coffee Example Class for Each Combination The Decorator Approach Compromise Other Considerations Further Reading Exercises Iterators: Decoupling Algorithms from Containers Type-Safe Iterators Factory: Encapsulating Object Creation Simple Factory Method Preventing direct creation Polymorphic Factories Abstract Factories Exercises Function Objects Command: Choosing the Operation at Runtime Strategy: Choosing the Algorithm at Runtime Chain of Responsibility Exercises Changing the Interface Adapter Façade Exercises Table-Driven Code: Configuration Flexibility Table-Driven Code Using Anonymous Inner Classes Observer Observing Flowers A Visual Example of Observers Exercises Multiple Dispatching Visitor Exercises Pattern Refactoring Simulating the Trash Recycler Improving the Design “Make More Objects” A Pattern for Prototyping Creation Trash Subclasses Parsing Trash from an External File Recycling with Prototyping Abstracting Usage Multiple Dispatching Implementing the Double Dispatch The Visitor Pattern A Reflective Decorator More Coupling? RTTI Considered Harmful? Summary Exercises Projects Rats & Mazes Other Maze Resources Indices and tables ¶ Index Search Page Next © Copyright 2008, Creative Commons Attribution-Share Alike 3.0. Revision 59754c87cfb0 . Built with Sphinx using a theme provided by Read the Docs . | 2026-01-13T08:49:46 |
https://dev.to/bhu_kalki/spring-security-implementation-overview-asked-in-3-yoe-interview-dl0#comments | Spring Security Implementation Overview asked in 3 yoe interview - 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 Er. Bhupendra Posted on Dec 30, 2025 Spring Security Implementation Overview asked in 3 yoe interview # webdev # programming # java # interview Spring Security Implementation Overview Security is primarily enforced on the backend , as client browsers are considered less secure. The backend uses JWT (JSON Web Tokens) for stateless authentication in REST APIs to avoid re-authenticating every request, enhancing performance. JWT tokens are passed from frontend to backend via cookies or sessions. Tokens come with a TTL (Time To Live) , requiring reauthentication upon expiration, handled using refresh tokens . For authorization servers, D has used Okta OAuth 2.0 integrated with Spring Security to handle authentication and authorization. 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 Er. Bhupendra Follow Ex-Software Developer at Nagarro || Java developer || SpringBoot || SpringJPA || Spring Security Location Bangalore Education Btech CSE Pronouns He Joined Dec 13, 2021 More from Er. Bhupendra POST ALL USES IN BRINGBOOT # api # java # springboot # tutorial @RequestBody in SpringBoot # backend # java # springboot ALL TYPE OF GET USES IN SPRING BOOT # api # java # springboot # tutorial 💎 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 | 2026-01-13T08:49:46 |
https://www.fullstackpython.com/ | Full Stack Python Full Stack Python All topics | Blog | Supporter's Edition | @fullstackpython | Facebook | What's new? Learn to Build, Deploy and Operate Python Applications You're knee deep in learning Python programming. The syntax is starting to make sense. The first few ahh-ha! moments hit you as you learn to use conditional statements, for loops and classes while coding with the open source libraries that make Python such an amazing programming ecosystem . Now you want to take your initial Python knowledge and make something real, like a web application to show off to friends or sell as a service to customers. That's where Full Stack Python comes in. You have come to the right place to learn everything you need to create , deploy and operate Python-powered applications. Full Stack Python is an open source book that explains technical concepts in plain language. Read everything online for free or purchase the Supporter's Edition for nicely-formatted ebook (PDF, EPUB, MOBI) versions. This guide branches out on topic because your learning requirements depend on what you're working on. Choose a topic from the links below or view the full table of contents to see even more subjects you can learn. What do you need to learn first? 1. Introduction 1.1 Learning Programming The Python Language Why Use Python? Python 2 or 3? Enterprise Python 1.2 Python Community Companies Using Python Best Python Resources Must-watch Python Videos Podcasts 2. Development Environments 2.1 Text Editors and IDEs Vim Emacs Sublime Text PyCharm Jupyter Notebook 2.2 Shells Bourne-again shell (Bash) Zsh PowerShell 2.3 Terminal multiplexers tmux Screen 2.4 Environment configuration Application dependencies virtual environments (virtualenvs) Localhost tunnels 2.5 Source Control Git Mercurial 3. Data 3.1 Relational databases PostgreSQL MySQL SQLite 3.2 Object-relational mappers SQLAlchemy Peewee Django ORM Pony ORM 3.3 NoSQL Redis MongoDB Apache Cassandra Neo4j 3.4 Data analysis pandas SciPy & Numpy 3.5 Data visualization Bokeh d3.js Matplotlib 3.6 Markup Languages Markdown reStructuredText 4. Web Development 4.1 Web Frameworks Django Flask Bottle Pyramid TurboGears Falcon Morepath Sanic Other web frameworks 4.2 Template Engines Jinja2 Mako Django Templates 4.3 Web design HTML CSS Responsive Design Minification 4.4 CSS Frameworks Bootstrap Foundation 4.5 JavaScript React Vue.js Angular 4.6 Task queues Celery Redis Queue (RQ) Dramatiq 4.7 Static site generators Pelican Lektor MkDocs 4.8 Testing Unit testing Integration testing Debugging Code Metrics 4.9 Networking HTTPS WebSockets WebRTC 4.10 Web APIs Microservices Webhooks Bots 4.11 API creation API Frameworks Django REST Framework 4.12 API integration Twilio Stripe Slack Okta 4.13 Web application security SQL injection Cross-Site Request Forgery 5. Web App Deployment 5.1 Hosting Servers Static content Content Delivery Networks (CDNs) 5.2 Virtual Private Servers (VPSs) Linode DigitalOcean Lightsail 5.3 Platform-as-a-Service Heroku PythonAnywhere AWS CodeStar 5.4 Operating systems Ubuntu Linux macOS FreeBSD Windows 5.5 Web servers Apache HTTP Server Nginx Caddy 5.6 WSGI servers Green Unicorn uWSGI mod_wsgi 5.7 Continuous integration Jenkins GoCD 5.8 Configuration management Ansible Salt 5.9 Containers Docker Kubernetes 5.10 Serverless Architectures AWS Lambda Azure Functions Google Cloud Functions 6. DevOps 6.1 Monitoring Datadog Prometheus Rollbar Sentry 6.2 Web App Performance Logging Caching Web Analytics 7. Meta Change log About the author What "full stack" means Page Statuses Future directions Matt Makai 2012-2022 | 2026-01-13T08:49:46 |
https://dev.to/rajatarora/breaking-the-interface-barrier-cglib-and-bytebuddy-462a#comments | Breaking the interface barrier: CGLIB and ByteBuddy - 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 Rajat Arora Posted on Jan 9 • Originally published at rajat.co Breaking the interface barrier: CGLIB and ByteBuddy # java # programming # learning # backend Java Proxies Unmasked: From Design Patterns to Bytecode Engineering (4 Part Series) 1 Understanding Proxy Patterns: The Why and How of Static and Dynamic Proxies in Java 2 Magic in the Wild: How Java Giants like Spring, Hibernate, and Mockito use Dynamic Proxies 3 Proxies the Native Way: JDK Dynamic Proxies 4 Breaking the interface barrier: CGLIB and ByteBuddy Welcome back! If you've been following along our journey through the world of Java proxies, you know we've spent a lot of time learning about the Proxy pattern and how it is used, its uses in various large libraries in the Java world, and even created a dynamic proxy using Java's internal feature: The JDK Dynamic Proxy. While using JDK Dynamic Proxies is easy ... after all, they're built right into the JDK! You don't have to import any third-party library in order to create a dynamic proxy. They are convenient and they are reliable... but, they're a bit too restrictive. They only work with interfaces . What if the class you want to proxy doesn't implement an interface? In that case, the JDK is going to look at your face and politely decline to help. But in the real world of Hibernate entities, Spring beans, and legacy monoliths, we often need to proxy classes directly. To break this interface barrier , we have to move away from high-level Java and start playing with the actual bytecode that makes up our classes. Class-based Proxies If you can't use an interface to define a proxy, how do you do it? The answer is surprisingly simple in theory: Inheritance . Instead of creating a sibling class that shares an interface, we create a child class at runtime. This child class overrides the methods of the parent and inserts the extra logic (logging, transactions, security) before calling super.method() . By becoming a subclass, the proxy is now an instance of the original class (thanks, polymorphism!), allowing it to be injected anywhere the original was expected. This is the bedrock of most Java frameworks, which rely on this "invisible" inheritance to add powerful features without forcing you to change a single line of your domain logic. But this capability didn't appear overnight. Before we reached the modern landscape of bytecode engineering, the Java community relied on a singular, powerful tool to bridge the gap where the JDK fell short. To understand where we are going with modern solutions, we first have to look at the library that paved the way and defined an entire era of enterprise Java development. The history of CGLIB: The Fallen Giant For over a decade, CGLIB ( C ode G eneration Lib rary) was the undisputed king of class-based proxies. If you've ever looked at a stack trace in a Spring Boot application and seen something like UserService$$EnhancerBySpringCGLIB$$ ..., you've seen CGLIB in action. CGLIB sat on top of ASM, a very low-level bytecode manipulation library. It provided a "high-level" (at the time) API to generate subclasses on the fly. Its most famous tools were the Enhancer class and the MethodInterceptor interface. While revolutionary, CGLIB is now considered "legacy". It hasn't kept pace with the rapid evolution of Java. Since Java 9, the JVM has become much more restrictive about illegal reflective access , and CGLIB's internal reliance on older ASM versions and dirty tricks for class loading started to cause headaches for developers moving to modern runtimes. The "Unsafe" instantiation One of the most notorious "dirty" tricks CGLIB employed (and a primary reason it has struggled with modern Java versions) is its use of the sun.misc.Unsafe API to instantiate proxy classes by skipping constructors entirely . To understand why this is a "trick," we have to look at how Java normally handles objects. Usually, when you extend a class, your constructor must call super() . But what if the parent class doesn't have a default constructor? Or what if the constructor does something heavy, like opening a database connection or throwing an exception? CGLIB wanted to create a proxy without triggering any of that parent logic. Here is a simplified look at the kind of "dirty" logic happening under the hood when you use CGLIB to proxy a class with a "difficult" constructor: import sun.misc.Unsafe ; import java.lang.reflect.Field ; public class DirtyInstantiator { public static void main ( String [] args ) throws Exception { // 1. Access the "Unsafe" instance via reflection // (It's private, so we have to cheat) Field f = Unsafe . class . getDeclaredField ( "theUnsafe" ); f . setAccessible ( true ); Unsafe unsafe = ( Unsafe ) f . get ( null ); // 2. Imagine 'ProxyClass' is the subclass CGLIB generated // We can create an instance of it WITHOUT calling the constructor // even if the constructor is private or throws an exception! TargetClass proxyInstance = ( TargetClass ) unsafe . allocateInstance ( TargetClass . class ); proxyInstance . doSomething (); } } class TargetClass { public TargetClass () { // This code will NEVER run when CGLIB uses the 'Unsafe' trick throw new RuntimeException ( "You cannot instantiate me directly!" ); } public void doSomething () { System . out . println ( "Wait... how am I running? My constructor failed!" ); } } Enter fullscreen mode Exit fullscreen mode This technique is considered dirty for several reasons that affect the stability and security of your application: Violates Language Guarantees: Java guarantees that a constructor will run before an object is used. By skipping it, CGLIB can leave internal fields uninitialized (null), leading to unpredictable NullPointerException errors later in the execution flow. Encapsulation Breaking: It relies on sun.misc.Unsafe , an internal API that was never meant for public use. Starting with Java 9 and the Module System (Project Jigsaw), the JVM began strictly "encapsulating" these internals. Security Risks: If a class has security checks in its constructor to prevent unauthorized instantiation, CGLIB’s trick bypasses those checks completely. JVM Fragility: Because this relies on internal JVM behavior, an update to the OpenJDK can (and often does) break this logic, leading to the "Illegal Reflective Access" warnings that have plagued Spring developers for years. Modern libraries like Byte Buddy still have to deal with constructor issues, but they prefer using documented, "cleaner" ways to handle class definition, or they provide much more transparent ways to handle the super() call requirements. While Unsafe allowed CGLIB to perform technical miracles, they also turned the library into a "black box" that grew increasingly fragile as the Java platform matured. This fragility eventually created a vacuum in the ecosystem for a tool that could handle the raw power of bytecode manipulation without resorting to the "dirty" hacks of the past. This is precisely where the industry shifted. We moved away from libraries that try to trick the JVM and toward a framework that works with the JVM's rules while providing a developer experience that feels like modern, idiomatic Java. Introducing Byte Buddy and the Fluent API If CGLIB is the aging rockstar of the 2000s, Byte Buddy is the modern virtuoso. Created by Rafael Winterhalter, Byte Buddy won the "Bytecode Wars" because it realized a simple truth: writing bytecode shouldn't feel like writing assembly. It should feel like writing Java. The Philosophy: Type Safety and Simplicity Byte Buddy’s philosophy is built on moving away from the "stringly-typed" and reflection-heavy approach of CGLIB. Instead of passing strings or raw method objects around and hoping for the best, it uses a Fluent DSL (Domain Specific Language) . This allows you to describe what you want the class to do in a way that the compiler can actually understand and validate, catching potential errors before your application even starts. Unlike its predecessors, which often felt like a black box of runtime magic, Byte Buddy is designed to be predictable. It doesn't try to hide the fact that it's generating a class; instead, it gives you a powerful, transparent set of tools to define exactly how that class should behave, ensuring compatibility with modern Java versions and the Module System. The Fluent DSL: Subclass, Method, Intercept To create a proxy in Byte Buddy, you follow a flow that reads like a sentence: subclass(Target.class) : "I want a new class that extends Target." method(ElementMatcher) : "I want to target these specific methods." intercept(Implementation) : "When those methods are called, do this ." ElementMatchers: The "SQL" of Methods One of the most powerful features of Byte Buddy is the ElementMatchers library. Instead of messy if statements, you select targets using declarative syntax like named("save") , isPublic() , or isAnnotatedWith(Transactional.class) . These are composable using .and() and .or() . Hands-on: Intercepting a UserService Let's build a real-world example. We have a UserService and we want to measure the execution time of the save() method. Here is a minimal implementation that includes a basic dependency (a logger or simulated database) and a method that we can easily target for interception. public class UserService { // A concrete method with logic we want to 'wrap' public String save ( String username ) { System . out . println ( ">>> UserService: Persisting user '" + username + "' to database..." ); try { // Simulate some network or disk latency Thread . sleep ( 200 ); } catch ( InterruptedException e ) { Thread . currentThread (). interrupt (); } return "SUCCESS: " + username + " is now in the system." ; } // A method we might want to ignore or match differently public void delete ( String username ) { System . out . println ( ">>> UserService: Deleting user '" + username + "'..." ); } } Enter fullscreen mode Exit fullscreen mode Here, we implement the Interceptor , which is roughly equivalent to InvocationHandler we wrote while creating a JDK Dynamic Proxy. The Interceptor defines the "extra" logic that we want to inject in our proxy. import net.bytebuddy.implementation.bind.annotation.* ; import java.lang.reflect.Method ; import java.util.concurrent.Callable ; public class PerformanceInterceptor { @RuntimeType public static Object intercept ( @Origin Method method , // The method being called @SuperCall Callable <?> zuper // The original method logic ) throws Exception { long start = System . currentTimeMillis (); try { return zuper . call (); // Execute super.save() } finally { System . out . println ( method . getName () + " took " + ( System . currentTimeMillis () - start ) + "ms" ); } } } Enter fullscreen mode Exit fullscreen mode Let's dig into the code a bit: @Origin Method method : This is the standard java.lang.reflect.Method object. It is Byte Buddy's way of handing you the "metadata" of the method being called. You can use this object to access the method name, its annotations, or its parameters without you doing any manual reflection. @SuperCall Callable<?> zuper : This is the real secret sauce. Byte Buddy creates a special auxiliary class that knows how to call the original method in the parent class. By wrapping it in a Callable , you can decide exactly when, or even if, the original logic should execute. The try/finally block: This ensures that even if the original method throws an exception, our timer still finishes. It is the standard way to implement reliable "around advice" in the AOP world. The last step is actually creating the proxy using Byte Buddy. Here we instruct JVM to build a new type. UserService proxy = new ByteBuddy () . subclass ( UserService . class ) . method ( ElementMatchers . named ( "save" )) . intercept ( MethodDelegation . to ( PerformanceInterceptor . class )) . make () . load ( UserService . class . getClassLoader (), ClassLoadingStrategy . Default . INWRAPPER ) . getLoaded () . getDeclaredConstructor (). newInstance (); proxy . save ( "Alice" ); Enter fullscreen mode Exit fullscreen mode In the above snippet: .subclass(UserService.class) : This tells Byte Buddy to generate a new class in memory that extends our UserService . To the JVM, this new class is a legitimate child of the original. .method(ElementMatchers.named("saveUser")) : Think of this as a filter. Byte Buddy iterates through all methods available in the subclass and only applies our "advice" to the ones that pass this test. .intercept(MethodDelegation.to(PerformanceInterceptor.class)) : Here, we are "binding" the matched method to our interceptor. Byte Buddy is smart enough to see the annotations in our interceptor and figure out how to pass the right arguments into it at runtime. .load(...) : This is the bridge to the JVM. We have the bytecode in a byte array, but to use it, we need to define it through a ClassLoader . The INWRAPPER strategy is the most common approach, as it loads the proxy in a child class loader of the original class, preventing class-loading conflicts. .getLoaded().getDeclaredConstructor().newInstance() : Finally, we treat the generated class like any other Java class. We grab its constructor and create an instance. This instance is what we pass around our application, and because of polymorphism, everyone thinks it's just a regular UserService . Did you notice that we only proxied the save() method of UserService and not the delete() ? Well this is another advantage of using Byte Buddy. In a JDK proxy, you are forced into a single InvocationHandler where you must handle every method call (including toString , equals , etc.) in one giant switch or if block. Byte Buddy allows you to be surgical. You can apply different interceptors to different methods within the same proxy definition. Why Byte Buddy is the current standard When you run the code above, Byte Buddy generates a class at runtime that effectively overrides the save method. But unlike CGLIB, Byte Buddy's generated code is highly optimized. It uses "Inlining" where possible and avoids the heavy overhead of reflection during every method call. Furthermore, Byte Buddy handles the complexity of Java's Module System (Project Jigsaw) gracefully. It knows how to "open" packages or define classes in a way that doesn't trigger security exceptions on modern JVMs (Java 11, 17, and 21). In the next part, we'll look at how these libraries handle "Redefinition" and "Rebasing"—techniques that allow you to modify existing classes rather than just creating subclasses. This is where we move into the territory of Java Agents and serious performance monitoring tools. For now, try running the Byte Buddy example and see if you can add a matcher that intercepts all methods except for those starting with "get". Java Proxies Unmasked: From Design Patterns to Bytecode Engineering (4 Part Series) 1 Understanding Proxy Patterns: The Why and How of Static and Dynamic Proxies in Java 2 Magic in the Wild: How Java Giants like Spring, Hibernate, and Mockito use Dynamic Proxies 3 Proxies the Native Way: JDK Dynamic Proxies 4 Breaking the interface barrier: CGLIB and ByteBuddy 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 Rajat Arora Follow Joined Aug 9, 2018 More from Rajat Arora Proxies the Native Way: JDK Dynamic Proxies # java # programming # backend # beginners Magic in the Wild: How Java Giants like Spring, Hibernate, and Mockito use Dynamic Proxies # java # spring # hibernate # mockito Understanding Proxy Patterns: The Why and How of Static and Dynamic Proxies in Java # java # programming # designpatterns 💎 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 | 2026-01-13T08:49:46 |
https://docs.suprsend.com/docs/amazon_s3_v2 | Amazon S3 v2.0 - SuprSend, Notification infrastructure for Product teams Skip to main content SuprSend, Notification infrastructure for Product teams home page Search... ⌘ K Community Trust Center Platform Status Postman Collection GETTING STARTED What is SuprSend? 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Navigation Connectors Amazon S3 v2.0 Documentation API Reference Management API CLI Reference Developer Resources Changelog Documentation API Reference Management API CLI Reference Developer Resources Changelog Connectors Amazon S3 v2.0 OpenAI Open in ChatGPT Export your notification logs to Amazon S3 for analytics, debugging, and compliance. OpenAI Open in ChatGPT Old S3 connector (v1.0) will be deprecated over time: If you’re using the existing S3 connector (v1.0), migrate to v2.0 to support the latest logging and analytics updates. The v2.0 connector exports all log types and notification analytics and fixes gaps in error logging present in v1.0. Export your SuprSend notification data directly to your S3 bucket. Build custom analytics dashboards, debug delivery issues, surface errors to your customers, or maintain compliance audit trails—all with data you fully own and control. How it works Every 5 minutes , SuprSend syncs your notification data to S3 in Parquet format. Data lands in hourly partitions across three data points, depending on your connector settings: Copy Ask AI your-bucket/ ├── year=2025/month=01/day=15/hour=14/messages.parquet ├── year=2025/month=01/day=15/hour=14/workflow_executions.parquet └── year=2025/month=01/day=15/hour=14/requests.parquet At every sync, we add or replace the existing hourly parquet files where the data has been changed. For query engines like AWS Athena, changes in hourly partitions are automatically detected and reflected in the final tables. For data warehouses that don’t support automatic row overwrites (e.g., BigQuery), use the updated_at column to select the latest state of the data. Data is encrypted with TLS 1.2+ in transit and SSE-S3/SSE-KMS at rest. The Parquet format and partition structure work natively with query engines like Athena, Spark, and Presto. If you pause sync, data from the pause period backfills automatically when you resume. What you can export You can choose which data points to sync based on your use case. Each data point should be synced in a separate table in your data warehouse. Most users sync Messages for analytics and delivery troubleshooting . For internal logging, error analysis, and audit trails, you can sync all data points . Data points Data point What’s in it Use it for Messages Delivery status, engagement, vendor info, failures Analytics, delivery troubleshooting Workflow Executions Step-by-step workflow logs Debugging workflow level errors or computations like user preferences Requests API payloads and their responses API debugging, Audit trails, Workflow Trigger level errors Errors logged in each table: Table Errors Requests API level errors, workflow trigger level errors (condition mismatch, user not found, etc.) Workflow Executions Workflow level errors (dynamic variables in workflow could not be resolved, template rendering failed, webhook returned a 404 response, etc.) Messages Delivery failures Table Schema Requests Workflow Executions Messages Column name Description Datatype api_type Entity type for the API call string api_name Workflow, event, or broadcast name passed in the API call string distinct_id_list List of user distinct_id values or object type/id the request was sent for array actor Actor passed in the event or workflow API request string tenant_id Tenant ID for which the API request was sent string payload Input payload passed in the trigger, including API call details json response HTTP API response json metadata SDK, machine, and location information for the request json errors Request-level errors with message and severity array(json) executions Workflow or broadcast execution IDs and slugs triggered by this API call. Execution IDs can be used to link with the workflow executions table array(json) idempotency_key Idempotency key passed in the API request. A UUID is generated if not provided string created_at Time when the request was received by SuprSend (UTC) datetime updated_at Time when this entry was last updated datetime status Status of the API request string status can have these values: completed : request is successfully processed. failure : request failed to process due to some error partial_failure : request has been partially processed with some failure or has an acceptable warning (like workflow conditions evaluated to false)* Column name Description Datatype execution_id Unique identifier for a workflow execution string recipient_distinct_id User distinct_id ; for objects, object_type/id string tenant_id Unique identifier of the tenant string idempotency_key Idempotency key passed in the API request. A UUID is generated if not provided string parent_object Parent object_type/id when the workflow runs for subscribers string parent_object_execution_id Execution ID of the parent object when triggered on an object string workflow_slug Unique slug of the workflow string workflow_version Version of the workflow string created_at Time when the workflow execution started datetime updated_at Time when the workflow step log was last updated datetime node_id Unique identifier of the node string node_name Name of the node string node_type Type of the node string execution_stage Current execution stage of the node string message Short description of the event or error at this stage string status Log status of the step ( error , warning , info ) string properties Additional input or output data for the node execution json Column name Description Datatype wf_execution_id Unique identifier for a workflow execution string broadcast_execution_id Unique identifier for a broadcast execution string message_id Message identifier; present only when there is no execution error string recipient_distinct_id User distinct_id ; for objects, object_type/id string tenant_id Unique identifier of the tenant string idempotency_key Idempotency key passed in the API request. A UUID is generated if not provided string parent_object Parent object_type/id when the workflow runs for subscribers string parent_object_execution_id Execution ID of the parent object when triggered on an object string workflow_slug Unique slug of the workflow string template_name Name of the template group string template_slug Unique slug of the template string status Delivery status of the message string created_at Time when this entry was created datetime updated_at Time when the message status was last updated datetime node_id Unique identifier of the node string node_name Name of the node string node_type Type of the node string execution_failure_reason Workflow execution–level failure details with severity json delivery_failure_reason Failure reason returned by the vendor string triggered_at Timestamp when SuprSend sent the message request to the vendor datetime delivered_at Timestamp when the vendor reported delivery datetime seen_at Timestamp when the message was seen by the user datetime clicked_at Timestamp when the message was clicked by the user datetime dismissed_at Timestamp when the message was dismissed by the user datetime vendor_ack_id Vendor-generated identifier for this request string vendor_fallback_applicable Indicates whether vendor fallback was enabled boolean vendor_fallback_level Order in which this vendor was used during fallback (starts at 0) integer vendor_name Vendor nickname configured in SuprSend string vendor_name_slug Vendor identifier combining vendor type and channel string is_smart Indicates if the node used smart channel routing boolean success_metric Success metric defined for smart channel routing string success_achieved_at Timestamp when the success metric was achieved datetime wait_time_in_seconds Wait time between channels for smart routing integer channel_slug Communication channel string channel_info Channel-specific value (e.g., email address) string webhook_data Request and response payload for webhook nodes json Linking different data points These data points are linked, allowing you to trace a notification from the initial API request to final delivery. The idempotency key is the common identifier across all tables and can be used to follow a single request end to end. Since the idempotency key is provided in the API request, you can also store it in your system to correlate SuprSend processing with your internal logs. From → To Join on Requests → Workflow Executions execution_id Workflow Executions → Messages wf_execution_id Requests → Messages (shortcut) idempotency_key Setup Step 1: Create your S3 bucket Open AWS S3 Console and create a bucket with these settings: Bucket name : Something like suprsend-logs-production (save this—you’ll need it) Region : Pick one close to you Block all public access : Yes Encryption : SSE-S3 (or SSE-KMS for compliance) Step 2: Create an IAM policy This gives SuprSend permission to write to your bucket. In IAM Console , create a policy with this JSON: Copy Ask AI { "Version" : "2012-10-17" , "Statement" : [{ "Sid" : "SuprSendS3ExportAccess" , "Effect" : "Allow" , "Action" : [ "s3:PutObject" , "s3:ListBucket" , "s3:GetObject" ], "Resource" : [ "arn:aws:s3:::YOUR_BUCKET_NAME/*" , "arn:aws:s3:::YOUR_BUCKET_NAME" ] }] } Replace YOUR_BUCKET_NAME with your actual bucket name. Save it as something like suprsend_s3_policy . Step 3: Set up authentication Two authentication methods are available: Method When to use We recommend IAM Role Production, enterprise, multi-account setups ✅ Yes—credentials rotate automatically, no secrets to manage IAM User Development, testing, quick POCs Only if IAM Role isn’t feasible. Requires manual key rotation every 90 days. IAM Role (Recommended) IAM User Use IAM Role when: Running in production environments Security compliance requires no long-lived credentials You have multi-account AWS setups You want zero credential management overhead Steps to create IAM Role: In IAM Console → Roles → Create Role Select Another AWS Account and enter SuprSend’s account ID: 924219879248 Attach the policy you just created Name it (e.g., suprsend_s3_role ) Now configure the trust relationship. Generate an External ID at uuidgenerator.net , then update the trust policy: Copy Ask AI { "Version" : "2012-10-17" , "Statement" : [{ "Effect" : "Allow" , "Principal" : { "AWS" : "arn:aws:iam::924219879248:root" }, "Action" : "sts:AssumeRole" , "Condition" : { "StringEquals" : { "sts:ExternalId" : "YOUR_EXTERNAL_ID" }} }] } Save these for the next step: Role ARN + External ID (case-sensitive, no extra spaces) Use IAM User when: Setting up for development or testing Quick proof-of-concept needed IAM Role setup isn’t feasible in your environment IAM User credentials require manual rotation every 90 days for security compliance. Steps to create IAM User: In IAM Console → Users → Add users Name it (e.g., suprsend-s3-connector ) Attach your policy Go to Security credentials → Create access key → Third party service Save immediately: Access Key ID + Secret Access Key to add in the next step (AWS won’t show the secret again) Step 4: Connect in SuprSend Go to Settings → Connectors → Amazon S3 v2.0 → Add Connector IAM Role IAM User Enter your AWS credentials, select which data points to export, then Save and toggle Enable sync . Step 5: Verify it’s working Give it about 10 minutes, then check your S3 bucket. You should see folders like year=2025/month=01/... appearing. Nothing showing up? Jump to FAQs for troubleshooting steps. Best practices Security Use IAM Role in production—no keys to manage Never commit credentials to git Keep your bucket private with encryption enabled (SSE-S3 or SSE-KMS) Block all public access to your bucket Managing roles & permissions Use IAM Role for production —credentials rotate automatically, no secrets to manage Rotate IAM User keys every 90 days —required for security compliance Use External ID for IAM Roles —prevents “confused deputy” attacks Assign policies to groups, not users —simplifies permission management Data syncing & querying Sync only what you need —for analytics, Messages is often enough. Add Workflow Executions and Requests for debugging. Use updated_at for incremental queries — updated_at tells you when a given row was last updated. You can filter by this field instead of scanning all data when you just need to recently updated data, especially while fetching logs. Clean up old data regularly — we always append new data. So, your files can accumulate over time. It’s better to clean up old data regularly to avoid unnecessary storage costs. FAQs Files not appearing? Work through this checklist: Wait 10 minutes —first sync takes time Check bucket name —must match exactly, case-sensitive Check region —must match in both AWS and SuprSend Check IAM —Check if the Role ARN, Access Key and External ID are correct. Check policy - See if the policy has these actions: "Action": ["s3:PutObject", "s3:ListBucket", "s3:GetObject"] assigned to the right bucket. How do I know it's working? It should work if the AWS setup is correct and in SuprSend → Settings → Connectors → Amazon S3 v2.0 , you see: Sync toggle is ON Status shows “Active” At least one dataset selected Missing data? Data point might not be selected—check your export settings When setting up the connector first time, data points only export going forward (no historical backfill) Were notifications actually sent during that time? If sync was paused, data backfills when you resume If you still find some gap in data, please contact support. How does backfilling work? What you did What happens Paused then resumed Backfills everything from the pause Added a new dataset Starts fresh, historical data will not be backfilled Re-enabled a dataset Backfills from when it was disabled Can I change data points later? Absolutely: Add one : Starts exporting going forward Remove one : Stops syncing, data stays in S3 Re-enable : Backfills automatically Was this page helpful? Yes No Suggest edits Raise issue Previous Overview Learn about database connector and how you can use it to auto sync list users by writing SQL query on your database. Next ⌘ I x github linkedin youtube Powered by On this page How it works What you can export Data points Table Schema Linking different data points Setup Step 1: Create your S3 bucket Step 2: Create an IAM policy Step 3: Set up authentication Step 4: Connect in SuprSend Step 5: Verify it’s working Best practices FAQs | 2026-01-13T08:49:46 |
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Kaustubh Trivedi Kaustubh Trivedi Kaustubh Trivedi Follow May 20 '22 What are some beginner level ReactJS questions to ask for interview? # discuss # beginners # react # interview 10 reactions Comments 7 comments 1 min read How to Rotate a String in JavaScript Kevin Kimani Kevin Kimani Kevin Kimani Follow May 22 '22 How to Rotate a String in JavaScript # javascript # beginners # interview # programming 7 reactions 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://tutswiki.com/pandas-cookbook/ | Pandas Cookbook :: TutsWiki Beta Machine Learning Decision Trees C++ Introduction Installation Functions Multithreading DSA Insertion Sort Bubble Sort Radix Sort Bucket Sort Counting Sort Quick Sort Heap Sort Merge Sort Tree Data Structure Binary Search Tree Binary Search Interpolation Search Exponential Search Java Classes & Objects Constructors Wrapper Class Serialization Exceptions Exception Handling throw and throws finally Lambda Expressions Regular Expressions Garbage Collection Annotations Database - PostgreSQL Generics Collections Python Introduction Threading Modules Decorators Exceptions Exception Handling Pandas Cookbook Chapter 1 Chapter 2 Chapter 3 Chapter 4 Chapter 5 Chapter 6 Chapter 7 Chapter 8 R Introduction Installation Average Variance Standard Deviation Blog Overloading and Overriding Methods Override/Overload Static Method in Java Medium Alternatives MLaaS Install deb file from command line SDKMan - Multiple Java Versions Writing and Reading JSON config file in Python Writing and Reading XML config file in Python Writing and Reading YAML config file in Python Top 4 Must Have Skills For A Project Manager QuestDB in Python Access internet on Linux using Android Tethering How to install software in Linux Writing and Reading config files in Angular Approximating Randomness How to convert a Python script to module Grunt Tutorial noprocrast sudo and node Yet another lousy monad tutorial A Deeper Look at Ruby's Enumerable A REST API in Clojure Abstract classes and interfaces in Python Deep Learning helped reducing variability in Cardiovascular Imaging Google engineers boycott Node.js on Google App Engine Angular 6 features Github alternatives What is the use of yield in Python? Difference between append and extend in Python How to print on same line with print in Python Writing and Reading config files in Python How to run a Python module as script? What is if __name__ == "__main__" in Python? More Tags GitHub Credits Facebook Star Fork Built by Community with Edit this page TutsWiki Beta > Pandas Cookbook Pandas Cookbook Introduction A newbie friendly introduction to Pandas with real life examples. | 2026-01-13T08:49:46 |
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https://opensource.org/about/brand-and-trademark-guidelines#content | Trademark and brand guidelines – 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 About Trademark and brand guidelines Trademark and brand guidelines The Open Source Initiative (OSI) trademarks, including “OSI,” “Open Source Initiative,” the “OSI logo,” and “OSI Approved Open Source License,” are protected on behalf of the open source community. As trademark owners, OSI is legally obligated to prevent confusingly similar uses by third parties. OSI trademarks and registration The OSI “Keyhole Logo,” designed by Colin Viebrock, symbolizes unlocking source code. 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Use for the first instance of the OSI Logo include the ® mark, and include the statement “The OSI logo trademark is the trademark of Open Source Initiative.” Never using the ® mark for OSI Logo, nor a trademark statement per the guidelines. Always distinguish trademarks from surrounding text with at least initial capital letters or in all capital letters. Open Source Initiative or OPEN SOURCE INITIATIVE open source initiative Always use a trademark as an adjective modifying a noun, or as a singular noun. This software is licensed under an Open Source Initiative Approved License®. I put Open Source Initiative software on AcmeCo’s server. Never use a trademark as a possessive. Instead, the following noun should be used in possessive form or the sentence reworded so there is no possessive. Many software programs licensed under OSI’s approved licenses are easy to use. OSI’s software is easy to use. Prohibited Uses: Do not use trademarks as possessives. Do not translate trademarks. 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http://pythontutor.com/visualize.html | Python Tutor code visualizer: Visualize code in Python, JavaScript, C, C++, and Java Python Tutor: Visualize Code and Get AI Help for Python , JavaScript , C , C++ , and Java Please wait ... your code is running (up to 10 seconds) Write code in Python 3.11 Python 3.6 [try if 3.11 doesn't work] Java C (C17 + GNU extensions) C++ (C++20 + GNU extensions) JavaScript (ES6) ------ Python 2.7 [unsupported] Visualize Execution NEW: teachers can get free access to ad-free/AI-free mode coming soon! ] Java options: pass in command-line arguments and feed user input to stdin--> hide exited frames [default] show all frames (Python) inline primitives and try to nest objects inline primitives, don't nest objects [default] render all objects on the heap (Python/Java) draw pointers as arrows [default] use text labels for pointers --> Python Tutor is designed to imitate what an instructor in an introductory programming class draws on the blackboard: Instructors use it as a teaching tool, and students use it to visually understand code examples and interactively debug their programming assignments. Quick links: Documentation and unsupported features FAQ for instructors using Python Tutor How the Python Tutor visualizer can help students in your Java programming courses How the Python Tutor visualizer can help students in your C or C++ courses Demo The screenshot below shows how a typical user (either an instructor or a student) would interact with it: (1) Go to pythontutor.com and select a language. Here the user chose Java and wrote code to recursively create a LinkedList . (2) Press ‘Visualize’ to run the code. This code ran for 46 steps, where each step is one executed line of code. Go to any step (2a) and see what line of code was being run at that step (2b). (3) See the frames of all functions/methods on the stack at this step, each of which shows its local variables. Here at step 41 we see main() along with 4 recursive calls to init() . (4) See all objects on the heap at the current step. Here it shows a LinkedList instance with first and last fields pointing to its first and last Node instances, respectively. Each Node has a numerical value and a next pointer. (5) See what has been printed up to this step. Here the print statement in the Node constructor (line 5) has run 3 times. The user can navigate forwards and backwards through all execution steps, and the visualization changes to match the run-time state of the stack and heap at each step. In this example, the user would see their custom LinkedList data structure getting incrementally built up one Node at a time via recursive calls to init() until the base case is reached when n==0 . Language Support Despite its name, Python Tutor is also a widely-used web-based visualizer for Java that helps students to understand and debug their code. It visualizes the majority of object-oriented programming concepts taught in introductory college courses (e.g., CS1 and CS2), high school AP Computer Science, and intermediate-level Java programming. Python Tutor is also a widely-used web-based visualizer for C and C++ meant to help students in introductory and intermediate-level courses. It uses Valgrind to perform memory-safe run-time traversal of data structures, which lets it display data more accurately than gdb or printf debugging. For instance, it can precisely visualize critical concepts such as pointers, uninitialized memory, out-of-bounds errors, nested arrays/structs/unions, type punning, and bit manipulation. Lastly, it also supports visualizing standalone JavaScript execution, but not web frontend code that does DOM manipulation on webpages. Unsupported Features Recall that Python Tutor is designed to imitate what an instructor in an introductory programming class draws on the blackboard: Thus, it is meant to illustrate small pieces of self-contained code that runs for not too many steps. After all, an instructor can't write hundreds of lines of code, draw hundreds of data structures and pointers, or walk through hundreds of execution steps on the board! Also, code in introductory classes usually doesn't access external libraries. If your code can't fit on a blackboard or presentation slide, it's probably too long to visualize effectively in Python Tutor. This tool is not meant as a professional-level debugger. Due to this ultra-focused design, the following features are not supported on purpose: Code that is too large in size shorten your code to what fits on a blackboard or presentation slide Python Tutor is not for debugging arbitrary code that you paste into it; you'll need to shorten your code to isolate what you want to debug Code that runs for too many steps (e.g., > 100) or for a long time (e.g., > 10 sec) shorten your code to isolate exactly what operations you want to visualize e.g., make your numbers/strings smaller, arrays/lists shorter, your data structures contain fewer items, and your loops/functions run fewer times for Python, set breakpoints using special #break comments ( example ) Code that defines too many variables or objects shorten your code to isolate what variables you want to visualize remove unnecessary variables and objects from your code for Python, use #pythontutor_hide to selectively hide objects ( example ) also use “Move and hide objects” option at bottom-left of visualizer to hide Advanced language features or subtleties that only experts need to know about Importing most external libraries (it’s meant for learning basic coding concepts) Visualizing custom data structures from libraries (it supports only built-in types) Interfacing with files, databases, networking, or other external resources Anything involving GUI programming or manipulating GUI/webpage components Multi-threaded / concurrent / asynchronous code (only supports single-threaded) Other general unsupported features: Command-line arguments (e.g., argv[] ) not supported; use hard-coded strings instead Reading data from external files is not supported (workaround: use strings to emulate files. StringIO examples for Python3 and Python2 ) You cannot step within a line of code to show how subexpressions get evaluated within that line; the best workaround is to manually split complex expressions into multiple lines and assign to temporary variables on each line ( example ). Printing to stderr probably won’t work; use print statements to print to stdout Some Unicode characters may not display if your browser doesn’t have those fonts or if you’re trying to print unprintable characters like binary data to terminal This tool uses slightly older versions of languages (e.g., Python 3.6) for greater stability and because instructional materials often rely on older versions. Upgrading to the newest versions can confuse beginners who are learning from instructional materials since the compiler/interpreter messages do not match their materials. For a detailed list of unsupported features for each programming language, view the full documentation here . Reporting Bugs The issue you’re encountering is likely listed in this document . If you're sure it's not, use the "Generate permanent link" button to make a URL of your code. Describe the expected behavior when running that code on your computer and how it differs from Python Tutor, then fill out this Google Form to report your bug or security issue. This form is not for requests or questions about desired features; it is only for reproducible bug reports and private disclosures of security-related issues. If you don't get a reply, assume your issue will not be addressed. Please do not submit duplicate issues in the form. There is no support for Python Tutor visualizations that are embedded in other people’s websites. Contact those site owners for help on how to use their sites. Ads keep this site free . We are not responsible for ad contents. Make a donation to go ad-free and get a faster AI Tutor 🚀 (teachers get free access ) | 2026-01-13T08:49:46 |
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https://www.devcycle.com/openfeature | Best OpenFeature Provider | DevCycle - OpenFeature Native Platform | DevCycle Product Solutions Resources Pricing Docs Book Demo Login Create Account Decouple Your Flags From Your Vendor All DevCycle SDKs come with OpenFeature built in, giving you a vendor-neutral, open standard for feature flags and protecting you from vendor lock-in. Start Free See Docs What is OpenFeature? OpenFeature is a CNCF -supported open specification that offers a vendor-agnostic, community-driven API for feature flagging. It standardizes feature management across tools and vendors, preventing vendor lock-in and provides a framework for building extensions and integrations that can be shared across the community. Always Own Your Flags Using a feature flag management tool with OpenFeature SDKs like DevCycle future-proofs your system. This lets you control your flags without locking them into a third party's system. Avoid Vendor Lock-In at the Code Level OpenFeature simplifies migration. Change providers at any time with minimal engineering and code changes. Use Any Vendor, Anytime OpenFeature is designed to work with any feature management vendor or in-house solution, allowing you to migrate between vendors or consolidate multiple platforms, without code refactoring. Built by Community Experts By using an OpenFeature-based feature flag platform, you'll ensure that you won't be reliant on your vendor for support. DevCycle is Committed to Open Standards The Most Comprehensive OpenFeature SDK Coverage DevCycle is the first and only platform that has OpenFeature support built into our open source SDKs , with wide support for client-side and server-side languages. Leaders in the OpenFeature Community DevCycle’s founder and CTO sits on the OpenFeature governance board of directors and is committed to supporting the community, its initiatives and promoting open standards. Proud Contributors and Supporters of Open Standards DevCycle developers actively contribute to the OpenFeature ecosystem and are proud to be among the thousands of developers supporting open standards. Learn More OpenFeature FAQs Everything you need to know about OpenFeature and how DevCycle provides the best OpenFeature experience. What is OpenFeature? + Why should I use OpenFeature? + Which programming languages are supported by OpenFeature? + Who is behind OpenFeature? + What is the difference between OpenFeature and proprietary feature flag SDKs? + How do I get started with OpenFeature? + What is an OpenFeature provider? + Can I use OpenFeature with my existing feature flag setup? + Is OpenFeature production-ready? + What are OpenFeature hooks? + How does OpenFeature handle feature flag evaluation? + Why choose DevCycle for OpenFeature? + Footer DevCycle What are Feature Flags? OpenFeature Create a Free Account Request a Demo Pricing Resources Documentation SDKs APIs Integrations Blog Contact Support Company About Us Careers Terms of Service Security & Compliance Privacy Policy Contact Us Discord X GitHub LinkedIn Bluesky © 2026 DevCycle All rights reserved. | 2026-01-13T08:49:46 |
https://zeroday.forem.com/t/soc#main-content | Soc - Security 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. 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 Security Forem Close # soc Follow Hide Discussions related to Security Operations Centers, including tools, processes, and analyst life. Create Post Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu 🔍 November: Strengthening Identity & Access Management (IAM) for SMBs Amit Ambekar Amit Ambekar Amit Ambekar Follow Nov 28 '25 🔍 November: Strengthening Identity & Access Management (IAM) for SMBs # iam # cybersecurity # soc # education Comments Add Comment 2 min read ✉️ December: Email Security — Your Strongest Defense Against Everyday Cyber Threats ✉️ Amit Ambekar Amit Ambekar Amit Ambekar Follow Dec 2 '25 ✉️ December: Email Security — Your Strongest Defense Against Everyday Cyber Threats ✉️ # email # cybersecurity # education # soc 1 reaction Comments 2 comments 3 min read osquery + OpenTelemetry = ❤️ Adam Gardner Adam Gardner Adam Gardner Follow Nov 16 '25 osquery + OpenTelemetry = ❤️ # devsecops # tools # soc Comments Add Comment 1 min read From Public Risk to Private Security: CloudFront with Internal ALB Ajay Shankar Ajay Shankar Ajay Shankar Follow Oct 7 '25 From Public Risk to Private Security: CloudFront with Internal ALB # cloudsecurity # aws # networksec # soc Comments Add Comment 2 min read loading... trending guides/resources ✉️ December: Email Security — Your Strongest Defense Against Everyday Cyber Threats ✉️ 🔍 November: Strengthening Identity & Access Management (IAM) for SMBs 💎 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 Security Forem — Your central hub for all things security. From ethical hacking and CTFs to GRC and career development, for beginners and pros alike 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 . Security Forem © 2016 - 2026. Share. Secure. Succeed Log in Create account | 2026-01-13T08:49:46 |
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Curated list of monospace coder fonts You can now use different monospace fonts in the editor − we now have a curated list of pretty awesome fonts available including premium ones. Just open the Coder Fonts mini-app from the sidebar or from Editor settings . My current favorites are Input and Commit Mono . CSS Flexbox generator as a JSFiddle app Our CSS Flexbox generator lets you create a layout, and skip knowing the confusing properties and value names (let's be honest the W3C did not make a good job here). Not gonna lie, this was heavily inspired by flexer.dev but coded completely from scratch. Behavior change for External Resources Adding External Resources will no longer create a list of resources in the sidebar but will be injected as a LINK or SCRIPT tag inside of the HTML panel. Code Completion with additional context The Code Completion will now also have the context of all panels before suggesting code to you - so if for example you have some CSS or JS, the HTML panel will suggest code based on the other two panels. 🦄 AI Code Completion (beta) Introducing some AI sprinkle in the editor - Code Completion based on the Codestral model (by Mistral ). For now it's a BYOK implmentation which means you need to provide your own API Key − you can get it for free . Editor switch from CodeMirror to Monaco (same as VSCode) After much deliberation I've decided to make the switch from CodeMirror to Monaco . There's a few reasons for this. CodeMirror 5 is no longer being developed, and the switch to 6 would be a huge rewrite since there's not much compatibility between the two versions. Monaco itself has lots of features already built-in, things that took quite a few external plugins to get into the CodeMirror implementation. 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https://peps.python.org/pep-0790/ | PEP 790 – Python 3.15 Release Schedule | peps.python.org Following system colour scheme Selected dark colour scheme Selected light colour scheme Python Enhancement Proposals Python » PEP Index » PEP 790 Toggle light / dark / auto colour theme PEP 790 – Python 3.15 Release Schedule Author : Hugo van Kemenade Status : Active Type : Informational Topic : Release Created : 26-Apr-2025 Python-Version : 3.15 Table of Contents Abstract Release manager and crew Release schedule 3.15.0 schedule 3.15 lifespan Copyright Abstract This document describes the development and release schedule for Python 3.15. Release manager and crew 3.15 release manager: Hugo van Kemenade Windows installers: Steve Dower Mac installers: Ned Deily Documentation: Julien Palard Release schedule 3.15.0 schedule The dates below use a 17-month development period that results in a 12-month release cadence between feature versions, as defined by PEP 602 . Actual: 3.15 development begins: Wednesday, 2025-05-07 3.15.0 alpha 1: Tuesday, 2025-10-14 3.15.0 alpha 2: Wednesday, 2025-11-19 3.15.0 alpha 3: Tuesday, 2025-12-16 Expected: 3.15.0 alpha 4: Tuesday, 2026-01-13 3.15.0 alpha 5: Tuesday, 2026-02-10 3.15.0 alpha 6: Tuesday, 2026-03-10 3.15.0 alpha 7: Tuesday, 2026-04-07 3.15.0 beta 1: Tuesday, 2026-05-05 (No new features beyond this point.) 3.15.0 beta 2: Tuesday, 2026-05-26 3.15.0 beta 3: Tuesday, 2026-06-16 3.15.0 beta 4: Tuesday, 2026-07-14 3.15.0 candidate 1: Tuesday, 2026-07-28 3.15.0 candidate 2: Tuesday, 2026-09-01 3.15.0 final: Thursday, 2026-10-01 Subsequent bugfix releases every two months. 3.15 lifespan Python 3.15 will receive bugfix updates approximately every second month for two years. Around the time of the release of 3.17.0 final, the final 3.15 bugfix update will be released. After that, it is expected that security updates (source only) will be released for the next three years, until five years after the release of 3.15.0 final, so until approximately October 2031. Copyright This document is placed in the public domain or under the CC0-1.0-Universal license, whichever is more permissive. Source: https://github.com/python/peps/blob/main/peps/pep-0790.rst Last modified: 2025-12-19 17:42:49 GMT Contents Abstract Release manager and crew Release schedule 3.15.0 schedule 3.15 lifespan Copyright Page Source (GitHub) | 2026-01-13T08:49:46 |
