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You will need\nto acquire a [**Warp runtime**](https://redirect.scaledynamics.io/warp/runtime) to use it.\n\nTo add _Warp_ API to your project:\n\n```\n$ npm install warp\n```\n\n## How to use it\n\n_Warp_ offers two main functions starting a [_warp_ task](#warp-task): `warp.call` and `warp.callAsPromise`.\nWe say that they perform a _warp_ call. By extension, we also say that code\n_warps_ a function or that the function is _warped_.\n\nHere is a very simple illustrative code sample where a CPU intensive function (`primeDecomposition`)\nis executed in parallel by a _warp_ call keeping the event loop free for any other processing.\n\nThe first example uses a callback-based function, whereas the second uses a Promise-based function.\n\n### With callback\n\n``` javascript\nconst warp = require('warp');\n\nfunction primeDecomposition(n, done) {\n let f = [];\n for (let i = 2; i <= n; i++)\n while (n % i === 0) {\n f.push(i);\n n /= i;\n }\n done(f);\n}\n\nwarp.call(primeDecomposition, 9007199254740991,\n (a) => console.log(`Value: ${a}`));\n```\n\nPrints out\n> Value: 6361,69431,20394401\n\n### With promise\n\n``` javascript\nconst warp = require('warp');\n\nfunction primeDecomposition(n) {\n let f = [];\n for (let i = 2; i <= n; i++)\n while (n % i === 0) {\n f.push(i);\n n /= i;\n }\n return f;\n}\n\nlet a = await warp.callAsPromise(primeDecomposition, 9007199254740991);\nconsole.log(`Value: ${a}`);\n```\n\nPrints out\n> Value: 6361,69431,20394401\n\n## How it works\n\nWhen you _warp_ call a function, the [execution context](#execution-context) (i.e. everything\nreachable from the function scope) is captured, then this context and the _warped_ function are\nsent to a distinct execution flow ([parallel flow](#parallel-flow)).\n\nOnce the [_warp_ task](#warp-task) is finished, the parallel [context](#execution-context) is\ncaptured and sent back to the main javascript flow. Then, in an event task of the main flow,\nthe context is updated, and:\n\n- If the _warp_ call is `call`, the callback is executed in the main flow, with the arguments\ngiven to the callback in the parallel flow.\n- If the _warp_ call is `callAsPromise`, the Promise returned by `callAsPromise` is resolved or\nrejected with the value or the exception obtained at the end of the parallel flow.\n\n### Scope\n\nThe _warped_ functions can read and modify anything reachable from their\n[scope](https://developer.mozilla.org/en-US/docs/Glossary/Scope).\n\nIn the following sample, the variable `o` is defined as a free variable (outside of the function).\nThe _warped_ function can read it, and also modify the object. Modifications made to `o` in the parallel\nflow are applied and visible in the main flow.\n\n``` javascript\nconst warp = require('warp');\n\nlet o = {};\nfunction primeDecomposition(n) {\n let f = [];\n for (let i = 2; i <= n; i++)\n while (n % i === 0) {\n f.push(i);\n n /= i;\n }\n o.result = f;\n}\n\nawait warp.callAsPromise(primeDecomposition, 9007199254740991);\nconsole.log(`Value: ${o.result}`);\n```\n\nPrints out\n> Value: 6361,69431,20394401\n\n### Shared resources and concurrency\n\n_Warp_ offers no new synchronization or semaphore mechanism. If you need to manage concurrent access\nto a value, you'll have to keep the modifying code in the main flow.\n\nIn the following example, we compute several prime decompositions in parallel.\n\n``` javascript\nconst warp = require('warp');\n\nlet primeDecompositions = [];\n\nfunction primeDecomposition(index, n) {\n let f = [];\n for (let i = 2; i <= n; i++)\n while (n % i === 0) {\n f.push(i);\n n /= i;\n }\n primeDecompositions[index] = f;\n}\n\nlet promises = []\nfor(let i = 0; i < 8; i++) {\n promises.push(warp.callAsPromise(primeDecomposition, i, 9007174991 + i));\n}\n\nawait Promise.all(promises);\n\nconsole.log(`Prime decompositions: %j`, primeDecompositions);\n```\n\nPrints out\n> Prime decompositions: [[17,131,4044533],[2,2,2,2,3,23,31,263183],[12071,746183],[2,37,53,2296577],[3,5,7,13,41,227,709],[2,2,2251793749],[59,109,1400587],[2,3,3,3,19,43,204161]]\n\nBut you need to be carefull about parallel access to shared variables or properties.