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Stack walk profiling NodeJS in Windows

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Last year I wrote a series of blog posts (1, 2, 3) about stack walk profiling Chromium using Windows native tools around ETW.

A fast recap: ETW support for stack walking in V8 allows to show V8 JIT generated code in the Windows Performance Analyzer. This is a powerful tool to analyze work loads where Javascript execution time is significant.

In this blog post, I will cover the usage of this very same tool, but to analyze NodeJS execution.

Enabling stack walk JIT information in NodeJS

In an ideal situation, V8 engines would always generate stack walk information when Windows is profiling. This is something we will want to consider in the future, as we prove enabling it has no cost if we are not in a tracing session.

Meanwhile, we need to set the V8 flag --enable-etw-stack-walking somehow. This will install hooks that, when a profiling session starts, will emit the JIT generated code addresses, and the information about the source code associated to them.

For a command line execution of NodeJS runtime, it is as simple as passing the command line flag:

node --enable-etw-stack-walking

This will work enabling ETW stack walking for that specific NodeJS session… Good, but not very useful.

Enabling ETW stack walking for a session

What’s the problem here? Usually, NodeJS is invoked indirectly through other tools (based or not in NodeJS). Some examples are Yarn, NPM, or even some Windows scripts or link files.

We could tune all the existing launching scripts to pass --enable-etw-stack-walking to the NodeJS runtime when it is called. But that is not much convenient.

There is a better way though, just using NODE_OPTIONS environment variable. This way, stack walking support can be enabled for all NodeJS calls in a shell session, or even system wide.

Bad news and good news

Some bad news: NodeJS was refusing --enable-etw-stack-walking in NODE_OPTIONS. There is a filter for which V8 options it accepts (mostly for security purposes), and ETW support was not considered.

Good news? I implemented a fix adding the flag to the list accepted by NODE_OPTIONS. It has been landed already, and it is available from NodeJS 19.6.0. Unfortunately, if you are using an older version, then you may need to backport the patch.

Using it: linting TypeScript

To explain how this can be used, I will analyse ESLint on a known workload: TypeScript. For simplicity, we are using the lint task provided by TypeScript.

This example assumes the usage of Git Bash.

First, clone TypeScript from GitHub, and go to the cloned copy:

git clone https://github.com/microsoft/TypeScript.git
cd TypeScript

Then, install hereby and the dependencies of TypeScript:

npm install -g hereby
npm ci

Now, we are ready to profile the lint task. First, set NODE_OPTIONS:

export NODE_OPTIONS="--enable-etw-stack-walking"

Then, launch UIForETW. This tool simplifies capturing traces, and will provide good defaults for Javascript ETW analysis. It provides a very useful keyboard shortcut, <Ctrl>+<Win>+R, to start and then stop a recording.

Switch to Git Bash terminal and do this sequence:

  • Write (without pressing <Enter>): hereby lint
  • Press <Ctrl>+<Win>+R to start recording. Wait 3-4 seconds as recording does not start immediately.
  • Press <Enter>. ESLint will traverse all the TypeScript code.
  • Press again <Ctrl>+<Win>+R to stop recording.

After a few seconds UIForETW will automatically open the trace in Windows Performance Analyzer. Thanks to settings NODE_OPTIONS all the child processes of the parent node.exe execution also have stack walk information.

Randomascii inclusive (stack) analysis

Focusing on node.exe instances, in Randomascii inclusive (stack) view, we can see where time is spent for each of the node.exe processes. If I take the bigger one (that is the longest of the benchmarks I executed), I get some nice insights.

The worker threads take 40% of the CPU processing. What is happening there? I basically see JIT compilation and garbage collection concurrent marking. V8 offloads that work, so there is a benefit from a multicore machine.

Most of the work happens in the main thread, as expected. And most of the time is spent parsing and applying the lint rules (half for each).

If we go deeper in the rules processing, we can see which rules are more expensive.

Memory allocation

In total commit view, we can observe the memory usage pattern of the process running ESLint. For most of the seconds of the workload, allocation grows steadily (to over 2GB of RAM). Then there is a first garbage collection, and a bit later, the process finishes and all the memory is deallocated.