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https://www.npopov.com/2025/01/05/This-year-in-LLVM-2024.html | This year in LLVM (2024) Blog by nikic . Find me on GitHub , StackOverflow , Twitter and Mastodon . Learn more about me . « Back to article overview. This year in LLVM (2024) 05. January 2025 Another year has passed, so it’s once again time for my yearly summary blog post. As usual, this summary is mostly about my own work, and only covers the more significant / higher level items. Previous years: 2023 , 2022 ptradd I started working on the ptradd migration last year, but the first significant steps towards it only landed this year. The goal is to move away from the type-based/structural getelementptr (GEP) instruction, to a ptradd instruction, which does no more and no less than adding an offset to a pointer. The value of that offset is computed using normal mul/add instructions, if necessary. The general implementation approach is to gradually canonicalize all getelementptrs into getelementptr i8 representation, which is equivalent to ptradd , at which point we can remove support for specifying other types. The first step was to canonicalize constant-offset GEPs . For example, getelementptr i32, ptr %p, i64 1 becomes getelementptr i8, ptr %p, i64 4 , removing the implicit multiplication. Just this step already fixed a number of optimization failures caused by the old representation. Of course, it also exposed new optimization weaknesses, like insufficient select unfolding in SROA . The second step was to canonicalize constant-expression GEPs as well. That is, getelementptr (i32, ptr @g, i64 1) is converted to getelementptr (i8, ptr @g, i64 4) . However, this first required a change to how the inrange attribute on GEP constant expressions is represented. ; Old: getelementptr inbounds ({ [ 4 x ptr ], [ 4 x ptr ] }, ptr @vt , i64 0 , inrange i32 1 , i64 2 ) ; New: getelementptr inbounds inrange ( -16 , 16 ) ( i8 , ptr @vt , i64 48 ) inrange is a niche feature that is only used when generating vtables. It specifies that the GEP result can only be accessed in a limited range, which enables global splitting. Previously, this range was specified by marking a GEP index as inrange , limiting any accesses to occur “below” that index only. The new representation explicitly specifies the range of valid offsets instead, which removes the dependence on the structural GEP type. The next step for this project will be to canonicalize getelementptr instructions with variable offsets as well, in which case we will have to emit explicit offset arithmetic. I hope we can take this step next year. getelementptr nuw I have worked on a number of new instruction flags, the most significant of which are probably the nusw (no unsigned-signed wrap) and nuw (no unsigned wrap) flags for getelementptr . Getelementptr instructions already supported the inbounds flag, which indicates that the pointer arithmetic cannot go outside the underlying allocated object. This also implies that the addition of the pointer, interpreted as an unsigned number, and the offset, interpreted as a signed number, cannot wrap around the address space. This implied property can now be specified using the nusw flag, without also requiring the stronger inbounds property. The intention of this change is to be more explicit about which property transforms actually need, and to allow frontends (e.g. Rust) to experiment with alternative semantics that don’t require the hard to formalize inbounds concept. However, the much more useful new flag is nuw , which specifies that the addition of the address and the offset does not wrap in an unsigned sense. Combined with nusw (or inbounds ), it implies that the offset is non-negative. This flag fixes two key problems. The first are bounds/overflow check elimination failures caused by not knowing that an offset is non-negative. For example, if we have a check like ptr + offset >= ptr , we want it to optimize to true , for the case where offset is unsigned and pointer arithmetic cannot wrap. Previously this was not possible, because the frontend had no way to convey that this is a valid optimization to LLVM. The second is accesses to structures like struct vec { size_t len; T elems[N]; } . The nuw flag allows us to convey that vec.elems[i] cannot access the len field using a negative i . The core work for the new GEP flags is complete. Both alias analysis and comparison simplification can take advantage of them. However, there is still a good bit of work that can be done to preserve the new flags in all parts of the compiler. One interesting complication of the nuw flag is the interaction with incorrectly implemented overflow checks in C code. The ptr + offset >= ptr example above is something we want to be able to optimize, because this kind of pattern can, for example, appear when using a hardened STL implementation. However, a C programmer might also write literally that check with the intention of detecting an overflowing pointer addition. This is incorrect, because ptr + offset will already trigger UB on overflow (or, in fact, just going out of bounds of the underlying object). These incorrect overflow checks will now be optimized away. I have extended the -Wtautological-compare warning to catch trivial cases of this problem, and the -fsanitize=pointer-overflow warning catches the issue reliably – if you have test coverage. trunc nuw/nsw Another new set of instruction flags are the nuw and nsw flags on trunc . These flags specify that only zero bits (nuw) or sign bits (nsw) are truncated. The important optimization property of these new flags is that zext (trunc nuw (x)) is just x and sext (trunc nsw (x)) is also just x . These kinds of patterns commonly occur when booleans are converted between their i1 value and i8 memory representation, or during widening of induction variables. Unfortunately, rolling out these flags did not go as smoothly as expected. While we do take advantage of the new flags to some degree, we don’t actually perform the motivating zext (trunc nuw (x)) -> x fold yet, and instead keep folding this to and x, 1 (for i1). The reason is that completely eliminating the zext/trunc loses the information that only the low bit may be set. We need to strengthen some other optimizations before we’ll be able to take this step. icmp samesign Yet another new instruction flag is samesign on icmp instructions . As one might guess from the name, it indicates that both sides of the comparison have the same sign, i.e. are both non-negative or both negative. If samesign is set, we can freely convert between signed and unsigned comparison predicates. The motivation is that LLVM generally tries to canonicalize signed to unsigned operations, including for comparisons. So something like icmp slt will become icmp ult if we can prove the operands have the same sign. However, after this has happened, later passes may have a hard time understanding how this unsigned comparison relates to another signed comparison that has related operands. The samesign flag allows easily converting back to a signed predicate when needed. The bring-up work for samesign has only just started, so there’s barely any visible optimization impact yet. Improvements to capture tracking Capture tracking, also known as escape analysis , is critical for the quality of memory optimizations. Once a pointer has “escaped”, we can no longer accurately track when the pointer may be accessed, disabling most optimizations. LLVM currently provides a nocapture attribute, which indicates that a call does not capture a certain parameter. However, this is an all-or-nothing attribute, which does not allow us to distinguish several different kinds of captures. I have proposed to replace nocapture with a captures(...) attribute, which allows a finer-grained specification. In particular, it separates capturing the address of the pointer, which is information about its integral value, and capturing the provenance of the pointer, which is the permission to perform memory accesses through the pointer. Provenance captures are what we usually call an “escape”, and only provenance captures are relevant for the purposes of alias analysis. Address and provenance are often captured together, but not always. For example, a pointer comparison only captures the address, but not the provenance. Rust makes address-only capture particularly clear with its strict provenance APIs, where ptr.addr() only returns the address of the pointer, without its provenance. The new captures attribute additionally allows specifying whether the full provenance is captured, or only read-only provenance. For example, a & (Freeze) reference argument in Rust could use readonly captures(address, read_provenance) attributes to indicate that not only does the function not modify the argument directly, it also can’t stash it somewhere and perform a modification through it after the function returns. As many optimizations are only inhibited by potential writes (“clobbers”), this is an important distinction. I have implemented the first step for this proposal and plan to continue this in the new year. Furthermore, this is only the first step towards improving capture analysis in LLVM. Some followups I have in mind are: Support captures attribute (or something similar) on ptrtoint instructions. This would allow us to accurately represent the semantics of ptr.add() in Rust. Support !captures metadata on stores. This would allow us to indicate that values passed to println!() in Rust are read-only escapes. Add a first-class operation for pointer subtraction, which is currently done through ptrtoint . Three-way comparison intrinsics Three-way comparisons return the comparison result as one of -1 (smaller), 0 (equal) or 1 (greater). Historically, LLVM did not have a canonical representation for such comparisons, instead they could be represented using a large number of different instruction sequences, none of which produced ideal optimization outcomes and codegen for all targets. I proposed adding three-way comparison intrinsics llvm.ucmp and llvm.scmp to represent such comparisons. Volodymyr Vasylkun implemented these as a GSoC project, including high-quality codegen, various middle-end optimizations and canonicalization to the new intrinsics. There is a short blog post on the topic, which is worth reading, and has an example illustrating how codegen improves for the C++ spaceship operator <=> . APInt assertions When constructing an arbitrary-precision integer (APInt) from a uint64_t , we previously performed implicit truncation: If the passed value was larger than the specified bit width, we’d just drop the top bits. Sometimes, this is exactly what we want, but in other cases it hides a bug. A particular common issue is to write something like APInt(BW, -1) without setting the isSigned=true flag. This would work correctly for bit widths <= 64, and then produce incorrect results for larger integers, which have much less coverage (both in terms of tests and in-the-wild usage). The APInt constructor now asserts that the passed value is a valid N-bit signed/unsigned integer. It took a good while to get there, because a lot of existing code had to be adjusted. This work is not fully complete yet, because ConstantInt::get() still enables implicit truncation. Changing this will require more work to adjust existing code. Quality of life improvements I have made a number of quality of life improvements when it comes to things I do often. Part of this are improvements to the IR parser in three areas: Do not require declarations or type mangling for intrinsics. You can now write call i32 @llvm.smax(i32 %x, i32 %y) and the parser will automatically determine the correct type mangling and insert the intrinsic declaration. This removes a big annoyance when writing proofs. Don’t require unnamed values to be consecutive. This makes it much easier to reduce IR with unnamed values by hand. Allow parsing of incomplete IR under the -allow-incomplete-ir option. This makes it easy to convert things like -print-after-all output into valid IR. Additionally, I have added support for pretty crash stacks for the new pass manager. This means that crashes now print which pass (with which options) crashed on which function. I have also written an InstCombine contributor guide . This helps new contributors write good PRs for InstCombine (and the middle-end in general), which makes the review process a lot more efficient. Another improvement to reviewer life was to remove complexity-based canonicalization . While well-intentioned, in practice this transform just made it hard to write test coverage that does what you intended, which especially new contributors often struggled with. This removes the need for the “thwart” test pattern. Compilation-time I have not done much work on compile-time myself this year, but other people have picked up the slack, so I’ll provide a summary of their work. Here is how compile-time developed since the start of 2024: The largest wins this year are in the ReleaseLTO-g configuration (about 10%). A big reason for this is the switch from debug intrinsics to debug records , which moves debug information out of the instruction list. This benefits all builds with debuginfo, but particularly optimized debuginfo builds. The two commits switching to the new representation amount to about 4% improvement ( 1 , 2 ). There will be some additional improvements once support for debug intrinsics is removed. Unoptimized O0-g configurations saw an improvement of about 4-6% this year, mostly thanks to a concerted effort by aengelke to improve unoptimized build times for JIT use cases. One of the largest individual wins was adding a fast-path to RegAllocFast, the O0 register allocator, for a 0.8% improvement . Caching the register alias iterator also produced a 0.6-0.8% improvement . Not computing unnecessary symbol names gave a 0.4% improvement and using a bump-pointer allocator for MCFragments gave a 0.5% improvement . Though that one came at a cost of increased max-rss, so I’m not sure if it was a good tradeoff. There were also many other small improvements, that add up to a large overall improvement. One regression for unoptimized builds was to stop using -mrelax-all . While this was a 0.6% compile-time regression , it also decreased binary size by 4-5% , which is a pretty good deal. Optimized builds also saw wins of about 5-7%. One of the key changes was the introduction of block numbers , which assign a unique number to each basic block in a function. These can then be used to map blocks to dominator tree nodes ( 1 , 2 ) using a vector instead of a hashtable, significantly reducing the cost of accesses. This results in a ~1.2% improvement ( 1 , 2 ), and will probably be useful for more things in the future. Another interesting changes is to not rerun the same pass if the IR did not change in the meantime, for a 0.5% improvement . I think this is currently less effective than it could be, because we have some passes that keep toggling the IR between two forms (e.g. adding and removing LCSSA phi nodes). A somewhat different compile-time improvement was a change to clang’s bitfield codegen . This resulted in a 0.3-0.6% improvement on stage 2 builds (where clang is compiled with clang). It’s an optimization improvement that has a large enough impact to affect compilation times. There was also a change that improves the time to build clang, which was the introduction of DynamicRecursiveASTVisitor , and migration of most visitors to use it. This switches many AST visitors away from huge CRTP template instantiations to using dynamic dispatch. The PR switching most visitors improved clang build times by 2% and the size of the resulting binary by nearly 6% (!). This does come at a small compile-time cost for small files, due to the increase in dynamic relocations. To close with some optimizations I actually did myself, I implemented a series of improvements to the SmallPtrSet data structure ( 1 , 2 , 3 ), to make sure that the fast-path is as efficient as possible. These add up to a 0.7% improvement ( 1 , 2 , 3 ). I also made a series of improvements to ScalarEvolution::computeConstantDifference() to make it usable in place of ScalarEvolution::getMinusSCEV() during SLP vectorization. This was a 10% improvement on one specific benchmark. Rust I updated Rust to LLVM 18 and LLVM 19 this year. Both of these came with very nice perf results ( LLVM 18 , LLVM 19 ). The LLVM 18 upgrade had quite a few complications, but probably the most disproportionately annoying was the fact that the LLVM soname changed from libLLVM-18.so to libLLVM.so.18.1 , with libLLVM-18.so being a symlink now. Threading the needle between all the constraints coming from Rust dylib linking, rustup and LLVM, this ultimately required converting libLLVM-18.so into a linker script. The LLVM 19 upgrade went pretty smoothly. One change worth mentioning is that LLVM 19 enabled the +multivalue and +extern-types wasm features by default. We could have handled this in various ways, but the decision was that Rust’s wasm32-unknown-unknown target should continue following Clang/LLVM defaults over time. There is a blog post with more information. We have also reached the point where we align with upstream LLVM very closely: We only carry a single permanent patch, and most backports are now handled via upstream patch releases, instead of Rust-only backports. I also implemented what has to be my lowest-effort compile-time win ever, which is to disable LLVM IR verification in production builds more thoroughly. This is a large win for debug builds. Finally, I presented a keynote at this year’s LLVM developer meeting with the title “Rust ❤️ LLVM” ( slides , recording ), discussing how Rust uses LLVM and some of the challenges involved. I had a lot of fruitful discussions on the topic as a result. The only downside is that people now think I know a lot more about Rust than I actually do… I’d also like to give a shout-out to DianQK , who has helped a lot with tracking down and fixing LLVM bugs that affect Rust. Packaging This year, the way LLVM is packaged for Fedora, CentOS Stream and RHEL underwent some major changes. This is something the entire LLVM team at Red Hat worked on to some degree. The first, and most significant, is that we now build multiple LLVM subprojects (llvm, clang, lld, lldb, compiler-rt, libomp, and python-lit) as part of a single build, while keeping the separate binary RPMs. Previously, we used standalone builds for each subproject. While standalone builds have their upsides (like faster builds if you’re only changing one subproject), they are very much a second class citizen in upstream LLVM, and typically only used by distros. Using a monorepo build moves us to a better supported configuration. Additionally, it simplifies the build process, because we previously had to do a coordinated rebuild of 14 different packages for each LLVM point release. For LLVM 19, we’re down to a single build on RHEL and 8 builds on Fedora, which ships more subprojects. For LLVM 20 we should get down to 4 builds, as we merge more subprojects into the monorepo build. The second change is related to the nightly snapshot builds we have been offering for a while already. These are now maintained directly on the Fedora rawhide branch of rpms/llvm , which supports building both the current LLVM version (19) and snapshots for the upcoming one (20) from the same spec file. This avoids divergence between the two branches, and (in theory) reduces an LLVM major version upgrade to a change in the build configuration. The final change is to consolidate the spec file for all operating systems we build for. The Fedora rawhide spec file can also be used to build for RHEL 8, 9 and 10 now. Again, this helps to prevent unintentional divergence between operating systems. Additionally, it means that LLVM snapshot builds are now available for RHEL as well. Other I have been nominated as the new lead maintainer for LLVM, taking over from Chris Lattner. What does this mean? Even more code review, of course! According to graphite, I’ve reviewed more than 2300 pull requests last year. I have also spent some time getting LLVM’s badly outdated list of maintainers up to date (though this isn’t entirely complete yet). N3322 , the C proposal I worked on together with Aaron Ballman, has been accepted for C2y, making memcpy(NULL, NULL, 0) well-defined . To close this blog post, I’d like to thank dtcxzyw for his incredible work on LLVM, both in identifying and fixing numerous miscompilation issues, and implementing many optimizations with demonstrable usefulness. llvm-opt-benchmark has quickly become an indispensable tool for analyzing optimization impact. If you liked this article, you may want to browse my other articles or follow me on Twitter or Mastodon . | 2026-01-13T08:49:46 |
https://docs.python.org/3.15/whatsnew/3.15.html#whatsnew315-sampling-profiler | What’s new in Python 3.15 — Python 3.15.0a3 documentation Theme Auto Light Dark Table of Contents What’s new in Python 3.15 Summary – Release highlights New features PEP 799 : A dedicated profiling package Tachyon: High frequency statistical sampling profiler Improved error messages Other language changes New modules math.integer Improved modules argparse base64 & binascii calendar collections collections.abc concurrent.futures dataclasses dbm difflib functools hashlib http.client http.cookies inspect locale math mimetypes mmap os os.path resource shelve socket sqlite3 ssl sys tarfile timeit tkinter types unicodedata unittest venv warnings xml.parsers.expat zlib Optimizations csv Upgraded JIT compiler Removed ctypes glob http.server importlib.resources pathlib platform sre_* sysconfig threading typing wave zipimport Deprecated New deprecations Pending removal in Python 3.16 Pending removal in Python 3.17 Pending removal in Python 3.18 Pending removal in Python 3.19 Pending removal in Python 3.20 Pending removal in future versions C API changes New features Changed C APIs Porting to Python 3.15 Removed C APIs Deprecated C APIs Build changes Porting to Python 3.15 Previous topic What’s New in Python Next topic What’s new in Python 3.14 This page Report a bug Show source Navigation index modules | next | previous | Python » 3.15.0a3 Documentation » What’s New in Python » What’s new in Python 3.15 | Theme Auto Light Dark | What’s new in Python 3.15 ¶ Editor : Hugo van Kemenade This article explains the new features in Python 3.15, compared to 3.14. For full details, see the changelog . Note Prerelease users should be aware that this document is currently in draft form. It will be updated substantially as Python 3.15 moves towards release, so it’s worth checking back even after reading earlier versions. Summary – Release highlights ¶ PEP 799 : A dedicated profiling package for organizing Python profiling tools PEP 799 : Tachyon: High frequency statistical sampling profiler profiling tools PEP 686 : Python now uses UTF-8 as the default encoding PEP 782 : A new PyBytesWriter C API to create a Python bytes object The JIT compiler has been significantly upgraded Improved error messages New features ¶ PEP 799 : A dedicated profiling package ¶ A new profiling module has been added to organize Python’s built-in profiling tools under a single, coherent namespace. This module contains: profiling.tracing : deterministic function-call tracing (relocated from cProfile ). profiling.sampling : a new statistical sampling profiler (named Tachyon). The cProfile module remains as an alias for backwards compatibility. The profile module is deprecated and will be removed in Python 3.17. See also PEP 799 for further details. (Contributed by Pablo Galindo and László Kiss Kollár in gh-138122 .) Tachyon: High frequency statistical sampling profiler ¶ A new statistical sampling profiler (Tachyon) has been added as profiling.sampling . This profiler enables low-overhead performance analysis of running Python processes without requiring code modification or process restart. Unlike deterministic profilers (such as profiling.tracing ) that instrument every function call, the sampling profiler periodically captures stack traces from running processes. This approach provides virtually zero overhead while achieving sampling rates of up to 1,000,000 Hz , making it the fastest sampling profiler available for Python (at the time of its contribution) and ideal for debugging performance issues in production environments. This capability is particularly valuable for debugging performance issues in production systems where traditional profiling approaches would be too intrusive. Key features include: Zero-overhead profiling : Attach to any running Python process without affecting its performance. Ideal for production debugging where you can’t afford to restart or slow down your application. No code modification required : Profile existing applications without restart. Simply point the profiler at a running process by PID and start collecting data. Flexible target modes : Profile running processes by PID ( attach ) - attach to already-running applications Run and profile scripts directly ( run ) - profile from the very start of execution Execute and profile modules ( run -m ) - profile packages run as python -m module Multiple profiling modes : Choose what to measure based on your performance investigation: Wall-clock time ( --mode wall , default): Measures real elapsed time including I/O, network waits, and blocking operations. Use this to understand where your program spends calendar time, including when waiting for external resources. CPU time ( --mode cpu ): Measures only active CPU execution time, excluding I/O waits and blocking. Use this to identify CPU-bound bottlenecks and optimize computational work. GIL-holding time ( --mode gil ): Measures time spent holding Python’s Global Interpreter Lock. Use this to identify which threads dominate GIL usage in multi-threaded applications. Exception handling time ( --mode exception ): Captures samples only from threads with an active exception. Use this to analyze exception handling overhead. Thread-aware profiling : Option to profile all threads ( -a ) or just the main thread, essential for understanding multi-threaded application behavior. Multiple output formats : Choose the visualization that best fits your workflow: --pstats : Detailed tabular statistics compatible with pstats . Shows function-level timing with direct and cumulative samples. Best for detailed analysis and integration with existing Python profiling tools. --collapsed : Generates collapsed stack traces (one line per stack). This format is specifically designed for creating flamegraphs with external tools like Brendan Gregg’s FlameGraph scripts or speedscope. --flamegraph : Generates a self-contained interactive HTML flamegraph using D3.js. Opens directly in your browser for immediate visual analysis. Flamegraphs show the call hierarchy where width represents time spent, making it easy to spot bottlenecks at a glance. --gecko : Generates Gecko Profiler format compatible with Firefox Profiler ( https://profiler.firefox.com ). Upload the output to Firefox Profiler for advanced timeline-based analysis with features like stack charts, markers, and network activity. --heatmap : Generates an interactive HTML heatmap visualization with line-level sample counts. Creates a directory with per-file heatmaps showing exactly where time is spent at the source code level. Live interactive mode : Real-time TUI profiler with a top-like interface ( --live ). Monitor performance as your application runs with interactive sorting and filtering. Async-aware profiling : Profile async/await code with task-based stack reconstruction ( --async-aware ). See which coroutines are consuming time, with options to show only running tasks or all tasks including those waiting. Opcode-level profiling : Gather bytecode opcode information for instruction-level profiling ( --opcodes ). Shows which bytecode instructions are executing, including specializations from the adaptive interpreter. See profiling.sampling for the complete documentation, including all available output formats, profiling modes, and configuration options. (Contributed by Pablo Galindo and László Kiss Kollár in gh-135953 and gh-138122 .) Improved error messages ¶ The interpreter now provides more helpful suggestions in AttributeError exceptions when accessing an attribute on an object that does not exist, but a similar attribute is available through one of its members. For example, if the object has an attribute that itself exposes the requested name, the error message will suggest accessing it via that inner attribute: @dataclass class Circle : radius : float @property def area ( self ) -> float : return pi * self . radius ** 2 class Container : def __init__ ( self , inner : Circle ) -> None : self . inner = inner circle = Circle ( radius = 4.0 ) container = Container ( circle ) print ( container . area ) Running this code now produces a clearer suggestion: Traceback (most recent call last): File "/home/pablogsal/github/python/main/lel.py", line 42, in <module> print(container.area) ^^^^^^^^^^^^^^ AttributeError : 'Container' object has no attribute 'area'. Did you mean: 'inner.area'? Other language changes ¶ Python now uses UTF-8 as the default encoding, independent of the system’s environment. This means that I/O operations without an explicit encoding, for example, open('flying-circus.txt') , will use UTF-8. UTF-8 is a widely-supported Unicode character encoding that has become a de facto standard for representing text, including nearly every webpage on the internet, many common file formats, programming languages, and more. This only applies when no encoding argument is given. For best compatibility between versions of Python, ensure that an explicit encoding argument is always provided. The opt-in encoding warning can be used to identify code that may be affected by this change. The special encoding='locale' argument uses the current locale encoding, and has been supported since Python 3.10. To retain the previous behaviour, Python’s UTF-8 mode may be disabled with the PYTHONUTF8=0 environment variable or the -X utf8=0 command-line option. See also PEP 686 for further details. (Contributed by Adam Turner in gh-133711 ; PEP 686 written by Inada Naoki.) Several error messages incorrectly using the term “argument” have been corrected. (Contributed by Stan Ulbrych in gh-133382 .) The interpreter now tries to provide a suggestion when delattr() fails due to a missing attribute. When an attribute name that closely resembles an existing attribute is used, the interpreter will suggest the correct attribute name in the error message. For example: >>> class A : ... pass >>> a = A () >>> a . abcde = 1 >>> del a . abcdf Traceback (most recent call last): ... AttributeError : 'A' object has no attribute 'abcdf'. Did you mean: 'abcde'? (Contributed by Nikita Sobolev and Pranjal Prajapati in gh-136588 .) Unraisable exceptions are now highlighted with color by default. This can be controlled by environment variables . (Contributed by Peter Bierma in gh-134170 .) The __repr__() of ImportError and ModuleNotFoundError now shows “name” and “path” as name=<name> and path=<path> if they were given as keyword arguments at construction time. (Contributed by Serhiy Storchaka, Oleg Iarygin, and Yoav Nir in gh-74185 .) The __dict__ and __weakref__ descriptors now use a single descriptor instance per interpreter, shared across all types that need them. This speeds up class creation, and helps avoid reference cycles. (Contributed by Petr Viktorin in gh-135228 .) The -W option and the PYTHONWARNINGS environment variable can now specify regular expressions instead of literal strings to match the warning message and the module name, if the corresponding field starts and ends with a forward slash ( / ). (Contributed by Serhiy Storchaka in gh-134716 .) Functions that take timestamp or timeout arguments now accept any real numbers (such as Decimal and Fraction ), not only integers or floats, although this does not improve precision. (Contributed by Serhiy Storchaka in gh-67795 .) Added bytearray.take_bytes(n=None, /) to take bytes out of a bytearray without copying. This enables optimizing code which must return bytes after working with a mutable buffer of bytes such as data buffering, network protocol parsing, encoding, decoding, and compression. Common code patterns which can be optimized with take_bytes() are listed below. Suggested optimizing refactors ¶ Description Old New Return bytes after working with bytearray def read () -> bytes : buffer = bytearray ( 1024 ) ... return bytes ( buffer ) def read () -> bytes : buffer = bytearray ( 1024 ) ... return buffer . take_bytes () Empty a buffer getting the bytes buffer = bytearray ( 1024 ) ... data = bytes ( buffer ) buffer . clear () buffer = bytearray ( 1024 ) ... data = buffer . take_bytes () Split a buffer at a specific separator buffer = bytearray ( b 'abc \n def' ) n = buffer . find ( b ' \n ' ) data = bytes ( buffer [: n + 1 ]) del buffer [: n + 1 ] assert data == b 'abc' assert buffer == bytearray ( b 'def' ) buffer = bytearray ( b 'abc \n def' ) n = buffer . find ( b ' \n ' ) data = buffer . take_bytes ( n + 1 ) Split a buffer at a specific separator; discard after the separator buffer = bytearray ( b 'abc \n def' ) n = buffer . find ( b ' \n ' ) data = bytes ( buffer [: n ]) buffer . clear () assert data == b 'abc' assert len ( buffer ) == 0 buffer = bytearray ( b 'abc \n def' ) n = buffer . find ( b ' \n ' ) buffer . resize ( n ) data = buffer . take_bytes () (Contributed by Cody Maloney in gh-139871 .) Many functions related to compiling or parsing Python code, such as compile() , ast.parse() , symtable.symtable() , and importlib.abc.InspectLoader.source_to_code() , now allow the module name to be passed. It is needed to unambiguously filter syntax warnings by module name. (Contributed by Serhiy Storchaka in gh-135801 .) Allowed defining the __dict__ and __weakref__ __slots__ for any class. (Contributed by Serhiy Storchaka in gh-41779 .) Allowed defining any __slots__ for a class derived from tuple (including classes created by collections.namedtuple() ). (Contributed by Serhiy Storchaka in gh-41779 .) The slice type now supports subscription, making it a generic type . (Contributed by James Hilton-Balfe in gh-128335 .) New modules ¶ math.integer ¶ This module provides access to the mathematical functions for integer arguments ( PEP 791 ). (Contributed by Serhiy Storchaka in gh-81313 .) Improved modules ¶ argparse ¶ The BooleanOptionalAction action supports now single-dash long options and alternate prefix characters. (Contributed by Serhiy Storchaka in gh-138525 .) Changed the suggest_on_error parameter of argparse.ArgumentParser to default to True . This enables suggestions for mistyped arguments by default. (Contributed by Jakob Schluse in gh-140450 .) Added backtick markup support in description and epilog text to highlight inline code when color output is enabled. (Contributed by Savannah Ostrowski in gh-142390 .) base64 & binascii ¶ CPython’s underlying base64 implementation now encodes 2x faster and decodes 3x faster thanks to simple CPU pipelining optimizations. (Contributed by Gregory P. Smith & Serhiy Storchaka in gh-143262 .) calendar ¶ Calendar pages generated by the calendar.HTMLCalendar class now support dark mode and have been migrated to the HTML5 standard for improved accessibility. (Contributed by Jiahao Li and Hugo van Kemenade in gh-137634 .) The calendar ’s command-line HTML output now accepts the year-month option: python -m calendar -t html 2009 06 . (Contributed by Pål Grønås Drange in gh-140212 .) collections ¶ Added collections.Counter.__xor__() and collections.Counter.__ixor__() to compute the symmetric difference between Counter objects. (Contributed by Raymond Hettinger in gh-138682 .) collections.abc ¶ collections.abc.ByteString has been removed from collections.abc.__all__ . collections.abc.ByteString has been deprecated since Python 3.12, and is scheduled for removal in Python 3.17. The following statements now cause DeprecationWarning s to be emitted at runtime: from collections.abc import ByteString import collections.abc; collections.abc.ByteString . DeprecationWarning s were already emitted if collections.abc.ByteString was subclassed or used as the second argument to isinstance() or issubclass() , but warnings were not previously emitted if it was merely imported or accessed from the collections.abc module. concurrent.futures ¶ Improved error reporting when a child process in a concurrent.futures.ProcessPoolExecutor terminates abruptly. The resulting traceback will now tell you the PID and exit code of the terminated process. (Contributed by Jonathan Berg in gh-139486 .) dataclasses ¶ Annotations for generated __init__ methods no longer include internal type names. dbm ¶ Added new reorganize() methods to dbm.dumb and dbm.sqlite3 which allow to recover unused free space previously occupied by deleted entries. (Contributed by Andrea Oliveri in gh-134004 .) difflib ¶ Introduced the optional color parameter to difflib.unified_diff() , enabling color output similar to git diff . This can be controlled by environment variables . (Contributed by Douglas Thor in gh-133725 .) Improved the styling of HTML diff pages generated by the difflib.HtmlDiff class, and migrated the output to the HTML5 standard. (Contributed by Jiahao Li in gh-134580 .) functools ¶ singledispatchmethod() now supports non- descriptor callables. (Contributed by Serhiy Storchaka in gh-140873 .) hashlib ¶ Ensure that hash functions guaranteed to be always available exist as attributes of hashlib even if they will not work at runtime due to missing backend implementations. For instance, hashlib.md5 will no longer raise AttributeError if OpenSSL is not available and Python has been built without MD5 support. (Contributed by Bénédikt Tran in gh-136929 .) http.client ¶ A new max_response_headers keyword-only parameter has been added to HTTPConnection and HTTPSConnection constructors. This parameter overrides the default maximum number of allowed response headers. (Contributed by Alexander Enrique Urieles Nieto in gh-131724 .) http.cookies ¶ Allow ‘ " ’ double quotes in cookie values. (Contributed by Nick Burns and Senthil Kumaran in gh-92936 .) inspect ¶ Add parameters inherit_class_doc and fallback_to_class_doc for getdoc() . (Contributed by Serhiy Storchaka in gh-132686 .) locale ¶ setlocale() now supports language codes with @ -modifiers. @ -modifiers are no longer silently removed in getlocale() , but included in the language code. (Contributed by Serhiy Storchaka in gh-137729 .) Undeprecate the locale.getdefaultlocale() function. (Contributed by Victor Stinner in gh-130796 .) math ¶ Add math.isnormal() and math.issubnormal() functions. (Contributed by Sergey B Kirpichev in gh-132908 .) Add math.fmax() , math.fmin() and math.signbit() functions. (Contributed by Bénédikt Tran in gh-135853 .) mimetypes ¶ Add application/node MIME type for .cjs extension. (Contributed by John Franey in gh-140937 .) Add application/toml . (Contributed by Gil Forcada in gh-139959 .) Rename application/x-texinfo to application/texinfo . (Contributed by Charlie Lin in gh-140165 .) Changed the MIME type for .ai files to application/pdf . (Contributed by Stan Ulbrych in gh-141239 .) mmap ¶ mmap.mmap now has a trackfd parameter on Windows; if it is False , the file handle corresponding to fileno will not be duplicated. (Contributed by Serhiy Storchaka in gh-78502 .) Added the mmap.mmap.set_name() method to annotate an anonymous memory mapping if Linux kernel supports PR_SET_VMA_ANON_NAME (Linux 5.17 or newer). (Contributed by Donghee Na in gh-142419 .) os ¶ Add os.statx() on Linux kernel versions 4.11 and later with glibc versions 2.28 and later. (Contributed by Jeffrey Bosboom and Victor Stinner in gh-83714 .) os.path ¶ Add support of the all-but-last mode in realpath() . (Contributed by Serhiy Storchaka in gh-71189 .) The strict parameter to os.path.realpath() accepts a new value, os.path.ALLOW_MISSING . If used, errors other than FileNotFoundError will be re-raised; the resulting path can be missing but it will be free of symlinks. (Contributed by Petr Viktorin for CVE 2025-4517 .) resource ¶ Add new constants: RLIMIT_NTHR , RLIMIT_UMTXP , RLIMIT_THREADS , RLIM_SAVED_CUR , and RLIM_SAVED_MAX . (Contributed by Serhiy Storchaka in gh-137512 .) shelve ¶ Added new reorganize() method to shelve used to recover unused free space previously occupied by deleted entries. (Contributed by Andrea Oliveri in gh-134004 .) socket ¶ Add constants for the ISO-TP CAN protocol. (Contributed by Patrick Menschel and Stefan Tatschner in gh-86819 .) sqlite3 ¶ The command-line interface has several new features: SQL keyword completion on <tab>. (Contributed by Long Tan in gh-133393 .) Prompts, error messages, and help text are now colored. This is enabled by default, see Controlling color for details. (Contributed by Stan Ulbrych and Łukasz Langa in gh-133461 .) Table, index, trigger, view, column, function, and schema completion on <tab>. (Contributed by Long Tan in gh-136101 .) ssl ¶ Indicate through ssl.HAS_PSK_TLS13 whether the ssl module supports “External PSKs” in TLSv1.3, as described in RFC 9258. (Contributed by Will Childs-Klein in gh-133624 .) Added new methods for managing groups used for SSL key agreement ssl.SSLContext.set_groups() sets the groups allowed for doing key agreement, extending the previous ssl.SSLContext.set_ecdh_curve() method. This new API provides the ability to list multiple groups and supports fixed-field and post-quantum groups in addition to ECDH curves. This method can also be used to control what key shares are sent in the TLS handshake. ssl.SSLSocket.group() returns the group selected for doing key agreement on the current connection after the TLS handshake completes. This call requires OpenSSL 3.2 or later. ssl.SSLContext.get_groups() returns a list of all available key agreement groups compatible with the minimum and maximum TLS versions currently set in the context. This call requires OpenSSL 3.5 or later. (Contributed by Ron Frederick in gh-136306 .) Added a new method ssl.SSLContext.set_ciphersuites() for setting TLS 1.3 ciphers. For TLS 1.2 or earlier, ssl.SSLContext.set_ciphers() should continue to be used. Both calls can be made on the same context and the selected cipher suite will depend on the TLS version negotiated when a connection is made. (Contributed by Ron Frederick in gh-137197 .) Added new methods for managing signature algorithms: ssl.get_sigalgs() returns a list of all available TLS signature algorithms. This call requires OpenSSL 3.4 or later. ssl.SSLContext.set_client_sigalgs() sets the signature algorithms allowed for certificate-based client authentication. ssl.SSLContext.set_server_sigalgs() sets the signature algorithms allowed for the server to complete the TLS handshake. ssl.SSLSocket.client_sigalg() returns the signature algorithm selected for client authentication on the current connection. This call requires OpenSSL 3.5 or later. ssl.SSLSocket.server_sigalg() returns the signature algorithm selected for the server to complete the TLS handshake on the current connection. This call requires OpenSSL 3.5 or later. (Contributed by Ron Frederick in gh-138252 .) sys ¶ Add sys.abi_info namespace to improve access to ABI information. (Contributed by Klaus Zimmermann in gh-137476 .) tarfile ¶ data_filter() now normalizes symbolic link targets in order to avoid path traversal attacks. (Contributed by Petr Viktorin in gh-127987 and CVE 2025-4138 .) extractall() now skips fixing up directory attributes when a directory was removed or replaced by another kind of file. (Contributed by Petr Viktorin in gh-127987 and CVE 2024-12718 .) extract() and extractall() now (re-)apply the extraction filter when substituting a link (hard or symbolic) with a copy of another archive member, and when fixing up directory attributes. The former raises a new exception, LinkFallbackError . (Contributed by Petr Viktorin for CVE 2025-4330 and CVE 2024-12718 .) extract() and extractall() no longer extract rejected members when errorlevel() is zero. (Contributed by Matt Prodani and Petr Viktorin in gh-112887 and CVE 2025-4435 .) extract() and extractall() now replace slashes by backslashes in symlink targets on Windows to prevent creation of corrupted links. (Contributed by Christoph Walcher in gh-57911 .) timeit ¶ The command-line interface now colorizes error tracebacks by default. This can be controlled with environment variables . (Contributed by Yi Hong in gh-139374 .) tkinter ¶ The tkinter.Text.search() method now supports two additional arguments: nolinestop which allows the search to continue across line boundaries; and strictlimits which restricts the search to within the specified range. (Contributed by Rihaan Meher in gh-130848 ) A new method tkinter.Text.search_all() has been introduced. This method allows for searching for all matches of a pattern using Tcl’s -all and -overlap options. (Contributed by Rihaan Meher in gh-130848 ) types ¶ Expose the write-through locals() proxy type as types.FrameLocalsProxyType . This represents the type of the frame.f_locals attribute, as described in PEP 667 . unicodedata ¶ The Unicode database has been updated to Unicode 17.0.0. Add unicodedata.isxidstart() and unicodedata.isxidcontinue() functions to check whether a character can start or continue a Unicode Standard Annex #31 identifier. (Contributed by Stan Ulbrych in gh-129117 .) unittest ¶ unittest.TestCase.assertLogs() will now accept a formatter to control how messages are formatted. (Contributed by Garry Cairns in gh-134567 .) venv ¶ On POSIX platforms, platlib directories will be created if needed when creating virtual environments, instead of using lib64 -> lib symlink. This means purelib and platlib of virtual environments no longer share the same lib directory on platforms where sys.platlibdir is not equal to lib . (Contributed by Rui Xi in gh-133951 .) warnings ¶ Improve filtering by module in warnings.warn_explicit() if no module argument is passed. It now tests the module regular expression in the warnings filter not only against the filename with .py stripped, but also against module names constructed starting from different parent directories of the filename (with /__init__.py , .py and, on Windows, .pyw stripped). (Contributed by Serhiy Storchaka in gh-135801 .) xml.parsers.expat ¶ Add SetAllocTrackerActivationThreshold() and SetAllocTrackerMaximumAmplification() to xmlparser objects to tune protections against disproportional amounts of dynamic memory usage from within an Expat parser. (Contributed by Bénédikt Tran in gh-90949 .) Add SetBillionLaughsAttackProtectionActivationThreshold() and SetBillionLaughsAttackProtectionMaximumAmplification() to xmlparser objects to tune protections against billion laughs attacks. (Contributed by Bénédikt Tran in gh-90949 .) zlib ¶ Allow combining two Adler-32 checksums via adler32_combine() . (Contributed by Callum Attryde and Bénédikt Tran in gh-134635 .) Allow combining two CRC-32 checksums via crc32_combine() . (Contributed by Bénédikt Tran in gh-134635 .) Optimizations ¶ Builds using Visual Studio 2026 (MSVC 18) may now use the new tail-calling interpreter . Results on Visual Studio 18.1.1 report between 15-20% speedup on the geometric mean of pyperformance on Windows x86-64 over the switch-case interpreter on an AMD Ryzen 7 5800X. We have observed speedups ranging from 14% for large pure-Python libraries to 40% for long-running small pure-Python scripts on Windows. This was made possible by a new feature introduced in MSVC 18. (Contributed by Chris Eibl, Ken Jin, and Brandt Bucher in gh-143068 . Special thanks to the MSVC team including Hulon Jenkins.) csv ¶ csv.Sniffer.sniff() delimiter detection is now up to 1.6x faster. (Contributed by Maurycy Pawłowski-Wieroński in gh-137628 .) Upgraded JIT compiler ¶ Results from the pyperformance benchmark suite report 4-5% geometric mean performance improvement for the JIT over the standard CPython interpreter built with all optimizations enabled on x86-64 Linux. On AArch64 macOS, the JIT has a 7-8% speedup over the tail calling interpreter with all optimizations enabled. The speedups for JIT builds versus no JIT builds range from roughly 15% slowdown to over 100% speedup (ignoring the unpack_sequence microbenchmark) on x86-64 Linux and AArch64 macOS systems. Attention These results are not yet final. The major upgrades to the JIT are: LLVM 21 build-time dependency New tracing frontend Basic register allocation in the JIT More JIT optimizations Better machine code generation LLVM 21 build-time dependency The JIT compiler now uses LLVM 21 for build-time stencil generation. As always, LLVM is only needed when building CPython with the JIT enabled; end users running Python do not need LLVM installed. Instructions for installing LLVM can be found in the JIT compiler documentation for all supported platforms. (Contributed by Savannah Ostrowski in gh-140973 .) A new tracing frontend The JIT compiler now supports significantly more bytecode operations and control flow than in Python 3.14, enabling speedups on a wider variety of code. For example, simple Python object creation is now understood by the 3.15 JIT compiler. Overloaded operations and generators are also partially supported. This was made possible by an overhauled JIT tracing frontend that records actual execution paths through code, rather than estimating them as the previous implementation did. (Contributed by Ken Jin in gh-139109 . Support for Windows added by Mark Shannon in gh-141703 .) Basic register allocation in the JIT A basic form of register allocation has been added to the JIT compiler’s optimizer. This allows the JIT compiler to avoid certain stack operations altogether and instead operate on registers. This allows the JIT to produce more efficient traces by avoiding reads and writes to memory. (Contributed by Mark Shannon in gh-135379 .) More JIT optimizations More constant-propagation is now performed. This means when the JIT compiler detects that certain user code results in constants, the code can be simplified by the JIT. (Contributed by Ken Jin and Savannah Ostrowski in gh-132732 .) The JIT avoids reference count s where possible. This generally reduces the cost of most operations in Python. (Contributed by Ken Jin, Donghee Na, Zheao Li, Hai Zhu, Savannah Ostrowski, Reiden Ong, Noam Cohen, Tomas Roun, PuQing, and Cajetan Rodrigues in gh-134584 .) Better machine code generation The JIT compiler’s machine code generator now produces better machine code for x86-64 and AArch64 macOS and Linux targets. In general, users should experience lower memory usage for generated machine code and more efficient machine code versus the old JIT. (Contributed by Brandt Bucher in gh-136528 and gh-136528 . Implementation for AArch64 contributed by Mark Shannon in gh-139855 . Additional optimizations for AArch64 contributed by Mark Shannon and Diego Russo in gh-140683 and gh-142305 .) Removed ¶ ctypes ¶ Removed the undocumented function ctypes.SetPointerType() , which has been deprecated since Python 3.13. (Contributed by Bénédikt Tran in gh-133866 .) glob ¶ Removed the undocumented glob.glob0() and glob.glob1() functions, which have been deprecated since Python 3.13. Use glob.glob() and pass a directory to its root_dir argument instead. (Contributed by Barney Gale in gh-137466 .) http.server ¶ Removed the CGIHTTPRequestHandler class and the --cgi flag from the python -m http.server command-line interface. They were deprecated in Python 3.13. (Contributed by Bénédikt Tran in gh-133810 .) importlib.resources ¶ Removed deprecated package parameter from importlib.resources.files() function. (Contributed by Semyon Moroz in gh-138044 ) pathlib ¶ Removed deprecated pathlib.PurePath.is_reserved() . Use os.path.isreserved() to detect reserved paths on Windows. (Contributed by Nikita Sobolev in gh-133875 .) platform ¶ Removed the platform.java_ver() function, which was deprecated since Python 3.13. (Contributed by Alexey Makridenko in gh-133604 .) sre_* ¶ Removed sre_compile , sre_constants and sre_parse modules. (Contributed by Stan Ulbrych in gh-135994 .) sysconfig ¶ Removed the check_home parameter of sysconfig.is_python_build() . (Contributed by Filipe Laíns in gh-92897 .) threading ¶ Remove support for arbitrary positional or keyword arguments in the C implementation of RLock objects. This was deprecated in Python 3.14. (Contributed by Bénédikt Tran in gh-134087 .) typing ¶ The undocumented keyword argument syntax for creating NamedTuple classes (for example, Point = NamedTuple("Point", x=int, y=int) ) is no longer supported. Use the class-based syntax or the functional syntax instead. (Contributed by Bénédikt Tran in gh-133817 .) Using TD = TypedDict("TD") or TD = TypedDict("TD", None) to construct a TypedDict type with zero fields is no longer supported. Use class TD(TypedDict): pass or TD = TypedDict("TD", {}) instead. (Contributed by Bénédikt Tran in gh-133823 .) Code like class ExtraTypeVars(P1[S], Protocol[T, T2]): ... now raises a TypeError , because S is not listed in Protocol parameters. (Contributed by Nikita Sobolev in gh-137191 .) Code like class B2(A[T2], Protocol[T1, T2]): ... now correctly handles type parameters order: it is (T1, T2) , not (T2, T1) as it was incorrectly inferred in runtime before. (Contributed by Nikita Sobolev in gh-137191 .) typing.ByteString has been removed from typing.__all__ . typing.ByteString has been deprecated since Python 3.9, and is scheduled for removal in Python 3.17. The following statements now cause DeprecationWarning s to be emitted at runtime: from typing import ByteString import typing; typing.ByteString . DeprecationWarning s were already emitted if typing.ByteString was subclassed or used as the second argument to isinstance() or issubclass() , but warnings were not previously emitted if it was merely imported or accessed from the typing module. Deprecated typing.no_type_check_decorator() has been removed. (Contributed by Nikita Sobolev in gh-133601 .) wave ¶ Removed the getmark() , setmark() and getmarkers() methods of the Wave_read and Wave_write classes, which were deprecated since Python 3.13. (Contributed by Bénédikt Tran in gh-133873 .) zipimport ¶ Remove deprecated zipimport.zipimporter.load_module() . Use zipimport.zipimporter.exec_module() instead. (Contributed by Jiahao Li in gh-133656 .) Deprecated ¶ New deprecations ¶ CLI: Deprecate -b and -bb command-line options and schedule them to become no-ops in Python 3.17. These were primarily helpers for the Python 2 -> 3 transition. Starting with Python 3.17, no BytesWarning will be raised for these cases; use a type checker instead. (Contributed by Nikita Sobolev in gh-136355 .) hashlib : In hash function constructors such as new() or the direct hash-named constructors such as md5() and sha256() , the optional initial data parameter could also be passed as a keyword argument named data= or string= in various hashlib implementations. Support for the string keyword argument name is now deprecated and is slated for removal in Python 3.19. Prefer passing the initial data as a positional argument for maximum backwards compatibility. (Contributed by Bénédikt Tran in gh-134978 .) __version__ The __version__ , version and VERSION attributes have been deprecated in these standard library modules and will be removed in Python 3.20. Use sys.version_info instead. argparse csv ctypes ctypes.macholib decimal (use decimal.SPEC_VERSION instead) http.server imaplib ipaddress json logging ( __date__ also deprecated) optparse pickle platform re socketserver tabnanny tkinter.font tkinter.ttk wsgiref.simple_server xml.etree.ElementTree xml.sax.expatreader xml.sax.handler zlib (Contributed by Hugo van Kemenade and Stan Ulbrych in gh-76007 .) Pending removal in Python 3.16 ¶ The import system: Setting __loader__ on a module while failing to set __spec__.loader is deprecated. In Python 3.16, __loader__ will cease to be set or taken into consideration by the import system or the standard library. array : The 'u' format code ( wchar_t ) has been deprecated in documentation since Python 3.3 and at runtime since Python 3.13. Use the 'w' format code ( Py_UCS4 ) for Unicode characters instead. asyncio : asyncio.iscoroutinefunction() is deprecated and will be removed in Python 3.16; use inspect.iscoroutinefunction() instead. (Contributed by Jiahao Li and Kumar Aditya in gh-122875 .) asyncio policy system is deprecated and will be removed in Python 3.16. In particular, the following classes and functions are deprecated: asyncio.AbstractEventLoopPolicy asyncio.DefaultEventLoopPolicy asyncio.WindowsSelectorEventLoopPolicy asyncio.WindowsProactorEventLoopPolicy asyncio.get_event_loop_policy() asyncio.set_event_loop_policy() Users should use asyncio.run() or asyncio.Runner with loop_factory to use the desired event loop implementation. For example, to use asyncio.SelectorEventLoop on Windows: import asyncio async def main (): ... asyncio . run ( main (), loop_factory = asyncio . SelectorEventLoop ) (Contributed by Kumar Aditya in gh-127949 .) builtins : Bitwise inversion on boolean types, ~True or ~False has been deprecated since Python 3.12, as it produces surprising and unintuitive results ( -2 and -1 ). Use not x instead for the logical negation of a Boolean. In the rare case that you need the bitwise inversion of the underlying integer, convert to int explicitly ( ~int(x) ). functools : Calling the Python implementation of functools.reduce() with function or sequence as keyword arguments has been deprecated since Python 3.14. logging : Support for custom logging handlers with the strm argument is deprecated and scheduled for removal in Python 3.16. Define handlers with the stream argument instead. (Contributed by Mariusz Felisiak in gh-115032 .) mimetypes : Valid extensions start with a ‘.’ or are empty for mimetypes.MimeTypes.add_type() . Undotted extensions are deprecated and will raise a ValueError in Python 3.16. (Contributed by Hugo van Kemenade in gh-75223 .) shutil : The ExecError exception has been deprecated since Python 3.14. It has not been used by any function in shutil since Python 3.4, and is now an alias of RuntimeError . symtable : The Class.get_methods method has been deprecated since Python 3.14. sys : The _enablelegacywindowsfsencoding() function has been deprecated since Python 3.13. Use the PYTHONLEGACYWINDOWSFSENCODING environment variable instead. sysconfig : The sysconfig.expand_makefile_vars() function has been deprecated since Python 3.14. Use the vars argument of sysconfig.get_paths() instead. tarfile : The undocumented and unused TarFile.tarfile attribute has been deprecated since Python 3.13. Pending removal in Python 3.17 ¶ collections.abc : collections.abc.ByteString is scheduled for removal in Python 3.17. Use isinstance(obj, collections.abc.Buffer) to test if obj implements the buffer protocol at runtime. For use in type annotations, either use Buffer or a union that explicitly specifies the types your code supports (e.g., bytes | bytearray | memoryview ). ByteString was originally intended to be an abstract class that would serve as a supertype of both bytes and bytearray . However, since the ABC never had any methods, knowing that an object was an instance of ByteString never actually told you anything useful about the object. Other common buffer types such as memoryview were also never understood as subtypes of ByteString (either at runtime or by static type checkers). See PEP 688 for more details. (Contributed by Shantanu Jain in gh-91896 .) encodings : Passing non-ascii encoding names to encodings.normalize_encoding() is deprecated and scheduled for removal in Python 3.17. (Contributed by Stan Ulbrych in gh-136702 ) typing : Before Python 3.14, old-style unions were implemented using the private class typing._UnionGenericAlias . This class is no longer needed for the implementation, but it has been retained for backward compatibility, with removal scheduled for Python 3.17. Users should use documented introspection helpers like typing.get_origin() and typing.get_args() instead of relying on private implementation details. typing.ByteString , deprecated since Python 3.9, is scheduled for removal in Python 3.17. Use isinstance(obj, collections.abc.Buffer) to test if obj implements the buffer protocol at runtime. For use in type annotations, either use Buffer or a union that explicitly specifies the types your code supports (e.g., bytes | bytearray | memoryview ). ByteString was originally intended to be an abstract class that would serve as a supertype of both bytes and bytearray . However, since the ABC never had any methods, knowing that an object was an instance of ByteString never actually told you anything useful about the object. Other common buffer types such as memoryview were also never understood as subtypes of ByteString (either at runtime or by static type checkers). See PEP 688 for more details. (Contributed by Shantanu Jain in gh-91896 .) Pending removal in Python 3.18 ¶ decimal : The non-standard and undocumented Decimal format specifier 'N' , which is only supported in the decimal module’s C implementation, has been deprecated since Python 3.13. (Contributed by Serhiy Storchaka in gh-89902 .) Pending removal in Python 3.19 ¶ ctypes : Implicitly switching to the MSVC-compatible struct layout by setting _pack_ but not _layout_ on non-Windows platforms. hashlib : In hash function constructors such as new() or the direct hash-named constructors such as md5() and sha256() , their optional initial data parameter could also be passed a keyword argument named data= or string= in various hashlib implementations. Support for the string keyword argument name is now deprecated and slated for removal in Python 3.19. Before Python 3.13, the string keyword parameter was not correctly supported depending on the backend implementation of hash functions. Prefer passing the initial data as a positional argument for maximum backwards compatibility. Pending removal in Python 3.20 ¶ The __version__ , version and VERSION attributes have been deprecated in these standard library modules and will be removed in Python 3.20. Use sys.version_info instead. argparse csv ctypes ctypes.macholib decimal (use decimal.SPEC_VERSION instead) http.server imaplib ipaddress json logging ( __date__ also deprecated) optparse pickle platform re socketserver tabnanny tkinter.font tkinter.ttk wsgiref.simple_server xml.etree.ElementTree xml.sax.expatreader xml.sax.handler zlib (Contributed by Hugo van Kemenade and Stan Ulbrych in gh-76007 .) Pending removal in future versions ¶ The following APIs will be removed in the future, although there is currently no date scheduled for their removal. argparse : Nesting argument groups and nesting mutually exclusive groups are deprecated. Passing the undocumented keyword argument prefix_chars to add_argument_group() is now deprecated. The argparse.FileType type converter is deprecated. builtins : Generators: throw(type, exc, tb) and athrow(type, exc, tb) signature is deprecated: use throw(exc) and athrow(exc) instead, the single argument signature. Currently Python accepts numeric literals immediately followed by keywords, for example 0in x , 1or x , 0if 1else 2 . It allows confusing and ambiguous expressions like [0x1for x in y] (which can be interpreted as [0x1 for x in y] or [0x1f or x in y] ). A syntax warning is raised if the numeric literal is immediately followed by one of keywords and , else , for , if , in , is and or . In a future release it will be changed to a syntax error. ( gh-87999 ) Support for __index__() and __int__() method returning non-int type: these methods will be required to return an instance of a strict subclass of int . Support for __float__() method returning a strict subclass of float : these methods will be required to return an instance of float . Support for __complex__() method returning a strict subclass of complex : these methods will be required to return an instance of complex . Delegation of int() to __trunc__() method. Passing a complex number as the real or imag argument in the complex() constructor is now deprecated; it should only be passed as a single positional argument. (Contributed by Serhiy Storchaka in gh-109218 .) calendar : calendar.January and calendar.February constants are deprecated and replaced by calendar.JANUARY and calendar.FEBRUARY . (Contributed by Prince Roshan in gh-103636 .) codecs : use open() instead of codecs.open() . ( gh-133038 ) codeobject.co_lnotab : use the codeobject.co_lines() method instead. datetime : utcnow() : use datetime.datetime.now(tz=datetime.UTC) . utcfromtimestamp() : use datetime.datetime.fromtimestamp(timestamp, tz=datetime.UTC) . gettext : Plural value must be an integer. importlib : cache_from_source() debug_override parameter is deprecated: use the optimization parameter instead. importlib.metadata : EntryPoints tuple interface. Implicit None on return values. logging : the warn() method has been deprecated since Python 3.3, use warning() instead. mailbox : Use of StringIO input and text mode is deprecated, use BytesIO and binary mode instead. os : Calling os.register_at_fork() in a multi-threaded process. pydoc.ErrorDuringImport : A tuple value for exc_info parameter is deprecated, use an exception instance. re : More strict rules are now applied for numerical group references and group names in regular expressions. Only sequence of ASCII digits is now accepted as a numerical reference. The group name in bytes patterns and replacement strings can now only contain ASCII letters and digits and underscore. (Contributed by Serhiy Storchaka in gh-91760 .) shutil : rmtree() ’s onerror parameter is deprecated in Python 3.12; use the onexc parameter instead. ssl options and protocols: ssl.SSLContext without protocol argument is deprecated. ssl.SSLContext : set_npn_protocols() and selected_npn_protocol() are deprecated: use ALPN instead. ssl.OP_NO_SSL* options ssl.OP_NO_TLS* options ssl.PROTOCOL_SSLv3 ssl.PROTOCOL_TLS ssl.PROTOCOL_TLSv1 ssl.PROTOCOL_TLSv1_1 ssl.PROTOCOL_TLSv1_2 ssl.TLSVersion.SSLv3 ssl.TLSVersion.TLSv1 ssl.TLSVersion.TLSv1_1 threading methods: threading.Condition.notifyAll() : use notify_all() . threading.Event.isSet() : use is_set() . threading.Thread.isDaemon() , threading.Thread.setDaemon() : use threading.Thread.daemon attribute. threading.Thread.getName() , threading.Thread.setName() : use threading.Thread.name attribute. threading.currentThread() : use threading.current_thread() . threading.activeCount() : use threading.active_count() . typing.Text ( gh-92332 ). The internal class typing._UnionGenericAlias is no longer used to implement typing.Union . To preserve compatibility with users using this private class, a compatibility shim will be provided until at least Python 3.17. (Contributed by Jelle Zijlstra in gh-105499 .) unittest.IsolatedAsyncioTestCase : it is deprecated to return a value that is not None from a test case. urllib.parse deprecated functions: urlparse() instead splitattr() splithost() splitnport() splitpasswd() splitport() splitquery() splittag() splittype() splituser() splitvalue() to_bytes() wsgiref : SimpleHandler.stdout.write() should not do partial writes. xml.etree.ElementTree : Testing the truth value of an Element is deprecated. In a future release it will always return True . Prefer explicit len(elem) or elem is not None tests instead. sys._clear_type_cache() is deprecated: use sys._clear_internal_caches() instead. C API changes ¶ New features ¶ Add PySys_GetAttr() , PySys_GetAttrString() , PySys_GetOptionalAttr() , and PySys_GetOptionalAttrString() functions as replacements for PySys_GetObject() . (Contributed by Serhiy Storchaka in gh-108512 .) Add PyUnstable_Unicode_GET_CACHED_HASH to get the cached hash of a string. See the documentation for caveats. (Contributed by Petr Viktorin in gh-131510 .) Add API for checking an extension module’s ABI compatibility: Py_mod_abi , PyABIInfo_Check() , PyABIInfo_VAR and Py_mod_abi . (Contributed by Petr Viktorin in gh-137210 .) Implement PEP 782 , the PyBytesWriter API . Add functions: PyBytesWriter_Create() PyBytesWriter_Discard() PyBytesWriter_FinishWithPointer() PyBytesWriter_FinishWithSize() PyBytesWriter_Finish() PyBytesWriter_Format() PyBytesWriter_GetData() PyBytesWriter_GetSize() PyBytesWriter_GrowAndUpdatePointer() PyBytesWriter_Grow() PyBytesWriter_Resize() PyBytesWriter_WriteBytes() (Contributed by Victor Stinner in gh-129813 .) Add a new PyImport_CreateModuleFromInitfunc() C-API for creating a module from a spec and initfunc . (Contributed by Itamar Oren in gh-116146 .) Add PyTuple_FromArray() to create a tuple from an array. (Contributed by Victor Stinner in gh-111489 .) Add PyUnstable_Object_Dump() to dump an object to stderr . It should only be used for debugging. (Contributed by Victor Stinner in gh-141070 .) Add PyUnstable_ThreadState_SetStackProtection() and PyUnstable_ThreadState_ResetStackProtection() functions to set the stack protection base address and stack protection size of a Python thread state. (Contributed by Victor Stinner in gh-139653 .) Changed C APIs ¶ If the Py_TPFLAGS_MANAGED_DICT or Py_TPFLAGS_MANAGED_WEAKREF flag is set then Py_TPFLAGS_HAVE_GC must be set too. (Contributed by Sergey Miryanov in gh-134786 ) Porting to Python 3.15 ¶ Private functions promoted to public C APIs: The pythoncapi-compat project can be used to get most of these new functions on Python 3.14 and older. Removed C APIs ¶ Remove deprecated PyUnicode functions: PyUnicode_AsDecodedObject() : Use PyCodec_Decode() instead. PyUnicode_AsDecodedUnicode() : Use PyCodec_Decode() instead; Note that some codecs (for example, “base64”) may return a type other than str , such as bytes . PyUnicode_AsEncodedObject() : Use PyCodec_Encode() instead. PyUnicode_AsEncodedUnicode() : Use PyCodec_Encode() instead; Note that some codecs (for example, “base64”) may return a type other than bytes , such as str . (Contributed by Stan Ulbrych in gh-133612 .) PyImport_ImportModuleNoBlock() | 2026-01-13T08:49:46 |
https://discuss.python.org/t/python-3-13-6-has-been-released/101482#p-265330-enjoy-the-new-releases-4 | Python 3.13.6 has been released - Core Development - Discussions on Python.org Discussions on Python.org Python 3.13.6 has been released Core Development release thomas (Thomas Wouters) August 6, 2025, 9:27pm 1 A day behind schedule in order to fix some last-minute issues, but it’s done: the latest version of the best [1] Python version is now available! Python 3.13.6 Python.org Python Release Python 3.13.6 The official home of the Python Programming Language This is the sixth maintenance release of Python 3.13 Python 3.13 is the newest major release of the Python programming language, and it contains many new features and optimizations compared to Python 3.12. 3.13.6 is the sixth maintenance release of 3.13, containing around 200 bugfixes, build improvements and documentation changes since 3.13.5. Full Changelog More resources Online Documentation PEP 719 , 3.13 Release Schedule Report bugs at https://github.com/python/cpython/issues . Help fund Python directly (or via GitHub Sponsors ), and support the Python community . Enjoy the new releases Thanks to all of the many volunteers who help make Python Development and these releases possible! Please consider supporting our efforts by volunteering yourself or through organization contributions to the Python Software Foundation, especially now . Regards from your package managers [2] , Thomas Wouters @thomas Ned Deily @nad Steve Dower @steve.dower Łukasz Langa @ambv so far. Or ever, according to some! Okay, me. Maybe. Prove me wrong! ↩︎ this is an inside joke that may become apparent later ↩︎ 16 Likes brettcannon (Brett Cannon) August 6, 2025, 9:54pm 2 WASI build at Release CPython 3.13.6 w/ WASI SDK 24 · brettcannon/cpython-wasi-build · GitHub 1 Like barry (Barry Warsaw) August 6, 2025, 10:17pm 3 CI Images are built. 1 Like Home Categories Guidelines Terms of Service Privacy Policy Powered by Discourse , best viewed with JavaScript enabled | 2026-01-13T08:49:46 |
https://www.fine.dev/blog/secure-startup-codebase#keep-dependencies-updated | Best Practices for Securing Your Startup's Codebase: A CTO’s Step-by-Step Guide Home Docs Changelog Pricing Sign in Get started -> Menu Home Docs Changelog Pricing <- Go Back Best Practices for Securing Your Startup's Codebase: A CTO’s Step-by-Step Guide Startups often prioritize speed over security, pushing out features to gain a competitive edge. However, overlooking security in the early stages can lead to costly issues down the road. This guide provides a step-by-step approach for CTOs to secure their startup's codebase effectively while maintaining agility. Table of Contents Implement Secure Coding Standards Automate Security Scans Embrace Code Reviews with Security in Mind Practice Least Privilege Use Secrets Management Keep Dependencies Updated Enable Logging and Monitoring Regular Security Audits Educate Your Team Plan for Incident Response 1. Implement Secure Coding Standards Define a set of secure coding practices from the get-go. Train developers on common vulnerabilities such as SQL injection, XSS, and insecure deserialization. Adopting secure coding standards helps prevent vulnerabilities that are often introduced during rapid development. 2. Automate Security Scans Incorporate automated security tools into your CI/CD pipeline to catch vulnerabilities before they reach production. Tools like Snyk can help monitor dependencies and flag security issues, allowing your team to act proactively. 3. Embrace Code Reviews with Security in Mind Encourage peer code reviews that emphasize security. By incorporating a security checklist in your code review process, developers are more likely to catch issues early. Using tools like GitHub or GitLab for code reviews can streamline collaboration. Fine can make code reviews a far less arduous process for developers, making it easier to maintain consistently high standards. 4. Practice Least Privilege Ensure that each part of your system has access only to what it needs. Avoid giving developers or third-party services more permissions than necessary. Regularly review and revoke access to prevent unauthorized data exposure. 5. Use Secrets Management Avoid hardcoding sensitive information such as API keys, database credentials, or access tokens directly into your codebase. Instead, utilize a secrets management tool like AWS Secrets Manager, HashiCorp Vault, or Azure Key Vault to keep these secure. 6. Keep Dependencies Updated Outdated third-party libraries can introduce security vulnerabilities. Use dependency management tools to keep track of which libraries are in use and stay updated with security patches. 7. Enable Logging and Monitoring Monitor for unusual activity to detect threats early. Ensure your logging system captures details like failed login attempts, unexpected API usage, and codebase modifications. Using centralized logging services such as ELK Stack or Splunk can streamline threat detection and response. 8. Regular Security Audits Perform periodic security audits and penetration tests to assess the overall health of your codebase. Startups should consider working with a third-party security expert to identify gaps that might be overlooked internally. 9. Educate Your Team Security is everyone’s responsibility. Conduct regular training sessions to keep your development team aware of the latest security threats and best practices. Tools like OWASP or even informal lunch-and-learns can help build a security-aware culture. 10. Plan for Incident Response Have an incident response plan in place in case a breach does occur. Document the steps your team needs to take to minimize damage and recover. Being prepared can make the difference between a minor incident and a major catastrophe. Securing your startup's codebase requires deliberate planning and effort, but these practices will pay off by protecting your company and its customers. Adopting a proactive security mindset now can save countless headaches in the future. If you're building a software startup, Fine can help you achieve your development goals faster. From within your issue management platform, delegate tasks to AI and get a PR to review when you're done. You can also get coding tasks gone on the go, without compromising on security. Try it out at https://ai.fine.dev Start building today Try out the smoothest way to build, launch and manage an app Try for Free -> © Fine.dev - All rights reserved. Product Overview AI Workflows Pricing & Plans Changelog Blog Docs Company Press Terms & Conditions Privacy policy | 2026-01-13T08:49:46 |
https://glaucoma.org.au | Home | Glaucoma Australia element to your page . --> Skip to main content Search Search How You Can Help News About Us Shop Events Cart Accessibility Support Glaucoma website logo What Is Glaucoma What Is Glaucoma Types of Glaucoma Primary Glaucoma Secondary Glaucoma Glaucoma Suspect Risk Factors for Glaucoma Testing for Glaucoma Glaucoma Treatments Eye Drops Oral Medication Laser Treatment MIGS Conventional Surgery Frequently Asked Questions | 2026-01-13T08:49:46 |
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https://discuss.python.org/t/python-3-13-6-has-been-released/101482#p-265330-more-resources-3 | Python 3.13.6 has been released - Core Development - Discussions on Python.org Discussions on Python.org Python 3.13.6 has been released Core Development release thomas (Thomas Wouters) August 6, 2025, 9:27pm 1 A day behind schedule in order to fix some last-minute issues, but it’s done: the latest version of the best [1] Python version is now available! Python 3.13.6 Python.org Python Release Python 3.13.6 The official home of the Python Programming Language This is the sixth maintenance release of Python 3.13 Python 3.13 is the newest major release of the Python programming language, and it contains many new features and optimizations compared to Python 3.12. 3.13.6 is the sixth maintenance release of 3.13, containing around 200 bugfixes, build improvements and documentation changes since 3.13.5. Full Changelog More resources Online Documentation PEP 719 , 3.13 Release Schedule Report bugs at https://github.com/python/cpython/issues . Help fund Python directly (or via GitHub Sponsors ), and support the Python community . Enjoy the new releases Thanks to all of the many volunteers who help make Python Development and these releases possible! Please consider supporting our efforts by volunteering yourself or through organization contributions to the Python Software Foundation, especially now . Regards from your package managers [2] , Thomas Wouters @thomas Ned Deily @nad Steve Dower @steve.dower Łukasz Langa @ambv so far. Or ever, according to some! Okay, me. Maybe. Prove me wrong! ↩︎ this is an inside joke that may become apparent later ↩︎ 16 Likes brettcannon (Brett Cannon) August 6, 2025, 9:54pm 2 WASI build at Release CPython 3.13.6 w/ WASI SDK 24 · brettcannon/cpython-wasi-build · GitHub 1 Like barry (Barry Warsaw) August 6, 2025, 10:17pm 3 CI Images are built. 1 Like Home Categories Guidelines Terms of Service Privacy Policy Powered by Discourse , best viewed with JavaScript enabled | 2026-01-13T08:49:46 |
https://www.npopov.com/2012/08/10/Are-PHP-developers-functophobic.html | Are PHP developers functophobic? Blog by nikic . Find me on GitHub , StackOverflow , Twitter and Mastodon . Learn more about me . « Back to article overview. Are PHP developers functophobic? 10. August 2012 There is this one thing that I noticed recently and that concerns me: PHP devs don’t use functions. Now, that was overly general, so let me clarify: PHP developers who have reached a certain degree of sophistication basically stop using plain functions - instead everything goes all classes and methods. At least that’s the observation I made when looking at various open-source libraries and frameworks. The only type of function you’ll find in any of the “high-quality” libs are anonymous functions. But that’s pretty much it. If you look at other languages, the landscape is different. For example Python code will to a large part be class definitions, but there will always be normal functions in between. So in PHP functions are basically used in two cases: If the programmer doesn’t yet use OOP or if the script isn’t worth using OOP for. The notion of “helper function” or something like that does not seem to exist. This somewhat concerns me because I think that sticking everything into classes isn’t really the right thing to do. This kind of behavior usually leads to Class-Oriented Programming, where you are basically just using classes for the sake of using them. (Reminder: Using classes does not mean your code is object-oriented!) I also think that the reluctance to define helper functions is what leads to the push for more and more functions in the PHP core. E.g. I recently have seen a few people asking for some kind of array_rand_value function. This function would basically be the same as array_rand , but it would return a value instead of a key. So it could be defined in userland code in two lines: function array_rand_value ( array $array ) { if ( empty ( $array )) return null ; return $array [ array_rand ( $array )]; } This is a tiny small function that you can easily define yourself. But then arises what I think is the main problem: Where should you put it? How do I incorporate it with the autoloader? PHP to large parts inherited the Java OOP model and one thing that came with it is having a one-to-one mapping between classes and files. PHP does not enforce this, but it is a very common convention. PHP’s autoloading support and the PSR-0 standard are emphasizing this further. Other languages similar to PHP do not have this convention. For example in Python it is very normal to define multiple related classes and functions in one file. In Python a file is rather a module, i.e. a group of related components. In such a setup it is obviously much easier to define small functions in between. Generally I think that the one-to-one file mapping so common in PHP is problematic. Apart from making it hard to use functions it also adds an additional cost to creating small classes: Object oriented programming done right usually leads to a large number of small classes. This is great for code reuse, maintainability and testing. But in PHP you have to create a new file for every one of those classes. And this is really getting in my way. I’d have no problem batch-defining ten tiny classes in one file. But I feel like creating ten distinct files for them is counterproductive (and hampers maintainability). Another tangentially related “standard” practice I feel badly about is the excessive use of doccomments. In most cases phpdoc comments just comment the obvious - at the same increasing the code size by a factor of two or three. I have no problem with doccomments where necessary , but in most cases (at least with well designed code) the behavior should be obvious from the method and parameter names. So, basically, what I’m thinking about here is being more “compact”: Instead of defining a file for every class, put related (smaller) classes into one file. Instead of defining a class for everything, just use a function. Instead of cluttering the code with lots of useless doccomments, just leave them out unless really necessary. But it’s just a thought ;) Maybe I got it all wrong. If you liked this article, you may want to browse my other articles or follow me on Twitter or Mastodon . | 2026-01-13T08:49:46 |
https://discuss.opensource.org/t/definition-validation-seeking-volunteers/320 | Definition Validation: Seeking Volunteers - Open Source AI - OSI Discuss OSI Discuss Definition Validation: Seeking Volunteers Open Source AI process Mer May 1, 2024, 5:37pm 1 CONTEXT Last week Stefano announced v. 0.0.8 , the first feature complete version of the Open Source AI Definition (OSAID). ASK We are now seeking volunteers to validate that definition by using it to review additional AI systems that are self-described as open. If you are interested, please comment below or DM me. TIME We would like to complete this validation task by Monday, May 20th . TASK You will have a spreadsheet (example below) in which you locate and link to the license, research paper, or other document that grants rights or provides information for each required component. You will then indicate in each cell whether the document Allows or Restricts the ability to study use, modify, or share that component. Screenshot 2024-05-01 at 10.08.59 AM 1920×950 194 KB Example: spreadsheet used to review Llama 2 according OSAID v. 0.0.6 SYSTEMS We are interested in reviewing about ten self-described open AI systems as part of this definitional process. Four (marked *) have already been reviewed by the workgroups . Below are some more systems we are interested in being part of this validation task. If there is another system you would like to review, please say so. Arctic Jesús M. Gonzalez-Barahona BLOOM * Danish Contractor, Jaan Li Falcon Casey Valk, Jean-Pierre Lorre Grok Victor Lu, Karsten Wade Llama 2 * Davide Testuggine, Jonathan Torres, Stefano Zacchiroli, Victor Lu Mistral Mark Collier, Jean-Pierre Lorre, Cailean Osborne OLMo Amanda Casari, Abdoulaye Diack OpenCV * Rasim Sen Phi-2 Seo-Young Isabelle Hwang Pythia * Seo-Young Isabelle Hwang, Stella Biderman, Hailey Schoelkopf, Aviya Skowron T5 Jaan Li TO VOLUNTEER Comment below or DM me if you would like to volunteer. Anyone who can complete the task may do so, either solo or as a group. If you are a creator or advisor on the system you are reviewing, we will also need to identity an unaffiliated individual to review the system, so please disclose that when you volunteer. Your name and organizational affiliation will also be made public as part of our transparency policy. Women, trans, and non-binary folx, black, indigenous, latine/o/a, and other people of color, immigrants, people with disabilities, and people from poor and working class backgrounds are encouraged to respond. Thanks EDIT: I’ll update the list above with volunteer names so it’s clear where there is greatest need. (last update: May 14th @ 11:03 am PDT) 3 Likes Draft v.0.0.8 of the Open Source AI Definition is available for comments Initial Report on Definition Validation Malicious compliance with the release candidate Open Source AI definition amcasari May 2, 2024, 1:30pm 2 I volunteer to help with a review! I have a conflict of interest with #10 , T5 (same employer), but could take the lead or assist on any others. I would prefer to start w/ OLMo, if that isn’t taken yet. Mer May 2, 2024, 4:29pm 3 Thank you, @amcasari ! You’ve got review on OLMo. I’m going to make up the new review spreadsheet today and will email you with further details. 1 Like stefano May 3, 2024, 12:06pm 4 Here is another one claiming to be “truly open”: Can we get someone to review it, please? Snowflake – 24 Apr 24 Snowflake Arctic - LLM for Enterprise AI Snowflake Arctic from the Snowflake AI research team is a top-tier enterprise LLM that pushes the frontiers of cost-effective training and openness. Est. reading time: 14 minutes 2 Likes Aspie96 May 4, 2024, 2:33am 5 Mer: If there is another system you would like to review, please say so. There are two kinds of systems I don’t see listed that I would like to see. Non-foundational models. Systems which are not based on deep learning (and, preferably, not even on machine learning). That said, if I can only suggest specific systems, I have at least two: Open Image Denoise , by Intel. NLP models such as the Stanford Log-linear Part-Of-Speech Tagger . 1 Like stefano May 6, 2024, 9:25am 6 Aspie96: That said, if I can only suggest specific systems, I have at least two: Good thinking, thanks! I think you can get started by cloning this table structure and fill in the details. 1 Like quaid May 13, 2024, 6:18pm 7 Heya Mer, I love this exercise! I’ve been doing this lightly across systems recently but not to this same depth and level of certainty. In fact, Snowflake Arctic is one I looked more closely at, so I’m happy to help with this one if needed. Otherwise, I have no preferences and will help wherever needed. Would you like to choose several for me, prioritize them if possible? I’m not aware of my having any affiliation with these systems, and Open Community Architects (OCA) is a neutral consultancy in those regards (aside from a bias for Open.) Karsten (quaid) 1 Like Mer May 13, 2024, 6:36pm 8 Thanks, @quaid . I think Arctic is well-covered, but let me see if anyone else needs help. If not, you can just pick a system that works for you. I’ll get back to you soon. Mer May 14, 2024, 6:02pm 9 @quaid I got no requests from the current volunteers, so I’m going to put you on Grok, which is a new system with only 1 volunteer. Please DM me your email address so I can add you to the reviewer chat and spreadsheet. Aspie96 May 16, 2024, 4:53am 10 Two models I hadn’t thought about mentioning previously, but are rather interesting, are Segment Anything, by Meta and Whisper, by OpenAI. What makes them interesting is the fact that they sparked a lot of attention when they were published and they are built by companies that usually make in-house models (OpenAI) or often release models under proprietary licenses (Meta), but in this case were released under open source licenses (both code and weigths): Apache 2.0 and MIT license respectively. Home Categories Guidelines Terms of Service Privacy Policy Powered by Discourse , best viewed with JavaScript enabled | 2026-01-13T08:49:46 |
https://www.npopov.com/2012/07/09/A-plea-for-less-XML-configuration-files.html | A plea for less (XML) configuration files Blog by nikic . Find me on GitHub , StackOverflow , Twitter and Mastodon . Learn more about me . « Back to article overview. A plea for less (XML) configuration files 09. July 2012 I recently tried using Phing (a PHP build system) to do some simple release automation. Just creating a PEAR package and doing a few string replacements here and there. The result? After several wasted hours I ended up using Phing only for PEAR packaging and doing everything else in a custom PHP build script. The reason? Phing uses XML files to configure what it should do during a build. So an excerpt from a build file might look like this: <?xml version="1.0" encoding="UTF-8"?> <project name= "SomeName" default= "package" basedir= ".." > <target name= "package" > <property file= "build/build.properties" /> <propertyprompt propertyName= "project.version" promptText= "Enter project version" /> <delete dir= "${path.results.lib}" /> <mkdir dir= "${path.results.lib}" /> <copy todir= "${path.results.lib}" > <fileset dir= "${path.lib}" > <include name= "**/**" /> </fileset> </copy> <!-- do more stuff --> </target> <!-- more targets --> </project> Could you explain me, why you have to do this? Why do you have to specify everything in an XML configuration file? Why can’t you just do the same thing in the programming language you’re using? E.g., why can’t I write this instead: function package ( Phing $phing ) { include 'properties.php' ; $project -> version = $phing -> prompt ( 'Enter project version' ); $phing -> deleteDir ( $path -> results -> lib ); $phing -> createDir ( $path -> results -> lib ); $phing -> copyDir ( $path -> lib , $path -> results -> lib ); // do more stuff, like replace version strings with $project->version } Don’t you think that this is much nicer? Some reasons why I prefer this over XML configs: It uses an environment you’re already used to. You don’t have to learn how exactly the Phing XML files work. You don’t need to learn where you can use properties and where you can’t. You simply know already. You can use the full power of the programming language. E.g. the main reason why I stopped using Phing was that I could not implement some slightly more complex string replacement in it without writing 200 lines of XML. I was able to implement those replacements in 5 lines of PHP on the other hand. All the tools you normally use for programming will work. E.g. the IDE will be able to provide autocompletion and error analysis. One could use phpDocumentor to document the different build targets and options. Heck, you could even unit test the building process, if you really wanted to. And obviously: XML is a rather verbose language, whereas most programming languages (short of Brainfuck) try to be concise and readable. At this point you might say that the above isn’t really a configuration file, but rather a program written in XML. I’d agree with you there, but I think the the above also applies to “real” configuration files. They can also benefit from the power of the programming language (like putting repeating configuration “patterns” into functions or loops), etc. Also, this isn’t specific to XML. I think that it is generally preferable to just use your usual programming language to write configuration, instead of using some special format. But don’t get me wrong, there certainly are cases where using a special configuration format is the way to go: If the configuration will be used by multiple programming languages. Obviously it doesn’t make sense to write PHP configs if they have to be used by Python too. If the type of configuration is very specific and writing it would be much easier using a Domain Specific Language. In my personal experience neither of those points apply for most of the config files I’ve encountered. So, what I ask you for is: If you’re creating a config file, consider writing it in your normal programming language instead of XML or some DSL. If you liked this article, you may want to browse my other articles or follow me on Twitter or Mastodon . | 2026-01-13T08:49:46 |
https://www.npopov.com/2011/12/28/Supercolliding-a-PHP-array.html | Supercolliding a PHP array Blog by nikic . Find me on GitHub , StackOverflow , Twitter and Mastodon . Learn more about me . « Back to article overview. Supercolliding a PHP array 28. December 2011 Did you know that inserting 2^16 = 65536 specially crafted values into a normal PHP array can take 30 seconds ? Normally this would take only 0.01 seconds . This is the code to reproduce it: $size = pow ( 2 , 16 ); // 16 is just an example, could also be 15 or 17 $startTime = microtime ( true ); $array = array (); for ( $key = 0 , $maxKey = ( $size - 1 ) * $size ; $key <= $maxKey ; $key += $size ) { $array [ $key ] = 0 ; } $endTime = microtime ( true ); echo 'Inserting ' , $size , ' evil elements took ' , $endTime - $startTime , ' seconds' , " \n " ; $startTime = microtime ( true ); $array = array (); for ( $key = 0 , $maxKey = $size - 1 ; $key <= $maxKey ; ++ $key ) { $array [ $key ] = 0 ; } $endTime = microtime ( true ); echo 'Inserting ' , $size , ' good elements took ' , $endTime - $startTime , ' seconds' , " \n " ; Try it yourself! You may need to adjust the number 16 in the $size = pow(2, 16); line based on what hardware you have. I would start with 14 and increase it one at a time. By the way, I intentionally don’t provide an online demo at the amazing Viper-7 codepad this time so that it doesn’t get overloaded. Here is a sample output from my machine: Inserting 65536 evil elements took 32.726480007172 seconds Inserting 65536 good elements took 0.014460802078247 seconds How does this work? PHP internally uses hashtables to store arrays. The above creates a hashtable with 100% collisions (i.e. all keys will have the same hash). For those who don’t know how hashtables work: When you write $array[$key] in PHP the $key is run through a fast hash function that yields an integer. This integer is then used as an offset into a “real” C array (here “array” means “chunk of memory”). Because every hash function has collisions this C array doesn’t actually store the value we want, but a linked list of possible values. PHP then walks these values one by one and does a full key comparison until it finds the right element with our $key . Normally there will be only a small number of collisions, so in most cases the linked list will only have one value. But the above script creates a hash where all elements collide. How can you make all of them collide? In PHP it’s very simple. If the key is an integer the hash function is just a no-op: The hash is the integer itself. All PHP does is apply a table mask on top of it: hash & tableMask . This table mask ensures that the resulting hash is within the bounds of the underlying real C array. This underlying C array has always a size which is a power of 2 (this way the hashtable is always reasonably efficient in both space and time). So if you store 10 elements the real size will be 16. If you store 33 it will be 64. If you store 63 it will also be 64. The table mask is the size minus one. So if the size is 64, i.e. 1000000 in binary the table mask will be 63, i.e. 0111111 in binary. So basically the table mask removes all bits that are greater than the hashtable size. And this is what we are exploiting: 0 & 0111111 = 0 , but 1000000 & 0111111 = 0 too, so is 10000000 & 0111111 = 0 and 11000000 & 0111111 = 0 . As long as we keep those lower bits the same the result of the hash will also stay the same. So if we insert a total of 64 elements, the first one 0, the second one 64, the third one 128, the fourth one 192, etc., all of those elements will have the same hash (namely 0) and all will be put into the same linked list. And that’s what the code does. Only not with 64 elements, but with a few more. Why is that so abysmally slow? Well, for every insertion PHP has to traverse the whole linked list, element for element. On the first insertion it needs to traverse 0 elements (there is nothing there yet). On the second one it traverses 1 element. On the third one 2, on the fourth 3 and on the 64th one 63. Those who know a little bit of math probably know that 0+1+2+3+...+(n-1) = (n-1)*(n-2)/2 . So the number of elements to traverse is quadratic. For 64 elements it’s 62*63/2 = 1953 traversals. For 2^16 = 65536 it’s 65534*65535/2=2147385345 . As you see, the numbers grow fast. And with the number of iteration grows the execution time. Hashtable collisions as DOS attack At this point you may wonder what the above is actually useful for. For the casual user: Not useful at all. But the “bad guys” can easily exploit behavior like the above to perform a DOS (Denial of Service) attack on a server. Remember that $_GET and $_POST and $_REQUEST are just normal arrays and suffer from the same problems. So by sending a specially crafted POST request you can easily take a server down. PHP is not the only language vulnerable to this. Actually pretty much all other languages used for creating websites have similar problems, as was presented at the 28C3 conference . But there is hope! PHP already landed a change (which will ship with PHP 5.3.9) which will add a max_input_vars ini setting which defaults to 1000 . This setting determines the maximum number of POST/GET variables that are accepted, so now only a maximum of 1000 collisions can be created. If you run the above script with 2^10 = 1024 elements you will get runtimes in the order of 0.003 seconds, which obviously is far less critical than 30 seconds. (Note though that above I am demonstrating an integer key collision. You can also collide string keys, in which case the traversal will be a good bit slower.) If you liked this article, you may want to browse my other articles or follow me on Twitter or Mastodon . | 2026-01-13T08:49:46 |
https://www.fine.dev/blog/secure-startup-codebase#automate-security-scans | Best Practices for Securing Your Startup's Codebase: A CTO’s Step-by-Step Guide Home Docs Changelog Pricing Sign in Get started -> Menu Home Docs Changelog Pricing <- Go Back Best Practices for Securing Your Startup's Codebase: A CTO’s Step-by-Step Guide Startups often prioritize speed over security, pushing out features to gain a competitive edge. However, overlooking security in the early stages can lead to costly issues down the road. This guide provides a step-by-step approach for CTOs to secure their startup's codebase effectively while maintaining agility. Table of Contents Implement Secure Coding Standards Automate Security Scans Embrace Code Reviews with Security in Mind Practice Least Privilege Use Secrets Management Keep Dependencies Updated Enable Logging and Monitoring Regular Security Audits Educate Your Team Plan for Incident Response 1. Implement Secure Coding Standards Define a set of secure coding practices from the get-go. Train developers on common vulnerabilities such as SQL injection, XSS, and insecure deserialization. Adopting secure coding standards helps prevent vulnerabilities that are often introduced during rapid development. 2. Automate Security Scans Incorporate automated security tools into your CI/CD pipeline to catch vulnerabilities before they reach production. Tools like Snyk can help monitor dependencies and flag security issues, allowing your team to act proactively. 3. Embrace Code Reviews with Security in Mind Encourage peer code reviews that emphasize security. By incorporating a security checklist in your code review process, developers are more likely to catch issues early. Using tools like GitHub or GitLab for code reviews can streamline collaboration. Fine can make code reviews a far less arduous process for developers, making it easier to maintain consistently high standards. 4. Practice Least Privilege Ensure that each part of your system has access only to what it needs. Avoid giving developers or third-party services more permissions than necessary. Regularly review and revoke access to prevent unauthorized data exposure. 5. Use Secrets Management Avoid hardcoding sensitive information such as API keys, database credentials, or access tokens directly into your codebase. Instead, utilize a secrets management tool like AWS Secrets Manager, HashiCorp Vault, or Azure Key Vault to keep these secure. 6. Keep Dependencies Updated Outdated third-party libraries can introduce security vulnerabilities. Use dependency management tools to keep track of which libraries are in use and stay updated with security patches. 7. Enable Logging and Monitoring Monitor for unusual activity to detect threats early. Ensure your logging system captures details like failed login attempts, unexpected API usage, and codebase modifications. Using centralized logging services such as ELK Stack or Splunk can streamline threat detection and response. 8. Regular Security Audits Perform periodic security audits and penetration tests to assess the overall health of your codebase. Startups should consider working with a third-party security expert to identify gaps that might be overlooked internally. 9. Educate Your Team Security is everyone’s responsibility. Conduct regular training sessions to keep your development team aware of the latest security threats and best practices. Tools like OWASP or even informal lunch-and-learns can help build a security-aware culture. 10. Plan for Incident Response Have an incident response plan in place in case a breach does occur. Document the steps your team needs to take to minimize damage and recover. Being prepared can make the difference between a minor incident and a major catastrophe. Securing your startup's codebase requires deliberate planning and effort, but these practices will pay off by protecting your company and its customers. Adopting a proactive security mindset now can save countless headaches in the future. If you're building a software startup, Fine can help you achieve your development goals faster. From within your issue management platform, delegate tasks to AI and get a PR to review when you're done. You can also get coding tasks gone on the go, without compromising on security. Try it out at https://ai.fine.dev Start building today Try out the smoothest way to build, launch and manage an app Try for Free -> © Fine.dev - All rights reserved. Product Overview AI Workflows Pricing & Plans Changelog Blog Docs Company Press Terms & Conditions Privacy policy | 2026-01-13T08:49:46 |
https://www.npopov.com/2011/12/10/PCRE-and-newlines.html | PCRE and newlines Blog by nikic . Find me on GitHub , StackOverflow , Twitter and Mastodon . Learn more about me . « Back to article overview. PCRE and newlines 10. December 2011 PCRE (this is what you use when you do a preg_* call in PHP) has a plethora of newline related escape sequences and options, but only few know about those. I want to shed light on some of those options in this post. \r\n , \n and \r Okay, everyone knows about those escape sequences: \r\n is the CRLF newline Windows uses \n is the LF newline Unix uses \r is the CR newline that old versions of Mac OS used A common combination is (?>\r\n|\n|\r) , which matches any CRLF type newline. Meet \R ! But apart from \r and \n PCRE also has another character group matching newlines: \R . By default \R matches Unicode newlines sequences, but it can be configured using several options: /(*BSR_ANYCRLF)\R/ : Matches any CRLF type newline sequence and thus is equivalent to the /(?>\r\n|\n|\r)/ regex /\R/ : Matches any Unicode newline sequence that is in the ASCII range. I.e. it is equivalent to /(?>\r\n|\n|\r|\f|\x0b|\x85)/ . So additionally to the CRLF type newlines it also matches FF formfeeds ( \f ), VT vertical tabs ( \x0b ) and the NEL next line character ( \x85 ). /\R/u ( u means UTF-8 mode): Matches any Unicode newline sequence including newline characters outside the ASCII range, which is equivalent to /(?>\r\n|\n|\r|\f|\x0b|\x85|\x{2028}|\x{2029})/ . This means only two additonal characters are added: The LS line separator ( \x{2028} ) and the PS paragraph separator ( \x{2029} ). Note that \R is not special in character classes. So /[^\R]/u for example will not match any non-newline character. Instead it will simply match any character which is not R . The magic . dot . is usally said to be “any character”. In a default configuration this is not quite true. . is “any character which is not a newline ”. What exactly a “newline” means here can also be configured similarly to \R : /(*CRLF)./ : . matches everything apart from CRLF ( \r\n ) characters /(*LF)./ : . matches everything apart from LF ( \n ) characters /(*CR)./ : . matches everything apart from CR ( \r ) characters /(*ANYCRLF)./ : . matches everything apart from CRLF style newlines, i.e. everything apart from CRLF, LF or CR. /(*ANY)./ : . matches everything apart from Unicode newline sequences (ASCII) /(*ANY)./u : . matches everything apart from Unicode newline sequences (any) /./ : What this matches depends on how PCRE was compiled, but the default is to behave as if (*LF) was specified. I.e. unless you compiled PCRE with some other newline configuration . will match everything apart from \n . To sum up, have a look at the following code: var_dump ( preg_match ( '/^a.+b$/' , "a \r\n b" )); // 0 (Newline \n is contained by \r\n) var_dump ( preg_match ( '/^a.+b$/' , "a \n b" )); // 0 (Newline \n is contained by \n) var_dump ( preg_match ( '/^a.+b$/' , "a \r b" )); // 1 (Newline \n is not contained by \r) var_dump ( preg_match ( '/(*CR)^a.+b$/' , "a \n b" )); // 1 (Newline \r is not contained by \n) var_dump ( preg_match ( '/(*CR)^a.+b$/' , "a \r b" )); // 0 (Newline \r is contained by \r) $LS = " \xE2\x80\xA8 " ; // Line Separator in UTF-8 var_dump ( preg_match ( '/(*ANY)^a.+b$/u' , "a { $LS } b" )); // 0 (Newline LS is contained by LS) var_dump ( preg_match ( '/(*ANY)^a.+b$/' , "a { $LS } b" )); // 1 (u modifier was not specified, so LS isn't a newline anymore) PCRE_DOTALL and \N PCRE also provides an option which instructs . to really match any character. This option is called PCRE_DOTALL and can be specified using the s modifier in PHP. So /./s will match absolutely any character, including newlines. But even in DOTALL mode you can get the behavior of the “normal” dot: The \N escape sequence behaves the same as . , but is not affected by the s modifier. So \N will always match any character which is not a newline (where “newline” is again defined by the above options). \N , just like \R , loses its special meaning within character groups. Whitespace character groups As a small addendum I would also like to point out what the different whitespace character groups contain, as this isn’t quite clear to most people: The commonly used \s group matches LF ( \n ), CR ( \r ), HT (tab), FF (form feed) and space characters. So it does not contain the VT vertical tab character. The POSIX character group [:space:] on the other hand includes the vertical tab, too. The \pZ Unicode character property for separators does not contain the “classic” newlines. But there are two special, PCRE specific, character properties for that purpose: p{Xsp} contains \pZ as well as LF, CR and FF. \p{Xps} additionally contains VT. Those two Unicode properties are also internally used in UCP mode ( UCP mode makes the normal \s style character groups behave like the Unicode character properties). I.e. (*UCP)\s is equivalent to \p{Xsp} and (*UCP)[:space:] is equivalent to \p{Xps} . There are also two more character groups for whitespace matching, namely \v for vertical whitespace and \h for horizontal. Contrary to the other \s style character groups these two match non-ASCII characters in UTF-8 mode even when not in UCP mode. The reason for this is that they were added only quite late, whereas the others existed pretty much from the beginning. \v matches CR, LF, VT, FF, NEL, LS, PS. \h matches HT, space and 17 other horizontal spaces which you wouldn’t normally know. Those contain things like “Six-per-em space” or “Medium mathematical space”. If you liked this article, you may want to browse my other articles or follow me on Twitter or Mastodon . | 2026-01-13T08:49:46 |
https://www.digitalpublicgoods.net/blog/reflections-from-the-2025-annual-members-meeting-in-brasilia | Home Who we are Members Governance Secretariat Team What We Do Roadmap DPGA Strategy 2023-2028 Community of Practice Reports Calls for Collaborative Action The State of the DPG Ecosystem Reports 50 in 5 Digital Public Goods DPG Registry DPG Standard Submission Guide DPGs Decoded DPG Application Toolkit DPG Application FAQs Get Involved Blog Home Blog Reflections from the 2025 ... Reflections from the 2025 Annual Members Meeting in Brasília December 1, 2025 Author: Lucy Harris, Chief Operating Officer, and Carol Matos, Senior Communications and Marketing Coordinator, DPGA Secretariat Last week, the Digital Public Goods Alliance (DPGA) concluded its fourth Annual Members Meeting (AMM)— its first ever in South America—with three energising days of collaboration, shared learning, and collective momentum. Taking place in Brasília and held in partnership with the Government of Brazil, represented by the Controladoria-Geral da União (CGU), the Ministério da Gestão e da Inovação em Serviços Públicos, and DATAPREV, this year’s AMM served as a capstone to 2025’s steady global progress and growing interest in digital public goods. DPGA member representatives gather in Brasília for the 4th Annual Members Meeting. Over the course of this year’s Annual Members Meeting, more than a hundred representatives from DPGA member organisations - including country governments, in addition to digital public good (DPG) product owners, explored how DPGs can help countries and development partners, including multilateral development banks and UN-agencies, navigate geopolitical and technological shifts while delivering real benefits for people’s lives and for the planet. It also served as an opportunity to welcome Co-Develop, co-coordinator of the 50-in-5 campaign, as the newest member of the DPGA. Desire N. Kachenje announces Co-Develop’s membership to the DPGA during the AMM 2025 opening panel. This year’s AMM reflected how far the DPGA has come, and the role it is increasingly poised to play amid rapid advances in technology and significant geopolitical change. The gathering opened with reflections on key achievements from the past year, including: Growth and maturity across the DPG ecosystem, seen through continued expansion of the DPG Registry —now with well over 200 verified digital public goods—and increased collaboration among DPGs themselves, demonstrating how open, interoperable digital solutions can drive scale and impact. Strengthened global alignment, with DPGs front and centre at major convenings including COP30, UN Open Source Week, the Internet Governance Forum in Norway, and the annual 50-in-5 Milestone Event on the sidelines of the UN General Assembly. Continued advances in understanding how DPGs can be used for DPI implementation, including the launch of the DPG4DPI Collection , which is already helping countries more easily identify DPGs that enable safe, inclusive, and interoperable DPI. Significant progress on climate, marked by a new framework to identify DPGs for climate action and Brazil’s announcement of a newly shared open-source module derived from its Rural Environmental Registry (RER) . Strengthening efforts to sustain DPGs, with growing alignment on the need for upstream maintenance, flexible financing, and stronger contribution pathways to ensure that governments and partners can adopt, adapt, and maintain DPGs over time. Together, these achievements created a strong foundation for workshops and roundtable discussions that unfolded in Brasília. Closing panel address by Cristina Kiomi Mori, Vice Minister of Management and Innovation in Public Services, Government of Brazil. “We believe that open technologies and global digital governance contribute to better governments, but also to stronger democracies and enhanced sovereignty. These joint activities and collective sharing really embody that spirit. Let us all work together in that direction to promote inclusive and sustainable development, powered by open technology strategies.” - Cristina Kiomi Mori - Vice Minister of Management and Innovation in Public Services, Government of Brazil A Week of Collaboration, Curiosity, and Shared Purpose The AMM highlighted what makes the DPGA community unique: genuine openness, practical collaboration, and a shared commitment to tackling complex challenges together. Throughout the week, there was a clear sense that the ecosystem is shifting—from isolated efforts to a more connected movement shaping global digital cooperation. Jon Lloyd, DPGA Secretariat's Director of Advocacy and 50-in-5 Program Director, engage in collaborative group discussions during the DPGA Annual Members Meeting in Brasília. Beyond the formal sessions, the week offered several opportunities to deepen those connections. The DPG Fair brought together more than 25 digital public goods, giving participants the chance to meet product teams, explore solutions up close, and identify practical ways to work together. Regional lunches allowed attendees from different parts of the world to compare experiences and approaches, while the social and cultural gatherings created a relaxed setting to build relationships and strengthen the sense of community that makes the DPGA unique. Following three jam packed days, a clear theme emerged: DPGs are becoming essential not only to the delivery of services, but also to safeguarding trust, resilience, and equitable access in an increasingly complex digital era. The DPG Fair featured digital public goods contributing to the broader DPG ecosystem. Many participants also took to social media throughout the week to share further insights , reflections , and highlights from the AMM—another sign of the community’s growing energy and desire for close collaboration. Lucy Harris, DPGA Secretariat's Chief Operating Officer, exchanges perspectives on advancing DPGs and strengthening global collaboration during the AMM 2025 closing panel. Through workshops and roundtable discussions, several key themes for 2026 took shape: Deepening DPG sustainability, ensuring countries can adopt, adapt, contribute to, and maintain DPGs for the long term, especially those that contribute to digital public infrastructure implementation. Accelerating climate action through DPGs, including the forthcoming Climate DPG Collection. Advancing public-interest AI, both by qualifying AI systems as DPGs and by supporting DPGs that make it easier to identify, prepare, and share high-quality open training data. Exploring public-interest alternatives to today’s social media platforms, in order to foster safety and trust online. Max Kintisch, DPGA Secretariat's Director of Research & Urgent Global Challenges, shares insights and sparks dialogue in one of the AMM’s roundtables. A sincere thank you to the Government of Brazil for co-hosting this year’s AMM, and to all members and product owners who travelled to be with us in Brasília. The DPGA Secretariat is deeply appreciative of such an engaged and committed community, and looks forward to carrying the lessons, insights, and connections from this week into a strong and purposeful year ahead. Together, we are well-positioned to shape the path forward for 2026. Connect Sign up to receive our monthly newsletter. Inquiries Have a question? Contact us here. Job Opportunities Learn about job openings. DPGA Brand Guide Digital Public Goods Alliance - 2025 | 2026-01-13T08:49:46 |