\n\nFor instance, the following example shows bad usage of a shared value causing indetermism. There, you\ndon't know in which order the additions will be made, but it is guaranteed that each `compute` sees\nthe initial value of `v` as `4`. This means you don't know what the final value of `v` will be, you\njust know it will be either `7` or `8`.\n\n``` javascript\nconst warp = require('warp');\n\nlet v = 4;\nfunction compute(num) {\n // compute increment from input\n let inc = num;\n v += inc;\n return;\n}\n\nlet promises = []\npromises.push(warp.callAsPromise(compute, 3));\npromises.push(warp.callAsPromise(compute, 4));\n\nawait Promise.all(promises);\n\nconsole.log(`Value: ${v}`);\n```\n\nTo obtain the correct behavior in this example, you'll need to apply the changes to the shared\nvariable in the main flow by using the `.then` of the promise.\n\n``` javascript\nconst warp = require('warp');\n\nlet v = 4;\nfunction compute(num) {\n // compute increment from input\n let inc = num;\n return inc;\n}\n\nlet promises = []\npromises.push(warp.callAsPromise(compute, 3).then((inc) => v += inc));\npromises.push(warp.callAsPromise(compute, 4).then((inc) => v += inc));\n\nawait Promise.all(promises);\n\nconsole.log(`Value: ${v}`);\n```\n\nPrints out\n> Value: 11\n\nThis way it'll end up with `11` as the final value.\n\n# Definitions\n\n## Parallel flow\n\nA **parallel flow** is a javascript execution flow distinct from the main javascript execution flow. The\nmain flow and some parallel flows are running at the same physical time.\n\n## Warp task\n\nA **warp task** is started by a _warp_ call (a call to `warp.call` or `warp.callAsPromise`).\nThe task is executed in a [parallel flow](#parallel-flow). It starts by executing the given\nfunction and continues until the end of the task is detected.\n\nThe end of the task is detected when:\n- an exception is thrown by the task\n\n**or**\n\n- If the task was started by `warp.callAsPromise`: \n - the function given to `callAsPromise` has returned \n - **And**, if its returned value is a Promise, it is\n [fulfilled or rejected](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Promise#Description).\n\n- If the task was started by `warp.call` \n - The callback is called, \n - **And** the function given to `call` has returned. \n\nNote that this doesn't mean that `return` was executed, it means that the execution has\nreturned to its caller. For example in the following code the end is detected during the line\n`a = await 3` when `await` yields and `a` is still `2`.\n\n``` javascript\nlet a = 0;\nasync function compute(done) {\n a = 1;\n done();\n a = 2;\n a = await 3; // End is here at `await` before assignation of `a`\n return;\n}\n```\n\n**Warning:** If the task were to attempt to execute code after the end of execution were detected\n(e.g. with a `setImmediate`, `setTimeout`, ...), then the behavior would be unspecified. This\nmeans that if the function given to `call` is starting any asynchronous processing, calling\nthe `callback` must be the very last thing done by the task.