September 2018 - Pharo-dev - lists.pharo.org

[Pharo 7.0-dev] Build #1268: 22488-Bootstrapping-from-outside-of-the-repository-broken

by ci-pharo-ci-jenkins2＠inria.fr

There is a new Pharo build available! The status of the build #1268 was: SUCCESS. The Pull Request #1826 was integrated: "22488-Bootstrapping-from-outside-of-the-repository-broken" Pull request url: https://github.com/pharo-project/pharo/pull/1826 Issue Url: https://pharo.fogbugz.com/f/cases/22488 Build Url: https://ci.inria.fr/pharo-ci-jenkins2/job/Test%20pending%20pull%20request%2…

Sept. 26, 2018

[Pharo 7.0-dev] Build #1267: 22478 button presenter does not take into account its color

by ci-pharo-ci-jenkins2＠inria.fr

There is a new Pharo build available! The status of the build #1267 was: SUCCESS. The Pull Request #1820 was integrated: "22478 button presenter does not take into account its color" Pull request url: https://github.com/pharo-project/pharo/pull/1820 Issue Url: https://pharo.fogbugz.com/f/cases/22478 Build Url: https://ci.inria.fr/pharo-ci-jenkins2/job/Test%20pending%20pull%20request%2…

Sept. 26, 2018

[Pharo 7.0-dev] Build #1266: 22440-Compiler-parseExpression-does-not-set-up-compilation-context-for-method-node

by ci-pharo-ci-jenkins2＠inria.fr

There is a new Pharo build available! The status of the build #1266 was: SUCCESS. The Pull Request #1825 was integrated: "22440-Compiler-parseExpression-does-not-set-up-compilation-context-for-method-node" Pull request url: https://github.com/pharo-project/pharo/pull/1825 Issue Url: https://pharo.fogbugz.com/f/cases/22440 Build Url: https://ci.inria.fr/pharo-ci-jenkins2/job/Test%20pending%20pull%20request%2…

Sept. 26, 2018

Re: [Pharo-dev] iceberg PrimitiveFailed allocateExecutablePage - PharoDebug.log

by Petr Fischer

> Hi Petr, > > along with Estebanâs request for the error code from allocateExecutablePage can you also see whether use of iceberg is successful the second time you launch Pharo? So start up your virtualbox, try and interact with iceberg, quit if it fails, relaunch and try again? Yes, after the tests were green (second time, after magic happens), Iceberg was also OK - and I mean the whole Iceberg cycle up to creating the Pharo pull request right from the Iceberg UI/image. I recreated whole virtualbox image from scratch and tune some vbox settings - described problems have gone and I am not able to recreate the same situation - let's forget it, it's not the Pharo thing. And finally - I see that a lot of work has been done on Iceberg - it's not even necessary to leave Pharo for a minute due to the final Github pull request in web browser, nice. pf > Also in your steps what do you do to prepare? eg do you boot in virtualbox, return from sleep, or...? > > FYI, allocateExecutablePage uses valloc (IIRC) to get a page from the OS and then uses mprotect to add executable permission to the page before answering the pageâs address as the result of the primitive. The callback machinery then uses the page to provide the executable blue code used in implementing callbacks. The address of a code sequence in the page is what is actually handed out to C code as a fu croon pointer. When external code calls this function pointer the code in the sequence invokes a callback into the vm before returning back to C. Consequently it is key that allocateExecutablePage works correctly. If it doesnât then no callbacks. > > _,,,^..^,,,_ (phone) > > > On Sep 24, 2018, at 11:11 AM, Petr Fischer via Pharo-dev <pharo-dev(a)lists.pharo.org> wrote: > > > > <mime-attachment>