https://www.npopov.com/2011/10/23/Improving-lexing-performance-in-PHP.html | Improving lexing performance in PHP Blog by nikic . Find me on GitHub , StackOverflow , Twitter and Mastodon . Learn more about me . « Back to article overview. Improving lexing performance in PHP 23. October 2011 Lexing isn’t something you would normally do in PHP, simply because other languages like C can easily outperform PHP by several orders of magnitude. Still it sometimes is desirable to write lexers in PHP, e.g. for tokenizing templates, doccomments and other DSLs . So I want to share some thoughts on how to write fast lexers in PHP. Lexing CSV files PHP already provides functions for parsing CSV files and strings . I will use CSV lexing as an example anyways, simply because it’s so simple. Here an example of a CSV line (as PHP implements it): Field,Another Field,"comma -> , <- comma","quote -> \" <- quote" If we define the tokens in terms of regular expressions, they would look roughly like this: $tokenMap = array ( '~[^",\r\n]+~A' => T_PLAIN_FIELD , '~"[^"\\\\]*(?:\\\\.[^"\\\\]*)*"~A' => T_QUOTED_FIELD , '~,~A' => T_FIELD_SEPARATOR , '~\r\n?|\n~A' => T_LINE_SEPARATOR , ); Looping through the regexes The most obvious approach to lexing in PHP is to simply loop through the regexes and match them against the current position, until there are no characters left: function lex ( $string , array $tokenMap ) { $tokens = array (); $offset = 0 ; // current offset in string while ( isset ( $string [ $offset ])) { // loop as long as we aren't at the end of the string foreach ( $tokenMap as $regex => $token ) { if ( preg_match ( $regex , $string , $matches , null , $offset )) { $tokens [] = array ( $token , // token ID (e.g. T_FIELD_SEPARATOR) $matches [ 0 ], // token content (e.g. ,) ); $offset += strlen ( $matches [ 0 ]); continue 2 ; // continue the outer while loop } } throw new LexingException ( sprintf ( 'Unexpected character "%s"' , $string [ $offset ])); } return $tokens ; } The drawback of this code is fairly obvious: On every new offset one needs to iterate through all regexes and match them one at the time. This maybe isn’t such a problem in this case as we only have four regexes, but when lexing some real language one usually deals with hundreds of them. Compiling into a single regex The solution is to compile all regexes into a single big one. Our above regex would be converted to: $regex = '~ ([^",\r\n]+) | ("[^"\\\\]*(?:\\\\.[^"\\\\]*)*") | (,) | (\r\n?|\n) ~xA' ; But how can we use this? How can we know which of the four subregexes matched the string? Simple: As all the subregexes are enclosed in parenthesis they are capturing groups. So our $matches array will contain the matched string at position [0] and at the position of the matched subregex. All other groups will be empty. An example: If the regex matched the , subregex, we would get this $matches array: array ( 0 => ',' , 1 => '' , 2 => '' , 3 => ',' , 4 => '' , ); From this we know that the 3rd subregex matched, as it is the one which has a value. The resulting code for an abstract lexer class would be: class Lexer { protected $regex ; protected $offsetToToken ; public function __construct ( array $tokenMap ) { $this -> regex = '((' . implode ( ')|(' , array_keys ( $tokenMap )) . '))A' ; $this -> offsetToToken = array_values ( $tokenMap ); } public function lex ( $string ) { $tokens = array (); $offset = 0 ; while ( isset ( $string [ $offset ])) { if ( ! preg_match ( $this -> regex , $string , $matches , null , $offset )) { throw new LexingException ( sprintf ( 'Unexpected character "%s"' , $string [ $offset ])); } // find the first non-empty element (but skipping $matches[0]) using a quick for loop for ( $i = 1 ; '' === $matches [ $i ]; ++ $i ); $tokens [] = array ( $matches [ 0 ], $this -> offsetToToken [ $i - 1 ]); $offset += strlen ( $matches [ 0 ]); } return $tokens ; } } How much does this really change? I am seeing approximately 30% performance improvement for the average case ( online demo ). But this value varies with different regexes and input. If the number of regexes increases the performance improvement is bigger. Additionally in the compiled-regex variant the order of the regexed has less influence on the execution time ( online demo ). I.e. it is not that important to put the more probable regexes first and the less probable ones last. (But it still is important, only less important!) If you liked this article, you may want to browse my other articles or follow me on Twitter or Mastodon . | 2026-01-13T08:49:46 |
https://www.npopov.com/2021/11/08/Type-variance-in-PHP.html | Type variance in PHP Blog by nikic . Find me on GitHub , StackOverflow , Twitter and Mastodon . Learn more about me . « Back to article overview. Type variance in PHP 08. November 2021 Inheritance in PHP enforces the Liskov substitution principle (LSP) to make sure that an instance of the parent class can be replaced with an instance of the child class. Of course, PHP cannot enforce this in full generality – it can only detect definitely incompatible cases by inspecting class member declarations. For example, these two classes are clearly incompatible: class A { public function method ( string $arg ) {} } class B extends A { public function method ( int $arg ) {} } An instance of A cannot be replaced by B , because A::method() will accept "foobar" , while B::method() will not. Prior to PHP 7.4, the LSP verification was rather simplistic and rejected many LSP-compatible overrides. PHP 7.4 introduced covariant return types and contravariant argument types, which are most concisely illustrated with nullable types: class A { public function method ( T $arg ): ?T {} } class B extends A { public function method ( ?T $arg ): T {} } For return types, LSP requires that the child return type is the same or “more specific”. If a caller could handle the ?T return type of A::method() , it will also be able to handle the T return type of B::method() . It has to deal with strictly less possible values. Conversely, the child argument type must be the same or “more general”. B::method() accepts anything that A::method() does, and more. Subtyping Formally, we define type variance in terms of subtyping relationships: Covariance (return types): The child type must be a subtype of the parent type. Contravariance (argument types): The parent type must be a subtype of the child type. Invariance (property types): The child type must be a subtype of the parent type and the parent type must be a subtype of the child type. This implies that the types are equal (in a certain sense). I will use the notation A <= B to denote that A is a subtype of B in the following. So, what are PHP’s subtyping rules? Let’s build them up one by one: 1. A <= A Subtyping is reflexive: A type is always a subtype of itself. 2. A <= B if exists X s.t. A <= X and X <= B Subtyping is transitive. 3. A <= B if A extends B or A implements B Together with the previous rule, this means that A is a subtype of B if it extends from B or implements B anywhere higher up in the hierarchy. It does not necessary have to extend/implement it directly. 3. A <= object forall A where A is a class/interface type 4. static <= self Any class type is a subtype of object , and static is a subtype of self . 5. A <= mixed forall A 6. never <= A forall A The mixed type is the top type, and the never type is the bottom type. 7. iterable == array|Traversable iterable is effectively an alias for array|Traversable . 8. U 1 |…|U n <= V if forall U i we have U i <= V 9. U 1 &…&U n <= V if exists U i s.t. U i <= V 10. U <= V 1 |…|V n if exists V i s.t. U <= V i 11. U <= V 1 &…&V n if forall V i we have U <= V i Now to the interesting cases involving union and intersection types. Some examples: A|B is a subtype of object , because A is a subtype of object and B is a subtype of object . A&B is a subtype of A , because A is a subtype of A . static is a subtype of self|null , because static is a subtype of self . If class X implements interfaces A and B , then X is a subtype of A&B , because X is a subtype of A and X is a subtype of B. From this, we can derive rules for how two union/intersection types interact (these are the rules we implement in practice): 8’. U 1 |…|U n <= V 1 |…|V n if forall U i exists V j s.t. U i <= V j 9’. U 1 &…&U n <= V 1 &…&V n if forall V j exists U i s.t. U i <= V j 10’. U 1 |…|U n <= V 1 &…&V n if forall U i forall V j we have U i <= V j 11’. U 1 &…&U n <= V 1 |…|V n if exists U i exists V j s.t. U i <= V j The reason why it’s worth explicitly considering these is that forall and exists quantifiers do not commute. That is, you could also construct the following two variants with forall/exists swapped: 8’’. U 1 |…|U n <= V 1 |…|V n if exists V j forall U i s.t. U i <= V j 9’’. U 1 &…&U n <= V 1 &…&V n if exists U i forall V j s.t. U i <= V j However, we can discard these two rules because they are strictly weaker than 8’ and 9’. For example, according to 8’ static|null is a subtype of self|null , because static is a subtype of self and null is a subtype of null . When using 8’’ instead, the precondition is not satisfied, because static|null is a neither a subtype of self , nor of null . Because the precondition is not satisfied, the rule makes no statement on whether it is a subtype or not. The reason we use rules 8’-11’ is that they are actually equivalences, i.e. we could replace “if” with “if and only if”. That means that we don’t need to check multiple variants and determine whether any one of them succeeds. Okay, with the subtyping relationship out of the way, surely we have solved the hard part of the problem? Unfortunately, this is just where the real fun begins… Cyclic dependencies The problem that makes variance checks hard are cyclic dependencies. Consider the following example: class A { public function method (): A {} } class B extends A { public function method (): C {} } class C extends B { } These classes satisfy LSP, because C is a subtype of A. However, at the time class B is declared, PHP doesn’t know anything about class C yet, so it doesn’t know that this is actually the case. This code will thus result in an inheritance error: Fatal error: Could not check compatibility between B::method(): C and A::method(): A, because class C is not available There is also no way in which we could reorder the declarations to make the code compile: A cyclic graph cannot be sorted topologically. However, PHP does support these kinds of cyclic references if an autoloader is used, as is customary in modern code. The following code runs without error: spl_autoload_register ( function ( string $class ) { if ( $class === 'A' ) { class A { public function method (): A {} } } else if ( $class === 'B' ) { class B extends A { public function method (): C {} } } else if ( $class === 'C' ) { class C extends B { } } }); $b = new B ; Going through an autoloader allows us to load additional dependencies during inheritance, though the particulars of how this works are somewhat involved. Early class registration Prior to PHP 7.4, we would first run inheritance on a class, and then insert it into the class table, making the symbol visible. With the introduction of type variance, we need to register the symbol for the “unlinked” class first, and then run inheritance (“linking”). The preceding example should make it clear why this is the case: We start off running inheritance on class B , but then need to load C to determine a subtyping relationship. But C in turn depends on B , which should be the B we’re currently trying to link, not a separate copy (otherwise we’d just recurse infinitely). At the same time, we can’t allow actually using the class in most circumstances, because it hasn’t finished inheritance yet. Apart from a few whitelisted usages related to inheritance, we will pretend that the class does not exist. This gives us Schrödinger’s class. On the one hand, new B in this code will claim that class B doesn’t exist: spl_autoload_register ( function ( string $class ) { if ( $class === 'A' ) { new B ; // Class "B" not found } else if ( $class === 'B' ) { class B extends A { } } }); $b = new B ; On the other hand, class B {} in this code will claim that B is already declared: spl_autoload_register ( function ( string $class ) { if ( $class === 'A' ) { class B {} // Cannot declare class B, because the name is already in use } else if ( $class === 'B' ) { class B extends A { } } }); $b = new B ; Both statements are somewhat true: The class is declared, but only visible for certain symbol references. There are two more subtleties here. The first is that we actually distinguish three states: unlinked, nearly linked and linked. A nearly linked class has completed inheritance apart from potentially outstanding variance checks. Unlinked classes can only be used during subtyping checks, while nearly linked classes can be used as parents or interfaces. We have to allow the use of unlinked classes for subtyping, because we can have cyclic dependencies there. However, the actual class hierarchy itself can never be cyclic. You can’t construct something like “A extends B extends A”. As such, allowing only “nearly linked” classes is sufficient here (and prevents recursive inheritance). The second subtlety relates to error handling. Normally, inheritance errors always result in a fatal error, because the inheritance process is implemented in a destructive fashion (the unlinked class template is modified in-place). However, due to certain requirements of the Symfony framework, we treat exceptions thrown while autoloading the parent class or an implemented interface specially. We make sure to load parent/interface dependencies before doing any destructive changes, which allows us to recover from a failure by simply unregistering the class again. Unfortunately, unlinked uses introduce a complication: We allow unlinked classes to participate in subtyping checks, on the premise that in the end either inheritance on all involved classes will succeed (and as such, the subtyping results were correct) or else inheritance will fail with a fatal error. If we were to unregister a class that participated in a subtyping check, this logic would no longer hold. Consider the following contrived example: spl_autoload_register ( function ( string $class ) { class X { public function test (): I {} } class Y extends X { public function test (): B {} } throw new Exception ( "Class $class not found" ); }); interface I {} class B extends A implements I {} An exception is thrown while loading the parent class A . If we were to simply unregister B and let it bubble up, the programmer could catch the exception and then declare B with a different hierarchy: try { class B extends A implements I {} } catch ( Exception ) { class B {} } However, we have already made use of the fact that B is a subtype of I when linking the classes X and Y . If we allowed this kind of code, the earlier subtyping assumption would no longer hold. For this reason we have to track whether a class has had any “unlinked uses”, in which case we must convert the autoloader exception into a fatal error: Fatal error: During inheritance of B with variance dependencies: Uncaught Exception: Class A not found This is a compromise to make Symfony’s optional dependency hacks work for the common case, while preserving correctness in the general case. Delayed variance obligations Subtyping checks can have three possible results: Success, failure and unresolved. The subtyping check is performed without autoloading, but allowing the use of unlinked classes. If it’s not possible to produce a definitive result, then all unknown classes mentioned in the two types are registered as “delayed autoloads” and the unresolved state is returned. It is important that we try to determine the subtyping relationship without loading additional classes first. The by far most common case is that types during inheritance are unchanged, and we don’t need class loading to determine that A is a subtype of A . We also don’t need class loading to know that A is a subtype of ?A , and so on. Triggering class loading for trivial subtyping relationships like these would greatly increase the number of loaded classes: Types mentioned in methods that are not otherwise used in the current request would have to be loaded. Class loading is expensive, and we want to minimize it as much as possible. Now, if we have received an unresolved variance result, then we will register a delayed variance obligation for later processing. There are three kinds of obligations: Method compatibilty obligation: Requires that a certain child method is compatible with a certain parent method. Property compatibility obligation: Requires that a certain child property is compatible with a certain parent property. Dependency obligation: Requires that a parent class or implemented interface will be linked. While we can use a “nearly linked” class during inheritance, all dependencies must be fully linked for the class to be fully linked. If the class has any open variance obligations after inheritance is otherwise finished (“nearly linked”), we will load all delayed autoloads and then process the obligations again. Dependency obligations are handled by checking obligations on the dependency first. If any obligations are still not satisfied, then inheritance fails with a fatal error, either because of an actual variance violation, or because a dependency is still missing despite the autoloading attempt. An important aspect of the variance implementation is that it ensures that classes are usable immediately after the class declaration. Consider the following variant of our motivating example: function printAvailable () { if ( class_exists ( A :: class , false )) echo "A" ; if ( class_exists ( B :: class , false )) echo "B" ; if ( class_exists ( C :: class , false )) echo "C" ; echo " \n " ; } spl_autoload_register ( function ( string $class ) { if ( $class === 'A' ) { class A { public function method (): A {} } echo "After A: " ; printAvailable (); } else if ( $class === 'B' ) { class B extends A { public function method (): C {} } echo "After B: " ; printAvailable (); } else if ( $class === 'C' ) { class C extends B { } echo "After C: " ; printAvailable (); } }); $b = new B ; // Prints: // After A: A // After C: ABC // After B: ABC Here we check which classes are available after each class declaration. The general user expectation is that a class is usable immediately after declaring it. While style guides generally discourage mixing declarations with code, supporting this is important for some use cases, such as calling class_alias() directly after a declaration, or calling a static initializer on the class. The order of the prints gives us a hint on how class linking plays out in this case: B is loaded and registered. A is loaded and linked (it is a leaf class), and new A is printed. C is added to the delayed autoloads and a method compatibility obligation between B::method() and A::method() is registered. After B is nearly linked, C is loaded via delayed autoload. It will use B while it is nearly linked, adding a dependency obligation. After C is nearly linked, there are no delayed autoloads and variance obligations on C are processed. There is a single dependency obligation on B. Thus variance obligations on B are processed first. The single method compatibility obligation is satisfied now that C is available. B becomes fully linked. As the dependency obligation has been satisfied, C becomes fully linked as well, and new C is printed. At this point we return to linking of B, but it is already linked now, so we’re done and print new B . The main peculiar bit here is that class B becomes fully linked (and thus fully available to code) during the declaration of class C. What happens if we tweak the previous code to make C the loaded root class instead? $c = new C ; // Prints: // After A: A // After B: AB // After C: ABC This case is simpler, because the classes are loaded in a nice chain, so no delayed variance obligations are involved here. We do make use of the fact that C is a subtype of A while C is still unlinked though. The interesting bit about this example is that class B becomes fully linked (and available) while C remains unlinked. Doesn’t this break variance, as linking of class C might still fail later? This is fine, based on the following reasoning: Before class C is fully linked, a call to B::method() cannot return successfully, because the C return type is not available yet. As such, it’s not possible to observe a broken variance promise on a call to this method. Lateron, either C will become fully linked and all is good, or C will fail inheritance and throw a fatal error. Even code executing after the fatal error (e.g. in a shutdown function) will not be able to register a new C with a different subtyping relationship, because the old stub class remains registered. Conclusion The addition of type variance support is one of the prime examples where a feature has been accepted without anything even approaching a complete understanding of its technical implications. The feature is conceptually simple, but the devil is very much in the details. Now, I do believe that this is a necessary feature, despite the complexity. However, none of this complexity was described in the original RFC, and it took significant effort to nail down the semantics after the fact. If you liked this article, you may want to browse my other articles or follow me on Twitter or Mastodon . | 2026-01-13T08:49:46 |
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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 Performance Follow Hide Tag for content related to software performance. Create Post submission guidelines Articles should be obviously related to software performance in some way. Possible topics include, but are not limited to: Performance Testing Performance Analysis Optimising for performance Scalability Resilience But most of all, be kind and humble. 💜 Older #performance posts 2 3 4 5 6 7 8 9 10 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu Concurrency in Rust (Threads, Channels) Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Jan 8 Concurrency in Rust (Threads, Channels) # performance # programming # rust # tutorial Comments Add Comment 10 min read Get Hit By Performance Bottleneck In Canvas Ikhwan A Latif Ikhwan A Latif Ikhwan A Latif Follow Jan 2 Get Hit By Performance Bottleneck In Canvas # learning # development # programming # performance Comments Add Comment 4 min read Why I Chose Rust Over Python for Production AI Systems Mayuresh Smita Suresh Mayuresh Smita Suresh Mayuresh Smita Suresh Follow Jan 7 Why I Chose Rust Over Python for Production AI Systems # ai # performance # python # rust 3 reactions Comments Add Comment 6 min read EP 7: The "Join" Tax vs. The "Storage" Tax Hrishikesh Dalal Hrishikesh Dalal Hrishikesh Dalal Follow Jan 2 EP 7: The "Join" Tax vs. The "Storage" Tax # systemdesign # architecture # database # performance Comments Add Comment 4 min read PriviMetrics: Privacy-First, Lightweight Analytics for Shared Hosting WebOrbiton WebOrbiton WebOrbiton Follow Jan 3 PriviMetrics: Privacy-First, Lightweight Analytics for Shared Hosting # showdev # analytics # performance # privacy Comments Add Comment 1 min read Sustainable AI Benchmarks Developers Will Be Asked About In 2026 Arbisoft Arbisoft Arbisoft Follow Jan 2 Sustainable AI Benchmarks Developers Will Be Asked About In 2026 # career # performance # ai # devops Comments Add Comment 3 min read Why sum(x**2 for x in range(1000000)) Uses 4000x Less Memory Samuel Ochaba Samuel Ochaba Samuel Ochaba Follow Jan 6 Why sum(x**2 for x in range(1000000)) Uses 4000x Less Memory # python # performance # programming # tutorial Comments 2 comments 2 min read Computed Fields Causing Infinite Recomputations (odoo) Aaron Jones Aaron Jones Aaron Jones Follow Jan 7 Computed Fields Causing Infinite Recomputations (odoo) # backend # performance # python # tutorial 5 reactions Comments Add Comment 3 min read 2026 Web Dev Trends That Actually Matter Abhijeet Bhale Abhijeet Bhale Abhijeet Bhale Follow Jan 6 2026 Web Dev Trends That Actually Matter # webdev # javascript # career # performance 1 reaction Comments Add Comment 4 min read Part 2 - 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https://www.npopov.com/2012/07/10/What-PHP-5-5-might-look-like.html | What PHP 5.5 might look like Blog by nikic . Find me on GitHub , StackOverflow , Twitter and Mastodon . Learn more about me . « Back to article overview. What PHP 5.5 might look like 10. July 2012 PHP 5.4 was released just four months ago, so it probably is a bit too early to look at the next PHP version. Still I’d like to give all the people who aren’t following the internals mailing list a small sneak peek at what PHP 5.5 might look like. But be sure to understand this: PHP 5.5 is in an early development stage, so nobody knows how the end result will look like. All I am talking about here are proposals . I’m pretty sure that not all of the things listed below will go into PHP 5.5, or at least not in their current form. So, don’t get too excited about this :) The list of new features / proposals is rather large and not sorted by significance. So if you don’t want to read through all of it, here are the four features I personally am most excited about: A simple API for password hashing Scalar typehinting Getters and setters Generators Now, without further ado, the list of stuff being worked on for PHP 5.5: Backwards compatibility breaks We’ll start off with two changes that already landed in master and represent BC breaks (to some degree at least): Windows XP and 2003 support dropped Status: landed; Responsible: Pierre Joye PHP 5.5 will no longer support Windows XP and 2003. Those systems are around a decade old, so PHP is pulling the plug on them. /e modifier deprecated Status: landed; Responsible: myself The e modifier instructs the preg_replace function to evaluate the replacement string as PHP code instead of just doing a simple string replacement. Unsurprisingly this behavior is a constant source of problems and security issues. That’s why use of this modifier will throw a deprecation warning as of PHP 5.5. As a replacement you should use the preg_replace_callback function. You can find more information on this change in the corresponding RFC . Function and class additions Next we’ll look at some the planned function and class additions: boolval() Status: landed; Responsible: Jille Timmermans PHP already implements the strval , intval and floatval functions. To be consistent the boolval function is now added, too. It does exactly the same thing as a (bool) cast, but can be used as a callback function. hash_pbkdf2() Status: landed; Responsible: Anthony Ferrara PBKDF2 stands for “Password-Based Key Derivation Function 2” and is - as the name already says - an algorithm for deriving a cryptographic key from a password. This is required for encryption algorithms, but can also be used for password hashing. For a more extensive description and usage examples see the RFC . Intl additions Status: landed; Responsible: Gustavo André dos Santos Lopes There have been many improvements to the intl extension . E.g. there will be new IntlCalendar , IntlGregorianCalendar , IntlTimeZone , IntlBreakIterator , IntlRuleBasedBreakIterator , IntlCodePointBreakIterator classes. I sadly don’t know much about the intl extension, so I will just direct you to the mailing list announcements for Calendar and BreakIterator , if you want to know more. array_column() Status: proposed; Responsible: Ben Ramsey There is a proposal pending for a new array_column (or array_pluck ) function that would behave as follows: $userNames = array_column ( $users , 'name' ); // is the same as $userNames = []; foreach ( $users as $user ) { $userNames [] = $user [ 'name' ]; } So it would be like fetching a column from a database, but for arrays. A simple API for password hashing Status: proposed; Responsible: Anthony Ferrara The recent password leaks (from LinkedIn etc) have shown that even large websites don’t get how to properly hash passwords. People have been advocating the use of bcrypt for years, but still most people seem to be using completely unsafe sha1 hashes. We figured that the reason for this might be the really hard to use API of the crypt function. Thus we would like to introduce a new, simple API for secure password hashing: $password = "foo" ; // creating the hash $hash = password_hash ( $password , PASSWORD_BCRYPT ); // verifying a password if ( password_verify ( $password , $hash )) { // password correct! } else { // password wrong! } The new hashing API comes with a few more features, which are outlined in the RFC . Language changes Now comes the really interesting stuff: New language features and enhancements. Constant dereferencing Status: landed; Responsible: Xinchen Hui “Constant dereferencing” means that array operations can be directly applied to string and array literals. Here two examples: function randomHexString ( $length ) { $str = '' ; for ( $i = 0 ; $i < $length ; ++ $i ) { $str . = "0123456789abcdef" [ mt_rand ( 0 , 15 )]; // direct dereference of string } } function randomBool () { return [ false , true ][ mt_rand ( 0 , 1 )]; // direct dereference of array } I don’t think that this feature is of much use in practice, but it makes the language a bit more consistent. See also the RFC . empty() works with function calls (and other expressions) Status: landed; Responsible: myself Currently the empty() language construct can only be used on variables, not on other expressions. In particular code like empty($this->getFriends()) would throw an error. As of PHP 5.5 this becomes valid code. For more info see the RFC . Getting the fully qualified class name Status: proposed; Responsible: Ralph Schindler PHP 5.3 introduced namespaces with the ability to alias classes and namespaces to shorter versions. This does not apply to string class names though: use Some\Deeply\Nested\Namespace\FooBar ; // does not work, because this will try to use the global `FooBar` class $reflection = new ReflectionClass ( 'FooBar' ); To solve this a new FooBar::class syntax is proposed, which returns the fully qualified name of the class: use Some\Deeply\Nested\Namespace\FooBar ; // this works because FooBar::class is resolved to "Some\\Deeply\\Nested\\Namespace\\FooBar" $reflection = new ReflectionClass ( FooBar :: class ); For more examples see the RFC . Parameter skipping Status: proposed; Responsible: Stas Malyshev If you have a function accepting multiple optional parameters there is currently no way to change just the last one, leaving all others at their default. Taking the example from the RFC , if you have a function like the following: function create_query($where, $order_by, $join_type='', $execute = false, $report_errors = true) { ... } Then there is no way to set $report_errors = false without replicating the other two default values. To solve this a way of skipping parameters is proposed: create_query("deleted=0", "name", default, default, false); Personally I’m not particular fond of this proposal. In my eyes code that needs this feature is just badly designed. Functions shouldn’t have 12 optional parameters. Scalar typehinting Status: proposed; Responsible: Anthony Ferrara Scalar typehinting was originally planned to go into 5.4, but never made it due to lack of consensus. For more info on why scalar typehints haven’t made it into PHP yet, see: Scalar typehints are harder than you think . For PHP 5.5 the discussion has come up again and I think there is a fairly decent proposal for scalar typehints with casting . It would work by casting the input value to the specified type, but only if the cast can occur without data loss . E.g. 123 , 123.0 , "123" would all be valid inputs for an int parameter, but "hallo world" would not. This matches the behavior of internal functions. function foo ( int $i ) { ... } foo ( 1 ); // $i = 1 foo ( 1.0 ); // $i = 1 foo ( "1" ); // $i = 1 foo ( "1abc" ); // not yet clear, maybe $i = 1 with notice foo ( 1.5 ); // not yet clear, maybe $i = 1 with notice foo ([]); // error foo ( "abc" ); // error Getters and setters Status: proposed; Responsible: Clint Priest If you’ve never been a fan of writing all those getXYZ() and setXYZ($value) methods, then this should be a welcome change for you. The proposal adds a new syntax for defining what should happen when a property is set / read: class TimePeriod { public $seconds ; public $hours { get { return $this -> seconds / 3600 ; } set { $this -> seconds = $value * 3600 ; } } } $timePeriod = new TimePeriod ; $timePeriod -> hours = 10 ; var_dump ( $timePeriod -> seconds ); // int(36000) var_dump ( $timePeriod -> hours ); // int(10) There are also some more features like read-only properties. If you want to know more, have a look at the RFC . Generators Status: proposed; Responsible: myself Currently custom iterators are used only rarely, because their implementation requires lots of boilerplate code. Generators solve this issue by providing an easy and boilerplate-free way to create iterators. For example, this is how you could define the range function, but as an iterator: function * xrange ( $start , $end , $step = 1 ) { for ( $i = $start ; $i < $end ; $i += $step ) { yield $i ; } } foreach ( xrange ( 10 , 20 ) as $i ) { // ... } The above xrange function has the same behavior as the builtin range function with one difference: Instead of returning an array with all the values, it returns an iterator which generates the values on-the-fly. For more in-depth introduction into the topic see the RFC . List comprehensions and generator expressions Status: proposed; Responsible: myself List comprehensions provide a simple way to do small operations on arrays: $firstNames = [foreach ($users as $user) yield $user->firstName]; The above list comprehension is equivalent to the following code: $firstNames = []; foreach ($users as $user) { $firstNames[] = $user->firstName; } It is also possible to filter arrays this way: $underageUsers = [foreach ($users as $user) if ($user->age < 18) yield $user]; Generator expressions are similar, but return an iterator (which generates the values on-the-fly) instead of an array. For more examples see the mailing list announcement . Wrapping up As you can see, there is a lot of awesome stuff being worked on for PHP 5.5. But as I already said, PHP 5.5 is still very young, so we don’t know for sure what will get in and what will not. If you want to stay updated on the new features or want to help out in discussions and/or development, be sure to subscribe to the internals mailing list . Comments welcome! If you liked this article, you may want to browse my other articles or follow me on Twitter or Mastodon . | 2026-01-13T08:49:46 |
https://opensource.org/blog/category/newsletter | Newsletter archive – 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 Blog Newsletter archive Newsletter archive Archive of previous newsletters. Celebrating Generosity and Growth in the OSI Community Celebrating Generosity and Growth in the OSI Community Members Newsletter – December 2025 As we reach the final weeks of the year, I find myself reflecting on a season that invites both gratitude and giving, two values that feel especially resonant for our community. Serving as Interim Executive Director these past months has only deepened my appreciation for the people who make Open Source possible. 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https://www.npopov.com/2012/06/15/The-true-power-of-regular-expressions.html | The true power of regular expressions Blog by nikic . Find me on GitHub , StackOverflow , Twitter and Mastodon . Learn more about me . « Back to article overview. The true power of regular expressions 15. June 2012 As someone who frequents the PHP tag on StackOverflow I pretty often see questions about how to parse some particular aspect of HTML using regular expressions. A common reply to such a question is: You cannot parse HTML with regular expressions, because HTML isn’t regular. Use an XML parser instead. This statement - in the context of the question - is somewhere between very misleading and outright wrong. What I’ll try to demonstrate in this article is how powerful modern regular expressions really are. What does “regular” actually mean? In the context of formal language theory , something is called “regular” when it has a grammar where all production rules have one of the following forms: B -> a B -> aC B -> ε You can read those -> rules as “The left hand side can be replaced with the right hand side”. So the first rule would be “B can be replaced with a”, the second one “B can be replaced with aC” and the third one “B can be replaced with the empty string” ( ε is the symbol for the empty string). So what are B , C and a ? By convention, uppercase characters denote so called “non-terminals” - symbols which can be broken down further - and lowercase characters denote “terminals” - symbols which cannot be broken down any further. All that probably sounds a bit abstract, so let’s look at an example: Defining the natural numbers as a grammar. N -> 0 N -> 1 N -> 2 N -> 3 N -> 4 N -> 5 N -> 6 N -> 7 N -> 8 N -> 9 N -> 0N N -> 1N N -> 2N N -> 3N N -> 4N N -> 5N N -> 6N N -> 7N N -> 8N N -> 9N What this grammar says is: A natural number (N) is ... one of the digits 0 to 9 or ... one of the digits 0 to 9 followed by another natural number (N) In this example the digits 0 to 9 would be terminals (as they can’t be broken down any further) and N would be the only non-terminal (as it can be and is broken down further). If you have another look at the rules and compare them to the definition of a regular grammar from above, you’ll see that they meet the criteria: The first ten rules are of the form B -> a and the second ten rules follow the form B -> aC . Thus the grammar defining the natural numbers is regular . Another thing you might notice is that even though the above grammar defines such a simple thing, it is already quite bloated. Wouldn’t it be better if we could express the same concept in a more concise manner? And that’s where regular expressions come in: The above grammar is equivalent to the regex [0-9]+ (which is a hell lot simpler). And this kind of transformation can be done with any regular grammar: Every regular grammar has a corresponding regular expression which defines all its valid strings. What can regular expressions match? Thus the question arises: Can regular expressions match only regular grammars, or can they also match more? The answer to this is both yes and no: Regular expressions in the formal grammar sense can (pretty much by definition) only parse regular grammars and nothing more. But when programmers talk about “regular expressions” they aren’t talking about formal grammars. They are talking about the regular expression derivative which their language implements. And those regex implementations are only very slightly related to the original notion of regularity. Any modern regex flavor can match a lot more than just regular languages. How much exactly, that’s what the rest of the article is about. To keep things simple, I’ll focus on the PCRE regex implementation in the following, simply because I know it best (as it’s used by PHP). Most other regex implementations are quite similar though, so most stuff should apply to them too. The language hierarchy In order to analyze what regular expressions can and cannot match, we first have to look at what other types of languages there are. A good starting point for this is the Chomsky hierarchy : Chomsky hierarchy: /-------------------------------------------\ | | | Recursively enumerable languages | Type 0 | | | /-----------------------------------\ | | | | | | | Context-sensitive languages | | Type 1 | | | | | | /---------------------------\ | | | | | | | | | | | Context-free languages | | | Type 2 | | | | | | | | | /-------------------\ | | | | | | | Regular languages | | | | Type 3 | | | \-------------------/ | | | | | \---------------------------/ | | | \-----------------------------------/ | \-------------------------------------------/ As you can see the Chomsky hierarchy divides formal languages into four types: Regular languages (Type 3) are the least-powerful, followed by the context-free languages (Type 2), the context-sensitive languages (Type 1) and at last the all-mighty recursively enumerable languages (Type 0). The Chomsky hierarchy is a containment hierarchy, so the smaller boxes in the above image are fully contained in the larger boxes. For example every regular language is also a context-free language (but not the other way around!) So, let’s move one step up in that hierarchy: We already know that regular expressions can match any regular language. But can they also match context-free languages? (Reminder: When I say “regular expression” here I obviously mean it in the programmer sense, not the formal language theory sense.) Matching context-free languages The answer to this is yes , they can! Let’s take the classical example of a context-free language, namely {a^n b^n, n>0} , which means “A number of a characters followed by the same number of b characters”. The (PCRE) regex for this language is: /^(a(?1)?b)$/ The regular expression is very simple: (?1) is a reference to the first subpattern, namely (a(?1)?b) . So basically you could replace the (?1) by that subpattern, thus forming a recursive dependency: /^(a(?1)?b)$/ /^(a(a(?1)?b)?b)$/ /^(a(a(a(?1)?b)?b)?b)$/ /^(a(a(a(a(?1)?b)?b)?b)?b)$/ # and so on From the above expansions it should be clear that this expression can match any string with the same number of a s and b s. Thus regular expressions can match at least some non-regular, context-free grammars. But can they match all? To answer that, we first have to look at how context-free grammars are defined. In a context-free grammar all production rules take the following form: A -> β Here A once again is a non-terminal symbol and β is an arbitrary string of terminals and non-terminals. Thus every production rule of a context-free grammar has a non-terminal on the left hand side and an arbitrary symbol string on the right hand side. As an example, have a look at the following grammar: function_declaration -> T_FUNCTION is_ref T_STRING '(' parameter_list ')' '{' inner_statement_list '}' is_ref -> '&' is_ref -> ε parameter_list -> non_empty_parameter_list parameter_list -> ε non_empty_parameter_list -> parameter non_empty_parameter_list -> non_empty_parameter_list ',' parameter // ... ... ... What you see there is an excerpt from the PHP grammar (just a few sample rules). The syntax is slightly different from what we used before, but should be easy to understand. One aspect worth mentioning is that the uppercase T_SOMETHING names here also are terminal symbols. These symbols which are usually called tokens encode more abstract concepts. E.g. T_FUNCTION represents the function keyword and T_STRING is a label token (like getUserById or some_other_name ). I’m using this example to show one thing: Context-free grammars are already powerful enough to encode quite complex languages. That’s why pretty much all programming languages have a context-free grammar. In particular this also includes well-formed HTML. Now, back to the actual question: Can regular expressions match all context-free grammars? Once again, the answer is yes ! This is pretty easy to prove as regular expressions (at least PCRE and similar) provide a syntax very similar to the above for constructing grammars: / (?(DEFINE) (?<addr_spec> (?&local_part) @ (?&domain) ) (?<local_part> (?&dot_atom) | (?&quoted_string) | (?&obs_local_part) ) (?<domain> (?&dot_atom) | (?&domain_literal) | (?&obs_domain) ) (?<domain_literal> (?&CFWS)? \[ (?: (?&FWS)? (?&dtext) )* (?&FWS)? \] (?&CFWS)? ) (?<dtext> [\x21-\x5a] | [\x5e-\x7e] | (?&obs_dtext) ) (?<quoted_pair> \\ (?: (?&VCHAR) | (?&WSP) ) | (?&obs_qp) ) (?<dot_atom> (?&CFWS)? (?&dot_atom_text) (?&CFWS)? ) (?<dot_atom_text> (?&atext) (?: \. (?&atext) )* ) (?<atext> [a-zA-Z0-9!#$%&'*+/=?^_`{|}~-]+ ) (?<atom> (?&CFWS)? (?&atext) (?&CFWS)? ) (?<word> (?&atom) | (?&quoted_string) ) (?<quoted_string> (?&CFWS)? " (?: (?&FWS)? (?&qcontent) )* (?&FWS)? " (?&CFWS)? ) (?<qcontent> (?&qtext) | (?&quoted_pair) ) (?<qtext> \x21 | [\x23-\x5b] | [\x5d-\x7e] | (?&obs_qtext) ) # comments and whitespace (?<FWS> (?: (?&WSP)* \r\n )? (?&WSP)+ | (?&obs_FWS) ) (?<CFWS> (?: (?&FWS)? (?&comment) )+ (?&FWS)? | (?&FWS) ) (?<comment> \( (?: (?&FWS)? (?&ccontent) )* (?&FWS)? \) ) (?<ccontent> (?&ctext) | (?&quoted_pair) | (?&comment) ) (?<ctext> [\x21-\x27] | [\x2a-\x5b] | [\x5d-\x7e] | (?&obs_ctext) ) # obsolete tokens (?<obs_domain> (?&atom) (?: \. (?&atom) )* ) (?<obs_local_part> (?&word) (?: \. (?&word) )* ) (?<obs_dtext> (?&obs_NO_WS_CTL) | (?&quoted_pair) ) (?<obs_qp> \\ (?: \x00 | (?&obs_NO_WS_CTL) | \n | \r ) ) (?<obs_FWS> (?&WSP)+ (?: \r\n (?&WSP)+ )* ) (?<obs_ctext> (?&obs_NO_WS_CTL) ) (?<obs_qtext> (?&obs_NO_WS_CTL) ) (?<obs_NO_WS_CTL> [\x01-\x08] | \x0b | \x0c | [\x0e-\x1f] | \x7f ) # character class definitions (?<VCHAR> [\x21-\x7E] ) (?<WSP> [ \t] ) ) ^(?&addr_spec)$ /x What you see above is a regular expression for matching email addresses as per RFC 5322 . It was constructed simply by transforming the BNF rules from the RFC into a notation that PCRE understands. The syntax is quite simple: All rules definitions are wrapped into a DEFINE assertion, which basically means that all those rules should not be directly matched against, they should just be defined. Only the ^(?&addr_spec)$ part at the end specifies what should be matched. The rule definitions are actually not really “rules” but rather named subpatterns. In the previous (a(?1)?b) example the 1 referenced the first subpattern. With many subpatterns this obviously is impractical, thus they can be named. So (?<xyz> ...) defines a pattern with name xyz . (?&xyz) then references it. Also, pay attention to another fact: The regular expression above uses the x modifier. This instructs the engine to ignore whitespace and to allow # -style comments. This way you can nicely format the regex, so that other people can actually understand it. (Much unlike this RFC 822 email address regex…) The above syntax thus allows simple mappings from grammars to regular expressions: A -> B C A -> C D // becomes (?<A> (?&B) (?&C) | (?&C) (?&D) ) The only catch is: Regular expressions don’t support left recursion. E.g. taking the above definition of a parameter list: non_empty_parameter_list -> parameter non_empty_parameter_list -> non_empty_parameter_list ',' parameter You can’t directly convert it into a grammar based regex. The following will not work: (?<non_empty_parameter_list> (?&parameter) | (?&non_empty_parameter_list) , (?&parameter) ) The reason is that here non_empty_parameter_list appears as the leftmost part of its own rule definition. This is called left-recursion and is very common in grammar definitions. The reason is that the LALR(1) parsers which are usually used to parse them handle left-recursion much better than right-recursion. But, no fear, this does not affect the power of regular expressions at all. Every left-recursive grammar can be transformed to a right-recursive one. In the above example it’s as simple as swapping the two parts: non_empty_parameter_list -> parameter non_empty_parameter_list -> parameter ',' non_empty_parameter_list So now it should be clear that regular expressions can match any context-free language (and thus pretty much all languages which programmers are confronted with). Only problem is: Even though regular expressions can match context-free languages nicely, they can’t usually parse them. Parsing means converting some string into an abstract syntax tree. This is not possible using regular expressions, at least not with PCRE (sure, in Perl where you can embed arbitrary code into a regex you can do pretty much everything…). Still, the above DEFINE based regex definition has proven to be very useful to me. Usually you don’t need full parsing support, but want to just match (e.g. email addresses) or extract small pieces of data (not the whole parse tree). Most complex string processing problems can be made much simpler using grammar based regexes :) At this point, let me point out again what I already quickly mentioned earlier: Well-formed HTML is context-free. So you can match it using regular expressions, contrary to popular opinion. But don’t forget two things: Firstly, most HTML you see in the wild is not well-formed (usually not even close to it). And secondly, just because you can , doesn’t mean that you should . You could write your software in Brainfuck, still for some reason you don’t. My opinion on the topic is: Whenever you need generic HTML processing, use a DOM library of your choice. It’ll gracefully handle malformed HTML and take the burden of parsing from you. On the other hand if you are dealing with specific situations a quick regular expression is often the way to go. And I have to admit: Even though I often tell people to not parse HTML with regular expressions I do it myself notoriously often. Simply because in most cases I deal with specific and contained situations in which using regex is just simpler. Context-sensitive grammars Now that we covered context-free languages extensively, let’s move up one step in the Chomsky hierarchy: Context-sensitive languages. In a context-sensitive language all production rules have the following form: αAβ → αγβ This mix of characters might start to look more complicated, but it is actually quite simple. At its core you still have the pattern A → γ , which was how we defined context-free grammars. The new thing now is that you additionally have α and β on both sides. Those two form the context (which also gives this grammar class the name). So basically A can now only be replaced with γ if it has α to its left and β to its right. To make this more clear, try to interpret the following rules: a b A -> a b c a B c -> a Q H c H B -> H C The English translations would be: Replace `A` with `c`, but only if it has `a b` to its left. Replace `B` with `Q H`, but only if it has `a` to its left and `c` to its right. Replace `B` with `C`, but only if it has `H` to its left. Context-sensitive languages are something that you will rarely encounter during “normal” programming. They are mostly important in the context of natural language processing (as natural languages are clearly not context-free. Words have different meaning depending on context). But even in natural language processing people usually work with so called “mildly context-sensitive languages”, as they are sufficient for modeling the language but can be parsed much faster. To understand just how powerful context-sensitive grammars are let’s look at another grammar class, which has the exact same expressive power as the context-sensitive ones: Non-contracting grammars. With non-contracting grammars every production rule has the form α -> β where both α and β are arbitrary symbol strings with just one restriction: The number of symbols on the right hand side is not less than on the left hand side. Formally this is expressed in the formula |α| <= |β| where |x| denotes the length of the symbol string. So non-contracting grammars allow rules of any form as long as they don’t shorten the input. E.g. A B C -> H Q would be an invalid rule as the left hand side has three symbols and the right hand side only two. Thus this rule would be shortening (or “contracting”). The reverse rule H Q -> A B C on the other hand would be valid, as the right side has more symbols than the left, thus being lengthening. This equivalence relationship of context-sensitive grammars and non-contracting grammars should make pretty clear that you can match near-everything with a context-sensitive grammar. Just don’t shorten :) To get an impression of why both grammar kinds have the same expressive power look at the following transformation example: // the non-contracting grammar A B -> C D // can be transformed to the following context-sensitive grammar A B -> A X A X -> Y X Y X -> Y D Y D -> C D Anyways, back to regular expressions. Can they match context-sensitive languages too? This time I can’t gave you definite answer. They certainly can match some context-sensitive languages, but I don’t know whether they can match all of them. An example of a context-sensitive language that can be easily matched using regex is a modification of the context-free language {a^n b^n, n>0} mentioned above. When you change it into {a^n b^n c^n, n>0} , i.e. some number of a s followed by the same number of b s and c s, it becomes context-sensitive. The PCRE regex for this language is this: /^ (?=(a(?-1)?b)c) a+(b(?-1)?c) $/x If you ignore the (?=...) assertion for now you’re left with a+(b(?-1)?c) . This checks that there is an arbitrary number of a s, followed by the same number of b s and c s. The (?-1) is a relative subpattern reference and means “the last defined subpattern”, which is (b(?-1)?c) in this case. The new thing now is the (?=...) which is a so called zero-width lookahead assertion. It checks that the following text matches the pattern, but it does not actually consume the text. Thus the text is basically checked against both patterns at the same time. The a+(b(?-1)?c) part verifies that the number of b s and c s is the same and the (a(?-1)?b)c part checks that the number of a s and b s is the same. Both pattern together thus ensure that the number of all three characters is the same. In the above regex you can already see how the concept of “context” is realized in regular expressions: Using assertions. If we get back to the definition of a context-sensitive grammar, you could now say that a production rule of type αAβ → αγβ can be converted into the following regex DEFINE rule: (?<A> (?<= α ) γ (?= β ) ) This would then say that A is γ , but only if it has α to its left and β to its right. Now, the above might look as if you can easily convert a context-sensitive grammar into a regular expression, but its not actually true. The reason is that lookbehind assertions ( (?<= ... ) ) have one very significant limitation: They have to be fixed-width. This means that the length of the text matched by the assertion has to known in advance. E.g. you can write (?<= a(bc|cd) ) , but you can’t write (?<= ab+) . In the first case the assertion matches exactly three characters in any case, thus being fixed-width. In the second case on the other hand the assertion could match ab , abb , abbb etc. All of those have different lengths. Thus the engine can’t know when it should start to match them and as such they are simply disallowed. This pretty much blows the easy conversion of context-sensitive grammars to regex. Pretty much all such grammars require variable-width lookbehind assertions. But the fact that there is no direct context-sensitive grammar to regex conversion doesn’t by itself mean that regular expressions can’t match all of them. E.g. the above {a^n b^n c^n, n>0} language also has a grammar that would require variable-width lookbehind assertions. But we can still avoid using them as regex isn’t bound to specifying rules in a grammar. Maybe the same is possible for all other context-sensitive grammars too. I honestly don’t know. So, what can we say here? Regex can match at least some context-sensitive languages, but it’s unknown whether it can match all of them. Unrestricted grammars The next grammar class in the Chomsky hierarchy are the unrestricted grammars. The language set which one can form using them is the set of all recursively enumerable languages. There is little to say about unrestricted grammars as they are, well, unrestricted. Production rules for unrestricted grammars have the form α -> β , where α and β are symbol strings with no restrictions whatsoever. So basically unrestricted grammars remove the “non-contracting” part of the non-contracting grammars. Thus for them A B C -> H Q would be a valid rule, even though previously it wasn’t. How powerful are unrestricted grammars exactly? They are as powerful as it gets: They are Turing-complete. There even is a “programming language” which is based on unrestricted grammars: Thue . As it is Turing-complete it can do everything that other languages can do. One implication of being Turing-complete is that checking whether a certain string adheres to some grammar is undecidable for the general case. Sadly I can’t say anything whatsoever about how regular expressions and unrestricted grammars relate. Heck, I couldn’t even find an example of a meaningful unrestricted grammar (that wasn’t non-contracting). But now that we started talking about Turing-completeness we get to another point: Regular expressions with backreferences are NP-complete There is another very powerful regular expression feature that I did not mentioned previously: backreferences. E.g. consider this very simple regex: /^(.+)\1$/ (.+) matches some arbitrary text and \1 matches the same text. In general \n means “whatever the n th subpattern matched”. E.g. if (.+) matched foo , then \1 will also match only foo and nothing else. Thus the expression (.+)\1 means “Some text followed by a copy of itself”. What this simple regex matches is called the “copy language” and is another typical example of a context-sensitive language. Similarly you can match the other example grammars from above using backreferences: # {a^n b^n, n>0} (context-free) /^ (?: a (?= a* (\1?+ b) ) )+ \1 $/x # {a^n b^n c^n, n>0} (context-sensitive) /^ (?: a (?= a* (\1?+ b) b* (\2?+ c) ) )+ \1 \2 $/x Explaining how these work is outside the scope of this article, but you can read an excellent explanation on StackOverflow . As you can see, the mere addition of backreference (without subpattern recursion support) already adds a lot of power to regular expressions. The addition is actually so powerful that it makes matching of regular expressions an NP-complete problem. What does NP-complete mean? NP-complete is a computational complexity class for decision problems in which many “hard” problems fall. Some examples of NP-complete problems are the traveling salesman problem (TSP), the boolean satisfiability problem (SAT) and the knapsack problem (BKP). One of the main conditions for a problem being NP-complete is that every other NP problem is reducible to it. Thus all NP-complete problems are basically interchangeable. If you find a fast solution to one of them, you got a fast solution to all of them. So if somebody found a fast solution to a NP-complete problem, pretty much all of the computationally hard problems of humanity would be solved all in one strike. This would mean the end to civilisation as we know. To prove that regular expressions with backreferences are indeed NP-complete one can simply take one of the known NP-complete problems and prove that it can be solved using regular expressions. As an example I choose the 3-CNF SAT problem: 3-CNF SAT stands for “3-conjunctive normal form boolean satisfiability problem” and is quite easy to understand. You get a boolean formula of the following form: (!$a || $b || $d) && ( $a || !$c || $d) && ( $a || !$b || !$d) && ( $b || !$c || !$d) && (!$a || $c || !$d) && ( $a || $b || $c) && (!$a || !$b || !$c) Thus the boolean formula is made up of a number of clauses separated by ANDs. Each of those clauses consists of three variables (or their negations) separated by ORs. The 3-CNF SAT problem now asks whether there exists a solution to the given boolean formula (such that it is true). The above boolean formula can be converted to the following regular expression: $regex = '/^ (x?)(x?)(x?)(x?) .* ; (?: x\1 | \2 | \4 ), (?: \1 | x\3 | \4 ), (?: \1 | x\2 | x\4 ), (?: \2 | x\3 | x\4 ), (?: x\1 | \3 | x\4 ), (?: \1 | \2 | \3 ), (?: x\1 | x\2 | x\3 ), $/x' ; $string = 'xxxx;x,x,x,x,x,x,x,' ; var_dump ( preg_match ( $regex , $string , $matches )); var_dump ( $matches ); If you run this code you’ll get the following $matches result: array(5) { [0]=> string(19) "xxxx;x,x,x,x,x,x,x," [1]=> string(1) "x" [2]=> string(1) "x" [3]=> string(0) "" [4]=> string(0) "" } This means that the above formula is satisfied if $a = true , $b = true , $c = false and $d = false . The regular expression works with a very simple trick: For ever 3-clause the string contains a x, which has to be matched. So if you have something like (?: \1 | x\3 | \4 ), in the regex, then the string can be only matched if either \1 is x (true), \3 is the empty string (false) or \4 is x (true). The rest is left up to the engine. It’ll try out different ways of matching the string until it either finds a solution or has to give up. Wrapping up As the article was quite long, here a summary of the main points: The “regular expressions” used by programmers have very little in common with the original notion of regularity in the context of formal language theory. Regular expressions (at least PCRE) can match all context-free languages. As such they can also match well-formed HTML and pretty much all other programming languages. Regular expressions can match at least some context-sensitive languages. Matching of regular expressions is NP-complete. As such you can solve any other NP problem using regular expressions. But don’t forget: Just because you can , doesn’t mean that you should . Processing HTML with regular expressions is a really bad idea in some cases. In other cases it’s probably the best thing to do. Just check what the easiest solution to your particular problem is and use it. If you choose to solve a problem using regular expressions, don’t forget about the x modifier, which allows you to nicely format your regex. For complex regular expressions also don’t forget to make use of DEFINE assertions and named subpatterns to keep your code clean and readable. That’s it. If you liked this article, you may want to browse my other articles or follow me on Twitter or Mastodon . | 2026-01-13T08:49:46 |