\n\n## Execution context\n\nAn **execution context** is referring to everything accessible from the\n[scope](https://developer.mozilla.org/en-US/docs/Glossary/Scope) of the considered\nfunction at a given point of the execution. This includes \n- parameters of the call, \n- local, free and global variables accessed by the function called or by all functions potentially\n called directly or indirectly, \n- any reachable objects (objects, arrays, functions, symbols) from the above defined parameters/variables. \n","readmeFilename":"README.md","_id":"warp@1.1.0-dev.72","_npmVersion":"6.4.1","_nodeVersion":"8.15.0","_npmUser":{"name":"lcars","email":"welcome@scaledynamics.io"},"dist":{"integrity":"sha512-FDBWwvdJS/a8tJf4du8/JrjZQNim1NvsNov19Pg2IcSBwBeN2B89xaKQVzxQHqn2aWDhcamDRwvL6rY6zxd9gQ==","shasum":"9f7553138971cf88bbca97f9db24c5a7c1f75c93","tarball":"https://registry.npmjs.org/warp/-/warp-1.1.0-dev.72.tgz","fileCount":4,"unpackedSize":14118,"npm-signature":"-----BEGIN PGP SIGNATURE-----\r\nVersion: OpenPGP.js v3.0.4\r\nComment: https://openpgpjs.org\r\n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\nywc6\r\n=ilt9\r\n-----END PGP SIGNATURE-----\r\n","signatures":[{"keyid":"SHA256:jl3bwswu80PjjokCgh0o2w5c2U4LhQAE57gj9cz1kzA","sig":"MEUCIQDrv+p1rarsiOxko2leyhMijlUDFq9GRU+zsZAVhAPv/QIgSkyff+XwudpKGHx19mfdmGQblqhoG8o0TaN68V6pqbQ="}]},"maintainers":[{"email":"jpl@scaledynamics.io","name":"jpl-scale"},{"email":"welcome@scaledynamics.io","name":"lcars"},{"email":"gc@scaledynamics.io","name":"scalejs"}],"directories":{},"_npmOperationalInternal":{"host":"s3://npm-registry-packages","tmp":"tmp/warp_1.1.0-dev.72_1549994917544_0.9422358242145057"},"_hasShrinkwrap":false,"deprecated":"Internal version, please, update to v1.1.0 minimum"},"1.1.0-dev.75":{"name":"warp","version":"1.1.0-dev.75","author":{"name":"ScaleDynamics SAS"},"license":"MIT","main":"warp.js","repository":{"type":"git","url":"git+https://github.com/ScaleDynamics/warp.git"},"description":"Warp is an API to run javascript functions in parallel: get the most of multi-core systems, shorten response time & intensive computations.","keywords":["node","starnode","parallel","concurrent","child_process","performance","speed","cpu","async","asynchronous"],"bugs":{"url":"https://github.com/ScaleDynamics/warp/issues"},"homepage":"https://scaledynamics.io/","dependencies":{},"build":{"date":"2019-02-12T18:31:19.324Z","user":"2834254","host":"dedi-03-ovh","sha":"c4ad617b8e7829bba77979fedd96d1048d7e8d74","id":"47231852","branch":"master"},"_resolved":"","_integrity":"","_from":"file:dist/warp-1.1.0-dev.75.tgz","readme":"\n\n\n# Warp\n\n_Warp_ is an API allowing easy parallel execution of javascript code, at the\nsame physical time as the main javascript flow and as other flows.\n\n```javascript\n// runs `f` in parallel\nwarp.call(f, cb);\n```\n\n## Installing\n\n_Warp_ module is an API and is not providing support for execution. You will need\nto acquire a [**Warp runtime**](https://redirect.scaledynamics.io/warp/runtime) to use it.\n\nTo add _Warp_ API to your project:\n\n```\n$ npm install warp\n```\n\n## How to use it\n\n_Warp_ offers two main functions starting a [_warp_ task](#warp-task): `warp.call` and `warp.callAsPromise`.\nWe say that they perform a _warp_ call. By extension, we also say that code\n_warps_ a function or that the function is _warped_.\n\nHere is a very simple illustrative code sample where a CPU intensive function (`primeDecomposition`)\nis executed in parallel by a _warp_ call keeping the event loop free for any other processing.\n\nThe first example uses a callback-based function, whereas the second uses a Promise-based function.\n\n### With callback\n\n``` javascript\nconst warp = require('warp');\n\nfunction primeDecomposition(n, done) {\n let f = [];\n for (let i = 2; i <= n; i++)\n while (n % i === 0) {\n f.push(i);\n n /= i;\n }\n done(f);\n}\n\nwarp.call(primeDecomposition, 9007199254740991,\n (a) => console.log(`Value: ${a}`));\n```\n\nPrints out\n> Value: 6361,69431,20394401\n\n### With promise\n\n``` javascript\nconst warp = require('warp');\n\nfunction primeDecomposition(n) {\n let f = [];\n for (let i = 2; i <= n; i++)\n while (n % i === 0) {\n f.push(i);\n n /= i;\n }\n return f;\n}\n\nlet a = await warp.callAsPromise(primeDecomposition, 9007199254740991);\nconsole.log(`Value: ${a}`);\n```\n\nPrints out\n> Value: 6361,69431,20394401\n\n## How it works\n\nWhen you _warp_ call a function, the [execution context](#execution-context) (i.e. everything\nreachable from the function scope) is captured, then this context and the _warped_ function are\nsent to a distinct execution flow ([parallel flow](#parallel-flow)).