More findings

At first sight, I observe we are creating the rules objects for all the execution of ESLint. What does it mean? Could we run faster reusing those? I can also observe that a big part of the time in main thread leads to leaves doing garbage collection.

This is a good start! You can see how ETW can give you insights of what is happening and how much time it takes. And even correlate that to memory usage, File I/O, etc.

Builtins fix

Using NodeJS, as is today, will still show many missing lines in the stack. I did those tests, and could do a useful analysis, because I applied a very recent patch I landed in V8.

Before the fix, we would have this sequence:

  • Enable ETW recording
  • Run several NodeJS tests.
  • Each of the tests creates one or more JS contexts.
  • That context then sends to ETW the information of any code compiled with JIT.

But there was a problem: any JS context has already a lot of pre-compiled code associated: builtins and V8 snapshot code. Those were missing from the ETW traces captured.

The fix, as said, has been already landed to V8, and hopefully will be available soon in future NodeJS releases.

Wrapping up

There is more work to do:

  • WASM is still not supported.
  • Ideally, we would want to have --enable-etw-stack-walking set by default, as the impact while not tracing is minimal.

In any case, after these new fixes, capturing ETW stack walks of code executed by NodeJS runtime is a bit easier. I hope this gives some joy to your performance research.

One last thing! My work for these fixes is possible thanks to the sponsorship from Igalia and Bloomberg.

Igalia

Native call stack profiling (3/3): 2022 work in V8

This is the last blog post of the series. In first post I presented some concepts of call stack profiling, and why it is useful. In second post I reviewed Event Tracing for Windows, the native tool for the purpose, and how it can be used to trace Chromium.

This last post will review the work done in 2022 to improve the support in V8 of call stack profiling in Windows.

I worked on several of the fixes this year. This work has been sponsored by Bloomberg and Igalia.

This work was presented as a lightning talk in BlinkOn 17.

Some bad news to start… and a fix

In March I started working on the report that Windows event traces where not properly resolving the Javascript symbols.

After some bisecting I found this was a regression introduced by this commit, that changed the --js-flags handling to a later stage. This happened to be after V8 initialization, so the code that would enable instrumentation would not consider the flag.

The fix I implemented moved flags processing to happen right before platform initialization, so instrumentation worked again.

Simplified method names

Another fix I worked was to improve the methods name generation. Windows tracing would show a quite redundant description of each level, and that was making analysis more difficult.

Before my work, the entries would look like this:

string-tagcloud.js!LazyCompile:~makeTagCloud- string-tagcloud.js:231-232:22 0x0

After my change, now it looks like this:

string-tagcloud.js!makeTagCloud-231:22 0x0

The fix adds a specific implementation for ETW. Instead of reusing the method name that is also used for Perf, it has a specific implementation for function that takes into account what ETW backend exports already, to avoid redundancy. It also takes advantage of the existing method DebugNameCStr to retrieve inferred method names in case there is no name available.

Problem with Javascript code compiled before tracing

The way V8 ETW worked was that, when tracing was ongoing and a new function was compiled in JIT, it would emit information to ETW.

This implied a big problem. If a function was compiled by V8 before tracing started, then ETW would not properly resolve the function names so, when analyzing the traces, it would not be possible to know which function was called at any of the samples.

The solution is conceptually simple. When tracing starts, V8 traverse the living Javascript contexts and emit all the symbols. This adds noise to the tracing, as it is an expensive process. But, as it happens at the start of the tracing, it is very easy to isolate in the captured trace.

And a performance fix

I also fixed a huge performance penalty when tracing code from snapshots, caused by calculating all the time the end line numbers of code instead of caching it.

Initialization improvements

Paolo Severini improved the initialization code, so the initialization of an ETW session was lighter, and also tracing would be started or stopped correctly.

Benchmarking ETW overhead

After all these changes I did some benchmarking with and without ETW. The goal was knowing if it would be good to enable by default ETW support in V8, not requiring to pass any JS flag.

With Sunspider in a Windows 64 bits build:

Image showing slight overhead with ETW and bigger one with interpreted frames.