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https://www.npopov.com/2015/05/05/Internal-value-representation-in-PHP-7-part-1.html | Internal value representation in PHP 7 - Part 1 Blog by nikic . Find me on GitHub , StackOverflow , Twitter and Mastodon . Learn more about me . « Back to article overview. Internal value representation in PHP 7 - Part 1 05. May 2015 My last article described the improvements to the hashtable implementation that were introduced in PHP 7. This followup will take a look at the new representation of PHP values in general. Due to the amount of material to cover, the article is split in two parts: This part will describe how the zval (Zend value) implementation differs between PHP 5 and PHP 7, and also discuss the implementation of references. The second part will investigate the realization of individual types like strings or objects in more detail. Zvals in PHP 5 In PHP 5 the zval struct is defined as follows: typedef struct _zval_struct { zvalue_value value ; zend_uint refcount__gc ; zend_uchar type ; zend_uchar is_ref__gc ; } zval ; As you can see, a zval consists of a value , a type and some additional __gc information, which we’ll talk about in a moment. The value member is a union of different possible values that a zval can store: typedef union _zvalue_value { long lval ; // For booleans, integers and resources double dval ; // For floating point numbers struct { // For strings char * val ; int len ; } str ; HashTable * ht ; // For arrays zend_object_value obj ; // For objects zend_ast * ast ; // For constant expressions } zvalue_value ; A C union is a structure in which only one member can be active at a time and those size matches the size of its largest member. All members of the union will be stored in the same place in memory and will be interpreted differently depending on which one you access. If you read the lval member of the above union, its value will be interpreted as a signed integer. If you read the dval member the value will be interpreted as a double-precision floating point number instead. And so on. To figure out which of these union members is currently in use, the type property of a zval stores a type tag, which is simply an integer: #define IS_NULL 0 /* Doesn't use value */ #define IS_LONG 1 /* Uses lval */ #define IS_DOUBLE 2 /* Uses dval */ #define IS_BOOL 3 /* Uses lval with values 0 and 1 */ #define IS_ARRAY 4 /* Uses ht */ #define IS_OBJECT 5 /* Uses obj */ #define IS_STRING 6 /* Uses str */ #define IS_RESOURCE 7 /* Uses lval, which is the resource ID */ /* Special types used for late-binding of constants */ #define IS_CONSTANT 8 #define IS_CONSTANT_AST 9 Reference counting in PHP 5 Zvals in PHP 5 are (with a few exceptions) allocated on the heap and PHP needs some way to keep track which zvals are currently in use and which should be freed. For this purpose reference counting is employed: The refcount__gc member of the zval structure stores how often a zval is currently “referenced”. For example in $a = $b = 42 the value 42 is referenced by two variables, so its refcount is 2. If the refcount reaches zero, it means a value is unused and can be freed. Note that the references that the refcount refers to (how many times a value is currently used) have nothing to do with PHP references (using & ). I will always using the terms “reference” and “PHP reference” to disambiguate both concepts in the following. For now we’ll ignore PHP references altogether. A concept that is closely related to reference counting is “copy on write”: A zval can only be shared between multiple users as long as it isn’t modified. In order to change a shared zval it needs to be duplicated (“separated”) and the modification will happen only on the duplicated zval. Lets look at an example that shows off both copy-on-write and zval destruction: $a = 42 ; // $a -> zval_1(type=IS_LONG, value=42, refcount=1) $b = $a ; // $a, $b -> zval_1(type=IS_LONG, value=42, refcount=2) $c = $b ; // $a, $b, $c -> zval_1(type=IS_LONG, value=42, refcount=3) // The following line causes a zval separation $a += 1 ; // $b, $c -> zval_1(type=IS_LONG, value=42, refcount=2) // $a -> zval_2(type=IS_LONG, value=43, refcount=1) unset ( $b ); // $c -> zval_1(type=IS_LONG, value=42, refcount=1) // $a -> zval_2(type=IS_LONG, value=43, refcount=1) unset ( $c ); // zval_1 is destroyed, because refcount=0 // $a -> zval_2(type=IS_LONG, value=43, refcount=1) Reference counting has one fatal flaw: It is not able to detect and release cyclic references. To handle this PHP uses an additional cycle collector . Whenever the refcount of a zval is decremented and there is a chance that this zval is part of a cycle, the zval is written into a “root buffer”. Once this root buffer is full, potential cycles will be collected using a mark and sweep garbage collection. In order to support this additional cycle collector, the actually used zval structure is the following: typedef struct _zval_gc_info { zval z ; union { gc_root_buffer * buffered ; struct _zval_gc_info * next ; } u ; } zval_gc_info ; The zval_gc_info structure embeds the normal zval, as well as one additional pointer - note that u is a union, so this is really just one pointer with two different types it may point to. The buffered pointer is used to store where in the root buffer this zval is referenced, so that it may be removed from it if it’s destroyed before the cycle collector runs (which is very likely). next is used when the collector destroys values, but I won’t go into that here. Motivation for change Let’s talk about sizes a bit (all sizes are for 64-bit systems): First of all, the zvalue_value union is 16 bytes large, because both the str and obj members have that size. The whole zval struct is 24 bytes (due to padding) and zval_gc_info is 32 bytes. On top of this, allocating the zval on the heap adds another 16 bytes of allocation overhead. So we end up using 48 bytes per zval - although this zval may be used by multiple places. At this point we can start thinking about the (many) ways in which this zval implementation is inefficient. Consider the simple case of a zval storing an integer, which by itself is 8 bytes. Additionally the type-tag needs to be stored in any case, which is a single byte by itself, but due to padding needs another 8 bytes. To these 16 bytes that we really “need” (in first approximation), we add another 16 bytes handling reference counting and cycle collection and another 16 bytes of allocation overhead. Not to mention that we actually have to perform that allocation and the subsequent free, both being quite expensive operations. This raises the question: Does a simple integer value really need to be stored as a reference-counted, cycle-collectible, heap-allocated value? The answer to this question is of course, no, this doesn’t make sense. Here is a summary of the primary problems with the PHP 5 zval implementation: Zvals (nearly) always require a heap allocation. Zvals are always reference counted and always have cycle collection information, even in cases where sharing the value is not worthwhile (an integer) and it can’t form cycles. Directly refcounting the zvals leads to double refcounting in the case of objects and resources. The reasons behind this will be explained in the next part. Some cases involve quite an awesome amount of indirection. For example to access the object stored in a variable, a total of four pointers need to be dereferenced (which means following a pointer chain of length four). Once again this will be discussed in the next part. Directly refcounting the zvals also means that values can only be shared between zvals. For example it’s not possible to share a string between a zval and hashtable key (without storing the hashtable key as a zval as well). Zvals in PHP 7 And this brings us to the new zval implementation in PHP 7. The fundamental change that was implemented, is that zvals are no longer individually heap-allocated and no longer store a refcount themselves. Instead any complex values they may point to (like strings, arrays or objects) will store the refcount themselves. This has the following advantages: Simple values do not require allocation and don’t use refcounting. There is no more double refcounting. In the object case, only the refcount in the object is used now. Because the refcount is now stored in the value itself, the value can be shared independently of the zval structure. A string can be used both in a zval and a hashtable key. There is a lot less indirection, i.e. the number of pointers you need to follow to get to a value is lower. Now lets take a look at how the new zval is defined: struct _zval_struct { zend_value value ; union { struct { ZEND_ENDIAN_LOHI_4 ( zend_uchar type , zend_uchar type_flags , zend_uchar const_flags , zend_uchar reserved ) } v ; uint32_t type_info ; } u1 ; union { uint32_t var_flags ; uint32_t next ; // hash collision chain uint32_t cache_slot ; // literal cache slot uint32_t lineno ; // line number (for ast nodes) uint32_t num_args ; // arguments number for EX(This) uint32_t fe_pos ; // foreach position uint32_t fe_iter_idx ; // foreach iterator index } u2 ; }; The first member stays pretty similar, this is still a value union. The second member is an integer storing type information, which is further subdivided into individual bytes using a union (you can ignore the ZEND_ENDIAN_LOHI_4 macro, which just ensures a consistent layout across platforms with different endianness). The important parts of this substructure are the type (which is similar to what it was before) and the type_flags , which I’ll explain in a moment. At this point there exists a small problem: The value member is 8 bytes large and due to struct padding adding even a single byte to that grows the zval size to 16 bytes. However we obviously don’t need 8 bytes just to store a type. This is why the zval contains the additional u2 union, which remains unused by default, but can be repurposed by the surrounding code to store 4 bytes of data. The different union members correspond to different usages of this extra data slot. The value union looks slightly different in PHP 7: typedef union _zend_value { zend_long lval ; double dval ; zend_refcounted * counted ; zend_string * str ; zend_array * arr ; zend_object * obj ; zend_resource * res ; zend_reference * ref ; zend_ast_ref * ast ; // Ignore these for now, they are special zval * zv ; void * ptr ; zend_class_entry * ce ; zend_function * func ; struct { ZEND_ENDIAN_LOHI ( uint32_t w1 , uint32_t w2 ) } ww ; } zend_value ; First of all, note that the value union is now 8 bytes instead of 16. It will only store integers ( lval ) and doubles ( dval ) directly, everything else is a pointer. All the pointer types (apart from those marked as special above) use refcounting and have a common header defined by zend_refcounted : struct _zend_refcounted { uint32_t refcount ; union { struct { ZEND_ENDIAN_LOHI_3 ( zend_uchar type , zend_uchar flags , uint16_t gc_info ) } v ; uint32_t type_info ; } u ; }; Of course the structure contains a refcount. Additionally it contains a type , some flags and gc_info . The type just duplicates the zval type and allows the GC to distinguish different refcounted structures without storing a zval. The flags are used for different purposes with different types and will be explained for each type separately in the next part. The gc_info is the equivalent of the buffered entry in the old zvals. However instead of storing a pointer into the root buffer it now contains an index into it. Because the root buffer has a fixed size (10000 elements) it is enough to use a 16 bit number for this instead of a 64 bit pointer. The gc_info info also encodes the “color” of the node, which is used to mark nodes during collection. Zval memory management I’ve mentioned that zvals are no longer individually heap-allocated. However they obviously still need to be stored somewhere , so how does this work? While zvals are still mostly part of heap-allocated structures, they are directly embedded into them. E.g. a hashtable bucket will directly embed a zval instead of storing a pointer to a separate zval. The compiled variables table of a function or the property table of an object will be zval arrays that are allocated in one chunk, instead of storing pointers to separate zvals. As such zvals are now usually stored with one level of indirection less. What was previously a zval* is now a zval . When a zval is used in a new place, previously this meant copying a zval* and incrementing its refcount. Now it means copying the contents of a zval (ignoring u2 ) instead and maybe incrementing the refcount of the value it points to, if said value uses refcounting. How does PHP know whether a value is refcounted? This cannot be determined solely based on the type, because some types like strings and arrays are not always refcounted. Instead one bit of the zvals type_info member determines whether or not the zval is refcounted. There are a number of other bits encoding properties of the type: #define IS_TYPE_CONSTANT (1<<0) /* special */ #define IS_TYPE_IMMUTABLE (1<<1) /* special */ #define IS_TYPE_REFCOUNTED (1<<2) #define IS_TYPE_COLLECTABLE (1<<3) #define IS_TYPE_COPYABLE (1<<4) #define IS_TYPE_SYMBOLTABLE (1<<5) /* special */ The three primary properties a type can have are “refcounted”, “collectable” and “copyable”. You already know what refcounted means. Collectable means that the zval can participate in a cycle. E.g. strings are (often) refcounted, but there’s no way you can create a cycle with a string in it. Copyability determines whether the value needs to copied when a “duplication” is performed. A duplication is a hard copy, e.g. if you duplicate a zval that points to an array, this will not simply increase the refcount on the array. Instead a new and independent copy of the array will be created. However for some types like objects and resources even a duplication should only increment the refcount - such types are called non-copyable. This matches the passing semantics of objects and resources (which are, for the record, not passed by reference). The following table shows the different types and what type flags they use. “Simple types” refers to types like integers or booleans that don’t use a pointer to a separate structure. A column for the “immutable” flag is also present, which is used to mark immutable arrays and will be discussed in more detail in the next part. | refcounted | collectable | copyable | immutable ----------------+------------+-------------+----------+---------- simple types | | | | string | x | | x | interned string | | | | array | x | x | x | immutable array | | | | x object | x | x | | resource | x | | | reference | x | | | At this point, lets take a look at two examples of how the zval management works in practice. First, an example using integers based off the PHP 5 example from above: $a = 42 ; // $a = zval_1(type=IS_LONG, value=42) $b = $a ; // $a = zval_1(type=IS_LONG, value=42) // $b = zval_2(type=IS_LONG, value=42) $a += 1 ; // $a = zval_1(type=IS_LONG, value=43) // $b = zval_2(type=IS_LONG, value=42) unset ( $a ); // $a = zval_1(type=IS_UNDEF) // $b = zval_2(type=IS_LONG, value=42) This is pretty boring. As integers are no longer shared, both variables will use separate zvals. Don’t forget that these are now embedded rather than allocated, which I try to signify by writing = instead of a -> pointer. Unsetting a variable will set the type of the corresponding zval to IS_UNDEF . Now consider a more interesting case where a complex value is involved: $a = []; // $a = zval_1(type=IS_ARRAY) -> zend_array_1(refcount=1, value=[]) $b = $a ; // $a = zval_1(type=IS_ARRAY) -> zend_array_1(refcount=2, value=[]) // $b = zval_2(type=IS_ARRAY) ---^ // Zval separation occurs here $a [] = 1 // $a = zval_1(type=IS_ARRAY) -> zend_array_2(refcount=1, value=[1]) // $b = zval_2(type=IS_ARRAY) -> zend_array_1(refcount=1, value=[]) unset ( $a ); // $a = zval_1(type=IS_UNDEF) and zend_array_2 is destroyed // $b = zval_2(type=IS_ARRAY) -> zend_array_1(refcount=1, value=[]) Here each variable still has a separate (embedded) zval, but both zvals point to the same (refcounted) zend_array structure. Once a modification is done the array needs to be duplicated. This case is similar to how things work in PHP 5. Types Lets take a closer look at what types are supported in PHP 7: // regular data types #define IS_UNDEF 0 #define IS_NULL 1 #define IS_FALSE 2 #define IS_TRUE 3 #define IS_LONG 4 #define IS_DOUBLE 5 #define IS_STRING 6 #define IS_ARRAY 7 #define IS_OBJECT 8 #define IS_RESOURCE 9 #define IS_REFERENCE 10 // constant expressions #define IS_CONSTANT 11 #define IS_CONSTANT_AST 12 // internal types #define IS_INDIRECT 15 #define IS_PTR 17 This list is quite similar to what was used in PHP 5, however there are a few additions: The IS_UNDEF type is used in places where previously a NULL zval pointer (not to be confused with an IS_NULL zval) was used. For example, in the refcounting examples above the IS_UNDEF type is set for variables that have been unset . The IS_BOOL type has been split into IS_FALSE and IS_TRUE . As such the value of the boolean is now encoded in the type, which allows the optimization of a number of type-based checks. This change is transparent to userland, where this is still a single “boolean” type. PHP references no longer use an is_ref flag on the zval and use a new IS_REFERENCE type instead. How this works will be described in the next section. The IS_INDIRECT and IS_PTR types are special internal types. The IS_LONG type now uses a zend_long value instead of an ordinary C long. The reason behind this is that on 64-bit Windows (LLP64) a long is only 32-bit wide, so PHP 5 ended up always using 32-bit numbers on Windows. PHP 7 will allow you to use 64-bit numbers if you’re on an 64-bit operating system, even if that operating system is Windows. Details of the individual zend_refcounted types will be discussed in the next part. For now we’ll only look at the implementation of PHP references. References PHP 7 uses an entirely different approach to handling PHP & references than PHP 5 (and I can tell you that this change is one of the largest source of bugs in PHP 7). Lets start by taking a look at how PHP references used to work in PHP 5: Normally, the copy-on-write principle says that before modifying a zval it needs to be separated, in order to make sure you don’t end up changing the value for every place sharing the zval. This matches by-value passing semantics. For PHP references this does not apply. If a value is a PHP reference, you want it to change for every user of the value. The is_ref flag that was part of PHP 5 zvals determined whether a value is a PHP reference and as such whether it required separation before modification. An example: $a = []; // $a -> zval_1(type=IS_ARRAY, refcount=1, is_ref=0) -> HashTable_1(value=[]) $b =& $a ; // $a, $b -> zval_1(type=IS_ARRAY, refcount=2, is_ref=1) -> HashTable_1(value=[]) $b [] = 1 ; // $a = $b = zval_1(type=IS_ARRAY, refcount=2, is_ref=1) -> HashTable_1(value=[1]) One significant problem with this design is that it’s not possible to share a value between a variable that’s a PHP reference and one that isn’t. Consider the following example: $a = []; // $a -> zval_1(type=IS_ARRAY, refcount=1, is_ref=0) -> HashTable_1(value=[]) $b = $a ; // $a, $b -> zval_1(type=IS_ARRAY, refcount=2, is_ref=0) -> HashTable_1(value=[]) $c = $b // $a, $b, $c -> zval_1(type=IS_ARRAY, refcount=3, is_ref=0) -> HashTable_1(value=[]) $d =& $c ; // $a, $b -> zval_1(type=IS_ARRAY, refcount=2, is_ref=0) -> HashTable_1(value=[]) // $c, $d -> zval_1(type=IS_ARRAY, refcount=2, is_ref=1) -> HashTable_2(value=[]) // $d is a reference of $c, but *not* of $a and $b, so the zval needs to be copied // here. Now we have the same zval once with is_ref=0 and once with is_ref=1. $d [] = 1 ; // $a, $b -> zval_1(type=IS_ARRAY, refcount=2, is_ref=0) -> HashTable_1(value=[]) // $c, $d -> zval_1(type=IS_ARRAY, refcount=2, is_ref=1) -> HashTable_2(value=[1]) // Because there are two separate zvals $d[] = 1 does not modify $a and $b. This behavior of references is one of the reasons why using references in PHP will usually end up being slower than using normal values. To give a less-contrived example where this is a problem: $array = range ( 0 , 1000000 ); $ref =& $array ; var_dump ( count ( $array )); // <-- separation occurs here Because count() accepts its value by-value, but $array is a PHP reference, a full copy of the array is done before passing it off to count() . If $array weren’t a reference, the value would be shared instead. Now, let’s switch to the PHP 7 implementation of PHP references. Because zvals are no longer individually allocated, it is not possible to use the same approach that PHP 5 used. Instead a new IS_REFERENCE type is added, which uses the zend_reference structure as its value: struct _zend_reference { zend_refcounted gc ; zval val ; }; So essentially a zend_reference is simply a refcounted zval. All variables in a reference set will store a zval with type IS_REFERENCE pointing to the same zend_reference instance. The val zval behaves like any other zval, in particular it is possible to share a complex value it points to. E.g. an array can be shared between a variable that is a reference and another that is a value. Lets go through the above code samples again, this time looking at the PHP 7 semantics. For the sake of brevity I will stop writing the individual zvals of the variables and only show what structure they point to. $a = []; // $a -> zend_array_1(refcount=1, value=[]) $b =& $a ; // $a, $b -> zend_reference_1(refcount=2) -> zend_array_1(refcount=1, value=[]) $b [] = 1 ; // $a, $b -> zend_reference_1(refcount=2) -> zend_array_1(refcount=1, value=[1]) The by-reference assignment created a new zend_reference . Note that the refcount is 2 on the reference (because two variables are part of the PHP reference set), but the value itself only has a refcount of 1 (because one zend_reference structure points to it). Now consider the case where references and non-references are mixed: $a = []; // $a -> zend_array_1(refcount=1, value=[]) $b = $a ; // $a, $b, -> zend_array_1(refcount=2, value=[]) $c = $b // $a, $b, $c -> zend_array_1(refcount=3, value=[]) $d =& $c ; // $a, $b -> zend_array_1(refcount=3, value=[]) // $c, $d -> zend_reference_1(refcount=2) ---^ // Note that all variables share the same zend_array, even though some are // PHP references and some aren't. $d [] = 1 ; // $a, $b -> zend_array_1(refcount=2, value=[]) // $c, $d -> zend_reference_1(refcount=2) -> zend_array_2(refcount=1, value=[1]) // Only at this point, once an assignment occurs, the zend_array is duplicated. The important difference to PHP 5 is that all variables were able to share the same array, even though some were PHP references and some weren’t. Only once some kind of modification is performed the array will be separated. This means that in PHP 7 it’s safe to pass a large, referenced array to count() , it is not going to be duplicated. References will still be slower than normal values, because they require allocation of the zend_reference structure (and indirection through it) and are usually not handled in the fast-path of engine code. Wrapping up To summarize, the primary change that was implemented in PHP 7 is that zvals are no longer individually heap-allocated and no longer store a refcount themselves. Instead any complex values they may point to (like strings, array or objects) will store the refcount themselves. This usually leads to less allocations, less indirection and less memory usage. In the second part of this article the remaining complex types will be discussed. If you liked this article, you may want to browse my other articles or follow me on Twitter or Mastodon . | 2026-01-13T08:49:46 |
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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 Open Forem Close Follow User actions David Scanu Data Engineer @ Carrefour specializing in AI & cloud. Building ML pipelines, GenAI apps & automation on GCP. Passionate about scalable data solutions & intelligent systems. Location Caen, France Joined Joined on Oct 23, 2023 Personal website https://github.com/DavidScanu github website twitter website Education Développeur en Intelligence Artificielle (RNCP 34757) & Expert en Data Science (RNCP 37431) Work Ingénieur IA & Data | Pipelines Data Cloud | SQL, ML & Python More info about @davidscanu 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. 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https://www.npopov.com/2012/06/29/PHP-solves-problems-Oh-and-you-can-program-with-it-too.html | PHP solves problems. Oh, and you can program with it too! Blog by nikic . Find me on GitHub , StackOverflow , Twitter and Mastodon . Learn more about me . « Back to article overview. PHP solves problems. Oh, and you can program with it too! 29. June 2012 I’d like to point your attention to one particular comment on Jeff Atwood’s new “PHP sucks!” blog post , a comment by Adam Victor Nazareth Brandizzi: I am a Java programmer at work (could be no more corporate-y) and a Python developer in my projects (could be no more hipster) but I admire PHP and its ability of solving problems. It grows because, some times, some poor soul wants to create an online encyclopaedia , or some teacher needs an online teaching platform , or someone wants to write a blog . Those people do not want to learn to program, they want to solve problems . I think this comment really nailed it. I think this is the most important reason for PHP’s success. People come to PHP because they have some problem and they need to solve it. This is what PHP really shines at. You can simply take your static HTML website, add a simple <?php include 'counter.php'; ?> in there, and … be done! From there you start writing simple scripts, learn how to process forms, how to talk to the database, etc. After some time you start using object oriented programming and maybe make use of some framework. That’s actually pretty much how I got into programming. With most other languages it is the other way around. With them you first study computer science for five years and then you go out into the world to find some problem you can solve. (You could say that PHP is a programmer-producing language, whereas most other languages are programmer-consuming.) At this point you may ask: Well, once you learned programming, why not switch to another language? Simple: PHP has its quirks, but it is not that bad. Sure, people always try to tell you that, but it just isn’t true. Most of the things people criticize about PHP are really non-issues practically. Like the inconsistent needle/haystack order. That’s always at the top of things that are wrong with PHP. But in reality it really doesn’t matter. Sure, it would be nice if the order was consistent, but my IDE does a very good job at reminding me how to do it correctly. To summarize: PHP is a great language to start programming! Once you started, PHP is also good for “real” programming (you know, object orientation and stuff). PHP is not as bad as they say. There are issues, like with every language, but they rarely cause problems in practice. To add to that, I also noticed that most of the PHP bashers have a ten-year-old image of the language. E.g. consider this quote from Jeff’s post: What’s depressing is not that PHP is horribly designed. Does anyone even dispute that PHP is the worst designed mainstream “language” to blight our craft in decades? What’s truly depressing is that so little has changed . This statement is outrageous. PHP has changed a lot in recent years, but most people seem to remember it as the shitty language with terrible OOP support that PHP 4 was. Well, I got news for you: That language is dead for nearly a decade now. PHP 5 has very good object orientation support, which is actually really similar to Java. PHP 5.3 additionally added namespace and lambda function support to the mix. (And PHP 5.5 will add a lot of awesome new features.) And you tell me nothing changed? End of rant. If you liked this article, you may want to browse my other articles or follow me on Twitter or Mastodon . | 2026-01-13T08:49:46 |
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http://greenteapress.com/thinkpython/html/index.html | Think Python Buy this book at Amazon.com Think Python: How to Think Like a Computer Scientist Allen B. Downey Version 2.0.17 Preface The strange history of this book Acknowledgments Contributor List The way of the program The Python programming language What is a program? What is debugging? Formal and natural languages The first program Debugging Glossary Exercises Variables, expressions and statements Values and types Variables Variable names and keywords Operators and operands Expressions and statements Interactive mode and script mode Order of operations String operations Comments Debugging Glossary Exercises Functions Function calls Type conversion functions Math functions Composition Adding new functions Definitions and uses Flow of execution Parameters and arguments Variables and parameters are local Stack diagrams Fruitful functions and void functions Why functions? Importing with from Debugging Glossary Exercises Case study: interface design TurtleWorld Simple repetition Exercises Encapsulation Generalization Interface design Refactoring A development plan docstring Debugging Glossary Exercises Conditionals and recursion Modulus operator Boolean expressions Logical operators Conditional execution Alternative execution Chained conditionals Nested conditionals Recursion Stack diagrams for recursive functions Infinite recursion Keyboard input Debugging Glossary Exercises Fruitful functions Return values Incremental development Composition Boolean functions More recursion Leap of faith One more example Checking types Debugging Glossary Exercises Iteration Multiple assignment Updating variables The while statement break Square roots Algorithms Debugging Glossary Exercises Strings A string is a sequence len Traversal with a for loop String slices Strings are immutable Searching Looping and counting String methods The in operator String comparison Debugging Glossary Exercises Case study: word play Reading word lists Exercises Search Looping with indices Debugging Glossary Exercises Lists A list is a sequence Lists are mutable Traversing a list List operations List slices List methods Map, filter and reduce Deleting elements Lists and strings Objects and values Aliasing List arguments Debugging Glossary Exercises Dictionaries Dictionary as a set of counters Looping and dictionaries Reverse lookup Dictionaries and lists Memos Global variables Long integers Debugging Glossary Exercises Tuples Tuples are immutable Tuple assignment Tuples as return values Variable-length argument tuples Lists and tuples Dictionaries and tuples Comparing tuples Sequences of sequences Debugging Glossary Exercises Case study: data structure selection Word frequency analysis Random numbers Word histogram Most common words Optional parameters Dictionary subtraction Random words Markov analysis Data structures Debugging Glossary Exercises Files Persistence Reading and writing Format operator Filenames and paths Catching exceptions Databases Pickling Pipes Writing modules Debugging Glossary Exercises Classes and objects User-defined types Attributes Rectangles Instances as return values Objects are mutable Copying Debugging Glossary Exercises Classes and functions Time Pure functions Modifiers Prototyping versus planning Debugging Glossary Exercises Classes and methods Object-oriented features Printing objects Another example A more complicated example The init method The __str__ method Operator overloading Type-based dispatch Polymorphism Debugging Interface and implementation Glossary Exercises Inheritance Card objects Class attributes Comparing cards Decks Printing the deck Add, remove, shuffle and sort Inheritance Class diagrams Debugging Data encapsulation Glossary Exercises Case study: Tkinter GUI Buttons and callbacks Canvas widgets Coordinate sequences More widgets Packing widgets Menus and Callables Binding Debugging Glossary Exercises Debugging Syntax errors Runtime errors Semantic errors Analysis of Algorithms Order of growth Analysis of basic Python operations Analysis of search algorithms Hashtables Lumpy State diagram Stack diagram Object diagrams Function and class objects Class Diagrams Index Buy this book at Amazon.com Contribute If you would like to make a contribution to support my books, you can use the button below. Thank you! Pay what you want: Small $1.00 USD Medium $5.00 USD Large $10.00 USD X-Large $20.00 USD XX-Large $50.00 USD Are you using one of our books in a class? We'd like to know about it. Please consider filling out this short survey . Think Bayes Think Python Think Stats Think Complexity This document was translated from L A T E X by H E V E A . | 2026-01-13T08:49:46 |
https://www.npopov.com/2011/12/27/Dont-be-STUPID-GRASP-SOLID.html | Don't be STUPID: GRASP SOLID! Blog by nikic . Find me on GitHub , StackOverflow , Twitter and Mastodon . Learn more about me . « Back to article overview. Don't be STUPID: GRASP SOLID! 27. December 2011 Ever heard of SOLID code? Probably: It is a term describing a collection of design principles for “good code” that was coined by Robert C. Martin (aka “uncle bob” ), our beloved evangelist of clean code. Programming is full of acronyms like this. Other examples are DRY (Don’t Repeat Yourself!) and KISS (Keep It Simple, Stupid!). But there obviously are many, many more… So, why not approach the problem from the other side for once? Looking at what makes up bad code. Sorry, but your code is STUPID! Nobody likes to hear that their code is stupid. It is offending. Don’t say it. But honestly: Most of the code being written around the globe is an unmaintainable, unreusable mess. What characterizes such code? What makes code STUPID ? S ingleton T ight coupling U ntestability P remature Optimization I ndescriptive Naming D uplication Do you agree with this list? Yes? Great. No? I’ll explain the individual points in greater detail in the following, so you can better understand why exactly those patterns were chosen. Singleton class DB { private static $instance ; public static function getInstance () { if ( ! isset ( self :: $instance )) { self :: $instance = new self ; } return self :: $instance ; } final private function __construct () { /* something */ } final private function __clone () { } /* actual methods here */ } The above is the typical database access implementation you will find in pretty much any PHP tutorial. I actually used something similar to this myself not too long ago. Now you wonder: What’s wrong with that? You can easily access the DB from anywhere using DB::getInstance() and the code also ensures that you only have one database connection open at a time. What could be bad about that? Well, yeah, I thought that too ^^ “I only need one connection.” When the application grew larger it turned out that I actually needed a second connection to a different database. And that’s where the mess began. I changed the singleton to have a ->getSecondInstance() , thus converting the singleton to a .. erm .. dupleton? Instead I should have realized that the database connection simply isn’t a singleton and thus can’t be sanely implemented as one. The same also applies to any other use of singletons that you will find. The request object surely is a singleton! Ever heard of subrequests? But the logger definitely is! Never wanted to log different things differently? And that was only one issue. Another important issue is that by using DB::getInstance() in your code you are binding your code to the DB classname. This means: You can’t extend the DB class. At some point I wanted to optionally log query performance data to APC. But the tight coupling to the class name did not allow me to. If my application had used dependency injection at that time I could have easily extended DB and passed the new instance. But the singleton prevented. What I did instead was somethink looking roughly like this: // original DB class class _DB { /* ... */ } // extending class class DB extends _DB { /* ... */ } One word: Ugly. One could add some other words like Hacky, Unmaintainable, Crap. Or STUPID. One last point to consider: Remember when I said “You can easily access the DB from anywhere using DB::getInstance() ”. Well, actually that’s a bad thing too. Read “from anywhere” as “globally” and translate to “A singleton is a global variable with a fancy name.” When you learned PHP you were probably told that it’s evil to use the global keyword. But by using a singleton you are doing just that: creating global state. This creates non-obvious dependencies and thus makes your app hard to reuse and test. Tight coupling You can actually generalize the Singleton issue to static methods and properties in general. Whenever you are writing Foo::bar() in your code you are tightly coupling your code to the Foo class. This makes extending Foo s functionality impossible and thus makes your code hard to reuse and hard to test. Similarly most other plain uses of class names are code smell too. This also applies to the new operator: class House { public function __construct () { $this -> door = new Door ; $this -> window = new Window ; } } How would you replace the door or the window in your house now? Simple: You can’t. As a good developer you will obviously find some dirty hack that does allow you to somehow replace the door or a window. But why not simply write this instead: class House { public function __construct ( Door $door , Window $window ) { // Door, Window are interfaces $this -> door = $door ; $this -> window = $window ; } } This way one can easily create houses with different doors and windows. The code is easy to extend, easy to reuse and easy to test. What could you want more? The above code is actually “dependency injection” in a nutshell. Many people associate DI with some Dependency Injection Container (DIC) like Symfony’s, but the actual concept of DI is so much simpler. Untestability Unit testing is important. If you don’t test your code, you are bound to ship broken code. But still most people don’t properly cover their code with tests. Why? Mostly because their code is hard to test . What makes code hard to test? Mainly the previous point: Tight coupling. Unit testing - it might seem obvious - tests units of code (usually classes). But how can you test individual classes if they are tightly coupled? You probably can somehow, with even more dirty hacks. But people usually don’t do those efforts and just leave their code untested and broken. Whenever you don’t write unit tests because you “don’t have time” the real cause probably is that your code is bad. If your code is good you can test it in no time. Only with bad code unit testing becomes a burden. Premature Optimization Here is a code snippet from an old version of a website I wrote: if ( isset ( $frm [ 'title_german' ][ strcspn ( $frm [ 'title_german' ], '<>' )])) { // ... } Guess what it does! How long did it take you to realize that this code does nothing more than check whether the German title contains the < or > character? Did you realize it at all? Let me explain: If < and > are both not contained, strcspn will return the length of the string. So the code will basically be isset($str[strlen($str)]) . As the maximum offset set in a string is the length minus one, this will return false . If one of the characters is contained the function will return a number smaller than the length of the string and thus the whole expression will be true . So why did I write this unintelligible piece of code? Why didn’t I write this instead: if ( strlen ( $frm [ 'title_german' ]) == strcspn ( $frm [ 'title_german' ], '<>' ))) { // ... } Because some days ago I read that isset is so much faster than strlen … But that code still is not particularly intelligible, because you need to know the exact semantics of the strcspn function (which probably most PHP programmers do not). So why not just write this: if ( preg_match ( '(<|>)' , $frm [ 'title_german' ])) { // ... } Because I read that regex is slow… (Which by the way is mostly a lie: regular expressions are much faster and much more powerful than you think.) So, what did I gain from these “optimizations”, apart from unreadable code? Nothing. Even now, when this site attracts approximately fourty million pageviews every month (at the time I wrote this code it was faaar less), even now this micro-optimization won’t make any difference. Simply because it is not the bottleneck of the application. The actual bottleneck is a tripple JOIN in the most-frequently accessed controller (the bottleneck of your application probably is similar). You will find many more micro-optimization tips like that on the internet. Like “use single quotes, they are faster”. Don’t listen. Most of the advice is plain wrong and even if it isn’t, it won’t make your code measurably faster, it’ll only waste your time. Indescriptive Naming By the way, do you know what the strpbrk PHP function does? No? You didn’t even know it existed? I’m not surprised. Nobody who wants to search a string for a list of characters looks for a function named strpbrk . Where did that name come from anyways? This function was inherited from C and its name stands for “string pointer break”. Yeah, really nice, especially in a language that doesn’t actually have pointers (I mean PHP, not C). Oh, and reading the code snippet in the above section, did you know what the strcspn function does off the top of your head? No? Again, I’m not surprised. It’s short for “string complement span”, just in case you didn’t know. The lesson from this: Please, name your classes, methods, variables properly, so that people actually know what you mean. I’m not arguing about variables like $i , those are short, but still self-explanatory. The problem is functions like the ones named above. Functions like strpbrk or variables like $yysstk may be obvious the author, but also only to the author. Duplication I think everybody agrees that code that is particularly short, concise and pertinent is considered especially elegant (oh, and I don’t mean the Perl/Ruby style “short”). On the other hand most people would consider long and redundant code rather ugly. This is what the aforementioned DRY (Don’t Repeat Yourself!) and KISS (Keep It Simple, Stupid!) design principle want to teach you. So where does code duplication come from? Programmers are lazy animals, so it would be only natural to type as little code as possible. Still duplication prevails. I think the most common reason for duplication is following the second STUPID principle: Tight Coupling. If your code is tightly coupled, you just can’t reuse it. And here comes your duplication. Don’t be STUPID: GRASP SOLID! So what are the alternatives to writing STUPID code? Simple, SOLID and GRASP . SOLID deciphers to: S ingle responsibility principle O pen/closed principle L iskov substitution principle I nterface segregation principle D ependency inversion principle GRASP stands for General Responsibility Assignment Software Principles, which are the following: Information Expert Creator Controller Low Coupling High Cohesion Polymorphism Pure Fabrication Indirection Protected Variations Happy coding and a happy new year to you! PS: If you wonder where STUPID comes from: The idea came up on the PHP chatroom on StackOverlow and the individual components were formed by edorian ( StackOverflow , Github , Twitter ), James and me. Gordon ( StackOverflow , Github , Twitter ) came up with the title of this blog post. If you liked this article, you may want to browse my other articles or follow me on Twitter or Mastodon . | 2026-01-13T08:49:46 |