\n\nOnce the [_warp_ task](#warp-task) is finished, the parallel [context](#execution-context) is\ncaptured and sent back to the main javascript flow. Then, in an event task of the main flow,\nthe context is updated, and:\n\n- If the _warp_ call is `call`, the callback is executed in the main flow, with the arguments\ngiven to the callback in the parallel flow.\n- If the _warp_ call is `callAsPromise`, the Promise returned by `callAsPromise` is resolved or\nrejected with the value or the exception obtained at the end of the parallel flow.\n\n### Scope\n\nThe _warped_ functions can read and modify anything reachable from their\n[scope](https://developer.mozilla.org/en-US/docs/Glossary/Scope).\n\nIn the following sample, the variable `o` is defined as a free variable (outside of the function).\nThe _warped_ function can read it, and also modify the object. Modifications made to `o` in the parallel\nflow are applied and visible in the main flow.\n\n``` javascript\nconst warp = require('warp');\n\nlet o = {};\nfunction primeDecomposition(n) {\n let f = [];\n for (let i = 2; i <= n; i++)\n while (n % i === 0) {\n f.push(i);\n n /= i;\n }\n o.result = f;\n}\n\nawait warp.callAsPromise(primeDecomposition, 9007199254740991);\nconsole.log(`Value: ${o.result}`);\n```\n\nPrints out\n> Value: 6361,69431,20394401\n\n### Shared resources and concurrency\n\n_Warp_ offers no new synchronization or semaphore mechanism. If you need to manage concurrent access\nto a value, you'll have to keep the modifying code in the main flow.\n\nIn the following example, we compute several prime decompositions in parallel.\n\n``` javascript\nconst warp = require('warp');\n\nlet primeDecompositions = [];\n\nfunction primeDecomposition(index, n) {\n let f = [];\n for (let i = 2; i <= n; i++)\n while (n % i === 0) {\n f.push(i);\n n /= i;\n }\n primeDecompositions[index] = f;\n}\n\nlet promises = []\nfor(let i = 0; i < 8; i++) {\n promises.push(warp.callAsPromise(primeDecomposition, i, 9007174991 + i));\n}\n\nawait Promise.all(promises);\n\nconsole.log(`Prime decompositions: %j`, primeDecompositions);\n```\n\nPrints out\n> Prime decompositions: [[17,131,4044533],[2,2,2,2,3,23,31,263183],[12071,746183],[2,37,53,2296577],[3,5,7,13,41,227,709],[2,2,2251793749],[59,109,1400587],[2,3,3,3,19,43,204161]]\n\nBut you need to be carefull about parallel access to shared variables or properties.\n\nFor instance, the following example shows bad usage of a shared value causing indetermism. There, you\ndon't know in which order the additions will be made, but it is guaranteed that each `compute` sees\nthe initial value of `v` as `4`. This means you don't know what the final value of `v` will be, you\njust know it will be either `7` or `8`.\n\n``` javascript\nconst warp = require('warp');\n\nlet v = 4;\nfunction compute(num) {\n // compute increment from input\n let inc = num;\n v += inc;\n return;\n}\n\nlet promises = []\npromises.push(warp.callAsPromise(compute, 3));\npromises.push(warp.callAsPromise(compute, 4));\n\nawait Promise.all(promises);\n\nconsole.log(`Value: ${v}`);\n```\n\nTo obtain the correct behavior in this example, you'll need to apply the changes to the shared\nvariable in the main flow by using the `.then` of the promise.