Other benchmarks I tried gave similar numbers.

So far, in 64 bits architecture I could not detect any overhead of enabling ETW support when recording is not happening, and the cost when it is enabled is very low.

Though, when combined with interpreted frames native stack, the overhead is close to 10%. This was expected as explained here.

So, good news so far. We still need to benchmark 32 bit architecture to see if the impact is similar.

Try it!

The work described in this post is available in V8 10.9.0. I hope you enjoy the improvements, and specially hope these tools help in the investigation of performance issues around Javascript, in NodeJS, Google Chrome or Microsoft Edge.

What next?

There is still a lot of things to do, and I hope I can continue working on improvements for V8 ETW support next year:

  • First, finishing the benchmarks, and considering to enable ETW instrumentation by default in V8 and derivatives.
  • Add full support for WASM.
  • Bugfixing, as we still see segments missing in certain benchnarmks.
  • Create specific events for when the JIT information of already compiled symbols is sent to ETW, to make it easier to differenciate from the code compiled while recording a trace.

If you want to track the work, keep an eye on V8 issue 11043.

The end

This is the last post in the series.

Thanks to Bloomberg and Igalia for sponsoring my work in ETW Chromium integration improvements!

Igalia

Native call stack profiling (2/3): Event Tracing for Windows and Chromium

In last blog post, I introduced call stack profiling, why it is useful, and how a system wide support can be useful. This new blog post will talk about Windows native call stack tracing, and how it is integrated in Chromium.

Event Tracing for Windows (ETW)

Event Tracing for Windows, usually also named with the acronym ETW, is a Windows kernel based tool that allows to log kernel and application events to a file.

A good description of its architecture is available at Microsoft Learn: About Event Tracing.

Essentially, it is an efficient event capturing tool, in some ways similar to LTTng. Its events recording stage is as lightweight as possible to avoid processing of collected data impacting the results as much as possible, reducing the observer effect.

The main participants are:
– Providers: kernel components (including device drivers) or applications that emit log events.
– Controllers: tools that control when a recording session starts and stops, which providers to record, and what each provider is expected to log. Controllers also decide where to dump the recorded data (typically a file).
– Consumers: tools that can read and analyze the recorded data, and combine with system information (i.e. debugging information). Consumers will usually get the data from previously recorded files, but it is also possible to consume tracing information in real time.

What about call stack profiling? ETW supports call stack sampling, allowing to capture call stacks when certain events happen, and associates the call stack to that event. Bruce Dawson has written a fantastic blog post about the topic.

Chromium call stack profiling in Windows

Chromium provides support for call stack profiling. This is done at different levels of the stack:
– It allows to build with frame pointers, so CPU profile samplers can properly capture the full call stack.
– v8 can generate symbol information for for JIT-compiled code. This is supported for ETW (and also for Linux Perf).

Compilation

In any platform compilation will usually benefit from compiling with the GN flag enable_profiling=true. This will enable frame pointers support. In Windows, it will also enable generation of function information for code generated by V8.

Also, symbol_level=1 should be added at least, so the compilation stage function names are available.

Chrome startup

To enable generation of V8 profiling information in Windows, these flags should be passed to chrome on launch:

chrome --js-flags="--enable-etw-stack-walking --interpreted-frames-native-stack"

--enable-etw-stack-walking will emit information of the functions compiled by V8 JIT engine, so they can be recorded while sampling the stack.

--interpreted-frames-native-stack will show the frames of interpreted code in the native stack, so external profilers as ETW can properly show those in the profiling samples.

Recording

Then, a session of the workload to analyze can be captured with Windows Performance Recorder.

An alternate tool with specific Chromium support, UIForETW can be used too. Main advantage is that it allows to select specific Chromium tracer categories, that will be emitted in the same trace. Its author, Bruce Dawson, has explained very well how to use it.

Analysis

For analysis, the tool Windows Performance Analyzer (WPA) can be used. Both UIForETW and Windows Performance Recorder will offer opening the obtained trace at the end of the capture for analysis.

Before starting analysis, in WPA, add the paths where the .PDB files with debugging information are available.

Then, select Computation/CPU Usage (Sampled):

.