https://www.npopov.com/2023/04/10/LLVM-Canonicalization-and-target-independence.html | LLVM: Canonicalization and target-independence Blog by nikic . Find me on GitHub , StackOverflow , Twitter and Mastodon . Learn more about me . « Back to article overview. LLVM: Canonicalization and target-independence 10. April 2023 Conceptually, the backend of an optimizing compiler is supposed to be the part that performs CPU architecture specific optimizations, while the middle-end is target-independent. In reality, the middle-end does need to take certain properties of the target into account. However, these need to be carefully managed to maintain the overall architecture of the compiler. In this article, I want to discuss in which ways target-specific information can affect the LLVM middle-end, and more importantly, in which ways it is not allowed to affect it. Data layout Every IR module has an associated data layout , which specifies information about the size and alignment of primitive types, as well as other basic information. This determines whether the target is little-endian or big-endian, whether pointers are 32-bit or 64-bit, whether doubles have 4 byte or 8 byte alignment, etc. Historically, LLVM used to allow modules without a data layout, which would in theory be completely target-independent. This turned out to be not particularly useful, as target-dependent aspects will make it into the IR anyway, for example due to ABI differences. Nowadays, the data layout is always required, and the memory layout of all structures is known. Relying on the data layout in the middle-end is always fine. This is the one bit of target-dependence that is approved for use everywhere, and is automatically available in most places in the compiler. Target library info TargetLibraryInfo (TLI) provided by the TargetLibraryAnalysis determines which library calls are assumed to be available on the target. This part is less about the target CPU architecture and more about the target OS and environment. For example, if you are targeting x86_64-unknown-linux-gnu (and not using -ffreestanding or similar), LLVM will assume that certain symbols are provided by glibc. When targeting linux-gnu , a call to strrchr() on a known-length string will be converted to memrchr() , while the same doesn’t happen when targeting windows-msvc . That’s because strrchr() is a standard C function, while memrchr() is a GNU extension. Using TLI in the middle-end is generally also fine. This is something that needs to be explicitly requested from the pass manager, and many passes don’t actually need this, but there are generally no concerns with adding additional TLI dependencies. Target transform info TargetTransformInfo (TTI) provided by the TargetIRAnalysis provides a wide range of hooks that can be overridden by backends. This includes both generic cost modelling APIs (what is the reverse throughput of this instruction?) and specialized APIs for specific passes (what are the unrolling preferences for this target?) Usage of TTI in the middle-end is tightly controlled. We make a distinction between target-independent canonicalization passes that are not allowed to use TTI, and cost model driven passes that can use TTI. Examples of cost model driven passes are LoopVectorize, SLPVectorize or VectorCombine. This is pretty obvious, because vectorization is fundamentally based around a cost model. Vectorization is only profitable if we can show that the vector instructions are cheaper than the scalar instructions. Canonicalization passes Canonicalization passes like InstCombine are intended to produce IR in a “canonical form” that other passes can depend on. This canonical form is chosen based on how amenable it is to further analysis and transforms, not how beneficial it is for a particular target. The canonical form can be undesirable for some or even all targets, because what is convenient for analysis is not always what is convenient for CPUs. In cases where the canonical form is undesirable for a target, a backend undo transform needs to be implemented. The undo transform will usually live either in CodeGenPrepare (CGP), DAGCombine, or some target-specific code. CGP is used for undo transforms that need to work across basic blocks, because this is not possible in DAGCombine. A common question here is why we go through the trouble of making InstCombine convert IR into one form, and then make the backend undo it. Wouldn’t it be simpler if we allowed backends to opt-out of the transform in the first place? Consider two equivalent code patterns A and B. If we have an InstCombine transform from A to B, but the target prefers A, we could suppress the transform. However, this would do nothing about the case where the code is in form B in the first place. As such, we need a reverse transform from B to A. We could implement both a transform in one direction and one in the other direction in InstCombine, and pick them depending on target. However, this means that there are now two different forms of the same pattern that other transforms need to deal with. We also need to consider more combinations of different patterns when it comes to ensuring that there are no infinite transform loops. The better choice is to decide on one direction in InstCombine, so that there is a single canonical pattern the middle-end needs to deal with, and move the undo transform into the backend. Another example of a canonicalization pass is LICM. LICM will move all loop-invariant code into the loop preheader. This is not always profitable, because it may increase register pressure, or unconditionally execute code that was previously conditional. One could imagine an alternative LICM implementation that would take into account register pressure via TTI and code hotness using PGO information. However, that would mean that other transforms cannot rely on loop invariant operands actually being loop invariant, and this is not an easy property to determine once memory operations are involved. LLVM makes the choice to make LICM a canonicalization transform, which may later be undone by other passes. LoopSink in the late middle-end optimization pipeline is PGO-based, while MachineSink is a backend pass. Of course, our policies on TTI dependence of passes are just a means to an end, and it’s sometimes necessary to make tradeoffs in favor of pragmatism. For example, we need to distinguish between using TTI for profitability queries and legality queries. While legality queries would preferably be answered by the data layout, the truth is that adding a new TTI hook is much simpler than encoding additional information in the data layout. As such, it is usually the pragmatic choice to permit a TTI legality query in passes that are otherwise target-independent. Even the InstCombine pass, which is likely the place with the hardest policy against target-dependent transforms, does use TTI to provide hooks for folding target-specific intrinsics. The thing we ultimately care about is that the canonical IR form remains target-independent to the degree that this is possible. Target-specific intrinsics naturally cannot have a target-independent canonical form. Canonical form The canonical IR form is not documented anywhere and essentially boils down to “whatever InstCombine produces, if it makes a choice one way or another”. In some cases, the choice of canonical form is obvious. If it’s possible to do the same thing with fewer instructions, that’s almost always preferable (exceptions may be expensive instructions like integer division or certain intrinsics). The question becomes more interesting when two sequences have the same number of instructions. For example, consider the following equivalent patterns: %tmp = add i32 %x , 2 %res = mul i32 %tmp , 3 %tmp = mul i32 %x , 3 %res = add i32 %tmp , 6 In principle, this could be canonicalized in either direction, and one might argue that the former is better because it leads to smaller constants. However, we prefer the latter. There are a few reasons for why this is a better choice, but the primary one is that we can always convert the former into the latter, but the converse is not true. If you change the add 6 to add 5 , it’s no longer possible to factor out the multiply. This allows us to establish a canonical ordering of multiplies and adds, where we prefer “add of multiply” over “multiply of add”. This canonical ordering makes patterns like the following fold in a two-step process: %tmp = add i32 %x , 2 %tmp2 = mul i32 %tmp , 3 %res = add i32 %tmp2 , 5 ; Step 1 %tmp = mul i32 %x , 3 %tmp2 = add i32 %tmp , 6 %res = add i32 %tmp2 , 5 ; Step 2 %tmp = mul i32 %x , 3 %res = add i32 %tmp , 11 As another example, let’s consider these patterns: %res = add i32 %x , %x %res = shl i32 %x , 1 These patterns are not equivalent: The latter is a refinement. This means we can convert the former into the latter, but the other way around requires the insertion of a freeze instruction. The reason for this is somewhat technical and I won’t go into it here. Even without this concern, we would canonicalize towards the latter pattern here, because it reduces the number of uses of %x , and this makes it more amenable to analysis. For example, the shl pattern makes it obvious that the low bit of the result is zero, while this would require special handling for the add pattern. Having only one use also makes it easier to fold the shl into whatever operation produced %x : %x = mul i32 %y , 3 %res = add i32 %x , %x ; Step 1 %x = mul i32 %y , 3 %res = shl i32 %x , 1 ; Step 2 %res = mul i32 %y , 6 As a rule of thumb, for two patterns with the same number of instructions, we’ll prefer the one with less value uses. And here we can also see an undo transform in effect: The x86 backend will convert the shl %x, 1 back into add %x, %x in order to form a lea instruction. The canonical IR preference goes against the target preference here. These are just some basic examples. InstCombine performs hundreds (thousands?) of different transforms, and the choice of canonical form is not always obvious. Sometimes it is entirely arbitrary, and we just chose something so that CSE/GVN sees a single pattern. Sometimes the canonical form changes, because we later realize that a different form composes better with further transforms, or is less prone to infinite combine loops. Such changes may require adjusting other transforms (and/or backends) to work on the new canonical form. These changes are always somewhat risky, in that they can have unanticipated effects. In any case, I hope this is enough to illustrate why we care about canonical IR form, and how it helps make transforms composable. Summary The LLVM middle-end is target-dependent through three main sources: data layout (DL), target library info (TLI) and target transform info (TTI). The first two are considered unproblematic, but the use of the latter is restricted. Canonicalization passes like InstCombine are not allowed to have target-dependent opt-outs or cost modelling. Instead, backend undo transforms should be implemented for undesirable canonicalizations. If you liked this article, you may want to browse my other articles or follow me on Twitter or Mastodon . | 2026-01-13T08:49:46 |
https://docs.suprsend.com/docs/notification-category#category-translations | Overview - SuprSend, Notification infrastructure for Product teams Skip to main content SuprSend, Notification infrastructure for Product teams home page Search... ⌘ K Community Trust Center Platform Status Postman Collection GETTING STARTED What is SuprSend? Quick Start Guide Best Practices Plan Your Integration Go-live checklist CORE CONCEPTS Templates Users Events Workflow Notification Categories Overview Manage Categories and Preferences Preferences Tenants Lists Broadcast Objects Translations DLT Guidelines Whatsapp Template Guidelines WORKFLOW BUILDER Design Workflow Node List Workflow Settings Trigger Workflow Validate Trigger Payload Tenant Workflows Notification Inbox Overview Multi Tabs React Javascript (Angular, Vuejs etc) React Native Flutter (Headless) PREFERENCE CENTRE Embedded Preference Centre Javascript Angular React VENDOR INTEGRATION GUIDE Overview Email Integrations SMS Integrations Android Push Whatsapp Integrations iOS Push Chat Integrations Vendor Fallback Tenant Vendor INTEGRATIONS Webhook Connectors MONITORING & DEBUGGING Logs Audit Logs Error Guides MANAGE YOUR ACCOUNT Authentication Methods Contact Us Get Started SuprSend, Notification infrastructure for Product teams home page Search... ⌘ K Ask AI Contact Us Get Started Get Started Search... Navigation Notification Categories Overview Documentation API Reference Management API CLI Reference Developer Resources Changelog Documentation API Reference Management API CLI Reference Developer Resources Changelog Notification Categories Overview OpenAI Open in ChatGPT Overview of Notification Categories: How they drive preferences, vendor selection, and latency rules in workflow execution OpenAI Open in ChatGPT Notification categories define the classification your workflow belongs to. Each workflow can be either to a root-category (system, transactional, or promotional) or a sub-category . User Preference rules are applied at the sub-category level. Categories serve three main purposes: Maintaining separate vendor config for marketing vs product notifications For Email and SMS channels, vendor is configured at root-category level . This is done to solve for the following use cases: Many companies separate promotional and transactional traffic to ensure that opt-outs from promotional messages do not impact critical system notifications. SMS vendors may also expose different APIs for system messages (e.g., OTPs) versus marketing messages. For Email and SMS, ensure a vendor is configured for the category used in the workflow; otherwise, delivery will fail. Picking the right notification queue We maintain separate notification queues for different notification categories to ensure that marketing and promotional notifications don’t delay system or time-sensitive notifications. Setting category-level preferences per-user and tenant You can create sub-categories for different types of notifications and give your users and tenants the option to set their notification preferences at the category level. See how to set it up in the next document . Mental model Notification categories use a functional hierarchy: Root-category → Section → Sub-category Concept Description Root-category Choose one of three: System , Transactional , or Promotional . This determines which notification queue or vendor to pick for the workflow. Preferences are not applied at the root-category level. You can’t create new ones. Sub-category Sub-categories are created inside a root-category to manage user preferences. When sub-category is assigned to the workflow, user preferences are evaluated before sending the notification. Sub-categories are what users see on preference / unsubscription page and can opt in/out of. Section Sections are optional UI groupings used to organize sub-categories on the preference page. Example structure: Copy Ask AI Promotional (root category) └── Marketing (section) ├── Newsletters (sub-category) ← Use sub-category slug in workflows to apply user preferences └── Product Announcements (sub-category) When users visit their preference page, they see sub-categories organized under sections. Root-categories control delivery behind the scenes but aren’t shown to users. Root-categories SuprSend has three root-categories — System , Transactional , and Promotional — which define latency and queueing behavior. Sub-categories are always created inside one of these three. How it works: Notification queues and vendors are inherited from the root-category at sub-category level User or tenant preferences are applied at the sub-category level Root-categories are not shown to users—only sub-categories appear on preference pages System Essential notifications that users can’t unsubscribe from. Common examples: OTP, Forgot Password, Incident reports Transactional Notifications sent in response to user actions or transactions. Common examples: Payment confirmation or reminders, Booking confirmation, Post shared/liked, Balance alerts, Account updates Promotional Notifications sent to promote products or re-engage users to your platform. Common examples: Newsletters, Announcements, Product updates, Sales/events, Deals and discounts, Price drop alerts Promotional notifications are sent in bulk and consume significant pipeline resources. To ensure that marketing notifications doesn’t impact the latency of product alerts, always use the promotional category for bulk messages and broadcasts. Sections and Sub-Categories Sub-categories Sub-categories are where notification preferences are applied. This is what appears on the preference page and what users can opt in/out of. Assign category slug to the workflow . You’ll get the slug by clicking on the sub-category on Preference page . Sections Sections are used to organize related sub-categories on the preference page. Think of them as folders that help users find notifications more easily. They are just used for visual grouping and are not used to apply preferences. Example: Quotes is a section containing the Quote Approval and Forecast sub-categories: Default preferences Default preferences determine how users receive notifications when they haven’t set their own preferences. Configure these at the sub-category level when setting up categories. Preference modes: On : Users receive notifications by default Off : Users must opt in to receive notifications Can’t Unsubscribe : Users cannot fully opt out (required notifications) When using Can’t Unsubscribe , channel-level opt-in/out still applies unless channels are marked mandatory. For detailed information on configuring default preferences, preference modes, and recommended defaults, see Default Preferences . Setting per-user and tenant preferences Users and tenants can set their notification preferences at the sub-category level. Users can opt in or out of specific sub-categories, channels or channels within a category, and tenants can set default preferences that apply to all their users. Copy Ask AI Default Preference (Sub-category) ↓ (tenant override) Tenant Preference (Applies to all users of the tenant) ↓ (user override) User Preference (Final preference) Override Rules: Tenants can override the default sub-category preference for their entire user base at the tenant level. Users can override the tenant-level preference for themselves at the user level. Once a tenant or user overrides a sub-category preference, changes to the default preference in that sub-category no longer affect them. For details, see User Preferences and Tenant Preferences . Tags Tags are used to filter categories on the preference page. Common usecases are to filter categories based on user role or department. Tags added at the section level are inherited by all sub-categories inside that section. You can filter categories using the tags query parameter in the get user preference API . Tags do not impact delivery logic or preference rules — they are only used for filtering and organizing the UI. Even if a category is hidden from the user on the preference page due to tag filters, the user can still opt in/out via API, and notifications will still be sent if the default preference is set to opt-in. Category translations This feature is only available for Enterprise plan customers or the ones who have enabled translation feature in their account. Translate categories and sections into users’ locale by uploading .json translations for each locale. Translations go live immediately after upload—no commit or publish required. How it works: English ( en ) is always available as the base language and is auto-generated from the category names and descriptions you define. You can download en.json file, translate it into your desired locale and upload it back. While loading preference page, pass the locale parameter to the API or preference SDK and the translations will be loaded for that locale. If a translation is missing for a specific locale or key in the passed locale, the system automatically falls back to first regional locale, and then to English. Example: User’s locale is set to locale=es-AR and translation is missing for one of the categories in es-AR.json , it will look for translation of that category first in es.json , then falls back to en.json if needed. Related documentation Manage Categories and Preferences - Complete guide to setting up and managing categories and preferences User Preferences - Overview of how preferences work Was this page helpful? Yes No Suggest edits Raise issue Previous Manage Categories and Preferences Set up and manage notification categories and preferences in SuprSend. Next ⌘ I x github linkedin youtube Powered by On this page Mental model Root-categories System Transactional Promotional Sections and Sub-Categories Sub-categories Sections Default preferences Setting per-user and tenant preferences Tags Category translations Related documentation | 2026-01-13T08:49:46 |
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https://docs.python.org/3/whatsnew/3.14.html#pep-765-control-flow-in-finally-blocks | What’s new in Python 3.14 — Python 3.14.2 documentation Theme Auto Light Dark Table of Contents What’s new in Python 3.14 Summary – Release highlights New features PEP 649 & PEP 749 : Deferred evaluation of annotations PEP 734 : Multiple interpreters in the standard library PEP 750 : Template string literals PEP 768 : Safe external debugger interface A new type of interpreter Free-threaded mode improvements Improved error messages PEP 784 : Zstandard support in the standard library Asyncio introspection capabilities Concurrent safe warnings control Other language changes Built-ins Command line and environment PEP 758: Allow except and except* expressions without brackets PEP 765: Control flow in finally blocks Incremental garbage collection Default interactive shell New modules Improved modules argparse ast asyncio calendar concurrent.futures configparser contextvars ctypes curses datetime decimal difflib dis errno faulthandler fnmatch fractions functools getopt getpass graphlib heapq hmac http imaplib inspect io json linecache logging.handlers math mimetypes multiprocessing operator os os.path pathlib pdb pickle platform pydoc re socket ssl struct symtable sys sys.monitoring sysconfig tarfile threading tkinter turtle types typing unicodedata unittest urllib uuid webbrowser zipfile Optimizations asyncio base64 bdb difflib gc io pathlib pdb textwrap uuid zlib Removed argparse ast asyncio email importlib.abc itertools pathlib pkgutil pty sqlite3 urllib Deprecated New deprecations Pending removal in Python 3.15 Pending removal in Python 3.16 Pending removal in Python 3.17 Pending removal in Python 3.18 Pending removal in Python 3.19 Pending removal in future versions CPython bytecode changes Pseudo-instructions C API changes Python configuration C API New features in the C API Limited C API changes Removed C APIs Deprecated C APIs Pending removal in Python 3.15 Pending removal in Python 3.16 Pending removal in Python 3.18 Pending removal in future versions Build changes build-details.json Discontinuation of PGP signatures Free-threaded Python is officially supported Binary releases for the experimental just-in-time compiler Porting to Python 3.14 Changes in the Python API Changes in annotations ( PEP 649 and PEP 749 ) Implications for annotated code Implications for readers of __annotations__ Related changes from __future__ import annotations Changes in the C API Notable changes in 3.14.1 Previous topic What’s New in Python Next topic What’s New In Python 3.13 This page Report a bug Show source Navigation index modules | next | previous | Python » 3.14.2 Documentation » What’s New in Python » What’s new in Python 3.14 | Theme Auto Light Dark | What’s new in Python 3.14 ¶ Editors : Adam Turner and Hugo van Kemenade This article explains the new features in Python 3.14, compared to 3.13. Python 3.14 was released on 7 October 2025. For full details, see the changelog . See also PEP 745 – Python 3.14 release schedule Summary – Release highlights ¶ Python 3.14 is the latest stable release of the Python programming language, with a mix of changes to the language, the implementation, and the standard library. The biggest changes include template string literals , deferred evaluation of annotations , and support for subinterpreters in the standard library. The library changes include significantly improved capabilities for introspection in asyncio , support for Zstandard via a new compression.zstd module, syntax highlighting in the REPL, as well as the usual deprecations and removals, and improvements in user-friendliness and correctness. This article doesn’t attempt to provide a complete specification of all new features, but instead gives a convenient overview. For full details refer to the documentation, such as the Library Reference and Language Reference . To understand the complete implementation and design rationale for a change, refer to the PEP for a particular new feature; but note that PEPs usually are not kept up-to-date once a feature has been fully implemented. See Porting to Python 3.14 for guidance on upgrading from earlier versions of Python. Interpreter improvements: PEP 649 and PEP 749 : Deferred evaluation of annotations PEP 734 : Multiple interpreters in the standard library PEP 750 : Template strings PEP 758 : Allow except and except* expressions without brackets PEP 765 : Control flow in finally blocks PEP 768 : Safe external debugger interface for CPython A new type of interpreter Free-threaded mode improvements Improved error messages Incremental garbage collection Significant improvements in the standard library: PEP 784 : Zstandard support in the standard library Asyncio introspection capabilities Concurrent safe warnings control Syntax highlighting in the default interactive shell , and color output in several standard library CLIs C API improvements: PEP 741 : Python configuration C API Platform support: PEP 776 : Emscripten is now an officially supported platform , at tier 3 . Release changes: PEP 779 : Free-threaded Python is officially supported PEP 761 : PGP signatures have been discontinued for official releases Windows and macOS binary releases now support the experimental just-in-time compiler Binary releases for Android are now provided New features ¶ PEP 649 & PEP 749 : Deferred evaluation of annotations ¶ The annotations on functions, classes, and modules are no longer evaluated eagerly. Instead, annotations are stored in special-purpose annotate functions and evaluated only when necessary (except if from __future__ import annotations is used). This change is designed to improve performance and usability of annotations in Python in most circumstances. The runtime cost for defining annotations is minimized, but it remains possible to introspect annotations at runtime. It is no longer necessary to enclose annotations in strings if they contain forward references. The new annotationlib module provides tools for inspecting deferred annotations. Annotations may be evaluated in the VALUE format (which evaluates annotations to runtime values, similar to the behavior in earlier Python versions), the FORWARDREF format (which replaces undefined names with special markers), and the STRING format (which returns annotations as strings). This example shows how these formats behave: >>> from annotationlib import get_annotations , Format >>> def func ( arg : Undefined ): ... pass >>> get_annotations ( func , format = Format . VALUE ) Traceback (most recent call last): ... NameError : name 'Undefined' is not defined >>> get_annotations ( func , format = Format . FORWARDREF ) {'arg': ForwardRef('Undefined', owner=<function func at 0x...>)} >>> get_annotations ( func , format = Format . STRING ) {'arg': 'Undefined'} The porting section contains guidance on changes that may be needed due to these changes, though in the majority of cases, code will continue working as-is. (Contributed by Jelle Zijlstra in PEP 749 and gh-119180 ; PEP 649 was written by Larry Hastings.) See also PEP 649 Deferred Evaluation Of Annotations Using Descriptors PEP 749 Implementing PEP 649 PEP 734 : Multiple interpreters in the standard library ¶ The CPython runtime supports running multiple copies of Python in the same process simultaneously and has done so for over 20 years. Each of these separate copies is called an ‘interpreter’. However, the feature had been available only through the C-API . That limitation is removed in Python 3.14, with the new concurrent.interpreters module. There are at least two notable reasons why using multiple interpreters has significant benefits: they support a new (to Python), human-friendly concurrency model true multi-core parallelism For some use cases, concurrency in software improves efficiency and can simplify design, at a high level. At the same time, implementing and maintaining all but the simplest concurrency is often a struggle for the human brain. That especially applies to plain threads (for example, threading ), where all memory is shared between all threads. With multiple isolated interpreters, you can take advantage of a class of concurrency models, like Communicating Sequential Processes (CSP) or the actor model, that have found success in other programming languages, like Smalltalk, Erlang, Haskell, and Go. Think of multiple interpreters as threads but with opt-in sharing. Regarding multi-core parallelism: as of Python 3.12, interpreters are now sufficiently isolated from one another to be used in parallel (see PEP 684 ). This unlocks a variety of CPU-intensive use cases for Python that were limited by the GIL . Using multiple interpreters is similar in many ways to multiprocessing , in that they both provide isolated logical “processes” that can run in parallel, with no sharing by default. However, when using multiple interpreters, an application will use fewer system resources and will operate more efficiently (since it stays within the same process). Think of multiple interpreters as having the isolation of processes with the efficiency of threads. While the feature has been around for decades, multiple interpreters have not been used widely, due to low awareness and the lack of a standard library module. Consequently, they currently have several notable limitations, which are expected to improve significantly now that the feature is going mainstream. Current limitations: starting each interpreter has not been optimized yet each interpreter uses more memory than necessary (work continues on extensive internal sharing between interpreters) there aren’t many options yet for truly sharing objects or other data between interpreters (other than memoryview ) many third-party extension modules on PyPI are not yet compatible with multiple interpreters (all standard library extension modules are compatible) the approach to writing applications that use multiple isolated interpreters is mostly unfamiliar to Python users, for now The impact of these limitations will depend on future CPython improvements, how interpreters are used, and what the community solves through PyPI packages. Depending on the use case, the limitations may not have much impact, so try it out! Furthermore, future CPython releases will reduce or eliminate overhead and provide utilities that are less appropriate on PyPI. In the meantime, most of the limitations can also be addressed through extension modules, meaning PyPI packages can fill any gap for 3.14, and even back to 3.12 where interpreters were finally properly isolated and stopped sharing the GIL . Likewise, libraries on PyPI are expected to emerge for high-level abstractions on top of interpreters. Regarding extension modules, work is in progress to update some PyPI projects, as well as tools like Cython, pybind11, nanobind, and PyO3. The steps for isolating an extension module are found at Isolating Extension Modules . Isolating a module has a lot of overlap with what is required to support free-threading , so the ongoing work in the community in that area will help accelerate support for multiple interpreters. Also added in 3.14: concurrent.futures.InterpreterPoolExecutor . (Contributed by Eric Snow in gh-134939 .) See also PEP 734 PEP 750 : Template string literals ¶ Template strings are a new mechanism for custom string processing. They share the familiar syntax of f-strings but, unlike f-strings, return an object representing the static and interpolated parts of the string, instead of a simple str . To write a t-string, use a 't' prefix instead of an 'f' : >>> variety = 'Stilton' >>> template = t 'Try some {variety} cheese!' >>> type ( template ) <class 'string.templatelib.Template'> Template objects provide access to the static and interpolated (in curly braces) parts of a string before they are combined. Iterate over Template instances to access their parts in order: >>> list ( template ) ['Try some ', Interpolation('Stilton', 'variety', None, ''), ' cheese!'] It’s easy to write (or call) code to process Template instances. For example, here’s a function that renders static parts lowercase and Interpolation instances uppercase: from string.templatelib import Interpolation def lower_upper ( template ): """Render static parts lowercase and interpolations uppercase.""" parts = [] for part in template : if isinstance ( part , Interpolation ): parts . append ( str ( part . value ) . upper ()) else : parts . append ( part . lower ()) return '' . join ( parts ) name = 'Wenslydale' template = t 'Mister {name} ' assert lower_upper ( template ) == 'mister WENSLYDALE' Because Template instances distinguish between static strings and interpolations at runtime, they can be useful for sanitising user input. Writing a html() function that escapes user input in HTML is an exercise left to the reader! Template processing code can provide improved flexibility. For instance, a more advanced html() function could accept a dict of HTML attributes directly in the template: attributes = { 'src' : 'limburger.jpg' , 'alt' : 'lovely cheese' } template = t '<img {attributes} >' assert html ( template ) == '<img src="limburger.jpg" alt="lovely cheese" />' Of course, template processing code does not need to return a string-like result. An even more advanced html() could return a custom type representing a DOM-like structure. With t-strings in place, developers can write systems that sanitise SQL, make safe shell operations, improve logging, tackle modern ideas in web development (HTML, CSS, and so on), and implement lightweight custom business DSLs. (Contributed by Jim Baker, Guido van Rossum, Paul Everitt, Koudai Aono, Lysandros Nikolaou, Dave Peck, Adam Turner, Jelle Zijlstra, Bénédikt Tran, and Pablo Galindo Salgado in gh-132661 .) See also PEP 750 . PEP 768 : Safe external debugger interface ¶ Python 3.14 introduces a zero-overhead debugging interface that allows debuggers and profilers to safely attach to running Python processes without stopping or restarting them. This is a significant enhancement to Python’s debugging capabilities, meaning that unsafe alternatives are no longer required. The new interface provides safe execution points for attaching debugger code without modifying the interpreter’s normal execution path or adding any overhead at runtime. Due to this, tools can now inspect and interact with Python applications in real-time, which is a crucial capability for high-availability systems and production environments. For convenience, this interface is implemented in the sys.remote_exec() function. For example: import sys from tempfile import NamedTemporaryFile with NamedTemporaryFile ( mode = 'w' , suffix = '.py' , delete = False ) as f : script_path = f . name f . write ( f 'import my_debugger; my_debugger.connect( { os . getpid () } )' ) # Execute in process with PID 1234 print ( 'Behold! An offering:' ) sys . remote_exec ( 1234 , script_path ) This function allows sending Python code to be executed in a target process at the next safe execution point. However, tool authors can also implement the protocol directly as described in the PEP, which details the underlying mechanisms used to safely attach to running processes. The debugging interface has been carefully designed with security in mind and includes several mechanisms to control access: A PYTHON_DISABLE_REMOTE_DEBUG environment variable. A -X disable-remote-debug command-line option. A --without-remote-debug configure flag to completely disable the feature at build time. (Contributed by Pablo Galindo Salgado, Matt Wozniski, and Ivona Stojanovic in gh-131591 .) See also PEP 768 . A new type of interpreter ¶ A new type of interpreter has been added to CPython. It uses tail calls between small C functions that implement individual Python opcodes, rather than one large C case statement. For certain newer compilers, this interpreter provides significantly better performance. Preliminary benchmarks suggest a geometric mean of 3-5% faster on the standard pyperformance benchmark suite, depending on platform and architecture. The baseline is Python 3.14 built with Clang 19, without this new interpreter. This interpreter currently only works with Clang 19 and newer on x86-64 and AArch64 architectures. However, a future release of GCC is expected to support this as well. This feature is opt-in for now. Enabling profile-guided optimization is highly recommendeded when using the new interpreter as it is the only configuration that has been tested and validated for improved performance. For further information, see --with-tail-call-interp . Note This is not to be confused with tail call optimization of Python functions, which is currently not implemented in CPython. This new interpreter type is an internal implementation detail of the CPython interpreter. It doesn’t change the visible behavior of Python programs at all. It can improve their performance, but doesn’t change anything else. (Contributed by Ken Jin in gh-128563 , with ideas on how to implement this in CPython by Mark Shannon, Garrett Gu, Haoran Xu, and Josh Haberman.) Free-threaded mode improvements ¶ CPython’s free-threaded mode ( PEP 703 ), initially added in 3.13, has been significantly improved in Python 3.14. The implementation described in PEP 703 has been finished, including C API changes, and temporary workarounds in the interpreter were replaced with more permanent solutions. The specializing adaptive interpreter ( PEP 659 ) is now enabled in free-threaded mode, which along with many other optimizations greatly improves its performance. The performance penalty on single-threaded code in free-threaded mode is now roughly 5-10%, depending on the platform and C compiler used. From Python 3.14, when compiling extension modules for the free-threaded build of CPython on Windows, the preprocessor variable Py_GIL_DISABLED now needs to be specified by the build backend, as it will no longer be determined automatically by the C compiler. For a running interpreter, the setting that was used at compile time can be found using sysconfig.get_config_var() . The new -X context_aware_warnings flag controls if concurrent safe warnings control is enabled. The flag defaults to true for the free-threaded build and false for the GIL-enabled build. A new thread_inherit_context flag has been added, which if enabled means that threads created with threading.Thread start with a copy of the Context() of the caller of start() . Most significantly, this makes the warning filtering context established by catch_warnings be “inherited” by threads (or asyncio tasks) started within that context. It also affects other modules that use context variables, such as the decimal context manager. This flag defaults to true for the free-threaded build and false for the GIL-enabled build. (Contributed by Sam Gross, Matt Page, Neil Schemenauer, Thomas Wouters, Donghee Na, Kirill Podoprigora, Ken Jin, Itamar Oren, Brett Simmers, Dino Viehland, Nathan Goldbaum, Ralf Gommers, Lysandros Nikolaou, Kumar Aditya, Edgar Margffoy, and many others. Some of these contributors are employed by Meta, which has continued to provide significant engineering resources to support this project.) Improved error messages ¶ The interpreter now provides helpful suggestions when it detects typos in Python keywords. When a word that closely resembles a Python keyword is encountered, the interpreter will suggest the correct keyword in the error message. This feature helps programmers quickly identify and fix common typing mistakes. For example: >>> whille True : ... pass Traceback (most recent call last): File "<stdin>" , line 1 whille True : ^^^^^^ SyntaxError : invalid syntax. Did you mean 'while'? While the feature focuses on the most common cases, some variations of misspellings may still result in regular syntax errors. (Contributed by Pablo Galindo in gh-132449 .) elif statements that follow an else block now have a specific error message. (Contributed by Steele Farnsworth in gh-129902 .) >>> if who == "me" : ... print ( "It's me!" ) ... else : ... print ( "It's not me!" ) ... elif who is None : ... print ( "Who is it?" ) File "<stdin>", line 5 elif who is None: ^^^^ SyntaxError: 'elif' block follows an 'else' block If a statement is passed to the Conditional expressions after else , or one of pass , break , or continue is passed before if , then the error message highlights where the expression is required. (Contributed by Sergey Miryanov in gh-129515 .) >>> x = 1 if True else pass Traceback (most recent call last): File "<string>" , line 1 x = 1 if True else pass ^^^^ SyntaxError : expected expression after 'else', but statement is given >>> x = continue if True else break Traceback (most recent call last): File "<string>" , line 1 x = continue if True else break ^^^^^^^^ SyntaxError : expected expression before 'if', but statement is given When incorrectly closed strings are detected, the error message suggests that the string may be intended to be part of the string. (Contributed by Pablo Galindo in gh-88535 .) >>> "The interesting object " The important object " is very important" Traceback (most recent call last): SyntaxError : invalid syntax. Is this intended to be part of the string? When strings have incompatible prefixes, the error now shows which prefixes are incompatible. (Contributed by Nikita Sobolev in gh-133197 .) >>> ub 'abc' File "<python-input-0>" , line 1 ub 'abc' ^^ SyntaxError : 'u' and 'b' prefixes are incompatible Improved error messages when using as with incompatible targets in: Imports: import ... as ... From imports: from ... import ... as ... Except handlers: except ... as ... Pattern-match cases: case ... as ... (Contributed by Nikita Sobolev in gh-123539 , gh-123562 , and gh-123440 .) Improved error message when trying to add an instance of an unhashable type to a dict or set . (Contributed by CF Bolz-Tereick and Victor Stinner in gh-132828 .) >>> s = set () >>> s . add ({ 'pages' : 12 , 'grade' : 'A' }) Traceback (most recent call last): File "<python-input-1>" , line 1 , in <module> s . add ({ 'pages' : 12 , 'grade' : 'A' }) ~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ TypeError : cannot use 'dict' as a set element (unhashable type: 'dict') >>> d = {} >>> l = [ 1 , 2 , 3 ] >>> d [ l ] = 12 Traceback (most recent call last): File "<python-input-4>" , line 1 , in <module> d [ l ] = 12 ~^^^ TypeError : cannot use 'list' as a dict key (unhashable type: 'list') Improved error message when an object supporting the synchronous context manager protocol is entered using async with instead of with , and vice versa for the asynchronous context manager protocol. (Contributed by Bénédikt Tran in gh-128398 .) PEP 784 : Zstandard support in the standard library ¶ The new compression package contains modules compression.lzma , compression.bz2 , compression.gzip and compression.zlib which re-export the lzma , bz2 , gzip and zlib modules respectively. The new import names under compression are the preferred names for importing these compression modules from Python 3.14. However, the existing modules names have not been deprecated. Any deprecation or removal of the existing compression modules will occur no sooner than five years after the release of 3.14. The new compression.zstd module provides compression and decompression APIs for the Zstandard format via bindings to Meta’s zstd library . Zstandard is a widely adopted, highly efficient, and fast compression format. In addition to the APIs introduced in compression.zstd , support for reading and writing Zstandard compressed archives has been added to the tarfile , zipfile , and shutil modules. Here’s an example of using the new module to compress some data: from compression import zstd import math data = str ( math . pi ) . encode () * 20 compressed = zstd . compress ( data ) ratio = len ( compressed ) / len ( data ) print ( f "Achieved compression ratio of { ratio } " ) As can be seen, the API is similar to the APIs of the lzma and bz2 modules. (Contributed by Emma Harper Smith, Adam Turner, Gregory P. Smith, Tomas Roun, Victor Stinner, and Rogdham in gh-132983 .) See also PEP 784 . Asyncio introspection capabilities ¶ Added a new command-line interface to inspect running Python processes using asynchronous tasks, available via python -m asyncio ps PID or python -m asyncio pstree PID . The ps subcommand inspects the given process ID (PID) and displays information about currently running asyncio tasks. It outputs a task table: a flat listing of all tasks, their names, their coroutine stacks, and which tasks are awaiting them. The pstree subcommand fetches the same information, but instead renders a visual async call tree, showing coroutine relationships in a hierarchical format. This command is particularly useful for debugging long-running or stuck asynchronous programs. It can help developers quickly identify where a program is blocked, what tasks are pending, and how coroutines are chained together. For example given this code: import asyncio async def play_track ( track ): await asyncio . sleep ( 5 ) print ( f '🎵 Finished: { track } ' ) async def play_album ( name , tracks ): async with asyncio . TaskGroup () as tg : for track in tracks : tg . create_task ( play_track ( track ), name = track ) async def main (): async with asyncio . TaskGroup () as tg : tg . create_task ( play_album ( 'Sundowning' , [ 'TNDNBTG' , 'Levitate' ]), name = 'Sundowning' ) tg . create_task ( play_album ( 'TMBTE' , [ 'DYWTYLM' , 'Aqua Regia' ]), name = 'TMBTE' ) if __name__ == '__main__' : asyncio . run ( main ()) Executing the new tool on the running process will yield a table like this: python -m asyncio ps 12345 tid task id task name coroutine stack awaiter chain awaiter name awaiter id ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ 1935500 0x7fc930c18050 Task-1 TaskGroup._aexit -> TaskGroup.__aexit__ -> main 0x0 1935500 0x7fc930c18230 Sundowning TaskGroup._aexit -> TaskGroup.__aexit__ -> album TaskGroup._aexit -> TaskGroup.__aexit__ -> main Task-1 0x7fc930c18050 1935500 0x7fc93173fa50 TMBTE TaskGroup._aexit -> TaskGroup.__aexit__ -> album TaskGroup._aexit -> TaskGroup.__aexit__ -> main Task-1 0x7fc930c18050 1935500 0x7fc93173fdf0 TNDNBTG sleep -> play TaskGroup._aexit -> TaskGroup.__aexit__ -> album Sundowning 0x7fc930c18230 1935500 0x7fc930d32510 Levitate sleep -> play TaskGroup._aexit -> TaskGroup.__aexit__ -> album Sundowning 0x7fc930c18230 1935500 0x7fc930d32890 DYWTYLM sleep -> play TaskGroup._aexit -> TaskGroup.__aexit__ -> album TMBTE 0x7fc93173fa50 1935500 0x7fc93161ec30 Aqua Regia sleep -> play TaskGroup._aexit -> TaskGroup.__aexit__ -> album TMBTE 0x7fc93173fa50 or a tree like this: python -m asyncio pstree 12345 └── ( T ) Task-1 └── main example.py:13 └── TaskGroup.__aexit__ Lib/asyncio/taskgroups.py:72 └── TaskGroup._aexit Lib/asyncio/taskgroups.py:121 ├── ( T ) Sundowning │ └── album example.py:8 │ └── TaskGroup.__aexit__ Lib/asyncio/taskgroups.py:72 │ └── TaskGroup._aexit Lib/asyncio/taskgroups.py:121 │ ├── ( T ) TNDNBTG │ │ └── play example.py:4 │ │ └── sleep Lib/asyncio/tasks.py:702 │ └── ( T ) Levitate │ └── play example.py:4 │ └── sleep Lib/asyncio/tasks.py:702 └── ( T ) TMBTE └── album example.py:8 └── TaskGroup.__aexit__ Lib/asyncio/taskgroups.py:72 └── TaskGroup._aexit Lib/asyncio/taskgroups.py:121 ├── ( T ) DYWTYLM │ └── play example.py:4 │ └── sleep Lib/asyncio/tasks.py:702 └── ( T ) Aqua Regia └── play example.py:4 └── sleep Lib/asyncio/tasks.py:702 If a cycle is detected in the async await graph (which could indicate a programming issue), the tool raises an error and lists the cycle paths that prevent tree construction: python -m asyncio pstree 12345 ERROR: await-graph contains cycles - cannot print a tree! cycle: Task-2 → Task-3 → Task-2 (Contributed by Pablo Galindo, Łukasz Langa, Yury Selivanov, and Marta Gomez Macias in gh-91048 .) Concurrent safe warnings control ¶ The warnings.catch_warnings context manager will now optionally use a context variable for warning filters. This is enabled by setting the context_aware_warnings flag, either with the -X command-line option or an environment variable. This gives predictable warnings control when using catch_warnings combined with multiple threads or asynchronous tasks. The flag defaults to true for the free-threaded build and false for the GIL-enabled build. (Contributed by Neil Schemenauer and Kumar Aditya in gh-130010 .) Other language changes ¶ All Windows code pages are now supported as ‘cpXXX’ codecs on Windows. (Contributed by Serhiy Storchaka in gh-123803 .) Implement mixed-mode arithmetic rules combining real and complex numbers as specified by the C standard since C99. (Contributed by Sergey B Kirpichev in gh-69639 .) More syntax errors are now detected regardless of optimisation and the -O command-line option. This includes writes to __debug__ , incorrect use of await , and asynchronous comprehensions outside asynchronous functions. For example, python -O -c 'assert (__debug__ := 1)' or python -O -c 'assert await 1' now produce SyntaxError s. (Contributed by Irit Katriel and Jelle Zijlstra in gh-122245 & gh-121637 .) When subclassing a pure C type, the C slots for the new type are no longer replaced with a wrapped version on class creation if they are not explicitly overridden in the subclass. (Contributed by Tomasz Pytel in gh-132284 .) Built-ins ¶ The bytes.fromhex() and bytearray.fromhex() methods now accept ASCII bytes and bytes-like objects . (Contributed by Daniel Pope in gh-129349 .) Add class methods float.from_number() and complex.from_number() to convert a number to float or complex type correspondingly. They raise a TypeError if the argument is not a real number. (Contributed by Serhiy Storchaka in gh-84978 .) Support underscore and comma as thousands separators in the fractional part for floating-point presentation types of the new-style string formatting (with format() or f-strings ). (Contributed by Sergey B Kirpichev in gh-87790 .) The int() function no longer delegates to __trunc__() . Classes that want to support conversion to int() must implement either __int__() or __index__() . (Contributed by Mark Dickinson in gh-119743 .) The map() function now has an optional keyword-only strict flag like zip() to check that all the iterables are of equal length. (Contributed by Wannes Boeykens in gh-119793 .) The memoryview type now supports subscription, making it a generic type . (Contributed by Brian Schubert in gh-126012 .) Using NotImplemented in a boolean context will now raise a TypeError . This has raised a DeprecationWarning since Python 3.9. (Contributed by Jelle Zijlstra in gh-118767 .) Three-argument pow() now tries calling __rpow__() if necessary. Previously it was only called in two-argument pow() and the binary power operator. (Contributed by Serhiy Storchaka in gh-130104 .) super objects are now copyable and pickleable . (Contributed by Serhiy Storchaka in gh-125767 .) Command line and environment ¶ The import time flag can now track modules that are already loaded (‘cached’), via the new -X importtime=2 . When such a module is imported, the self and cumulative times are replaced by the string cached . Values above 2 for -X importtime are now reserved for future use. (Contributed by Noah Kim and Adam Turner in gh-118655 .) The command-line option -c now automatically dedents its code argument before execution. The auto-dedentation behavior mirrors textwrap.dedent() . (Contributed by Jon Crall and Steven Sun in gh-103998 .) -J is no longer a reserved flag for Jython , and now has no special meaning. (Contributed by Adam Turner in gh-133336 .) PEP 758: Allow except and except* expressions without brackets ¶ The except and except* expressions now allow brackets to be omitted when there are multiple exception types and the as clause is not used. For example: try : connect_to_server () except TimeoutError , ConnectionRefusedError : print ( 'The network has ceased to be!' ) (Contributed by Pablo Galindo and Brett Cannon in PEP 758 and gh-131831 .) PEP 765: Control flow in finally blocks ¶ The compiler now emits a SyntaxWarning when a return , break , or continue statement have the effect of leaving a finally block. This change is specified in PEP 765 . In situations where this change is inconvenient (such as those where the warnings are redundant due to code linting), the warning filter can be used to turn off all syntax warnings by adding ignore::SyntaxWarning as a filter. This can be specified in combination with a filter that converts other warnings to errors (for example, passing -Werror -Wignore::SyntaxWarning as CLI options, or setting PYTHONWARNINGS=error,ignore::SyntaxWarning ). Note that applying such a filter at runtime using the warnings module will only suppress the warning in code that is compiled after the filter is adjusted. Code that is compiled prior to the filter adjustment (for example, when a module is imported) will still emit the syntax warning. (Contributed by Irit Katriel in gh-130080 .) Incremental garbage collection ¶ The cycle garbage collector is now incremental. This means that maximum pause times are reduced by an order of magnitude or more for larger heaps. There are now only two generations: young and old. When gc.collect() is not called directly, the GC is invoked a little less frequently. When invoked, it collects the young generation and an increment of the old generation, instead of collecting one or more generations. The behavior of gc.collect() changes slightly: gc.collect(1) : Performs an increment of garbage collection, rather than collecting generation 1. Other calls to gc.collect() are unchanged. (Contributed by Mark Shannon in gh-108362 .) Default interactive shell ¶ The default interactive shell now highlights Python syntax. The feature is enabled by default, save if PYTHON_BASIC_REPL or any other environment variable that disables colour is set. See Controlling color for details. The default color theme for syntax highlighting strives for good contrast and exclusively uses the 4-bit VGA standard ANSI color codes for maximum compatibility. The theme can be customized using an experimental API _colorize.set_theme() . This can be called interactively or in the PYTHONSTARTUP script. Note that this function has no stability guarantees, and may change or be removed. (Contributed by Łukasz Langa in gh-131507 .) The default interactive shell now supports import auto-completion. This means that typing import co and pressing <Tab> will suggest modules starting with co . Similarly, typing from concurrent import i will suggest submodules of concurrent starting with i . Note that autocompletion of module attributes is not currently supported. (Contributed by Tomas Roun in gh-69605 .) New modules ¶ annotationlib : For introspecting annotations . See PEP 749 for more details. (Contributed by Jelle Zijlstra in gh-119180 .) compression (including compression.zstd ): A package for compression-related modules, including a new module to support the Zstandard compression format. See PEP 784 for more details. (Contributed by Emma Harper Smith, Adam Turner, Gregory P. Smith, Tomas Roun, Victor Stinner, and Rogdham in gh-132983 .) concurrent.interpreters : Support for multiple interpreters in the standard library. See PEP 734 for more details. (Contributed by Eric Snow in gh-134939 .) string.templatelib : Support for template string literals (t-strings). See PEP 750 for more details. (Contributed by Jim Baker, Guido van Rossum, Paul Everitt, Koudai Aono, Lysandros Nikolaou, Dave Peck, Adam Turner, Jelle Zijlstra, Bénédikt Tran, and Pablo Galindo Salgado in gh-132661 .) Improved modules ¶ argparse ¶ The default value of the program name for argparse.ArgumentParser now reflects the way the Python interpreter was instructed to find the __main__ module code. (Contributed by Serhiy Storchaka and Alyssa Coghlan in gh-66436 .) Introduced the optional suggest_on_error parameter to argparse.ArgumentParser , enabling suggestions for argument choices and subparser names if mistyped by the user. (Contributed by Savannah Ostrowski in gh-124456 .) Enable color for help text, which can be disabled with the optional color parameter to argparse.ArgumentParser . This can also be controlled by environment variables . (Contributed by Hugo van Kemenade in gh-130645 .) ast ¶ Add compare() , a function for comparing two ASTs. (Contributed by Batuhan Taskaya and Jeremy Hylton in gh-60191 .) Add support for copy.replace() for AST nodes. (Contributed by Bénédikt Tran in gh-121141 .) Docstrings are now removed from an optimized AST in optimization level 2. (Contributed by Irit Katriel in gh-123958 .) The repr() output for AST nodes now includes more information. (Contributed by Tomas Roun in gh-116022 .) When called with an AST as input, the parse() function now always verifies that the root node type is appropriate. (Contributed by Irit Katriel in gh-130139 .) Add new options to the command-line interface: --feature-version , --optimize , and --show-empty . (Contributed by Semyon Moroz in gh-133367 .) asyncio ¶ The function and methods named create_task() now take an arbitrary list of keyword arguments. All keyword arguments are passed to the Task constructor or the custom task factory. (See set_task_factory() for details.) The name and context keyword arguments are no longer special; the name should now be set using the name keyword argument of the factory, and context may be None . This affects the following function and methods: asyncio.create_task() , asyncio.loop.create_task() , asyncio.TaskGroup.create_task() . (Contributed by Thomas Grainger in gh-128307 .) There are two new utility functions for introspecting and printing a program’s call graph: capture_call_graph() and print_call_graph() . See Asyncio introspection capabilities for more details. (Contributed by Yury Selivanov, Pablo Galindo Salgado, and Łukasz Langa in gh-91048 .) calendar ¶ By default, today’s date is highlighted in color in calendar ’s command-line text output. This can be controlled by environment variables . (Contributed by Hugo van Kemenade in gh-128317 .) concurrent.futures ¶ Add a new executor class, InterpreterPoolExecutor , which exposes multiple Python interpreters in the same process (‘subinterpreters’) to Python code. This uses a pool of independent Python interpreters to execute calls asynchronously. This is separate from the new interpreters module introduced by PEP 734 . (Contributed by Eric Snow in gh-124548 .) On Unix platforms other than macOS, ‘forkserver’ is now the default start method for ProcessPoolExecutor (replacing ‘fork’ ). This change does not affect Windows or macOS, where ‘spawn’ remains the default start method. If the threading incompatible fork method is required, you must explicitly request it by supplying a multiprocessing context mp_context to ProcessPoolExecutor . See forkserver restrictions for information and differences with the fork method and how this change may affect existing code with mutable global shared variables and/or shared objects that can not be automatically pickled . (Contributed by Gregory P. Smith in gh-84559 .) Add two new methods to ProcessPoolExecutor , terminate_workers() and kill_workers() , as ways to terminate or kill all living worker processes in the given pool. (Contributed by Charles Machalow in gh-130849 .) Add the optional buffersize parameter to Executor.map to limit the number of submitted tasks whose results have not yet been yielded. If the buffer is full, iteration over the iterables pauses until a result is yielded from the buffer. (Contributed by Enzo Bonnal and Josh Rosenberg in gh-74028 .) configparser ¶ configparser will no longer write config files it cannot read, to improve security. Attempting to write() keys containing delimiters or beginning with the section header pattern will raise an InvalidWriteError . (Contributed by Jacob Lincoln in gh-129270 .) contextvars ¶ Support the context manager protocol for Token objects. (Contributed by Andrew Svetlov in gh-129889 .) ctypes ¶ The layout of bit fields in Structure and Union objects is now a closer match to platform defaults (GCC/Clang or MSVC). In particular, fields no longer overlap. (Contributed by Matthias Görgens in gh-97702 .) The Structure._layout_ class attribute can now be set to help match a non-default ABI. (Contributed by Petr Viktorin in gh-97702 .) The class of Structure / Union field descriptors is now available as CField , and has new attributes to aid debugging and introspection. (Contributed by Petr Viktorin in gh-128715 .) On Windows, the COMError exception is now public. (Contributed by Jun Komoda in gh-126686 .) On Windows, the CopyComPointer() function is now public. (Contributed by Jun Komoda in gh-127275 .) Add memoryview_at() , a function to create a memoryview object that refers to the supplied pointer and length. This works like ctypes.string_at() except it avoids a buffer copy, and is typically useful when implementing pure Python callback functions that are passed dynamically-sized buffers. (Contributed by Rian Hunter in gh-112018 .) Complex types, c_float_complex , c_double_complex , and c_longdouble_complex , are now available if both the compiler and the libffi library support complex C types. (Contributed by Sergey B Kirpichev in gh-61103 .) Add ctypes.util.dllist() for listing the shared libraries loaded by the current process. (Contributed by Brian Ward in gh-119349 .) Move ctypes.POINTER() types cache from a global internal cache ( _pointer_type_cache ) to the _CData.__pointer_type__ attribute of the corresponding ctypes types. This will stop the cache from growing without limits in some situations. (Contributed by Sergey Miryanov in gh-100926 .) The py_object type now supports subscription, making it a generic type . (Contributed by Brian Schubert in gh-132168 .) ctypes now supports free-threading builds . (Contributed by Kumar Aditya and Peter Bierma in gh-127945 .) curses ¶ Add the assume_default_colors() function, a refinement of the use_default_colors() function which allows changing the color pair 0 . (Contributed by Serhiy Storchaka in gh-133139 .) datetime ¶ Add the strptime() method to the datetime.date and datetime.time classes. (Contributed by Wannes Boeykens in gh-41431 .) decimal ¶ Add Decimal.from_number() as an alternative constructor for Decimal . (Contributed by Serhiy Storchaka in gh-121798 .) Expose IEEEContext() to support creation of contexts corresponding to the IEEE 754 (2008) decimal interchange formats. (Contributed by Sergey B Kirpichev in gh-53032 .) difflib ¶ Comparison pages with highlighted changes generated by the HtmlDiff class now support ‘dark mode’. (Contributed by Jiahao Li in gh-129939 .) dis ¶ Add support for rendering full source location information of instructions , rather than only the line number. This feature is added to the following interfaces via the show_positions keyword argument: dis.Bytecode dis.dis() dis.distb() dis.disassemble() This feature is also exposed via dis --show-positions . (Contributed by Bénédikt Tran in gh-123165 .) Add the dis --specialized command-line option to show specialized bytecode. (Contributed by Bénédikt Tran in gh-127413 .) errno ¶ Add the EHWPOISON error code constant. (Contributed by James Roy in gh-126585 .) faulthandler ¶ Add support for printing the C stack trace on systems that support it via the new dump_c_stack() function or via the c_stack argument in faulthandler.enable() . (Contributed by Peter Bierma in gh-127604 .) fnmatch ¶ Add filterfalse() , a function to reject names matching a given pattern. (Contributed by Bénédikt Tran in gh-74598 .) fractions ¶ A Fraction object may now be constructed from any object with the as_integer_ratio() method. (Contributed by Serhiy Storchaka in gh-82017 .) Add Fraction.from_number() as an alternative constructor for Fraction . (Contributed by Serhiy Storchaka in gh-121797 .) functools ¶ Add the Placeholder sentinel. This may be used with the partial() or partialmethod() functions to reserve a place for positional arguments in the returned partial object . (Contributed by Dominykas Grigonis in gh-119127 .) Allow the initial parameter of reduce() to be passed as a keyword argument. (Contributed by Sayandip Dutta in gh-125916 .) getopt ¶ Add support for options with optional arguments. (Contributed by Serhiy Storchaka in gh-126374 .) Add support for returning intermixed options and non-option arguments in order. (Contributed by Serhiy Storchaka in gh-126390 .) getpass ¶ Support keyboard feedback in the getpass() function via the keyword-only optional argument echo_char . Placeholder characters are rendered whenever a character is entered, and removed when a character is deleted. (Contributed by Semyon Moroz in gh-77065 .) graphlib ¶ Allow TopologicalSorter.prepare() to be called more than once as long as sorting has not started. (Contributed by Daniel Pope in gh-130914 .) heapq ¶ The heapq module has improved support for working with max-heaps, via the following new functions: heapify_max() heappush_max() heappop_max() heapreplace_max() heappushpop_max() hmac ¶ Add a built-in implementation for HMAC ( RFC 2104 ) using formally verified code from the HACL* project. This implementation is used as a fallback when the OpenSSL implementation of HMAC is not available. (Contributed by Bénédikt Tran in gh-99108 .) http ¶ Directory lists and error pages generated by the http.server module allow the browser to apply its default dark mode. (Contributed by Yorik Hansen in gh-123430 .) The http.server module now supports serving over HTTPS using the http.server.HTTPSServer class. This functionality is exposed by the command-line interface ( python -m http.server ) through the following options: --tls-cert <path> : Path to the TLS certificate file. --tls-key <path> : Optional path to the private key file. --tls-password-file <path> : Optional path to the password file for the private key. (Contributed by Semyon Moroz in gh-85162 .) imaplib ¶ Add IMAP4.idle() , implementing the IMAP4 IDLE command as defined in RFC 2177 . (Contributed by Forest in gh-55454 .) inspect ¶ signature() takes a new argument annotation_format to control the annotationlib.Format used for representing annotations. (Contributed by Jelle Zijlstra in gh-101552 .) Signature.format() takes a new argument unquote_annotations . If true, string annotations are displayed without surrounding quotes. (Contributed by Jelle Zijlstra in gh-101552 .) Add function ispackage() to determine whether an object is a package or not. (Contributed by Zhikang Yan in gh-125634 .) io ¶ Reading text from a non-blocking stream with read may now raise a BlockingIOError if the operation cannot immediately return bytes. (Contributed by Giovanni Siragusa in gh-109523 .) Add the Reader and Writer protocols as simpler alternatives to the pseudo-protocols typing.IO , typing.TextIO , and typing.BinaryIO . (Contributed by Sebastian Rittau in gh-127648 .) json ¶ Add exception notes for JSON serialization errors that allow identifying the source of the error. (Contributed by Serhiy Storchaka in gh-122163 .) Allow using the json module as a script using the -m switch: python -m json . This is now preferred to python -m json.tool , which is soft deprecated . See the JSON command-line interface documentation. (Contributed by Trey Hunner in gh-122873 .) By default, the output of the JSON command-line interface is highlighted in color. This can be controlled by environment variables . (Contributed by Tomas Roun in gh-131952 .) linecache ¶ getline() can now retrieve source code for frozen modules. (Contributed by Tian Gao in gh-131638 .) logging.handlers ¶ QueueListener objects now support the context manager protocol. (Contributed by Charles Machalow in gh-132106 .) QueueListener.start now raises a RuntimeError if the listener is already started. (Contributed by Charles Machalow in gh-132106 .) math ¶ Added more detailed error messages for domain errors in the module. (Contributed by Charlie Zhao and Sergey B Kirpichev in gh-101410 .) mimetypes ¶ Add a public command-line for the module, invoked via python -m mimetypes . (Contributed by Oleg Iarygin and Hugo van Kemenade in gh-93096 .) Add several new MIME types based on RFCs and common usage: Microsoft and RFC 8081 MIME types for fonts Embedded OpenType: application/vnd.ms-fontobject OpenType Layout (OTF) font/otf TrueType: font/ttf WOFF 1.0 font/woff WOFF 2.0 font/woff2 RFC 9559 | 2026-01-13T08:49:46 |