\n\n``` javascript\nconst warp = require('warp');\n\nlet v = 4;\nfunction compute(num) {\n // compute increment from input\n let inc = num;\n return inc;\n}\n\nlet promises = []\npromises.push(warp.callAsPromise(compute, 3).then((inc) => v += inc));\npromises.push(warp.callAsPromise(compute, 4).then((inc) => v += inc));\n\nawait Promise.all(promises);\n\nconsole.log(`Value: ${v}`);\n```\n\nPrints out\n> Value: 11\n\nThis way it'll end up with `11` as the final value.\n\n# Definitions\n\n## Parallel flow\n\nA **parallel flow** is a javascript execution flow distinct from the main javascript execution flow. The\nmain flow and some parallel flows are running at the same physical time.\n\n## Warp task\n\nA **warp task** is started by a _warp_ call (a call to `warp.call` or `warp.callAsPromise`).\nThe task is executed in a [parallel flow](#parallel-flow). It starts by executing the given\nfunction and continues until the end of the task is detected.\n\nThe end of the task is detected when:\n- an exception is thrown by the task\n\n**or**\n\n- If the task was started by `warp.callAsPromise`: \n - the function given to `callAsPromise` has returned \n - **And**, if its returned value is a Promise, it is\n [fulfilled or rejected](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Promise#Description).\n\n- If the task was started by `warp.call` \n - The callback is called, \n - **And** the function given to `call` has returned. \n\nNote that this doesn't mean that `return` was executed, it means that the execution has\nreturned to its caller. For example in the following code the end is detected during the line\n`a = await 3` when `await` yields and `a` is still `2`.\n\n``` javascript\nlet a = 0;\nasync function compute(done) {\n a = 1;\n done();\n a = 2;\n a = await 3; // End is here at `await` before assignation of `a`\n return;\n}\n```\n\n**Warning:** If the task were to attempt to execute code after the end of execution were detected\n(e.g. with a `setImmediate`, `setTimeout`, ...), then the behavior would be unspecified. This\nmeans that if the function given to `call` is starting any asynchronous processing, calling\nthe `callback` must be the very last thing done by the task.\n\n## Execution context\n\nAn **execution context** is referring to everything accessible from the\n[scope](https://developer.mozilla.org/en-US/docs/Glossary/Scope) of the considered\nfunction at a given point of the execution. This includes \n- parameters of the call, \n- local, free and global variables accessed by the function called or by all functions potentially\n called directly or indirectly, \n- any reachable objects (objects, arrays, functions, symbols) from the above defined parameters/variables. \n","readmeFilename":"README.md","_id":"warp@1.1.0-dev.75","_npmVersion":"6.4.1","_nodeVersion":"8.15.0","_npmUser":{"name":"lcars","email":"welcome@scaledynamics.io"},"dist":{"integrity":"sha512-T64AsT4ErBAm6rNueKtwMhqloUy54awTWaSMf11yLjt+QzrvriApX9j2nMU3WKrL5zphkRxev5E8QEEIb2Ebtw==","shasum":"a31c5a20eb3b802b480f628a00276db3136c0ef0","tarball":"https://registry.npmjs.org/warp/-/warp-1.1.0-dev.75.tgz","fileCount":4,"unpackedSize":14110,"npm-signature":"-----BEGIN PGP SIGNATURE-----\r\nVersion: OpenPGP.js v3.0.4\r\nComment: https://openpgpjs.org\r\n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\nLgoe\r\n=ef08\r\n-----END PGP SIGNATURE-----\r\n","signatures":[{"keyid":"SHA256:jl3bwswu80PjjokCgh0o2w5c2U4LhQAE57gj9cz1kzA","sig":"MEUCIQD/E13ZTBvvPPzvNGylb0pNcD+JNMIaI+R0bQmtbgNLJgIgLWgj5/o0MYsRCi/L5IHrBgdEsc6axXhu9gOctsPH8ec="}]},"maintainers":[{"email":"jpl@scaledynamics.io","name":"jpl-scale"},{"email":"welcome@scaledynamics.io","name":"lcars"},{"email":"gc@scaledynamics.io","name":"scalejs"}],"directories":{},"_npmOperationalInternal":{"host":"s3://npm-registry-packages","tmp":"tmp/warp_1.1.0-dev.75_1549996340174_0.9156559761158185"},"_hasShrinkwrap":false,"deprecated":"Internal version, please, update