Sept. 26, 2018

Re: [Pharo-dev] [Pharo-users] [ANN] Success story Mobility Map

by Sven Van Caekenberghe

> On 25 Sep 2018, at 14:39, Norbert Hartl <norbert(a)hartl.name> wrote: > > > >> Am 25.09.2018 um 12:52 schrieb Sven Van Caekenberghe <sven(a)stfx.eu>: >> >> Wow. Very nice, well done. >> >> Any chance on some more technical details, as in what 'connected by a message queue for the communication' exactly means ? How did you approach micro services exactly ? >> > Sure :) Thanks, this is very interesting ! > The installation spawns multiple physical machines. All the machines are joined to a docker swarm. The installation is reified as either task or service from the view on the docker swarm. Meaning you instantiate an arbitrary amount of services and docker swarm distributes them among the physical machines. Usually you donât take control which is running where but you can. At this point you have spread dozens of pharo images among multiple machines and each of them has an IP address. Furthermore in docker swarm you have a reification of a network meaning that every instance in a network can see all other instances on this network. Each service can be reached by its service name in that network. Docker swarm does all the iptables/firewall and DNS setup for you. Are you happy with docker swarm's availability/fail-over behaviour ? In other words: does it work when one image/instance goes bad, does it detect and restore the missing functionality ? > In order to have communication between those runtimes we use rabbitmq because you were so nice writing a driver for it ;) The rabbitmq does have a support for cluster setup, meaning each of the physical machines has a rabbitmq installation and they know each other. So it does not matter to which instance you send messages to and on which you register for receiving messages. So every pharo image connects to the service rabbitmq and opens a queue for interaction. Same question: does RabbitMQ's clustering work well under stress/problems ? Syncing all queues between all machines sounds quite heavy (I never tried it, but maybe it just works). > Each service like the car sharing opens a queue e.g. /queue/carSharing and listens on it. The broker images are stateful so they open queues like /queue/mobility-map-afdeg32 where afdeg32 is the container id of the instance (hostname in docker). In each request the queue name to reply is sent as a header. So we can make sure that the right image gets the message back. This way we can have sticky sessions keeping volatile data in memory for the lifecycle of a session. There is one worker image which opens a queue /queue/mobility-map where session independent requests can be processed. I think I understand ;-) > In order to ease development we are sharing code between the broker and the micro service. Each micro service has a -Common package where the classes are in that build the interface. The classes in here are a kind of data entity facades. They use NeoJSON to map to and from a stream. The class name is send with the message as a header so the remote side knows what to materialize. The handling is unified for the four cases > > - Request as inquiry to another micro service > - Response returns values to a Request > - Error is transferred like a Response but is then signalled on the receiving side > - Notification connects the announcers on the broker and the micro service side. Yes, makes total sense. > Asynchronous calls we solved using Promises and Futures. Each async call to the Q becomes a promise (that blocks on #value) and is combined to a future value containing all promises with support to generate a delta of all resolved promises. This we need because you issue a search that takes longer and you want to display results as soon as they are resolved not after all haven been resolved. Which Promise/Future framework/library are you using in Pharo ? You did not go for single threaded worker images ? > And a lot more. This is a coarse grained overview over the architecture. Iâm happy to answer further questions about this. > > Norbert > >>> On 25 Sep 2018, at 12:20, Norbert Hartl <norbert(a)hartl.name> wrote: >>> >>> As presented on ESUG here is the brief description of one of our current projects. >>> >>> Mobility Map >>> ââââââ >>> >>> Mobility Map is a broker for mobility services. It offers multi-modal routing search enabling users to find the best travel options between locations. Travel options include car sharing, bikes, trains, busses etc. Rented cars can be offered for ride sharing on booking time letting other people find it to participate in the ride. Single travel options are combined in travel plans that can be booked and managed in a very easy way. >>> >>> For this project main requirements were scalability to serve a large user base and flexibility to add more additional providers to the broker. The application has been realized using web technologies for the frontend and pharo for the backend. Using a microservice architecture combined with a broker it is easy to extend the platform with additional brokers. Deployment is done using docker swarm for distributing dozens of pharo images among multiple server machines connected by a message queue for the communication. Pharo supported that scenario very well enabling us the meet the requirements with less effort. >>> >>> Pharo turned out to be a perfect fit to develop the application in a agile way. Small development cycles with continuous integration and continuous delivery enables fast turnarounds for the customers to validate progress. >>> >>> This is a screenshot of the search page for multi-modal results: >>> >>> >>> <Screen Shot 2018-09-21 at 16.54.30.png> >> >> > >