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https://www.npopov.com/2012/07/27/How-to-add-new-syntactic-features-to-PHP.html | How to add new (syntactic) features to PHP Blog by nikic . Find me on GitHub , StackOverflow , Twitter and Mastodon . Learn more about me . « Back to article overview. How to add new (syntactic) features to PHP 27. July 2012 Several people have recently asked me where you should start if you want to add some new (syntactic) feature to PHP. As I’m not aware of any existing tutorials on that matter, I’ll try to illustrate the whole process in the following. At the same time this is a general introduction to the workings of the Zend Engine. So upfront: I apologize for this overly long post. This post assumes that you already have some basic knowledge of C and also know the fundamental concepts of the PHP implementation (like zvals). If not, you should read up on them beforehand. As an example I’ll use the addition of an in operator which you might already know from other languages like Python. It works as follows: $words = ['hello', 'world', 'foo', 'bar']; var_dump('hello' in $words); // true var_dump('foo' in $words); // true var_dump('blub' in $words); // false $string = 'PHP is fun!'; var_dump('PHP' in $string); // true var_dump('Python' in $string); // false So basically, for arrays the in operator is the same as the in_array function (but without the needle/haystack problem) and for strings it’s like doing a false !== strpos($str2, $str1) . Prerequisites Before we can get going, you’ll have to first check out and compile PHP. To do so, you need a few tools. Most of them are probably already installed on your system, but you may need to install “re2c” and “bison” using the package manager of your choice. On Ubuntu you’d do this: $ sudo apt-get install re2c $ sudo apt-get install bison Next, clone php-src from git and compile it: // get source code $ git clone http://git.php.net/repository/php-src.git $ cd php-src // create new branch for in operator $ git checkout -b addInOperator // build ./configure script $ ./buildconf // configure PHP in debug mode and with thread safety $ ./configure --disable-all --enable-debug --enable-maintainer-zts // compile (4 is the number of cores you have) $ make -j4 The PHP binary should now be available in sapi/cli/php . You can try to do a few things: $ sapi/cli/php -v $ sapi/cli/php -r 'echo "Hallo World!";' Now that you have a (hopefully) working PHP compile, we’ll take a look at what PHP actually does when it runs a script. The life of a PHP script To run a script PHP goes through three main phases: Tokenization Parsing & Compilation Execution In the following I’ll explain what exactly is done in each phase, how it is implemented and what we need to change in order to get the in operator working. Tokenization In the first phase PHP reads in the source code and breaks it down into smaller units called “tokens”. For example the PHP code <?php echo "Hello World!"; would be broken down to the following tokens: T_OPEN_TAG (<?php ) T_ECHO (echo) T_WHITESPACE ( ) T_CONSTANT_ENCAPSED_STRING ("Hello World!") ';' As you can see the raw source code was broken down into semantically meaningful tokens. The process of doing so is referred to as tokenization, lexing or scanning and is implemented in the zend_language_scanner.l file of the Zend/ directory. If you open the file and scroll down a bit (to somewhere around line 1000), you’ll find a large number of token definitions that look like this: <ST_IN_SCRIPTING>"exit" { return T_EXIT; } The meaning should be rather obvious: If exit is encountered in the source code, the lexer should tag it as T_EXIT . The content between < and > is the state that the text should be matched in. ST_IN_SCRIPTING is the normal state for PHP code. Some examples of other states are ST_DOUBLE_QUOTE (in double quoted string), ST_HEREDOC (in heredoc string), etc. Another thing that can be done in the scanning routines is specifying a “semantic” value (also called “lower value” or “lval” for short). Here is an example: <ST_IN_SCRIPTING,ST_VAR_OFFSET>{LABEL} { zend_copy_value(zendlval, yytext, yyleng); zendlval->type = IS_STRING; return T_STRING; } {LABEL} matches a PHP identifier (it is defined as [a-zA-Z_\x7f-\xff][a-zA-Z0-9_\x7f-\xff]* ) and the code then returns the token T_STRING . Additionally it copies the text of the token into zendlval . So if the lexer encounters an identifier like FooBarClass it’ll set FooBarClass as the lval. The same is also done for strings, numbers, variable names, etc. Luckily the in operator does not require in-depth knowledge of the lexer. We just have to add this code snippet somewhere in the file (analogous to the exit token above): <ST_IN_SCRIPTING>"in" { return T_IN; } Furthermore we have to let the engine know that we added a new token. For this open the zend_language_parser.y and insert the following line somewhere among its peers: %token T_IN "in (T_IN)" Now you should compile PHP again using make -j4 (you have to run it in the top level php-src folder, not in Zend/ ). This will generate a new lexer using re2c and compile it. To test that it worked, you can try running something like this: $ sapi/cli/php -r 'in' This should give you a nice parse error: Parse error: syntax error, unexpected 'in' (T_IN) in Command line code on line 1 A last thing we have to do is regenerate the data used by the tokenizer extension (which exposes the internal lexer to userland PHP code). For this you have to cd into the ext/tokenizer folder and execute ./tokenizer_data_gen.sh . If you run git diff --stat now, you will see something like this: Zend/zend_language_parser.y | 1 + Zend/zend_language_scanner.c | 1765 +++++++++++++++++++------------------ Zend/zend_language_scanner.l | 4 + Zend/zend_language_scanner_defs.h | 2 +- ext/tokenizer/tokenizer_data.c | 4 +- 5 files changed, 904 insertions(+), 872 deletions(-) The zend_language_scanner.c file is the actual lexer generated using re2c. Because it contains line number information every change to the lexer will cause a huge diff. So don’t worry about that ;) Parsing & Compilation Now that the source code is broken down in meaningful tokens PHP has to recognize larger structures like “this is an if block” or “you’re defining a function there”. This process is called parsing and is defined in the zend_language_parser.y file. Again this is just a definition file and the actual parser is generated using bison. To understand how the parser definitions work, let’s look at an example: class_statement: variable_modifiers { CG(access_type) = Z_LVAL($1.u.constant); } class_variable_declaration ';' | class_constant_declaration ';' | trait_use_statement | method_modifiers function is_reference T_STRING { zend_do_begin_function_declaration(&$2, &$4, 1, $3.op_type, &$1 TSRMLS_CC); } '(' parameter_list ')' method_body { zend_do_abstract_method(&$4, &$1, &$9 TSRMLS_CC); zend_do_end_function_declaration(&$2 TSRMLS_CC); } ; For now, let’s leave the parts in curly braces out, so we’re left with the following: class_statement: variable_modifiers class_variable_declaration ';' | class_constant_declaration ';' | trait_use_statement | method_modifiers function is_reference T_STRING '(' parameter_list ')' method_body ; You can read this as: A class statement is a variable declaration (with access modifier) or a class constant declaration or a trait use statement or a method (with method modifier, optional return-by-ref, method name, parameter list and method body) . To find out what exactly a “method modifier” is you’d then go to the method_modifier definition, etc. Should be fairly straightforward. So in order to add in support to the parser, all you have to do is add a new expr T_IN expr rule to expr_without_variable : expr_without_variable: ... | expr T_IN expr ... ; If you now run make -j4 again, bison will attempt to rebuild the parser, but it will fail with the following rather obscure error message: conflicts: 87 shift/reduce /some/path/php-src/Zend/zend_language_parser.y: expected 3 shift/reduce conflicts make: *** [/some/path/php-src/Zend/zend_language_parser.c] Error 1 A shift/reduce conflict basically means that the parser doesn’t know what to do in some situation. The PHP grammar has three shift/reduce conflicts by itself (which is expected due to stuff like the dangling elseif/else ambiguity). The remaining 84 conflicts are caused by the new rule. The reason is that we didn’t specify how in should behave around other operators. An example: // if you write $foo in $bar && $someOtherCond // should PHP interpret this as ($foo in $bar) && $someOtherCond // or as $foo in ($bar && $someOtherCond) The above is called “operator precedence”. A related concept is “operator associativity”, which determines what happens when you write $foo in $bar in $baz . In order to fix the shift/reduce conflicts all you have to do is find the following line at the start of the parser and add T_IN at the end of it: %nonassoc '<' T_IS_SMALLER_OR_EQUAL '>' T_IS_GREATER_OR_EQUAL What this means is that in has the same operator precedence as the < -style comparison operators and that the operator is non-associative. Here are some examples of what this does: $foo in $bar && $someOtherCond // is interpreted as ($foo in $bar) && $someOtherCond // because `&&` has lower precedence than `in` $foo in ['abc', 'def'] + ['ghi', 'jkl'] // is interpreted as $foo in (['abc', 'def'] + ['ghi', 'jkl']) // because `+` has a higher precedence than `in` $foo in $bar in $baz // will throw a parse error, because `in` is non-associative If you rerun make -j4 now everything should work out fine. After that you can try out running something like sapi/cli/php -r '"foo" in "bar";' . This should do nothing, apart from printing a memory leak info: [Thu Jul 26 22:33:14 2012] Script: '-' Zend/zend_language_scanner.l(876) : Freeing 0xB777E7AC (4 bytes), script=- === Total 1 memory leaks detected === This is expected because we haven’t told the parser yet what it should do when it matches an in operator. And this is where the curly braces come in. What you have to do is replace the existing expr T_IN expr rule with the following: expr T_IN expr { zend_do_binary_op(ZEND_IN, &$$, &$1, &$3 TSRMLS_CC); } The part in the curly braces is called a semantic action and is run whenever the parser matches a certain rule (or part of it). The strange looking $$ , $1 and $3 variables in there are nodes. For example $1 refers to the first expr , $3 refers to the second expr ( $3 because it is the third element in the rule) and $$ is the result node. zend_do_binary_op is a compiler instruction. It tells the compiler to emit a ZEND_IN opcode that will take $1 and $3 as operands and put the result into $$ . Compiler instructions are defined in zend_compile.c (with a header entry in zend_compile.h ). zend_do_binary_op for example looks like this: void zend_do_binary_op ( zend_uchar op , znode * result , const znode * op1 , const znode * op2 TSRMLS_DC ) { zend_op * opline = get_next_op ( CG ( active_op_array ) TSRMLS_CC ); opline -> opcode = op ; opline -> result_type = IS_TMP_VAR ; opline -> result . var = get_temporary_variable ( CG ( active_op_array )); SET_NODE ( opline -> op1 , op1 ); SET_NODE ( opline -> op2 , op2 ); GET_NODE ( result , opline -> result ); } The code should be easy to grasp and the next section should help putting it into context. One last thing to mention here is that in most cases you will have to add your own zend_do_* function when adding some new syntax. Adding a new binary operator is one of the few cases where you don’t have to. So if you have to add a new zend_do_* function, just have a look at the existing ones. Most of them are quite simple. Execution In the previous section I already mentioned that the compiler is emitting opcodes. Let’s look closer at how those opcodes look like (see zend_compile.h ): struct _zend_op { opcode_handler_t handler ; znode_op op1 ; znode_op op2 ; znode_op result ; ulong extended_value ; uint lineno ; zend_uchar opcode ; zend_uchar op1_type ; zend_uchar op2_type ; zend_uchar result_type ; }; A short description of what the individual components mean: opcode : This is the actual operation that should be executed. This could for example be ZEND_ADD or ZEND_SUB . op1 , op2 , result : Every operation can have a maximum of two operands (it can obviously also use just one of them, or even none at all) and a result node. The type of the nodes is given by op1_type , op2_type and result_type . We’ll cover how nodes looks like and what types there are in a minute. extended_value : The extended value is used to store flags or some other integer value. E.g. the variable fetching instruction uses it to store the variable kind (like ZEND_FETCH_LOCAL or ZEND_FETCH_GLOBAL ). handler : To optimize opcode execution this stores the handler function associated with the opcode and the operand types. This is determined automatically, so it doesn’t have to be set in the compilation code. lineno : You know what that means… There are five basic types that can go into the *_type properties: IS_TMP_VAR : A temporary variable, usually the result of some expression like $foo + $bar . Temporary variables cannot be shared, so they don’t implement refcounting. They are usually very short lived, so one instruction creates them and the next one already frees them again. Temporary variables are usually written as ~n , so ~0 would be the first temporary variable, ~1 the second, etc. IS_CV : A compiled variable. To save hash table lookups PHP caches the location of simple variables like $foo in an array (C array). Furthermore compiled variables allow PHP to optimize the hash table away altogether. CVs are denoted using !n ( n here is the offset into the compiled-variable array.) IS_VAR : Only simple variables can be turned into CVs. All other kinds of variable accesses, like $foo['bar'] or $foo->bar return an IS_VAR variable. It basically is just a normal zval (with refcounting and everything). Vars are written as $n . IS_CONST : Constants are literals in the code. For example if you write "foo" or 3.141 in your code, those will be of type IS_CONST . Constants allow for some further optimizations, like reusing zvals for the same value, or precalculating hashes. IS_UNUSED : Operand not used. Related to this is how znode_op itself looks like: typedef union _znode_op { zend_uint constant ; zend_uint var ; zend_uint num ; zend_ulong hash ; zend_uint opline_num ; zend_op * jmp_addr ; zval * zv ; zend_literal * literal ; void * ptr ; } znode_op ; As you can see a node is a union, i.e. it can contain one of the elements above (just one!), depending on context. For example zv is used to store IS_CONST zvals, var is used to store the variable number for IS_CV , IS_VAR and IS_TMP_VAR variables. The rest is used in various special circumstances. E.g. jmp_addr is used with the JMP* instructions (which are required for conditions and loops). Others again are used only during compilation, not during execution (like constant ). So now that we know how individual ops look like, the only remaining question is where those are stored: For every function (and file) PHP creates a zend_op_array , which stores the opcodes as well as a lot of other information. I don’t want to go into detail what the individual components are for, you should just know that this structure exists. Now let’s get back to the implementation of the in operator! We already instructed the compiler to emit a ZEND_IN opcode. Now we have to define what this opcode does. This is done in the zend_vm_def.h file. If you look at it, you’ll find that it is full of definitions like this: ZEND_VM_HANDLER ( 1 , ZEND_ADD , CONST | TMP | VAR | CV , CONST | TMP | VAR | CV ) { USE_OPLINE zend_free_op free_op1 , free_op2 ; SAVE_OPLINE (); fast_add_function ( & EX_T ( opline -> result . var ). tmp_var , GET_OP1_ZVAL_PTR ( BP_VAR_R ), GET_OP2_ZVAL_PTR ( BP_VAR_R ) TSRMLS_CC ); FREE_OP1 (); FREE_OP2 (); CHECK_EXCEPTION (); ZEND_VM_NEXT_OPCODE (); } The ZEND_IN opcode will look very similar to this, so it’s worth understanding what is going on there. I’ll go through it line by line: // The header defines four things: // 1. This is the opcode with ID 1 // 2. This opcode is called ZEND_ADD // 3. This opcode accepts CONST, TMP, VAR and CV as the first operand // 4. This opcode accepts CONST, TMP, VAR and CV as the second operand ZEND_VM_HANDLER ( 1 , ZEND_ADD , CONST | TMP | VAR | CV , CONST | TMP | VAR | CV ) { // USE_OPLINE means that we want to access the zend_op as `opline`. // This is required for all opcodes accessing operands or setting a return value. USE_OPLINE // For every operand that is accessed a free_op* variable has to be defined. // It is used to figure out whether the operand needs freeing. zend_free_op free_op1 , free_op2 ; // SAVE_OPLINE() actually loads the zend_op into `opline`. // USE_OPLINE was only the declaration SAVE_OPLINE (); // Call the fast add function fast_add_function ( // And tell it to put the result into the temporary result variable // EX_T here accesses the temporary variable with ID opline->result.var. & EX_T ( opline -> result . var ). tmp_var , // Fetch the first operand for reading (the R in BP_VAR_R) GET_OP1_ZVAL_PTR ( BP_VAR_R ), // Fetch the second operand for reading GET_OP2_ZVAL_PTR ( BP_VAR_R ) TSRMLS_CC ); // Free both operands (if necessary) FREE_OP1 (); FREE_OP2 (); // Check for exceptions. Exceptions can occur virtually everywhere, so one has to check for them in nearly all // opcodes. If in doubt, add the check. CHECK_EXCEPTION (); // Go to the next opcode ZEND_VM_NEXT_OPCODE (); } As you probably noticed there is a lot UPPERCASE_STUFF in there. The reason is that zend_vm_def.h once again is only a definition file. The actual Zend VM is generated from it and stored in zend_vm_execute.h (biiig file). PHP has three different virtual machine kinds, namely CALL (default), GOTO and SWITCH . Because they all have different implementation details the definition file uses lots of pseudo-macros like USE_OPLINE that are later replaced by some concrete implementation. Furthermore the generated VM creates specialized implementations from all possible operand-type permutations. So in the end there won’t be a single ZEND_ADD function, but rather different functions for ZEND_ADD_CONST_CONST , ZEND_ADD_CONST_TMP , ZEND_ADD_CONST_VAR … Now, in order to implement the ZEND_IN opcode, you should add a new opcode definition skeleton at the end of the zend_vm_def.h file: // 159 is the number of the next free opcode for me. You may need to choose a larger number ZEND_VM_HANDLER ( 159 , ZEND_IN , CONST | TMP | VAR | CV , CONST | TMP | VAR | CV ) { USE_OPLINE zend_free_op free_op1 , free_op2 ; zval * op1 , * op2 ; SAVE_OPLINE (); op1 = GET_OP1_ZVAL_PTR ( BP_VAR_R ); op2 = GET_OP2_ZVAL_PTR ( BP_VAR_R ); /* TODO */ FREE_OP1 (); FREE_OP2 (); CHECK_EXCEPTION (); ZEND_VM_NEXT_OPCODE (); } This does nothing more than fetching the operands and discarding them again right away. In order to generate a new VM you now have to run php zend_vm_gen.php from within the Zend/ directory. (If it gives you lots of warnings about the /e modifier being deprecated, ignore those.) After that go into the top level directory again and run make -j4 to recompile. If everything worked out fine you can now run sapi/cli/php -r '"foo" in "bar";' without getting any errors (but it still won’t do anything). Now, finally, we can implement the actual logic. Let’s start with the string case: if ( Z_TYPE_P ( op2 ) == IS_STRING ) { zval op1_copy ; int use_copy ; /* Convert the needle into a string */ zend_make_printable_zval ( op1 , & op1_copy , & use_copy ); if ( use_copy ) { op1 = & op1_copy ; } if ( Z_STRLEN_P ( op1 ) == 0 ) { /* For empty needles return true */ ZVAL_TRUE ( & EX_T ( opline -> result . var ). tmp_var ); } else { char * found = zend_memnstr ( Z_STRVAL_P ( op2 ), /* haystack */ Z_STRVAL_P ( op1 ), /* needle */ Z_STRLEN_P ( op1 ), /* needle length */ Z_STRVAL_P ( op2 ) + Z_STRLEN_P ( op2 ) /* haystack end ptr */ ); ZVAL_BOOL ( & EX_T ( opline -> result . var ). tmp_var , found != NULL ); } /* Free copy */ if ( use_copy ) { zval_dtor ( & op1_copy ); } } The hardest part here is actually casting the needle into a string. This is done using zend_make_printable_zval . This function may either have to create a new zval, or not. That’s why we pass op1_copy and use_copy into it. If the function copied the value we just put it into the op1 variable (so we don’t have to deal with two different variables everywhere). Furthermore the copy has to be freed at the end (what the last three lines do). After that everything is simple. We can find out whether the haystack contains the needle using zend_memnstr . If the needle is an empty string we just return true directly (because the empty string is part of every string). Now, if you added the above code in place of the /* TODO */ , reran zend_vm_gen.php and recompiled using make -j4 , you will already have a half-working in operator: $ sapi/cli/php -r 'var_dump("foo" in "bar");' bool(false) $ sapi/cli/php -r 'var_dump("foo" in "foobar");' bool(true) $ sapi/cli/php -r 'var_dump("foo" in "hallo foo world");' bool(true) $ sapi/cli/php -r 'var_dump(2 in "123");' bool(true) $ sapi/cli/php -r 'var_dump(5 in "123");' bool(false) $ sapi/cli/php -r 'var_dump("" in "test");' bool(true) Next, we have to implement the array behavior: else if ( Z_TYPE_P ( op2 ) == IS_ARRAY ) { HashPosition pos ; zval ** value ; /* Start under the assumption that the value isn't contained */ ZVAL_FALSE ( & EX_T ( opline -> result . var ). tmp_var ); /* Iterate through the array */ zend_hash_internal_pointer_reset_ex ( Z_ARRVAL_P ( op2 ), & pos ); while ( zend_hash_get_current_data_ex ( Z_ARRVAL_P ( op2 ), ( void ** ) & value , & pos ) == SUCCESS ) { zval result ; /* Compare values using == */ if ( is_equal_function ( & result , op1 , * value TSRMLS_CC ) == SUCCESS && Z_LVAL ( result )) { ZVAL_TRUE ( & EX_T ( opline -> result . var ). tmp_var ); break ; } zend_hash_move_forward_ex ( Z_ARRVAL_P ( op2 ), & pos ); } } Here the haystack is simply traversed and every values is checked against the needle. We compare using == . To compare using === one would have to replace is_equal_function with is_identical_function . After rerunning zend_vm_gen.php and make -j4 the in operator should be fully operational: $ sapi/cli/php -r 'var_dump("test" in []);' bool(false) $ sapi/cli/php -r 'var_dump("test" in ["foo", "bar"]);' bool(false) $ sapi/cli/php -r 'var_dump("test" in ["foo", "test", "bar"]);' bool(true) $ sapi/cli/php -r 'var_dump(0 in ["foo"]);' bool(true) // because we're comparing using == One last thing to consider is what should happen when the second operator is neither array nor string. I’ll just take the easy way out for this: Throw a warning and return false: else { zend_error ( E_WARNING , "Right operand of in has to be either string or array" ); ZVAL_FALSE ( & EX_T ( opline -> result . var ). tmp_var ); } After rebuilding and recompiling the VM: $ sapi/cli/php -r 'var_dump("foo" in new stdClass);' Warning: Right operand of in has to be either string or array in Command line code on line 1 bool(false) This might not be the best behavior. E.g. one could allow to do things like 2 in 123 or 3.14 in 3.141 . But I’m too lazy for that right now ;) Finishing thoughts I hope the above helped you understand how to add new features to PHP and what the Zend Engine does when it runs a PHP script. But even though the article is quite long I covered only small parts of the whole system. So when you want to do modifications to the ZE the largest part of the job will be reading the existing code. The cross-reference tool helps a lot when browsing through the PHP source code. Apart from that you can always ask questions in the #php.pecl room on efnet. After you created an implementation for whatever feature you want, the next step is bringing it up on the internals mailing list . People will then look at your feature and decide whether or not it should go in. Oh, and one last thing: The in operator here was just an example. I don’t plan on proposing it for inclusion ;) As always, if you have any further comments or questions, please leave them below. If you liked this article, you may want to browse my other articles or follow me on Twitter or Mastodon . | 2026-01-13T08:49:46 |
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Report Abuse Ntombizakhona Mabaso for AWS Community Builders Posted on Jan 2 Identify AWS Access Management Capabilities # aws # cloud # cloudcomputing # cloudpractitioner Exam Guide: Cloud Practitioner (22 Part Series) 1 Cloud Practitioner Exam Guide 2 Define the Benefits of the AWS Cloud ... 18 more parts... 3 Identify Design Principles of the AWS Cloud 4 Understand the Benefits of and Strategies for Migration to the AWS Cloud 5 Understand Concepts of Cloud Economics 6 Understand the AWS Shared Responsibility Model 7 Understand AWS Cloud Security, Governance, and Compliance Concepts 8 Identify AWS Access Management Capabilities 9 Identify Components and Resources for Security 10 Define Methods of Deploying and Operating in the AWS Cloud 11 Define the AWS Global Infrastructure 12 Identify AWS Compute Services 13 Identify AWS Database Services 14 Identify AWS Network Services 15 Identify AWS Storage Services 16 Identify AWS Artificial Intelligence and Machine Learning (AI/ML) Services And Analytics Services 17 Identify Services From Other In-Scope AWS Service Categories 18 Compare AWS Pricing Models 19 Understand Resources For Billing, Budget, and Cost Management 20 Identify AWS Technical Resources And AWS Support Options 21 Technologies and Concepts: Cloud Practitioner (CLF-C02) 22 My Cloud Practitioner Certification Journey and the Resources to Certify with Confidence 🔑 Exam Guide: Cloud Practitioner Domain 2: Security & Compliance 📘 Task Statement 2.3 🎯 What Is This Task Testing? This objective checks whether you understand how AWS manages identities and permissions, including: IAM basics (users, groups, roles, policies) Why and how to protect the root user The principle of least privilege IAM Identity Center (AWS Single Sign-On) and federated access Credentials: access keys , password policies, and secure storage (Secrets Manager / Systems Manager) 1) 🧠 IAM Basics Who You Are vs What You Can Do In AWS: An identity (user/role) answers: “Who is making the request?” A policy answers: “What are they allowed to do?” Core IAM components IAM Users : individual identities (often for people). IAM Groups : collections of users with shared permissions. IAM Roles : identities assumed temporarily (recommended for AWS services, cross-account access, and federation). IAM Policies : permission documents (JSON) that allow/deny actions on resources. Prefer roles + temporary credentials over long-lived credentials whenever possible. 2) 🛡️ Principle of Least Privilege Least privilege means granting only the permissions required to perform a task—nothing more. Use narrow permissions (specific actions + specific resources) Avoid using "*" for actions/resources unless required Assign permissions to groups/roles , not directly to many users (easier governance) Use managed policies where appropriate, but prefer custom policies when you need tighter control 3) 📄 Policies Managed vs Custom AWS Managed Policies Created and maintained by AWS Useful for common job roles and quick starts Might be broader than necessary Customer Managed Policies (Custom) Created and maintained by you Best when you must enforce strict least privilege Reusable across users/roles/accounts Inline Policies Attached to a single user/group/role Harder to manage at scale (use with care) 4) ✅ Authentication Methods in AWS You should recognize common ways users and systems authenticate: Username/password: IAM user sign-in to AWS console Access keys: programmatic access via CLI/SDK, should be protected and rotated Multi-factor authentication (MFA): strongly recommended, especially for privileged users IAM Identity Center (AWS SSO): centralized workforce access, typically backed by an identity provider Cross-account IAM roles: secure access across AWS accounts without sharing long-term credentials Federated access: external identity provider signs users in; AWS issues temporary credentials 5) 🏢 IAM Identity Center AWS Single Sign-On IAM Identity Center provides centralized access management for workforce users: One place to assign access to AWS accounts and applications Supports SSO and typically integrates with external identity providers (federation) Helps reduce the need for many separate IAM users in each account 6) Access Keys, Password Policies, and Credential Storage 🔐 Access keys Used for programmatic access (CLI/SDK) Should be treated like passwords (never hard-code in code repositories) Best practice is to prefer roles and temporary credentials when possible Password policies (for IAM users) Password policies can enforce: minimum length complexity requirements rotation/expiration preventing password reuse Credential storage (don’t store secrets in code) AWS Secrets Manager : purpose-built for managing secrets (credentials, API keys) and can support rotation workflows. AWS Systems Manager Parameter Store : stores configuration and secrets (often used for parameters; can store secure strings). “Where should we store database passwords securely?” → Secrets Manager Parameter Store is also valid in many scenarios depending on wording. 7) ⚠️ Root User Why It Matters and What Only Root Can Do The root user has full, unrestricted access to the account. It should be used only for tasks that require it. Tasks that commonly require the root user Changing the account’s email address or certain account settings Managing root-level security settings (e.g., some billing/ownership functions) Closing the AWS account Certain billing and payment configuration actions root is for rare, account-level administrative tasks. 8) 🛡️ Root User Protection Methods You should know best practices for protecting root: Enable MFA on the root user Do not use root for daily administration Create admin access for humans via IAM users/roles or IAM Identity Center Secure root credentials: strong password store credentials securely Use monitoring and detection (e.g., alerts on root activity) if mentioned “How do you best protect the root account?” → Enable MFA and avoid routine use . 9) 🔄 Federated Identity Very common in enterprises Users authenticate with an external identity provider (IdP), then receive access to AWS—often via: IAM Identity Center assumed roles (temporary credentials) Why it matters: Federation reduces password sprawl and avoids creating lots of IAM users for employees. Quick Exam-Style Summary ✅ IAM controls access using identities (users/groups/roles) + policies . Apply least privilege : only required actions, only required resources. Roles + temporary credentials are preferred over long-lived access keys. IAM Identity Center (SSO) supports centralized, federated workforce access. Store secrets in AWS Secrets Manager (or Parameter Store when appropriate), not in code. Root user is powerful and should be protected with MFA and used only when necessary. Additional Resources What is IAM? AWS account root user Root user best practices for your AWS account AWS IAM Identity Center AWS Identity and Access Management - Architecture and Terminology Exam Guide: Cloud Practitioner (22 Part Series) 1 Cloud Practitioner Exam Guide 2 Define the Benefits of the AWS Cloud ... 18 more parts... 3 Identify Design Principles of the AWS Cloud 4 Understand the Benefits of and Strategies for Migration to the AWS Cloud 5 Understand Concepts of Cloud Economics 6 Understand the AWS Shared Responsibility Model 7 Understand AWS Cloud Security, Governance, and Compliance Concepts 8 Identify AWS Access Management Capabilities 9 Identify Components and Resources for Security 10 Define Methods of Deploying and Operating in the AWS Cloud 11 Define the AWS Global Infrastructure 12 Identify AWS Compute Services 13 Identify AWS Database Services 14 Identify AWS Network Services 15 Identify AWS Storage Services 16 Identify AWS Artificial Intelligence and Machine Learning (AI/ML) Services And Analytics Services 17 Identify Services From Other In-Scope AWS Service Categories 18 Compare AWS Pricing Models 19 Understand Resources For Billing, Budget, and Cost Management 20 Identify AWS Technical Resources And AWS Support Options 21 Technologies and Concepts: Cloud Practitioner (CLF-C02) 22 My Cloud Practitioner Certification Journey and the Resources to Certify with Confidence Top comments (0) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. 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https://www.npopov.com/2021/10/20/Early-binding-in-PHP.html | Early binding in PHP Blog by nikic . Find me on GitHub , StackOverflow , Twitter and Mastodon . Learn more about me . « Back to article overview. Early binding in PHP 20. October 2021 Translations: 🇯🇵 Japanese PHP allows using a class before its declaration in the same file – sometimes. Internally we call this “early binding”. However, the precise behavior is rather arcane and not well documented. After reading this blog post, you’ll probably appreciate why bug reports related to early binding go right on the “won’t fix” pile. Early binding != class hoisting The most basic example of early binding is the following: $test = new Test ; class Test { /* ... */ } This code works fine, even though the class Test is used before its declaration. Now, one could assume that this works because PHP performs class hoisting, i.e. implicitly converts the code to: class Test { /* ... */ } $test = new Test ; However, the reality is more complicated than this. Consider the following example: # a.php class Test {} require 'b.php' ; # b.php if ( class_exists ( Test :: class )) { return ; } class Test {} If the class declaration in b.php were hoisted to the top of the file, this would result in a class redeclaration error. To still support this kind of early-exit code, we need to make early binding behave as follows: If the class does not exist at the start of the script execution, declare it then. Otherwise, declare it at its original point of declaration. However, this isn’t all. Consider the following example: # a.php require 'b.php' ; class Test2 extends Test {} # b.php class Test {} If the class declaration in a.php were hoisted to the top of the file, it would occur before the require which pulls in a necessary dependency. As such, we need to adjust our rule: If the class does not exist at the start of the script execution and all dependencies of the class are available, declare it then. Otherwise, declare it at its original point of declaration. Limitations The “all dependencies are available” requirement is tricky, because variance rules make it hard to determine this a priori. For example, is A a required dependency in the following code? class Test2 extends Test { public function method (): A {} } The answer to that question depends on how Test looks like. If Test is declared as follows, then A is not a dependency, because we can establish a subtyping relationship without loading the class. A is always a subtype of A , regardless of its actual identity. class Test { public function method (): A {} } However, if the class declaration instead looks as follows, then both A and B would be required dependencies, as we need the class declarations of A and B to determine if these classes are in a subtyping relationship: class Test { public function method (): B {} } This is relatively simple to check when working on a class that has at most a parent class. It’s easy to determine which method would override which parent method and perform a variance check. If the variance check comes back unresolved, we can’t early bind and should fall back to late binding. The situation quickly deteriorates once interfaces and especially traits get involved. Trait use adaptations like aliases make it hard to determine what overrides what and which subtyping relationships need to be proven for inheritance to succeed. At that point, the only really robust way to determine whether inheritance will succeed is to actually do it. That is, create a copy of the class, perform inheritance on it and discard the result if it fails. While we use this approach for preloading since PHP 8.1, I’m rather leery of using it for early binding. Inheritance in PHP is not designed to fail gracefully. Maybe it would be worthwhile to change it in that direction (with the added benefit that inheritance errors could throw an exception rather than a fatal error), but that’s not what we have right now. The end result is that early binding is not performed if the class implements interfaces or uses traits: If the class does not exist at the start of the script execution, the class does not implement interfaces or use traits, and all dependencies of the class are available, declare it then. Otherwise, declare it at its original point of declaration. It is worth noting that “implements interfaces” also includes implicitly implemented interfaces. Classes implementing __toString() are not eligible for early binding, because they implement Stringable . Similarly, enums are not early bound, because they implement UnitEnum or BackedEnum . Delayed early binding The situation becomes more complicated once opcache gets involved. Normally, early binding is attempted directly during compilation. If it succeeds, the class is registered, otherwise a DECLARE_CLASS opcode is emitted. This wouldn’t work for opcache, because cached scripts must be isolated and cannot use dependencies from other scripts. A dependency might not be available during initial compilation (should not early bind) but be available during a later use of the cached script (should early bind). Opcache solves this through “delayed early binding”. DECLARE_CLASS_DELAYED opcodes are emitted for classes that are potentially eligible for early binding and placed in a linked list. When a script is loaded, opcache walks the DECLARE_CLASS_DELAYED opcodes and tries to perform early binding. If it succeeds, it marks the class as already declared in the run-time cache, so that another declaration is not attempted when the class declaration opcode is executed through normal control flow. Of course, it turns out that this approach is still too simplistic. Consider the following variant: if ( true ) { return ; } class Test2 extends Test {} In this case, the early return is always taken, and the optimizer will detect this and remove any following code – including the DECLARE_CLASS_DELAYED opcode. However, per our early binding semantics, the class should still be delared if Test is available at the time the script is executed. This particular problem is only fixed in PHP 8.2, where classes that require delayed early binding are now tracked in a separate structure that is independent of the DECLARE_CLASS_DELAYED opcodes that may be optimized away. Despite all this, the behavior of early binding with and without opcache is still not quite the same. Consider the following example: new Test2 ; class Test2 extends Test {} class Test {} Without opcache this will error: Class Test2 is not early bound, because the dependency Test is not available at the time of declaration. However, Test is early bound. With opcache Test is early bound and Test2 queued for delayed early binding. At the time early binding is actually attempted Test does exist and the code will finish without error. Effectively this means that without opcache, there is a single early binding pass, while with opcache there are two. Conclusion There are two sensible ways in which class declarations could have worked: The class could be declared exactly where it was written in the code. This is nice and simple, but may be something of an inconvenience for code not following the “single class per file” style. All (top-level) class declarations could be hoisted to the start of the script. This would also be easy to support, including reordering of class declarations to account for dependencies. Of course, PHP picked the third way: “Why don’t we have both?” Now we have a complicated system that only works some of the time. If you liked this article, you may want to browse my other articles or follow me on Twitter or Mastodon . | 2026-01-13T08:49:46 |
https://ocw.mit.edu/courses/6-0001-introduction-to-computer-science-and-programming-in-python-fall-2016/resources/lecture-videos/ | Introduction to Computer Science and Programming in Python | Electrical Engineering and Computer Science | MIT OpenCourseWare Browse Course Material Syllabus Instructor Insights Readings Lecture Videos Lecture Slides and Code In-Class Questions and Video Solutions Lecture 1 Lecture 2 Lecture 3 Lecture 4 Lecture 5 Lecture 7 Lecture 8 Lecture 9 Assignments Course Info Instructors Dr. Ana Bell Prof. Eric Grimson Prof. John Guttag Departments Electrical Engineering and Computer Science As Taught In Fall 2016 Level Undergraduate Topics Engineering Computer Science Algorithms and Data Structures Programming Languages Learning Resource Types assignment Problem Sets notes Lecture Notes theaters Lecture Videos assignment_turned_in Programming Assignments with Examples Download Course menu search Give Now About OCW Help & Faqs Contact Us search GIVE NOW about ocw help & faqs contact us 6.0001 | Fall 2016 | Undergraduate Introduction to Computer Science and Programming in Python Menu More Info Syllabus Instructor Insights Readings Lecture Videos Lecture Slides and Code In-Class Questions and Video Solutions Lecture 1 Lecture 2 Lecture 3 Lecture 4 Lecture 5 Lecture 7 Lecture 8 Lecture 9 Assignments Lecture Videos video 96 MB Lecture 1: What is Computation? video 98 MB Lecture 2: Branching and Iteration video 102 MB Lecture 3: String Manipulation, Guess and Check, Approximations, Bisection video 93 MB Lecture 4: Decomposition, Abstraction, and Functions video 94 MB Lecture 5: Tuples, Lists, Aliasing, Mutability, and Cloning video 108 MB Lecture 6: Recursion and Dictionaries video 93 MB Lecture 7: Testing, Debugging, Exceptions, and Assertions video 94 MB Lecture 8: Object Oriented Programming video 106 MB Lecture 9: Python Classes and Inheritance video 116 MB Lecture 10: Understanding Program Efficiency, Part 1 video 110 MB Lecture 11: Understanding Program Efficiency, Part 2 video 109 MB Lecture 12: Searching and Sorting Course Info Instructors Dr. Ana Bell Prof. Eric Grimson Prof. John Guttag Departments Electrical Engineering and Computer Science As Taught In Fall 2016 Level Undergraduate Topics Engineering Computer Science Algorithms and Data Structures Programming Languages Learning Resource Types assignment Problem Sets notes Lecture Notes theaters Lecture Videos assignment_turned_in Programming Assignments with Examples Download Course Over 2,500 courses & materials Freely sharing knowledge with learners and educators around the world. Learn more © 2001–2026 Massachusetts Institute of Technology Accessibility Creative Commons License Terms and Conditions Proud member of: © 2001–2026 Massachusetts Institute of Technology You are leaving MIT OpenCourseWare close Please be advised that external sites may have terms and conditions, including license rights, that differ from ours. MIT OCW is not responsible for any content on third party sites, nor does a link suggest an endorsement of those sites and/or their content. Stay Here Continue | 2026-01-13T08:49:46 |
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https://docs.suprsend.com/docs/embeddable-inbox#integrate-as-npm-package | Integration - SuprSend, Notification infrastructure for Product teams Skip to main content SuprSend, Notification infrastructure for Product teams home page Search... ⌘ K Community Trust Center Platform Status Postman Collection GETTING STARTED What is SuprSend? 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Navigation Javascript (Angular, Vuejs etc) Integration Documentation API Reference Management API CLI Reference Developer Resources Changelog Documentation API Reference Management API CLI Reference Developer Resources Changelog Javascript (Angular, Vuejs etc) Integration OpenAI Open in ChatGPT How to integrate SuprSend inbox/feed components in Angular, Vue, VanillaJS, and other non-React frameworks. OpenAI Open in ChatGPT End of Support for @suprsend/web-inbox . Migrate to @suprsend/web-components We have upgraded authentication of inbox from HMAC to JWT as it is more secure. Please migrate to newer SDK if you are on old one. There are 2 ways in which you can implement inbox functionality: Drop-in components: Pre-built UI with many customizable options which require minimal effort to build. Headless implementation: For more advanced use cases where you want to build UI/UX from scratch. This guide help you integrate drop-in components in your non-react frameworks (angular, vuejs, vanillajs etc). If you want to build your own UI (headless) instead of using drop-in components please refer docs . Integration Integrate using script tag This integration is used in Vanillajs, Django, Laravel, ruby etc where npm is not used. Copy Ask AI <!-- for dropin inbox with bell --> < div id = "suprsend-inbox" ></ div > <!-- for feed without bell as a fullscreen notification etc --> < div id = "suprsend-feed" ></ div > < script > window . suprsendConfig = { distinctId: "YOUR_DISTINCT_ID" , publicApiKey: "YOUR_PUBLIC_API_KEY" , userAuthenticationHandler : ({ response }) => { console . log ( "User Authentication Response" , response ); }, }; let scriptElem = document . createElement ( "script" ); scriptElem . async = 1 ; scriptElem . src = "https://web-components.suprsend.com/v0.3.0/bundle.umd.js" ; scriptElem . onload = () => { console . log ( "SuprSend SDK loaded" , window . suprsend ); }; document . body . appendChild ( scriptElem ); </ script > Integrate as npm package This integration is used in framework based applications like angular, vuejs etc. Copy Ask AI npm install @suprsend/web-components@latest Copy Ask AI import { initSuprSend , clearSuprSend } from "@suprsend/web-components" ; // for dropin inbox with bell < div id = "suprsend-inbox" ></ div > // for feed without bell as a fullscreen notification etc < div id = "suprsend-feed" ></ div > const suprsendConfig = { distinctId: "YOUR_DISTINCT_ID" , publicApiKey: "YOUR_PUBLIC_API_KEY" , userAuthenticationHandler : ({ response }) => { console . log ( "User Authentication Response" , response ); }, }; initSuprSend ( suprsendConfig ) // for creating instance and rendering component console . log ( "Instance created but user authentication pending" , window . suprsend ) NOTE: If you are using suprsend-feed , specify height for the container for infinite scroll to work properly. Copy Ask AI const suprsendConfig = { distinctId: "YOUR_DISTINCT_ID" , publicApiKey: "YOUR_PUBLIC_API_KEY" , feed: { theme: { notificationsContainer: { container: { height: "100vh" } } }, // add this to specify height }, }; Removing instance Components will be removed automatically if you navigate away from the page (on unmounting). If you want to remove them manually, you can use below methods. Using script tag Using npm package Copy Ask AI window . suprsend . clearSuprSend (); // clears instance and remove all components window . suprsend . clearSuprSendInbox (); // unmount only inbox component window . suprsend . clearSuprSendFeed (); // unmount only feed component Updating configuration dynamically Copy Ask AI window . suprsend . updateSuprSendConfig ( config : IUpdateSuprSendConfigOptions ); // refresh userToken, change locale, translations dymanically window . suprsend . updateInboxConfig ( config : IInbox ); window . suprsend . updateFeedConfig ( config : IFeed ); window . suprsend . updateToastConfig ( config : IToastNotificationProps ); Accessing other instance methods SDK internally calls new SuprSend() when you call initSuprSend() then you can access instance using window.suprsend.client . This instance has methods like preferences , webpush , event and user updates . Copy Ask AI // example methods window . suprsend . client . isIdentified (); window . suprsend . client . user . addEmail ( email : string ); window . suprsend . client . track ( event : string , properties ?: Dictionary ) window . suprsend . client . webpush . registerPush (); window . suprsend . client . user . preferences . getPreferences ( args ?: {tenantId? : string }); Config options To customise SuprSend components you can pass config object. Config Options Inbox Config Options Feed Config Options Toast Config Options Copy Ask AI interface ConfigProps { publicApiKey : string ; distinctId ? : unknown ; userToken ? : string ; host ? : string ; initOnLoad ? : boolean ; // pass false if you don't want to initialise instance just after loading script refreshUserToken ? : ( oldUserToken : string , tokenPayload : Dictionary ) => Promise < string > ; vapidKey ? : string ; swFileName ? : string ; userAuthenticationHandler ? : ({ response : ApiResponse }) => void ; inbox ? : IInbox ; // inbox config options feed ? : IFeed ; // feed config options toast ? : IToastNotificationProps ; // toast config options shadowRoot ?: ShadowRoot ; //shadowRoot reference } Parameter Description publicApiKey Public API Key is mandatory field without which error will be thrown by SuprSendProvider. You can get this from SuprSend Dashboard . distinctId Unique identifier to identify a user across platform. If a value is passed SDK will create user and authenticate user. If null value is passed authenticated user’s instance data will be cleared in your application, kind of logout. userToken Mandatory when enhanced security mode is on. This is ES256 JWT token generated in your server-side. Refer docs to create userToken. refreshUserToken This function is called by SDK internally to get new userToken before existing token is expired. The returned JWT token string is used as the new userToken. userAuthenticationHandler This callback will be called after authenticating user internally when you pass distinctId field to give you back the response of user creation API call. host Customise the host url. vapidKey This key is needed only if you are implementing WebPush notifications. You can get it in SuprSend Dashboard —> Vendors —> WebPush swFileName This key is needed only if you are implementing WebPush notifications and want to customise default serviceworker.js file name with your own service worker file name. shadowRoot Shadow root reference to render components inside shadow dom For further component specific customisations please refer to the docs . Was this page helpful? Yes No Suggest edits Raise issue Previous Customization options How to customize the styling, CSS, and layout of the Inbox Feed to match your product’s design in non-React websites. Next ⌘ I x github linkedin youtube Powered by On this page Integration Integrate using script tag Integrate as npm package Removing instance Updating configuration dynamically Accessing other instance methods Config options | 2026-01-13T08:49:46 |