to v1.1.0 minimum"},"1.1.0-dev.101":{"name":"warp","version":"1.1.0-dev.101","author":{"name":"ScaleDynamics SAS"},"license":"MIT","main":"warp.js","repository":{"type":"git","url":"git+https://github.com/ScaleDynamics/warp.git"},"description":"Warp is an API to run JavaScript functions in parallel: get the most of multi-core systems, shorten response time & intensive computations.","keywords":["node","starnode","parallel","concurrent","performance","speed","cpu","child_process","worker","workers","thread","threads","worker_threads","async","asynchronous"],"bugs":{"url":"https://github.com/ScaleDynamics/warp/issues"},"homepage":"https://scaledynamics.io/","dependencies":{},"build":{"date":"2019-02-15T14:10:15.170Z","user":"2834254","host":"dedi-03-ovh","sha":"91b057303e907f9067fa3e563ec5d9c70e4db617","id":"47698812","branch":"master"},"_resolved":"","_integrity":"","_from":"file:dist/warp-1.1.0-dev.101.tgz","readme":"[](https://scaledynamics.io)\n\n# Warp\n\n_Warp_ is an API allowing easy parallel execution of JavaScript code, at the\nsame physical time as the main JavaScript thread and as other threads.\n\n```javascript\n// runs `f` in parallel\nwarp.call(fnct, , cb);\n```\n\nDiscover Warp in this short YouTube video:\n\n[](https://www.youtube.com/watch?v=d54AOpRgfg0)\n\n## Installing\n\n_Warp_ module is an API and is not providing support for execution. You will need\nto acquire a [**Warp runtime**](https://redirect.scaledynamics.io/warp/runtime) to use it.\n\nTo add _Warp_ API to your project:\n\n```\n$ npm install warp\n```\n\n## How to use it\n\n_Warp_ offers two main functions starting a [_warp_ task](#warp-task): `warp.call` and `warp.callAsPromise`.\nWe say that they perform a _warp_ call. By extension, we also say that code\n_warps_ a function or that the function is _warped_.\n\nHere is a very simple illustrative code sample where a CPU intensive function (`computePrimeFactorization`)\nis executed in parallel by a _warp_ call keeping the event loop free for any other processing. If you\nwant to see complete code, browse the GitHub repository.\n\nThe first example uses a callback-based function, whereas the second uses a Promise-based function.\n\n### With callback\n\n``` javascript\nconst warp = require('warp');\n\nfunction computePrimeFactorization(n, done) {\n // Compute f\n done(f);\n}\n\nwarp.call(computePrimeFactorization, 9007199254740991,\n (a) => console.log(`Prime factors of ${a.value} are ${a.factors}`));\n```\n\nPrints out\n> Prime factors of 9007199254740991 are 6361,69431,20394401\n\n### With promise\n\n``` javascript\nconst warp = require('warp');\n\nfunction computePrimeFactorization(n) {\n // Compute f\n return f;\n}\n\nlet a = await warp.callAsPromise(computePrimeFactorization, 9007199254740991);\nconsole.log(`Prime factors of ${a.value} are ${a.factors}`);\n```\n\nPrints out\n> Prime factors of 9007199254740991 are 6361,69431,20394401\n\n## How it works\n\n\n\nWhen you _warp_ call a function, the [execution context](#execution-context) (i.e. everything\nreachable from the function scope) is captured, then this context and the _warped_ function are\nsent to a distinct and [parallel _warp_ thread](#parallel-thread) (see label `A` in the drawing).\n\nOnce the [_warp_ task](#warp-task) is finished, the parallel [context](#execution-context) is\ncaptured and sent back to the main JavaScript thread (see label `B` in the drawing). Then,\nin an event task of the main thread, the context is updated, and:\n\n- If the _warp_ call is `call`, the callback is executed in the main thread, with the arguments\ngiven to the callback in the parallel _warp_ thread.\n- If the _warp_ call is `callAsPromise`, the Promise returned by `callAsPromise` is resolved or\nrejected with the value or the exception obtained at the end of the parallel _warp_ thread.