Sept. 25, 2018

[Pharo 7.0-dev] Build #1265: 22479-Imporove-kernel-testing

by ci-pharo-ci-jenkins2＠inria.fr

There is a new Pharo build available! The status of the build #1265 was: SUCCESS. The Pull Request #1821 was integrated: "22479-Imporove-kernel-testing" Pull request url: https://github.com/pharo-project/pharo/pull/1821 Issue Url: https://pharo.fogbugz.com/f/cases/22479 Build Url: https://ci.inria.fr/pharo-ci-jenkins2/job/Test%20pending%20pull%20request%2…

Sept. 25, 2018

Re: [Pharo-dev] [ANN] Success story Mobility Map

by Esteban Maringolo

Thanks for sharing this Norbert. I'm happy for you as a company, and also for Pharo, this should help promoting it to bystanders, the whole set of tools and libraries helps demonstrating the convenience and applicability of Pharo in "modern" designs (docker, swarms, MQ, microservices, and whatnot). Regards Esteban A. Maringolo El mar., 25 sept. 2018 a las 9:40, Norbert Hartl (<norbert(a)hartl.name>) escribiÃ³: > > > > Am 25.09.2018 um 12:52 schrieb Sven Van Caekenberghe <sven(a)stfx.eu>: > > > > Wow. Very nice, well done. > > > > Any chance on some more technical details, as in what 'connected by a > message queue for the communication' exactly means ? How did you approach > micro services exactly ? > > > Sure :) > > The installation spawns multiple physical machines. All the machines are > joined to a docker swarm. The installation is reified as either task or > service from the view on the docker swarm. Meaning you instantiate an > arbitrary amount of services and docker swarm distributes them among the > physical machines. Usually you donât take control which is running where > but you can. At this point you have spread dozens of pharo images among > multiple machines and each of them has an IP address. Furthermore in docker > swarm you have a reification of a network meaning that every instance in a > network can see all other instances on this network. Each service can be > reached by its service name in that network. Docker swarm does all the > iptables/firewall and DNS setup for you. > > In order to have communication between those runtimes we use rabbitmq > because you were so nice writing a driver for it ;) The rabbitmq does have > a support for cluster setup, meaning each of the physical machines has a > rabbitmq installation and they know each other. So it does not matter to > which instance you send messages to and on which you register for receiving > messages. So every pharo image connects to the service rabbitmq and opens a > queue for interaction. > > Each service like the car sharing opens a queue e.g. /queue/carSharing and > listens on it. The broker images are stateful so they open queues like > /queue/mobility-map-afdeg32 where afdeg32 is the container id of the > instance (hostname in docker). In each request the queue name to reply is > sent as a header. So we can make sure that the right image gets the message > back. This way we can have sticky sessions keeping volatile data in memory > for the lifecycle of a session. There is one worker image which opens a > queue /queue/mobility-map where session independent requests can be > processed. > > In order to ease development we are sharing code between the broker and > the micro service. Each micro service has a -Common package where the > classes are in that build the interface. The classes in here are a kind of > data entity facades. They use NeoJSON to map to and from a stream. The > class name is send with the message as a header so the remote side knows > what to materialize. The handling is unified for the four cases > > - Request as inquiry to another micro service > - Response returns values to a Request > - Error is transferred like a Response but is then signalled on the > receiving side > - Notification connects the announcers on the broker and the micro service > side. > > Asynchronous calls we solved using Promises and Futures. Each async call > to the Q becomes a promise (that blocks on #value) and is combined to a > future value containing all promises with support to generate a delta of > all resolved promises. This we need because you issue a search that takes > longer and you want to display results as soon as they are resolved not > after all haven been resolved. > > And a lot more. This is a coarse grained overview over the architecture. > Iâm happy to answer further questions about this. > > Norbert > > >> On 25 Sep 2018, at 12:20, Norbert Hartl <norbert(a)hartl.name> wrote: > >> > >> As presented on ESUG here is the brief description of one of our > current projects. > >> > >> Mobility Map > >> ââââââ > >> > >> Mobility Map is a broker for mobility services. It offers multi-modal > routing search enabling users to find the best travel options between > locations. Travel options include car sharing, bikes, trains, busses etc. > Rented cars can be offered for ride sharing on booking time letting other > people find it to participate in the ride. Single travel options are > combined in travel plans that can be booked and managed in a very easy way. > >> > >> For this project main requirements were scalability to serve a large > user base and flexibility to add more additional providers to the broker. > The application has been realized using web technologies for the frontend > and pharo for the backend. Using a microservice architecture combined with > a broker it is easy to extend the platform with additional brokers. > Deployment is done using docker swarm for distributing dozens of pharo > images among multiple server machines connected by a message queue for the > communication. Pharo supported that scenario very well enabling us the meet > the requirements with less effort. > >> > >> Pharo turned out to be a perfect fit to develop the application in a > agile way. Small development cycles with continuous integration and > continuous delivery enables fast turnarounds for the customers to validate > progress. > >> > >> This is a screenshot of the search page for multi-modal results: > >> > >> > >> <Screen Shot 2018-09-21 at 16.54.30.png> > > > > > > >