https://dev.to/sunny7899/indias-ai-model-approach-2553 | India's AI model approach - 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 Neweraofcoding Posted on Jan 10 • Edited on Jan 11 India's AI model approach India lacks its own major AI models due to lower R&D investment, focus on IT services over deep research, hardware limitations (GPU scarcity), and market competition from global giants, hindering local startups; to achieve self-reliance, India needs massive infrastructure investment, government-private collaboration, focus on specific Indian needs (languages, culture), and fostering long-term research to build sovereign, localized AI for the nation. Why India doesn't have its own major AI models (Yet) Research Focus: India traditionally excels in IT services rather than foundational AI research, unlike the US and China, which invest heavily in fundamental science. Investment Shortfall: R&D spending (around 0.6% of GDP) is significantly lower than global peers (US 3.4%, China 2.4%), with insufficient private sector R&D and concentrated government bets. Hardware & Infrastructure: Training large models requires vast amounts of high-end GPUs, which India lacks, leading dependence on foreign cloud providers and data centers. Market Competition: India's open market allows large US firms to dominate, making it hard for local startups to compete and scale without a protected environment like China's. Talent Drain: Top Indian talent often works for foreign firms, with revenue streams and innovation incentives directed abroad. This video explains why India hasn't created its own ChatGPT: How India can achieve sovereign AI (Not sharing data) Invest in Infrastructure: Build domestic data centers and secure massive GPU clusters for large-scale training. Fund Long-Term Research: Shift from quick-return projects to sustained, large-scale investment in fundamental AI research, as seen in Korea and China. Foster Collaboration: Create strong public-private partnerships (PPP) to pool resources and efforts. Focus on Local Needs: Develop applied AI for Bharat (India) in local languages and contexts (e.g., IndicTrans2), proving value at smaller scales where resources allow. Build Ecosystem: Support startups to create trustworthy, affordable, India-ready AI tools, ensuring local solutions are available for domestic use. Control Data & Standards: Establish robust data governance (like the DPDP Act) and create open datasets and interoperable standards to control India's AI future. India has a significant and rapidly growing data center industry with numerous facilities operated by major global and domestic companies. It is a common misconception that India lacks data centers, but the country is a key market for data storage and processing. Here is what India does not have, in the context of its data center market: A shortage of data centers in general: India has a robust and expanding data center market. The first national data center was launched in Hyderabad in 2008, and there are now hundreds of facilities across the country in cities like Mumbai, Chennai, Hyderabad, and Delhi. Absence of major tech giants: Global companies such as Amazon Web Services (AWS), Microsoft Azure, Google Cloud, and Equinix have established or are actively investing in data centers and cloud regions in India. Sufficient capacity to meet demand: While the number of data centers is high, India generates approximately 20% of global data traffic but holds only about 3% of the world's data center capacity. This highlights a significant gap between data generation and processing capacity within the country, which is currently being addressed through massive investments. A large-scale, world-class specialized workforce: India possesses a large IT workforce, but there is a recognized talent gap in the specific expertise required for operating modern, complex data centers, such as specialized mechanical and electrical engineers and cybersecurity experts in critical infrastructure. Total independence from foreign infrastructure: For the foreseeable future, India's digital ecosystem will continue to rely on a mix of local and international data center infrastructure to meet its vast data processing needs. https://www.linkedin.com/posts/shaheennabi_why-india-will-never-build-its-own-llm-activity-7332303784661954560-0-Sf?utm_source=share&utm_medium=member_desktop&rcm=ACoAABhacnABGS_mFSUdxJeEM4xeEAc0yga9X4I https://www.linkedin.com/posts/jitendrachouksey_perplexity-doesnt-have-its-own-ai-replit-activity-7355143866846474241-RejQ?utm_source=share&utm_medium=member_desktop&rcm=ACoAABhacnABGS_mFSUdxJeEM4xeEAc0yga9X4I 🇮🇳 Why doesn’t India have a widely used sovereign AI model yet? India does have AI research and early models , but not yet a globally dominant, fully sovereign foundation model like GPT, Claude, or Gemini. The reasons are structural—not lack of talent. 1️⃣ Compute power is extremely expensive Training large AI models requires: 10,000–100,000+ GPUs Continuous power, cooling, and networking Cost: ₹5,000–₹20,000 crore+ for a single frontier model Most Indian startups and institutions simply can’t afford this scale yet. 2️⃣ Late entry into the AI race Companies like OpenAI , Google, and Meta: Started 10–15 years ago Had access to global cloud infrastructure Benefited from massive venture and enterprise funding India focused earlier on: IT services SaaS Digital public infrastructure (UPI, Aadhaar) AI foundation models became priority only recently. 3️⃣ Data is fragmented and sensitive India has rich data (languages, healthcare, governance), but: It’s siloed across ministries High privacy and legal constraints No unified, clean national AI dataset (yet) 4️⃣ Brain drain problem Many top Indian AI researchers: Work in the US / Europe Are employed by foreign AI labs Don’t have incentives to return without comparable infra & funding 5️⃣ Policy focus came late Until recently, India: Promoted AI adoption Not AI infrastructure ownership That is now changing. 🚀 Is India doing something now? Yes. Actively. Recent initiatives include: IndiaAI Mission (₹10,000+ crore) National GPU cloud access Open datasets in Indian languages Support for Bharat-focused LLMs But these will take 3–5 years to mature. 🔐 If YOU want to train an AI model without sharing data with anyone , here’s how to do it This is absolutely achievable today. ✅ Option 1: On-premise / Private AI (Most secure) Best for banks, govt, healthcare, enterprises What you need: Your own servers (or private data center) NVIDIA GPUs (A100 / H100 / L40S) Open-source models (no data sharing) How it works: Your Data → Your Servers → Your Model (No internet, no cloud, no data leakage) Enter fullscreen mode Exit fullscreen mode Tools: LLaMA / Mistral / Falcon (open-source) PyTorch + Hugging Face (offline mode) Kubernetes + Slurm (optional) 📌 Data never leaves your premises ✅ Option 2: Sovereign Cloud (India-only) Good balance between cost & privacy Use Indian-hosted cloud providers with: Data residency guarantees No foreign jurisdiction access Examples: Government empaneled clouds Indian private data centers Still train open-source models , not proprietary APIs. ✅ Option 3: Fine-tune instead of training from scratch (Recommended) Training from scratch is overkill for most use cases. Instead: Take a base open-source LLM Fine-tune it on your private data Run it fully offline 💡 This gives 90% capability at 10% cost 🔒 Key Rules to ensure ZERO data sharing Follow these strictly: ✔ Use open-source models only ✔ Disable telemetry & external calls ✔ No SaaS AI APIs ✔ Self-host embeddings & vector DB ✔ Use air-gapped or VPC networks If you do this, not even the model creator sees your data . 🧠 Can India build its own GPT-level model? Yes — but it requires: Requirement Status Talent ✅ Strong Data ✅ Huge Compute ⚠️ Catching up Policy ⚠️ Improving Funding ⚠️ Growing India will likely produce: Bharat-focused LLMs first Then global-scale models later 🧩 Practical takeaway (important) You do NOT need a national GPT to be secure. Most organizations should: Build private AI on open models , hosted in India, trained on their own data. That’s already more secure than using public AI APIs. 🇮🇳 Yes, India has many data centres India already hosts hundreds of enterprise-grade data centres , run by both Indian and global companies. Major operators in India STT GDC Nxtra Data CtrlS Yotta Sify AdaniConneX 📍 Major hubs: Mumbai, Chennai, Hyderabad, Bengaluru, Noida, Pune ❓ Then why do people say “India doesn’t have data centres” ? Because they usually mean something very specific , not normal data centres. Let’s clarify 👇 ⚠️ What India does NOT yet have enough of 1️⃣ AI-grade GPU superclusters For training GPT-level models you need: 10,000–100,000 GPUs Ultra-low latency networking (InfiniBand) Massive power density (30–80 kW per rack) India currently has far fewer such clusters compared to the US. ➡️ Most Indian data centres are: CPU-heavy Storage-heavy Enterprise / cloud workload focused —not AI foundation model training focused 2️⃣ Hyperscaler-owned AI infra Companies like: OpenAI Google Meta Own or tightly control custom-built AI data centres . In India: Hyperscalers mostly rent capacity GPU supply is limited Long wait times for H100 / A100 GPUs 3️⃣ Cheap power at massive scale AI training burns insane electricity . Country Power cost US Lower for hyperscalers Middle East Very cheap India Higher + grid constraints This makes frontier AI training more expensive in India today. 4️⃣ Advanced AI networking stack AI needs: NVLink InfiniBand Custom cooling (liquid) Most Indian DCs are: Tier III / Tier IV compliant ✅ But not AI-optimized yet ⚠️ ✅ What India IS actually very good at Area Status Enterprise DCs ✅ Excellent Data residency ✅ Strong Government workloads ✅ Strong Banking & FinTech infra ✅ World-class SaaS hosting ✅ Mature This is why: Banks UIDAI-like systems Stock exchanges already run fully inside India 🚀 What’s changing right now (important) India is actively building: National GPU clouds AI-first data centres Public-private AI infra The IndiaAI Mission aims to: Provide shared GPU access Reduce dependence on foreign AI infra Enable sovereign AI models Timeline: 2–4 years 🔐 So can you train AI in India without sharing data ? YES. 100%. Today. You can: Host models in Indian data centres Use open-source LLMs Block all outbound internet Stay compliant with Indian laws This already works for: Banks Defense contractors Healthcare orgs 🧠 Final clarity (very important) ❌ “India has no data centres” → False ✅ “India lacks large AI superclusters (for now)” → True And for most real-world AI use cases , you do not need GPT-scale infra. 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 Neweraofcoding Follow Expert Front end developer with Angular, and React experience Location Delhi India Joined Nov 4, 2020 More from Neweraofcoding High-performance GPUs or TPUs vs CPUs # architecture # machinelearning # performance # ai Getting Started with Vite # beginners # frontend # javascript # tooling comprehensive guide to Google Jules, how it relates to AI Pro users, how it uses Gemini 3 models 💎 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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NOTE: Tracking that is built into the DevCycle SDK does not count against billable events. What is EdgeDB? EdgeDB is a lightning-fast, globally replicated edge storage tool that allows you to store information about your users for future use in Targeting Rules. For example, you can set a custom property when a user performs a key action in your application, and then target based on that property in the future without having to continuously provide that data in the SDK. How are Overages Billed? The Developer and Business plans include a set number of Client-Side MAUs, Cloud Config Requests, Server Config Requests, and Events. If you exceed these limits, you'll be billed monthly at the rate specified for your plan, subject to applicable annual discounts. Build Better Software With DevCycle DevCycle is designed from the ground up to help you ship better software, faster. Sign up today and start improving your software development process. 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https://devcycle.com/pricing#server-config-requests | Pricing | DevCycle Product Solutions Resources Pricing Docs Book Demo Login Create Account Powerful Feature Flags. Fair Pricing. DevCycle is affordable on all plans. With all the features your team needs and none you don't. Monthly Use setting Annually (Save 20%) Free $0 No credit card required For small projects, or people that just want to give DevCycle a try. Unlimited Seats Up to 1,000 Client-side MAUs A Monthly Active User (MAU) is a unique user with at least one Client-Side SDK initialization in a month. All the features you need to get started. Get Started Core Features, including Unlimited Seats Unlimited Flags All Integrations A/B Testing MCP Server ...and more Developer $ 10 Per Month, Billed Annually For startups who are trying to improve their development process. Unlimited Seats 1,000 MAUs Included A Monthly Active User (MAU) is a unique user with at least one Client-Side SDK initialization in a month. 10,000 Events per Month Included Pricing Estimate: 1,000 MAUs Create Account Everything in Free, plus AI Generated Feature Summaries AI Generated Schemas Audit Logging Feature Opt-in Flag Schemas Custom Property Schemas Business $ 500 Per Month, Billed Annually For organizations with multiple teams that need permissions. Unlimited Seats 100,000 MAUs Included A Monthly Active User (MAU) is a unique user with at least one Client-Side SDK initialization in a month 500,000 Events per Month Included Pricing Estimate: 100,000 MAUs Create Account Everything in Developer, plus Roles & Permissions Stale Flag Detection Custom Property Storage (EdgeDB) Custom Domain Proxy Enterprise Custom Billed Annually For enterprise teams that have strict governance and SLA requirements. 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Book a Call Everything in Business, plus Approval Workflows Custom SSO/SAML SCIM Provisioning 3rd Party Data ETL Event Relay Proxy Premium Support Uptime SLA Pricing that grows with your business DevCycle Feature List Free Developer Business Enterprise Pricing Breakdown Base Price Free $12.50 / month $625 / month Custom Client-Side MAUs 1,000 Included 1,000 Included then $7.00 per 1,000 100,000 Included then $2.50 per 1,000 Custom Cloud Config Requests 10,000 / month Included 10,000 / month Included then $6 per 10,000 1,000,000 / month Included then $2 per 10,000 Custom Server Config Requests 100,000 / month Included 100,000 / month Included then $6 per 100,000 10,000,000 / month Included then $2 per 100,000 Custom Events 5,000 / month Included 10,000 / month Included then $1 per 10,000 500,000 / month Included then $0.5 per 10,000 Custom Core Features Feature Flags Unlimited Unlimited Unlimited Unlimited Seats Unlimited Unlimited Unlimited Unlimited Environments Unlimited Unlimited Unlimited Unlimited Projects Unlimited Unlimited Unlimited Unlimited A/B Testing & Experimentation Debugging Tools All Integrations Real-Time Updates Targeting & Segmentation Percentage-Based Rollouts Global Flag State Visibility OpenFeature Support Across All SDKs REST API CLI Advanced Features Variable Types Multi-Step Rollouts Rollouts by Custom Property Reusable Audiences Custom Property Targeting One-Click Self Targeting Flag Name Obfuscation Realtime Updates Feature Opt-in Custom Property Schemas Flag Schemas Stale Flag Detection/Notification EdgeDB (Stored Custom Properties) Roles & Permissions Approval Workflows AI-Enabled Features MCP Server AI Generated Feature Summaries AI Generated Schemas Workflow Tools Embedded Debugging Tools Code Generation Tools Flag Importer Code Pipeline Integrations Code References Webhooks VS Code Extension Terraform Provider Slack App Snowflake Data Sharing 3rd party ETL Security & Compliance SOC 2 Type 2 Certified Audit Logging Custom Domain Proxy SAML SSO SCIM Provisioning SDK Proxy Implementation Support & Service Guarantees Discord Community Email Support Shared Slack Channel Custom Migration Support First Reply SLA Uptime SLA Custom Legal Terms Frequently Asked Questions What is a Monthly Active User (MAU)? A Monthly Active User (MAU) is a unique user ID that has at least one Client-Side SDK initialization in a month. What is a Cloud Config Request? A Cloud Config Request happens on initialization or identification update of a client-side SDK such as web and mobile, as well as all calls to our Bucketing API or our server-side SDKs, when configured to run in cloud-bucketing mode. All of these calls grab the latest Feature Flag value/configuration from DevCycle's Edge Workers. What is a Server Config Request? A Server Config Request is a request to the DevCycle config CDN to fetch the latest project Configuration by any of our local bucketing server-side SDKs whether on startup, via polling or triggered by an SSE event. What is an Event? An Event is a single data point sent to DevCycle using the Track API or Track function in our SDKs. These can be any custom event whether tracking conversions or latency. Events serve as a foundation for creating custom metrics. NOTE: Tracking that is built into the DevCycle SDK does not count against billable events. What is EdgeDB? EdgeDB is a lightning-fast, globally replicated edge storage tool that allows you to store information about your users for future use in Targeting Rules. For example, you can set a custom property when a user performs a key action in your application, and then target based on that property in the future without having to continuously provide that data in the SDK. How are Overages Billed? The Developer and Business plans include a set number of Client-Side MAUs, Cloud Config Requests, Server Config Requests, and Events. If you exceed these limits, you'll be billed monthly at the rate specified for your plan, subject to applicable annual discounts. Build Better Software With DevCycle DevCycle is designed from the ground up to help you ship better software, faster. Sign up today and start improving your software development process. 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https://dev.to/aws-builders/understand-concepts-of-cloud-economics-3ki4 | Understand Concepts of Cloud Economics - 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 Ntombizakhona Mabaso for AWS Community Builders Posted on Dec 31, 2025 Understand Concepts of Cloud Economics # aws # cloud # cloudcomputing # cloudpractitioner Exam Guide: Cloud Practitioner (22 Part Series) 1 Cloud Practitioner Exam Guide 2 Define the Benefits of the AWS Cloud ... 18 more parts... 3 Identify Design Principles of the AWS Cloud 4 Understand the Benefits of and Strategies for Migration to the AWS Cloud 5 Understand Concepts of Cloud Economics 6 Understand the AWS Shared Responsibility Model 7 Understand AWS Cloud Security, Governance, and Compliance Concepts 8 Identify AWS Access Management Capabilities 9 Identify Components and Resources for Security 10 Define Methods of Deploying and Operating in the AWS Cloud 11 Define the AWS Global Infrastructure 12 Identify AWS Compute Services 13 Identify AWS Database Services 14 Identify AWS Network Services 15 Identify AWS Storage Services 16 Identify AWS Artificial Intelligence and Machine Learning (AI/ML) Services And Analytics Services 17 Identify Services From Other In-Scope AWS Service Categories 18 Compare AWS Pricing Models 19 Understand Resources For Billing, Budget, and Cost Management 20 Identify AWS Technical Resources And AWS Support Options 21 Technologies and Concepts: Cloud Practitioner (CLF-C02) 22 My Cloud Practitioner Certification Journey and the Resources to Certify with Confidence 💸 Exam Guide: Cloud Practitioner Domain 1: Cloud Concepts 📘 Task Statement 1.4 🎯 What Is This Task Testing? This objective checks whether you can explain how cloud changes the cost model and why it can reduce total cost of ownership (TCO). You should be able to discuss: fixed vs variable costs on-premises cost drivers licensing strategies (BYOL vs included) rightsizing automation benefits (e.g., AWS CloudFormation) the value of managed services (e.g., RDS, ECS/EKS, DynamoDB) 1) 🧠 Cloud Economics Cloud economics is about shifting from “buy and maintain infrastructure” to “consume resources as needed.” The cloud can lower costs by: reducing upfront purchases reducing wasted capacity reducing operational overhead through automation and managed services enabling faster delivery (which can also improve business outcomes) 2) 🧾Fixed Costs vs Variable Costs Fixed costs (on-premises) Costs that remain relatively constant regardless of usage, such as: purchasing servers and networking equipment data center leases/build-outs long depreciation cycles Variable costs (cloud) Costs that scale with usage, such as: compute hours consumed storage used per GB data transfer and request-based pricing (service-dependent) AWS helps you trade fixed costs (CapEx) for variable costs (OpEx) so you pay more closely in line with actual demand. 3) 🏢 Costs Associated with On-Premises Environments Recognize and understand that on-premises cost is more than just hardware. Common on-prem cost categories: hardware purchases and refresh cycles data center space (rent, facilities) power and cooling physical security networking equipment and maintenance contracts IT labor for racking/stacking, patching, monitoring, backups, and incident response overprovisioning (buying for peak demand “just in case”) downtime risk and disaster recovery duplication (secondary sites) 4) 📄 Licensing Strategies: BYOL vs Included Licenses BYOL (Bring Your Own License) You use existing software licenses in the cloud (when terms allow). Common reasons to choose BYOL: you already own licenses and want to extend their value it may reduce software costs versus purchasing new licenses Included licenses The AWS service/resource pricing includes the license cost. Common reasons to choose included: simpler procurement and management predictable billing (license bundled) good for short-term needs or when you don’t already own licenses 5) 🧮 Rightsizing Rightsizing means selecting the most cost-effective resource type and size that meets performance requirements. What rightsizing looks like in practice: reducing oversized instances (CPU/RAM far above actual need) choosing the right storage tier/performance level scaling resources dynamically rather than keeping everything “always on” 6) 🤖 Benefits of Automation (Provisioning & Configuration) Automation reduces manual work, improves consistency, and speeds delivery—often lowering operational cost and risk. Example: AWS CloudFormation AWS CloudFormation helps you define infrastructure using templates (Infrastructure as Code). Benefits: repeatable, consistent deployments faster provisioning (minutes vs manual setup) fewer configuration errors (less drift) easier auditing and change management 7) 🛠️ Managed AWS Services Managed services offload infrastructure operations (patching, backups, scaling tasks, high availability setup) to AWS, reducing your operational burden. Examples and their general category: Amazon RDS : managed relational databases (AWS handles backups, patching, maintenance features) Amazon DynamoDB : managed NoSQL database (serverless-style scaling, reduced ops) Amazon ECS : managed container orchestration (run containers without managing orchestration from scratch) Amazon EKS : managed Kubernetes control plane (AWS manages control plane components) Why managed services matter economically: lower labor/operations cost faster time-to-market improved reliability through standardized managed components ✅ Quick Exam-Style Summary Cloud shifts you from fixed costs (CapEx-heavy on-prem) to variable costs (pay for usage). On-prem costs include facilities, power/cooling, security, IT labor, maintenance, and overprovisioning. Licensing: BYOL = reuse existing licenses; included = simpler, bundled licensing cost. Rightsizing reduces waste by matching resources to actual needs. Automation (e.g., CloudFormation) improves speed and consistency, reducing errors and ops effort. Managed services (RDS, ECS/EKS, DynamoDB) reduce operational overhead and can lower total cost. Additional Resources Introduction to AWS Economics The Business Value of AWS The Business Value of Migrating to AWS Exam Guide: Cloud Practitioner (22 Part Series) 1 Cloud Practitioner Exam Guide 2 Define the Benefits of the AWS Cloud ... 18 more parts... 3 Identify Design Principles of the AWS Cloud 4 Understand the Benefits of and Strategies for Migration to the AWS Cloud 5 Understand Concepts of Cloud Economics 6 Understand the AWS Shared Responsibility Model 7 Understand AWS Cloud Security, Governance, and Compliance Concepts 8 Identify AWS Access Management Capabilities 9 Identify Components and Resources for Security 10 Define Methods of Deploying and Operating in the AWS Cloud 11 Define the AWS Global Infrastructure 12 Identify AWS Compute Services 13 Identify AWS Database Services 14 Identify AWS Network Services 15 Identify AWS Storage Services 16 Identify AWS Artificial Intelligence and Machine Learning (AI/ML) Services And Analytics Services 17 Identify Services From Other In-Scope AWS Service Categories 18 Compare AWS Pricing Models 19 Understand Resources For Billing, Budget, and Cost Management 20 Identify AWS Technical Resources And AWS Support Options 21 Technologies and Concepts: Cloud Practitioner (CLF-C02) 22 My Cloud Practitioner Certification Journey and the Resources to Certify with Confidence Top comments (0) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. 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https://dev.to/alexanderhodes/xcode-cloud-build-fails-due-command-exited-with-non-zero-exit-code-70-6aj#investigating-it-further | XCode Cloud Build fails due Command exited with non-zero exit-code: 70 - 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 Alexander Hodes Posted on Jan 12 XCode Cloud Build fails due Command exited with non-zero exit-code: 70 # appdev # ios # cicd Back from vacation and some days after the new year started our build pipeline for the iOS app in Xcode Cloud fails. The xcodebuild command still succedded but the signing of the app for ad-hoc and app-store distribution failed with Command exited with non-zero exit-code: 70 That's a snippet from the log. Run command: 'xcodebuild -exportArchive -archivePath /Volumes/workspace/tmp/3dbe9cdf-8b26-4d08-98fc-ec820978e845.xcarchive -exportPath /Volumes/workspace/adhocexport -exportOptionsPlist /Volumes/workspace/ci/ad-hoc-exportoptions.plist '-DVTPortalRequest.Endpoint=http://172.16.47.196:8089' -DVTProvisioningIsManaged=YES -IDEDistributionLogDirectory=/Volumes/workspace/tmp/ad-hoc-export-archive-logs -DVTSkipCertificateValidityCheck=YES -DVTServicesLogLevel=3' Error Command exited with non-zero exit-code: 70 Enter fullscreen mode Exit fullscreen mode Some background why we use Xcode cloud. At the beginning of last year, we've migrated from Azure Devops to Xcode Cloud because the build of the iOS version of our React Native app took about one hour. For internal testing we push the distribute the app by Firebase App Distribution . The migration was pretty easy using some additional steps in the iOS build process with the custom build scripts . With using XCode cloud the build time decreased by more than 50%. Investigating it further During the vacation days nothing has changed. Our workflow was still the same and there weren't any code changes which could lead to the problem. Therefore the only reason could be expired certificates or provisioning profiles. Unfortunately, there were no certificates expired or revoked. One important artifact of every build in XCode cloud is the Log file which contains the logs of the xcodebuild and signing steps. After comparing the logs for signing from the failed with the last successful one something weird was visible. The request for requesting the DVTServices: Response payload didn't contain any certificates. 2026-01-12T12:23:16.992744779Z 2025-12-23 06:56:24.555 xcodebuild[26013:105669] DVTServices: Response payload: { 2026-01-12T12:23:16.992747015Z "data" : [] 2026-01-12T12:23:16.992808870Z "links" : { 2026-01-12T12:23:16.992811619Z "self" : "https://developer-ci.corp.apple.com:443/services/v1/certificates?filter%5BcertificateType%5D=DISTRIBUTION_MANAGED&limit=200" 2026-01-12T12:23:16.992814240Z }, 2026-01-12T12:23:16.992816002Z "meta" : { 2026-01-12T12:23:16.992817707Z "paging" : { 2026-01-12T12:23:16.992819465Z "total" : 1, 2026-01-12T12:23:16.992821323Z "limit" : 200 2026-01-12T12:23:16.992823022Z } 2026-01-12T12:23:16.992824692Z } 2026-01-12T12:23:16.992826793Z } Enter fullscreen mode Exit fullscreen mode In the last successful run, there was one included. 2025-12-23T14:56:24.992744779Z 2025-12-23 06:56:24.555 xcodebuild[26013:105669] DVTServices: Response payload: { 2025-12-23T14:56:24.992747015Z "data" : [ { 2025-12-23T14:56:24.992749303Z "type" : "certificates", 2025-12-23T14:56:24.992751380Z "id" : "id", 2025-12-23T14:56:24.992753249Z "attributes" : { 2025-12-23T14:56:24.992755418Z "serialNumber" : "abc", 2025-12-23T14:56:24.992773108Z "certificateContent" : "", 2025-12-23T14:56:24.992784914Z "displayName" : "Company Name", 2025-12-23T14:56:24.992787108Z "name" : "Apple Distribution: Company Name", 2025-12-23T14:56:24.992789263Z "platform" : null, 2025-12-23T14:56:24.992791524Z "responseId" : "136ed97e-949c-428b-b0a3-c5513e2cfacc", 2025-12-23T14:56:24.992793996Z "expirationDate" : "2026-04-07T08:06:15.000+00:00", 2025-12-23T14:56:24.992796344Z "certificateType" : "DISTRIBUTION_MANAGED" 2025-12-23T14:56:24.992798263Z }, 2025-12-23T14:56:24.992800337Z "links" : { 2025-12-23T14:56:24.992802983Z "self" : "https://developer-ci.corp.apple.com:443/services/v1/certificates/abc" 2025-12-23T14:56:24.992805363Z } 2025-12-23T14:56:24.992807115Z } ], 2025-12-23T14:56:24.992808870Z "links" : { 2025-12-23T14:56:24.992811619Z "self" : "https://developer-ci.corp.apple.com:443/services/v1/certificates?filter%5BcertificateType%5D=DISTRIBUTION_MANAGED&limit=200" 2025-12-23T14:56:24.992814240Z }, 2025-12-23T14:56:24.992816002Z "meta" : { 2025-12-23T14:56:24.992817707Z "paging" : { 2025-12-23T14:56:24.992819465Z "total" : 1, 2025-12-23T14:56:24.992821323Z "limit" : 200 2025-12-23T14:56:24.992823022Z } 2025-12-23T14:56:24.992824692Z } 2025-12-23T14:56:24.992826793Z } Enter fullscreen mode Exit fullscreen mode Solving the signing issue Solving this issue is much simpler than expected. In the Apple Developer Portal you need to open the Certificates, Identifiers & Profiles section. There some certificates created by Xcode Cloud will appear. These certificates are created automatically by Xcode Cloud when starting a workflow. You just need to revoke those certificates by clicking on revoke in the detail view of the certificate. After the deletion of these certificates, you can trigger your workflows again. The signing for ad-hoc and app-store distribution should work and new certificates should be generated. The reason for this issue might be that Apple internally generates some private keys which will expire or will be deleted due to the end of the year. 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 Alexander Hodes Follow Location Fulda, Germany Work Fullstack Developer Joined Jan 24, 2021 Trending on DEV Community Hot How to Crack Any Software Developer Interview in 2026 (Updated for AI & Modern Hiring) # softwareengineering # programming # career # interview What was your win this week??? # weeklyretro # discuss I Didn’t “Become” a Senior Developer. I Accumulated Damage. # programming # ai # career # discuss 💎 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 | 2026-01-13T08:49:46 |
https://www.medicalnewstoday.com/articles/untreated-glaucoma | Untreated glaucoma: Consequences, progression, and outlook Medical News Today Health Conditions Health Conditions Alzheimer's & Dementia Anxiety Asthma & Allergies Atopic Dermatitis Breast Cancer Cancer Cardiovascular Health COVID-19 Diabetes Endometriosis Environment & Sustainability Exercise & Fitness Eye Health Headache & Migraine Health Equity HIV & AIDS Human Biology Leukemia LGBTQIA+ Men's Health Mental Health Multiple Sclerosis (MS) Nutrition Parkinson's Disease Psoriasis Sexual Health Ulcerative Colitis Women's Health Health Products Health Products All Nutrition & Fitness Vitamins & Supplements CBD Sleep Mental Health At-Home Testing Men’s Health Women’s Health Discover News Latest News Medicare 2026 Costs Original Series Medical Myths Honest Nutrition Through My Eyes New Normal Health Podcasts All Artificial sweeteners and brain aging: What we know so far Does the Mediterranean diet hold the key to longevity? 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Medically reviewed by Vicente Diaz, MD, MBA — Written by Caitlin Geng on May 21, 2024 Without treatment Progression rate Treatment options Contacting a doctor FAQ Summary Without treatment, glaucoma can cause irreversible, progressive vision loss and blindness. The progression rate may depend on the type of glaucoma someone has. Glaucoma is a progressive condition that occurs when pressure builds up in the eye. There is no cure for glaucoma, but treatment can help people manage the symptoms and avoid further complications. Increasing eye pressure can lead to irreversible damage to the optic nerve without treatment. This article explains what happens if a person does not receive treatment for glaucoma, its progression rate, treatment options, and when to contact a doctor. What happens if someone does not treat glaucoma? Share on Pinterest Monty Rakusen/Getty Images The most common type of glaucoma is open-angle glaucoma (OAG). In this type, the eye does not drain fluid effectively, causing a buildup of pressure. Over time, the pressure can damage the optic nerve. Closed-angle glaucoma (CAG) occurs less often. In this type of glaucoma, the iris of the eye is close to the drainage angle, through which eye fluid drains. The iris may block the drainage angle and cause a rapid buildup of eye pressure. Both types of glaucoma involve damage to the optic nerve, which can lead to vision loss and blindness . Around 10% of people with glaucoma experience some vision impairment. Typically , vision loss from glaucoma first affects a person’s peripheral vision . As the condition progresses, it may affect their central vision, which a person requires for daily tasks such as driving and reading. Glaucoma is especially prevalent in older adults. In 2020, the condition accounted for 11% of global blindness in adults ages 50 years and older. Treatment cannot reverse damage to the optic nerve due to glaucoma. However, according to a 2023 overview article on glaucoma, it can help slow and prevent further damage. Without treatment, glaucoma will progress. Over time, the condition can cause severe vision impairment and even blindness. Early diagnosis and treatment may help significantly minimize damage to the optic nerve, and vision loss. Learn about open-vs. closed-angle glaucoma. How quickly does glaucoma progress? OAG typically progresses gradually and may not cause vision loss for several years . With treatment, individuals often retain satisfactory vision as long as 20 years after their OAG diagnosis. However, any vision loss that occurs is irreversible, so treating slow progression can still be beneficial. CAG can also develop gradually and without noticeable symptoms, which may mean that people do not realize they have glaucoma until the damage is severe. CAG can result in sudden attacks of acute glaucoma . An attack of acute glaucoma is a medical emergency and can result in permanent and irreversible vision loss within hours or days . Learn more about acute angle-closure glaucoma . Treatment options for glaucoma A person should seek treatment for glaucoma as soon as possible to help delay the progression of the condition and prevent further damage. Treatment for glaucoma can differ depending on the type and severity of the condition. Available options may include : Medicated eye drops: A doctor may prescribe medicated eye drops to help reduce eye pressure. These may help treat glaucoma by helping fluid flow through the drainage angle more effectively or reducing fluid production in the eye. Laser surgery: Laser surgery can help drain fluid from the eye to reduce pressure. Types include trabeculoplasty, which improves the drainage angle in people with OAG, and iridotomy, which creates a small hole in the iris for fluid drainage in people with CAG. Surgery: Some types of surgery for glaucoma occur in an operating room. This may include fitting drainage devices, cataract surgery to improve the drainage channel, and trabeculectomy , which creates a tiny flap in the sclera. Learn more about treatment options for glaucoma . When to contact a doctor Early diagnosis and treatment can significantly reduce a person’s risk of further vision loss and blindness. If a person experiences any signs or symptoms of glaucoma, they should contact a doctor. These can include: blurred vision changes in peripheral vision blind spots If a person experiences acute glaucoma symptoms, they should seek immediate emergency medical care at the nearest emergency room or call 911. Symptoms may include: intense eye pain seeing rainbow-colored haloes around lights redness in the eye blurred vision a headache nausea and vomiting Learn about the different types of eye doctors and what they do . Risk factors A person should attend regular eye exams even if they do not have symptoms of glaucoma or other eye problems. Individuals can also request a comprehensive dilated eye exam to help doctors diagnose glaucoma early. People with a higher risk of glaucoma than the larger population can contact a doctor to request a glaucoma test. High risk groups include : people with a family history of glaucoma people with diabetes African American people ages 40 and older all people ages 60 years and older Learn about tests for glaucoma . Frequently asked questions Below are the answers to some frequently asked questions about glaucoma. What is the life expectancy of a person with glaucoma? Researchers do not associate glaucoma with a higher risk of mortality, and a person with the condition typically has the same life expectancy as the larger population. What causes glaucoma to worsen? Various medications can increase eye pressure and worsen glaucoma, including steroids and many cold and flu medications that contain decongestants and antihistamines . People with glaucoma should speak with a healthcare professional to determine which medications they should avoid depending on their type of glaucoma. Can someone live with glaucoma without going blind? Only a small number of people who have glaucoma experience complete blindness as a result of the condition. Many people with glaucoma retain their vision and can see quite well, especially if they receive treatment. Summary Glaucoma is a condition in which pressure in the eye damages the optic nerve. Without treatment, it can progress to more severe vision loss and blindness. There is no cure for glaucoma, but treatment can help slow its progression and prevent further complications. Early diagnosis and treatment can minimize damage to the optic nerve. A person can lower the risk of vision loss from glaucoma by attending regular eye exams. Individuals who experience symptoms of glaucoma should contact a doctor. Eye health resources Visit our dedicated hub for more research-backed information and in-depth resources on eye health . Eye Health / Blindness Preventive Medicine How we reviewed this article: Sources Medical News Today has strict sourcing guidelines and relies on peer-reviewed studies, academic research institutions, and medical journals and associations. We only use quality, credible sources to ensure content accuracy and integrity. You can learn more about how we ensure our content is accurate and current by reading our editorial policy . Boyd K. (2023). What is glaucoma? Symptoms, causes, diagnosis, treatment. https://www.aao.org/eye-health/diseases/what-is-glaucoma Don’t let glaucoma steal your sight! (2020). https://www.cdc.gov/visionhealth/resources/features/glaucoma-awareness.html Causes of blindness and vision impairment in 2020 and trends over 30 years, and prevalence of avoidable blindness in relation to VISION 2020: The Right to Sight: An analysis for the Global Burden of Disease Study. (2020). https://www.thelancet.com/journals/langlo/article/PIIS2214-109X(20)30489-7/fulltext Glaucoma. (2023). https://www.nei.nih.gov/learn-about-eye-health/eye-conditions-and-diseases/glaucoma Khazaeni B, et al. (2023). Acute angle-closure glaucoma. https://www.ncbi.nlm.nih.gov/books/NBK430857/ Kühn T, et al. (2021). Glaucoma and mortality risk: Findings from a prospective population-based study. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8175711/ Mukamal R. (2023). Common drugs that can worsen glaucoma. https://www.aao.org/eye-health/tips-prevention/dangerous-medications-glaucoma-dayquil-bendadryl Overview: Glaucoma. (2023). https://www.ncbi.nlm.nih.gov/books/NBK367579/ Sheybani A, et al. (2019). Open-angle glaucoma: Burden of illness, current therapies, and the management of nocturnal IOP variation. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7054505/ Share this article Medically reviewed by Vicente Diaz, MD, MBA — Written by Caitlin Geng on May 21, 2024 Latest news Many Brazilians live past 110: What are their secrets? Exercise may reduce depression symptoms as effectively as therapy Seasonal slump or mental health myth? The truth about Blue Monday Restoring missing lipid may help ease dementia damage in brain, study finds Experimental drug reverses Alzheimer's in mice Related Coverage Macular degeneration vs. glaucoma: What to know AMD and glaucoma can both lead to vision loss. Read on for the symptoms and risk factors, the differences between each eye condition, preventions, and… READ MORE What does glaucoma vision look like? People with glaucoma may experience changes to their vision. These can include blurriness, blind spots, and tunnel vision. Learn more here. READ MORE What is the outlook for someone with glaucoma? Medically reviewed by Vicente Diaz, MD, MBA Glaucoma is not life threatening. However, without treatment, it can cause progressive vision loss and blindness. Learn the outlook and more here. READ MORE What are some natural treatments for glaucoma? Medically reviewed by Leela Raju, MD Natural remedies for glaucoma include a whole food diet, herbal supplements, and certain lifestyle measures. These can complement prescribed… READ MORE © 2026 Healthline Media UK Ltd, London, UK. All rights reserved. MNT is the registered trade mark of Healthline Media. Healthline Media is an RVO Health Company. Any medical information published on this website is not intended as a substitute for informed medical advice and you should not take any action before consulting with a healthcare professional. See additional information . About Us Contact Us Terms of Use Privacy Policy Privacy Settings Advertising Policy Health Topics Health Hubs Medical Affairs Content Integrity Newsletters © 2026 Healthline Media UK Ltd, London, UK. All rights reserved. MNT is the registered trade mark of Healthline Media. Healthline Media is an RVO Health Company. Any medical information published on this website is not intended as a substitute for informed medical advice and you should not take any action before consulting with a healthcare professional. See additional information . © 2026 Healthline Media UK Ltd, London, UK. All rights reserved. MNT is the registered trade mark of Healthline Media. Healthline Media is an RVO Health Company. Any medical information published on this website is not intended as a substitute for informed medical advice and you should not take any action before consulting with a healthcare professional. See additional information . 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Report Abuse Ntombizakhona Mabaso for AWS Community Builders Posted on Jan 6 Identify AWS Artificial Intelligence and Machine Learning (AI/ML) Services And Analytics Services # aws # cloud # cloudcomputing # cloudpractitioner Exam Guide: Cloud Practitioner (22 Part Series) 1 Cloud Practitioner Exam Guide 2 Define the Benefits of the AWS Cloud ... 18 more parts... 3 Identify Design Principles of the AWS Cloud 4 Understand the Benefits of and Strategies for Migration to the AWS Cloud 5 Understand Concepts of Cloud Economics 6 Understand the AWS Shared Responsibility Model 7 Understand AWS Cloud Security, Governance, and Compliance Concepts 8 Identify AWS Access Management Capabilities 9 Identify Components and Resources for Security 10 Define Methods of Deploying and Operating in the AWS Cloud 11 Define the AWS Global Infrastructure 12 Identify AWS Compute Services 13 Identify AWS Database Services 14 Identify AWS Network Services 15 Identify AWS Storage Services 16 Identify AWS Artificial Intelligence and Machine Learning (AI/ML) Services And Analytics Services 17 Identify Services From Other In-Scope AWS Service Categories 18 Compare AWS Pricing Models 19 Understand Resources For Billing, Budget, and Cost Management 20 Identify AWS Technical Resources And AWS Support Options 21 Technologies and Concepts: Cloud Practitioner (CLF-C02) 22 My Cloud Practitioner Certification Journey and the Resources to Certify with Confidence 📊 Exam Guide: Cloud Practitioner Domain 3: Cloud Technology & Services 📘 Task Statement 3.7 🎯 What Is This Task Testing? You need to recognize common AWS services for: AI/ML and what each service is used for (SageMaker, Lex, Kendra) Analytics and when to use each service (Athena, Kinesis, Glue, QuickSight) 1) 🤖 AWS AI/ML Services Amazon SageMaker A managed service to build, train, and deploy machine learning models . Use Amazon Sagemaker When: you need an end-to-end ML platform ( data prep, training, tuning, deployment ) you want to manage ML workflows without building all tooling yourself “train a model,” “deploy an ML model,” “ML lifecycle” → SageMaker . Amazon Lex A service for building chatbots and conversational interfaces (text and voice). Use Amazon Lex When: you want a chatbot for customer support, internal help desk, or booking flows you need natural language understanding for conversation-style interfaces “chatbot,” “conversational interface,” “voice/text bot” → Lex . Amazon Kendra An intelligent search service for searching across large volumes of content (documents, knowledge bases). Use Amazon Kendra When: you want enterprise search across documents and internal data sources you need more “meaning-based” search than basic keyword matching “search documents/knowledge base,” “enterprise search” → Kendra . 2) 🗺️ AWS Analytics Services Ingestion → ETL → Query → Visualization A helpful way to remember analytics services is by the stage they support. Amazon Kinesis: Streaming Ingestion/Processing A platform for real-time streaming data . Use Amazon Kinesis When: you need to ingest or process data continuously (clickstreams, IoT telemetry, logs) you need near-real-time analytics “real-time streams,” “ingest streaming data” → Kinesis . AWS Glue: ETL and Data Integration A managed service for ETL (extract, transform, load) and data preparation. Use AWS Glue When: you need to clean/transform and move data between sources and targets you need a managed data integration/ETL service “ETL,” “transform data,” “prepare data for analytics” → Glue . Amazon Athena: Query Data in S3 Using SQL A serverless query service that lets you analyze data in Amazon S3 using SQL . Use Amazon Athena When: you want ad-hoc queries without managing servers your data is already in S3 and you want SQL-based analysis “query S3 with SQL,” “serverless interactive queries” → Athena . Amazon QuickSight: Visualization / BI A business intelligence service for dashboards and data visualization . Use Amazon QuickSight When: you want interactive dashboards and reporting for stakeholders you need BI-style visual analytics “dashboards,” “visualize data,” “BI reporting” → QuickSight . “Match the Service” “Build/train/deploy ML models” → SageMaker “Create a chatbot” → Lex “Search across documents/knowledge bases” → Kendra “Ingest streaming data in real time” → Kinesis “ETL / data preparation” → Glue “Run SQL queries directly on S3” → Athena “Build dashboards and visual reports” → QuickSight ✅ Quick Exam-Style Summary AI/ML: SageMaker ( ML platform ), Lex ( chatbots ), Kendra ( intelligent search ). Analytics: Kinesis ( streaming ), Glue ( ETL ), Athena ( SQL on S3 ), QuickSight ( dashboards ). Additional Resources Analytics Machine Learning (ML) and Artificial Intelligence (AI) Exam Guide: Cloud Practitioner (22 Part Series) 1 Cloud Practitioner Exam Guide 2 Define the Benefits of the AWS Cloud ... 18 more parts... 3 Identify Design Principles of the AWS Cloud 4 Understand the Benefits of and Strategies for Migration to the AWS Cloud 5 Understand Concepts of Cloud Economics 6 Understand the AWS Shared Responsibility Model 7 Understand AWS Cloud Security, Governance, and Compliance Concepts 8 Identify AWS Access Management Capabilities 9 Identify Components and Resources for Security 10 Define Methods of Deploying and Operating in the AWS Cloud 11 Define the AWS Global Infrastructure 12 Identify AWS Compute Services 13 Identify AWS Database Services 14 Identify AWS Network Services 15 Identify AWS Storage Services 16 Identify AWS Artificial Intelligence and Machine Learning (AI/ML) Services And Analytics Services 17 Identify Services From Other In-Scope AWS Service Categories 18 Compare AWS Pricing Models 19 Understand Resources For Billing, Budget, and Cost Management 20 Identify AWS Technical Resources And AWS Support Options 21 Technologies and Concepts: Cloud Practitioner (CLF-C02) 22 My Cloud Practitioner Certification Journey and the Resources to Certify with Confidence Top comments (0) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. 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https://discuss.opensource.org/t/open-source-ai-impact-japan-s-draft-principle-code-comments-open-until-jan-26-jst/1354 | Open Source AI Impact: Japan’s Draft “Principle-Code” (Comments open until Jan 26 JST) - Open Source AI - OSI Discuss OSI Discuss Open Source AI Impact: Japan’s Draft “Principle-Code” (Comments open until Jan 26 JST) Open Source AI news shujisado January 10, 2026, 6:37am 1 Hello OSI community, I am writing from Japan to flag an ongoing public consultation by the Cabinet Office of Japan. The Cabinet Office has published a draft “Principle-Code for Protection of Intellectual Property and Transparency for the Appropriate Use of Generative AI” (provisional title), and is currently accepting public comments. Call to action (deadline): Public comments are open until January 26, 2026, 23:59 Japan time (JST) . Submissions are accepted in English as well as Japanese. Why this matters outside Japan The draft explicitly says it applies even if a business does not have its head office in Japan, as long as the generative AI system or service is provided to Japan (including when it is available to Japanese nationals). This is why Open Source developers and global service providers should pay attention. What in the draft could affect Open Source and global providers 1) Very broad scope of “developer” and “provider”. A “generative AI developer” is defined broadly as someone responsible for building a “generative AI system”, including a model and the system infrastructure of the model, plus related components, and who provides all or part of that system to the public. Depending on interpretation, this could create uncertainty not only for model publishers, but also for projects and platforms in the wider ecosystem. 2) “Comply or explain”, but with publication and annual updates. Businesses that accept the principles are expected to publish an acceptance statement and the implementation status for each principle on their corporate website, submit the same to the Cabinet Office in a prescribed format, and update it annually. The Cabinet Office plans to publish a list of submitters and links. The draft also anticipates government incentives based on disclosures and initiatives, which can turn a voluntary code into a practical requirement over time. 3) Deep transparency expectations (including crawling practices). The accompanying “specific examples” document includes disclosures such as crawler purpose, collection period, crawler identifiers, and whether third-party crawlers are used. It also includes respecting paywalls and robots.txt, publishing measures with user agents, and notifying changes. It further references retention of learning logs and traceability practices as examples. 4) Disclosure request frameworks (Principle 2 and Principle 3). Under Principle 2, the draft contemplates responding to requests that include disclosure of certain “control information” (for example, whether training/validation data includes URLs queried by the AI business). It also states that even if requested matters are considered trade secrets, businesses are expected to first seriously consider and discuss the matter. Principle 3 similarly contemplates requests by users, with the prompt and generated output provided, and requests related to URLs that host allegedly similar content. 5) The “Open Source” exception may not reduce the burden in practice. The draft provides an exception where disclosure is difficult due to the use of Open Source software, allowing a form of substitute disclosure by clarifying the use of Open Source software and license details. However, this may not meaningfully reduce uncertainty for Open Source AI projects. In particular, projects that already publish model weights, training data, or other artifacts may still be expected to provide additional “control information” and explanations in a prescribed format. This could unintentionally impose a higher operational burden on the most transparent projects, and may discourage publication or distribution to users in Japan. What you might comment on If you publish open-weight models, operate generative AI services reachable from Japan, or participate in dataset/crawling pipelines, you may want to comment on: Clearer scope boundaries and exclusions, so foundational tooling and community projects are not unintentionally captured. Proportionality for small developers, researchers, and community-led efforts. Stronger safeguards for trade secrets and practical limits on “control information” disclosure. A clearer and workable Open Source safe harbor that reduces uncertainty, not just a label. Below are the official documents and the submission form. Public comment guidance (JP) / includes deadline and says English submissions are accepted https://public-comment.e-gov.go.jp/pcm/download?seqNo=0000304677 Principle-Code (draft) English PDF (provisional translation) https://public-comment.e-gov.go.jp/pcm/download?seqNo=0000304679 Specific examples of disclosures (English PDF) https://public-comment.e-gov.go.jp/pcm/download?seqNo=0000304681 Submission form (JP UI, English text accepted) form.cao.go.jp 内閣府共通意見等登録システム - 内閣府 内閣府のホームページです。内閣府の組織、政策、報道発表資料、統計・調査などに関する情報を掲載しています。 Thank you for taking a look, and for sharing this with relevant Open Source projects and providers. Chairman of Open Source Group Japan Shuji Sado 2 Likes nick January 10, 2026, 2:53pm 2 Thank you @shujisado -san. I’ll be sharing this in our newsletter. 1 Like shujisado January 12, 2026, 3:11am 3 As an additional practical lens, consider two edge cases that are common in the Open Source AI ecosystem. If we assume Hugging Face is only a distribution platform (not a model developer), and PyTorch is only a system infrastructure project (not an AI service operator), “comply or explain” style adherence could still translate into real operational duties: Common baseline (both): publish an acceptance statement, disclose implementation status (or explanations), submit in the government’s format, and update annually. Hugging Face as a distributor: Require uploaders to provide structured disclosures (model cards and metadata) to meet deep transparency expectations, or publicly “explain” gaps at scale. Establish and operate an intake process for rights-holder and user disclosure requests, including verification, anti-abuse controls, record-keeping, and response timelines. When the platform cannot answer, it may be pushed to identify and disclose the responsible developer/provider to route the request. PyTorch as infrastructure: Even if it cannot possess training data, crawling details, or learning logs, it would still be expected to publish clear “not applicable / not held” explanations and boundaries. Set up contact points and documentation for disclosure requests, while stating that relevant “control information” resides with downstream model developers or service operators. This is why the draft may have a disproportionate impact on Open Source AI distribution and infrastructure, not just on large commercial model providers. If your project or service is reachable from Japan, submitting a comment before the deadline matters. Home Categories Guidelines Terms of Service Privacy Policy Powered by Discourse , best viewed with JavaScript enabled | 2026-01-13T08:49:46 |
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