\n\n### Scope\n\nThe _warped_ functions can read and modify anything reachable from their\n[scope](https://developer.mozilla.org/en-US/docs/Glossary/Scope).\n\nIn the following sample, the variable `o` is defined as a free variable (outside of the function).\nThe _warped_ function can read it, and also modify the object. Modifications made to `o` in the parallel\n_warp_ thread are applied and visible in the main thread.\n\n``` javascript\nconst warp = require('warp');\n\nlet object = {};\nfunction computePrimeFactorization(n) {\n // Compute f\n o.result = f;\n}\n\nawait warp.callAsPromise(computePrimeFactorization, 9007199254740991);\nconsole.log(`Prime factors of ${object.value} are ${object.factors}`);\n```\n\nPrints out\n> Prime factors of 9007199254740991 are 6361,69431,20394401\n\n### Shared resources and concurrency\n\n_Warp_ offers no new synchronization or semaphore mechanism. If you need to manage concurrent access\nto a value, you'll have to keep the modifying code in the main thread.\n\nIn the following example, we compute several prime factorizations in parallel.\n\n``` javascript\nconst warp = require('warp');\n\nlet primeFactorizations = [];\n\nfunction computePrimeFactorization(index, n) {\n // Compute f\n primeFactorizations[index] = f;\n}\n\nlet promises = []\nfor(let i = 0; i < 8; i++) {\n promises.push(warp.callAsPromise(computePrimeFactorization, i, 9007174991 + i));\n}\n\nawait Promise.all(promises);\n\nconsole.log(`Prime factorizations: %j`, primeFactorizations);\n```\n\nPrints out\n> Prime factorizations: [{\"value\":9007174991,\"factors\":[17,131,4044533]},{\"value\":9007174997,\"factors\":{\"0\":59,\"1\":109,\"2\":1400587,\"value\":9007174993,\"factors\":[12071,746183]}},{\"0\":59,\"1\":109,\"2\":1400587,\"value\":9007174993,\"factors\":[12071,746183]},{\"0\":2,\"1\":2,\"2\":2251793749,\"value\":9007174994,\"factors\":[2,37,53,2296577]},{\"value\":9007174995,\"factors\":[3,5,7,13,41,227,709]},{\"value\":9007174997,\"factors\":{\"0\":59,\"1\":109,\"2\":1400587,\"value\":9007174993,\"factors\":[12071,746183]}},{\"value\":9007174997,\"factors\":{\"0\":59,\"1\":109,\"2\":1400587,\"value\":9007174993,\"factors\":[12071,746183]}},{\"value\":9007174998,\"factors\":[2,3,3,3,19,43,204161]}]\n\nBut you need to be carefull about parallel access to shared variables or properties.\n\nFor instance, the following example shows bad usage of a shared value causing indetermism. There, you\ndon't know in which order the additions will be made, but it is guaranteed that each `fnct` sees\nthe initial value of `v` as `4`. This means you don't know what the final value of `v` will be, you\njust know it will be either `7` or `8`.\n\n``` javascript\nconst warp = require('warp');\n\nlet v = 4;\nfunction fnct(num) {\n let inc = num;\n v += inc;\n return;\n}\n\nlet promises = []\npromises.push(warp.callAsPromise(fnct, 3));\npromises.push(warp.callAsPromise(fnct, 4));\n\nawait Promise.all(promises);\n\nconsole.log(`Value: ${v}`);\n```\n\nTo obtain the correct behavior in this example, you'll need to apply the changes to the shared\nvariable in the main thread by using the `.then` of the promise.\n\n``` javascript\nconst warp = require('warp');\n\nlet v = 4;\nfunction fnct(num) {\n let inc = num;\n return inc;\n}\n\nlet promises = []\npromises.push(warp.callAsPromise(fnct, 3).then((inc) => v += inc));\npromises.push(warp.callAsPromise(fnct, 4).then((inc) => v += inc));\n\nawait Promise.all(promises);\n\nconsole.log(`Value: ${v}`);\n```\n\nPrints out\n> Value: 11\n\nThis way it'll end up with `11` as the final value.\n\n# Definitions\n\n## Parallel thread\n\nA **parallel thread** is a JavaScript execution thread distinct from the main JavaScript execution thread. The\nmain thread and some parallel _warp_ threads are running at the same physical time. _Warp_ threads don't necessarily belong to the same process. It can come from the fork of a new process or even in a remote machine.