From the available charts, we are interested in the ones providing stackwalk information:

Next

In the last post of this series, I will present the work done in 2022 to improve V8 support for Windows ETW.

Igalia

Native call stack profiling (1/3): introduction

This week I presented a lightning talk in BlinkOn 17. There I talked about the work for improving native stack profiling support
in Windows.

This post starts a series where I will provide more context and details
to the presentation.

Why callstack profiling

First, a definition:

Callstack profiling: a performance analysis tool, that samples periodically the call stacks of all threads, for a specific workload.

Why is it useful? It provides a better undestanding of performance problems, specially if they are caused by CPU-bound bottle necks.

As we sample the full stack for each thread, we are capturing a handful of information:
– Which functions are using more CPU directly.
– As we capture the full stacktrace, we know also which functions involve more CPU usage, even if it is indirectly through the calls they do.

But it is not only useful for CPU waits. It will also capture when a method is waiting for something (i.e. because of networking, or a semaphore).

The provided information is useful for initial analysis of the problem, as it will give a high level view of where time could be spent by the application. But it will also be useful in further stages of the analysis, and even for comparing different implementations and consider possible changes.

How does it work?

For call stack sampling, we need some infrastructure to be able to capture and traverse properly the callstack for each thread.

In compilation stage, information is added for function names and the frame pointers. This allows, for a specific stack, to resolve later the actual names, and even lines of code that are captured.

In runtime stage, function information will be required for generated code. I.e. in a web browser, the Javascript code that is compiled in runtime.

Then, every sample will extract the callstack of all the threads of all the analysed processes. This will happen periodically, at the rate established by the profiling tool.

System wide native callstack profiling

When possible, sampling the call stacks of the full system can be benefitial for the analysis.

First, we may want to include system libraries and other dependencies of our component in the analysis. But also, system analyzers can provide other metrics that can give a better context to the analysed workload (network or CPU load, memory usage, swappiness, …).

In the end, many problems are not bound to a single component, so capturing the interaction with other components can be useful.

Next

In next blog posts in this series, I will present native stack profiling for Windows, and how it is integrated with Chromium.

Igalia, LG SVL

3 events in a month

As part of my job at Igalia, I have been attending 2-3 events per year. My role mostly as a Chromium stack engineer is not usually much demanding regarding conference trips, but they are quite important as an opportunity to meet collaborators and project mates.

This month has been a bit different, as I ended up visiting Santa Clara LG Silicon Valley Lab in California, Igalia headquarters in A Coruña, and Dresden. It was mostly because I got involved in the discussions for the web runtime implementation being developed by Igalia for AGL.

AGL f2f at LGSVL

It is always great to visit LG Silicon Valley Lab (Santa Clara, US), where my team is located. I have been participating for 6 years in the development of the webOS web stack you can most prominently enjoy in LG webOS smart TV.

One of the goals for next months at AGL is providing an efficient web runtime. In LGSVL we have been developing and maintaining WAM, the webOS web runtime. And as it was released with an open source license in webOS Open Source Edition, it looked like a great match for AGL. So my team did a proof of concept in May and it was succesful. At the same time Igalia has been working on porting Chromium browser to AGL. So, after some discussions AGL approved sponsoring my company, Igalia for porting the LG webOS web runtime to AGL.

As LGSVL was hosting the september 2018 AGL f2f meeting, Igalia sponsored my trip to the event.

AGL f2f Santa Clara 2018, AGL wiki CC BY 4.0

So we took the opportunity to continue discussions and progress in the development of the WAM AGL port. And, as we expected, it was quite beneficial to unblock tasks like AGL app framework security integration, and the support of AGL latest official release, Funky Flounder. Julie Kim from Igalia attended the event too, and presented an update on the progress of the Ozone Wayland port.

The organization and the venue were great. Thanks to LGSVL!

Web Engines Hackfest 2018 at Igalia

Next trip was definitely closer. Just 90 minutes drive to our Igalia headquarters in A Coruña.


Igalia has been organizing this event since 2009. It is a cross-web-engine event, where engineers of Mozilla, Chromium and WebKit have been meeting yearly to do some hacking, and discuss the future of the web.