Sept. 25, 2018

Re: [Pharo-dev] [ANN] Pharo Consortium upgrade to Platinum: ZWEIDENKER

by Ben Coman

On Tue, 25 Sep 2018 at 20:03, Marcus Denker <marcus.denker(a)inria.fr> wrote: > The Pharo Consortium is very happy to announce that ZWEIDENKER has ugraded > to be a Platinum member. > Its great to see your support and commitment to Pharo - in addition to the many direct code contributions. cheers -ben

Sept. 25, 2018

Re: [Pharo-dev] [ANN] Success story Mobility Map

by Norbert Hartl

> Am 25.09.2018 um 12:52 schrieb Sven Van Caekenberghe <sven(a)stfx.eu>: > > Wow. Very nice, well done. > > Any chance on some more technical details, as in what 'connected by a message queue for the communication' exactly means ? How did you approach micro services exactly ? > Sure :) The installation spawns multiple physical machines. All the machines are joined to a docker swarm. The installation is reified as either task or service from the view on the docker swarm. Meaning you instantiate an arbitrary amount of services and docker swarm distributes them among the physical machines. Usually you donât take control which is running where but you can. At this point you have spread dozens of pharo images among multiple machines and each of them has an IP address. Furthermore in docker swarm you have a reification of a network meaning that every instance in a network can see all other instances on this network. Each service can be reached by its service name in that network. Docker swarm does all the iptables/firewall and DNS setup for you. In order to have communication between those runtimes we use rabbitmq because you were so nice writing a driver for it ;) The rabbitmq does have a support for cluster setup, meaning each of the physical machines has a rabbitmq installation and they know each other. So it does not matter to which instance you send messages to and on which you register for receiving messages. So every pharo image connects to the service rabbitmq and opens a queue for interaction. Each service like the car sharing opens a queue e.g. /queue/carSharing and listens on it. The broker images are stateful so they open queues like /queue/mobility-map-afdeg32 where afdeg32 is the container id of the instance (hostname in docker). In each request the queue name to reply is sent as a header. So we can make sure that the right image gets the message back. This way we can have sticky sessions keeping volatile data in memory for the lifecycle of a session. There is one worker image which opens a queue /queue/mobility-map where session independent requests can be processed. In order to ease development we are sharing code between the broker and the micro service. Each micro service has a -Common package where the classes are in that build the interface. The classes in here are a kind of data entity facades. They use NeoJSON to map to and from a stream. The class name is send with the message as a header so the remote side knows what to materialize. The handling is unified for the four cases - Request as inquiry to another micro service - Response returns values to a Request - Error is transferred like a Response but is then signalled on the receiving side - Notification connects the announcers on the broker and the micro service side. Asynchronous calls we solved using Promises and Futures. Each async call to the Q becomes a promise (that blocks on #value) and is combined to a future value containing all promises with support to generate a delta of all resolved promises. This we need because you issue a search that takes longer and you want to display results as soon as they are resolved not after all haven been resolved. And a lot more. This is a coarse grained overview over the architecture. Iâm happy to answer further questions about this. Norbert >> On 25 Sep 2018, at 12:20, Norbert Hartl <norbert(a)hartl.name> wrote: >> >> As presented on ESUG here is the brief description of one of our current projects. >> >> Mobility Map >> ââââââ >> >> Mobility Map is a broker for mobility services. It offers multi-modal routing search enabling users to find the best travel options between locations. Travel options include car sharing, bikes, trains, busses etc. Rented cars can be offered for ride sharing on booking time letting other people find it to participate in the ride. Single travel options are combined in travel plans that can be booked and managed in a very easy way. >> >> For this project main requirements were scalability to serve a large user base and flexibility to add more additional providers to the broker. The application has been realized using web technologies for the frontend and pharo for the backend. Using a microservice architecture combined with a broker it is easy to extend the platform with additional brokers. Deployment is done using docker swarm for distributing dozens of pharo images among multiple server machines connected by a message queue for the communication. Pharo supported that scenario very well enabling us the meet the requirements with less effort. >> >> Pharo turned out to be a perfect fit to develop the application in a agile way. Small development cycles with continuous integration and continuous delivery enables fast turnarounds for the customers to validate progress. >> >> This is a screenshot of the search page for multi-modal results: >> >> >> <Screen Shot 2018-09-21 at 16.54.30.png> > >