This time my main interest was participating in the discussions about the effort by Igalia and Google to support Wayland natively in Chromium. I was pleased to know around 90% of the work had already landed in upstream Chromium. Great news as it will smooth integration of Chromium for embedders using Ozone Wayland, like webOS. It was also great to know the work for improving GPU performance reducing the number of copies required for painting web contents.

Web Engines Hackfest 2018 CC BY-SA 2.0

Other topics of my interest:
– We did a follow-up of the discussion in last BlinkOn about the barriers for Chromium embedders, sharing the experiences maintaining a downstream Chromium tree.
– Joined the discussions about the future of WebKitGTK. In particular the graphics pipeline adaptation to the upcoming GTK+ 4.

As usual, the organization was great. We had 70 people in the event, and it was awesome to see all the activity in the office, and so many talented engineers in the same place. Thanks Igalia!

Web Engines Hackfest 2018 CC BY-SA 2.0

AGL All Members Meeting Europe 2018 at Dresden

The last event in barely a month was my first visit to the beautiful town of Dresden (Germany).

The goal was continuing the discussions for the projects Igalia is developing for AGL platform: Chromium upstream native Wayland support, and the WAM web runtime port. We also had a booth showcasing that work, but also our lightweight WebKit port WPE that was, as usual, attracting interest with its 60fps video playback performance in a Raspberry Pi 2.

I co-presented with Steve Lemke a talk about the automotive activities at LGSVL, taking the opportunity to update on the status of the WAM web runtime work for AGL (slides here). The project is progressing and Igalia should be landing soon the first results of the work.

Igalia booth at AGL AMM Europe 2018

It was great to meet all this people, and discuss in person the architecture proposal for the web runtime, unblocking several tasks and offering more detailed planning for next months.

Dresden was great, and I can’t help highlighting the reception and guided tour in the Dresden Transportation Museum. Great choice by the organization. Thanks to Linux Foundation and the AGL project community!

Next: Chrome Dev Summit 2018

So… what’s next? I will be visiting San Francisco in November for Chrome Dev Summit.

I can only thank Igalia for sponsoring my attendance to these events. They are quite important for keeping things moving forward. But also, it is also really nice to meet friends and collaborators. Thanks Igalia!

Igalia, LG SVL

Updated Chromium Legacy Wayland Support

Introduction

Future Ozone Wayland backend is still not ready for shipping. So we are announcing the release of an updated Ozone Wayland backend for Chromium, based on the implementation provided by Intel. It is rebased on top of latest stable Chromium release and you can find it in my team Github. Hope you will appreciate it.

Official Chromium on Linux desktop nowadays

Linux desktop is progressively migrating to use Wayland as the display server. It is the default option in Fedora, Ubuntu ~~and, more importantly, the next Ubuntu Long Term Support release will ship Gnome Shell Wayland display server by default~~ (P.S. since this post was originally written, Ubuntu has delayed the Wayland adoption for LTS).

As is, now, Chromium browser for Linux desktop support is based on X11. This means it will natively interact with an X server and with its XDG extensions for displaying the contents and receiving user events. But, as said, next generation of Linux desktop will be using Wayland display servers instead of X11. How is it working? Using XWayland server, a full X11 server built on top of Wayland protocol. Ok, but that has an impact on performance. Chromium needs to communicate and paint to X11 provided buffers, and then, those buffers need to be shared with Wayland display server. And the user events will need to be proxied from the Wayland display server through the XWayland server and X11 protocol. It requires more resources: more memory, CPU, and GPU. And it adds more latency to the communication.

Ozone

Chromium supports officially several platforms (Windows, Android, Linux desktop, iOS). But it provides abstractions for porting it to other platforms.

The set of abstractions is named Ozone (more info here). It allows to implement one or more platform components with the hooks for properly integrating with a platform that is in the set of officially supported targets. Among other things it provides abstractions for:
* Obtaining accelerated surfaces.
* Creating and obtaining windows to paint the contents.
* Interacting with the desktop cursor.
* Receiving user events.
* Interacting with the window manager.

Chromium and Wayland (2014-2016)

Even if Wayland was not used on Linux desktop, a bunch of embedded devices have been using Wayland for their display server for quite some time. LG has been shipping a full Wayland experience on the webOS TV products.

In the last 4 years, Intel has been providing an implementation of Ozone abstractions for Wayland. It was an amazing work that allowed running Chromium browser on top of a Wayland compositor. This backend has been the de facto standard for running Chromium browser on all these Wayland-enabled embedded devices.

But the development of this implementation has mostly stopped around Chromium 49 (though rebases on top of Chromium 51 and 53 have been provided).

Chromium and Wayland (2018+)

Since the end of 2016, Igalia has been involved on several initiatives to allow Chromium to run natively in Wayland. Even if this work is based on the original Ozone Wayland backend by Intel, it is mostly a rewrite and adaptation to the future graphics architecture in Chromium (Viz and Mus).

This is being developed in the Igalia GitHub, downstream, though it is expected to be landed upstream progressively. Hopefully, at some point in 2018, this new backend will be fully ready for shipping products with it. But we are still not there. ~~Some major missing parts are Wayland TextInput protocol and content shell support~~ (P.S. since this was written, both TextInput and content shell support are working now!).

More information on these posts from the authors:
* June 2016: Understanding Chromium’s runtime ozone platform selection (by Antonio Gomes).
* October 2016: Analysis of Ozone Wayland (by Frédéric Wang).
* November 2016: Chromium, ozone, wayland and beyond (by Antonio Gomes).
* December 2016: Chromium on R-Car M3 & AGL/Wayland (by Frédéric Wang).
* February 2017: Mus Window System (by Frédéric Wang).
* May 2017: Chromium Mus/Ozone update (H1/2017): wayland, x11 (by Antonio Gomes).
* June 2017: Running Chromium m60 on R-Car M3 board & AGL/Wayland (by Maksim Sisov).

Releasing legacy Ozone Wayland backend (2017-2018)

Ok, so new Wayland backend is still not ready in some cases, and the old one is unmaintained. For that reason, LG is announcing the release of an updated legacy Ozone Wayland backend. It is essentially the original Intel backend, but ported to current Chromium stable.

Why? Because we want to provide a migration path to the future Ozone Wayland backend. And because we want to share this effort with other developers, willing to run Chromium in Wayland immediately, or that are still using the old backend and cannot immediately migrate to the new one.

WARNING If you are starting development for a product that is going to happen in 1-2 years… Very likely your best option is already migrating now to the new Ozone Wayland backend (and help with the missing bits). We will stop maintaining it ourselves once new Ozone Wayland backend lands upstream and covers all our needs.

What does this port include?
* Rebased on top of Chromium m60, m61, m62 and m63.
* Ported to GN.
* It already includes some changes to adapt to the new Ozone Wayland refactors.

It is hosted at https://github.com/lgsvl/chromium-src.

Enjoy it!

Originally published at webOS Open Source Edition Blog. and licensed under Creative Commons Attribution 4.0.

Gnome, Igalia, Maemo

WebKitGTK+ accelerated composition on Wayland

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As part of my work at Igalia browsers team, I am working on making WebKitGTK+ and Epiphany work on Wayland.

Just running non 3D websites on Wayland did not involve too much work. But running the OpenGL accelerated code in WebKit was a bit more complicated. Though, I’ve got a first working version.

Video: Epiphany on Wayland running WebGL and CSS-3D

On WebKitGTK+, we enable the use of hardware acceleration with OpenGL for:

  • WebGL: web pages with a canvas using WebGL are run using the 3D hardware available.
  • Accelerated composition of layers. With stuff like CSS-3D transformations, 3D hardware acceleration is handy to composite the layers of a webpage.
You can read more about accelerated compositing on these posts from Martin Robinson: WebKitGTK+ hackfest wrapup, and Accelerated compositing update.

On X11, we use XComposite, sharing a Window among the GTK+ widget (WebKitWebView) and the GL contexts for WebGL and accelerated composition. We have a tree of layers, each one rendering to a texture. Then these textures are composited rendering directly to the X11 window.