Sept. 25, 2018

Re: [Pharo-dev] Fraction and ScaledDecimal should be not be serialized as Float in STON format

by Sven Van Caekenberghe

> On 18 Sep 2018, at 16:45, Sven Van Caekenberghe <sven(a)stfx.eu> wrote: > > Of course, we could also extend the basic number parser and allow the native (stored) notation > > 1/3 > 3/2s2 > > Note how that last one should use the more exact #storeOn: notation, not the #printOn: > > I'll have to think about this a bit more, as I can really not choose right now. I am still not sure if we should do this or not, but here is a POC implementation of the above. It implements the following syntax extension (see the class comment of STON for the rest). number int int denominator int denominator scale int frac int exp int frac exp denominator / digits scale s digits STONWriter>>#writeFraction: fraction jsonMode ifTrue: [ self writeFloat: fraction asFloat ] ifFalse: [ writeStream print: fraction numerator; nextPut: $/; print: fraction denominator ] STONWriter>>#writeScaledDecimal: scaledDecimal jsonMode ifTrue: [ self writeFloat: scaledDecimal asFloat ] ifFalse: [ writeStream print: scaledDecimal numerator; nextPut: $/; print: scaledDecimal denominator; nextPut: $s; print: scaledDecimal scale ] Fraction>>#stonOn: stonWriter stonWriter writeFraction: self ScaledDecimal>>#stonOn: stonWriter stonWriter writeScaledDecimal: self STONReader>>parseNumber | negated number | negated := readStream peekFor: $-. number := self parseNumberInteger. (readStream peekFor: $/) ifTrue: [ number := Fraction numerator: number denominator: self parseNumberInteger. (readStream peekFor: $s) ifTrue: [ number := ScaledDecimal newFromNumber: number scale: self parseNumberInteger ] ] ifFalse: [ (readStream peekFor: $.) ifTrue: [ number := number + self parseNumberFraction ]. ((readStream peekFor: $e) or: [ readStream peekFor: $E ]) ifTrue: [ number := number * self parseNumberExponent ] ]. negated ifTrue: [ number := number negated ]. self consumeWhitespace. ^ number Sven

Sept. 25, 2018