On Wayland, things are a bit different. Wayland protocol does not define a way to share a buffer among clients, nor a way to “insert” a window inside another window. My solution is just making the accelerated compositor render the layers to another texture. When the time comes for the WebKitWebView to be drawn (using Cairo), we render this texture too. If we build GTK+ for using EGL, then this process happens completely on GPU.

Next step will be adding support for accelerated composition in WebKit2GTK+. The main challenge here is that the WebKitWebView widget is on UI process and the WebGL contexts and layers rendering are in Web Process. So, if we want to avoid buffers going to/from GPU, we need to share them between the two processes. DRM authentication through EGL_mesa_drm extension could help here.

Gnome, Igalia, Maemo

IwkMail, mixing WebKit Gtk+, Camel and JQuery Mobile

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In the last few weeks, as part of my work here at Igalia, I’ve been playing a bit with the concept of hybrid applications. In this case, I’ve created a basic prototype of a mail application, with its user interface completely written using JQuery Mobile, and with backend code in C and GObject. The result is iwkmail.

Screencast of iwkmail in action

Though it’s a simple experiment, I’ve added some mail basic functionality, so I could try to catch as much as possible of real requirements for how  we could improve the developers WebKit+GNOME experience creating hybrid applications.

My first conclusion is that it’s surprisingly easy and fast to develop such applications. Second, I could reuse tons of source code and modules from my old projects. This approach surely provides a way to create cool GNOME applications, using the most fashionable web client technologies.

So, you’ll get:

  • Browsing messages
  • Read/unread flags
  • Deleting messages
  • Creating and deleting mail accounts.
  • Storage protocols supported: IMAP and POP.
  • For sending mails, we support SMTP. There’s support for an outbox holding the messages to be sent.
  • A plain text composer, allowing to add attachments.

The UI is completely written in Javascript + HTML, using JQuery Mobile.

The backend side is done using Camel library inside Evolution Data Server, so we rely on a library well tested for more than 10 years.  All the code related to this is implemented in C+GObject, and I reused a good set of code from Modest, the default mail client for Nokia N810 and N900. I’ve got involved on its development for 3 years, so that’s a bunch of code I know well enough.

For communication, I use the AJAX-like JSONP protocol, and custom SoupRequest URI scheme handlers. Basically I expose some methods as iwk:addAcccount, iwk:getMessage, etc, and arguments are passed as usual in a web request. The result I obtain from this calls is a JSON object with the results of the call. Simple, and works very well.

I’ve pushed the work on github: https://github.com/jdapena/iwkmail. Feel free to try it!

Oh, I guess it’s very obvious that I did not spend too much time thinking on the project name… So, anyone proposing something that matches the IM acronym (I don’t want to rewrite the class names!) would deserve a beer.

Last, lots of thanks to Igalia for giving me the opportunity to do this experiment. As usual, fun stuff to work with.

Gnome, Igalia, Maemo

Epiphany meets the web app stores

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In last weeks, I’ve been taking a look at the web applications standards support in Epiphany, as part of my work at Igalia. Xan wrote about the Save as web application feature present in Epiphany 3.2, that is a base for very simple (and userful) web applications support in Gnome desktop.

To continue with this work, I’ve been investigating on adding support for some web app stores. So I’ve done an experimental implementation for Mozilla Open Web Apps (as in 2011 tech preview), Chrome Web Store hosted and packaged apps, and Chrome CRX-less apps.


Screencast using Chrome Web Store.

This is an experiment. Not supported, and it may actually stay out of official Epiphany. So there are lots of things not working at all. This is first a way to have a big number of apps to play with our application mode, and improve it. So no permissions check, URL’s match may be broken, many apps will fail to even log in… Did I say it is an experiment? Most obvious issues are related with this external links handling bug.

But, if you just want to play with it, just try my branch webapp in my Epiphany Github repository. By default, support is disabled, so you’ll have to enable these keys:

$ gsettings set org.gnome.Epiphany.web enable-chrome-apps true
$ gsettings set org.gnome.Epiphany.web enable-open-web-apps true

You can try with Mozilla Labs Apps Dir from 2011 tech preview and Chrome Web Store.