\n\n## Warp task\n\nA **warp task** is started by a _warp_ call (a call to `warp.call` or `warp.callAsPromise`).\nThe task is executed in a [parallel thread](#parallel-thread). It starts by executing the given\nfunction and continues until the end of the task is detected.\n\nThe end of the task is detected when:\n- an exception is thrown by the task\n\n**or**\n\n- If the task was started by `warp.callAsPromise`: \n - the function given to `callAsPromise` has returned \n - **And**, if its returned value is a Promise, it is\n [fulfilled or rejected](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Promise#Description).\n\n- If the task was started by `warp.call` \n - The callback is called, \n - **And** the function given to `call` has returned. \n\nNote that this doesn't mean that `return` was executed, it means that the execution has\nreturned to its caller. For example in the following code the end is detected during the line\n`a = await 3` when `await` yields and `a` is still `2`.\n\n``` javascript\nlet a = 0;\nasync function fnct(done) {\n a = 1;\n done();\n a = 2;\n a = await 3; // End is here at `await` before assignation of `a`\n return;\n}\n```\n\n**Warning:** If the task were to attempt to execute code after the end of execution were detected\n(e.g. with a `setImmediate`, `setTimeout`, ...), then the behavior would be unspecified. This\nmeans that if the function given to `call` is starting any asynchronous processing, calling\nthe `callback` must be the very last thing done by the task.\n\n## Execution context\n\nAn **execution context** is referring to everything accessible from the\n[scope](https://developer.mozilla.org/en-US/docs/Glossary/Scope) of the considered\nfunction at a given point of the execution. This includes \n- parameters of the call, \n- local, free and global variables accessed by the function called or by all functions potentially\n called directly or indirectly, \n- any reachable objects (objects, arrays, functions, symbols) from the above defined parameters/variables. \n","readmeFilename":"README.md","_id":"warp@1.1.0-dev.101","_npmVersion":"6.4.1","_nodeVersion":"8.15.0","_npmUser":{"name":"lcars","email":"welcome@scaledynamics.io"},"dist":{"integrity":"sha512-tax1Y7QHCA7AJdE4atdjee77Hj/jhN7ocwNNKFfUrYZsdoExCF3yluRBTIVoztK5Ka5fdGIZB5lLvAT4MyJHzQ==","shasum":"51640f4aa7817092c5706c00d3261af268adf76b","tarball":"https://registry.npmjs.org/warp/-/warp-1.1.0-dev.101.tgz","fileCount":4,"unpackedSize":15260,"npm-signature":"-----BEGIN PGP SIGNATURE-----\r\nVersion: OpenPGP.js v3.0.4\r\nComment: 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computations.","keywords":["node","starnode","parallel","concurrent","performance","speed","cpu","child_process","worker","workers","thread","threads","worker_threads","async","asynchronous"],"bugs":{"url":"https://github.com/ScaleDynamics/warp/issues"},"homepage":"https://scaledynamics.io/","dependencies":{},"build":{"date":"2019-03-04T13:24:00.682Z","user":"2834254","host":"dedi-02-ovh","sha":"bfca2213fcb2b20fdc651efa9501bb2b9f213741","id":"50193378","branch":"master"},"_resolved":"","_integrity":"","_from":"file:dist/warp-1.1.0-dev.112.tgz","readme":"[](https://scaledynamics.io)\n\n# Warp\n\n_Warp_ is an API allowing easy parallel execution of JavaScript code, at the\nsame physical time as the main JavaScript thread and as other threads.\n\n```javascript\n// runs `f` in parallel\nwarp.call(fnct, , cb);\n```\n\nDiscover Warp in this short YouTube video:\n\n[](https://www.youtube.com/watch?v=d54AOpRgfg0)\n\n## Installing\n\n_Warp_ module is an API and is not providing support for execution. You will need\nto acquire a [**Warp runtime**](https://redirect.scaledynamics.io/warp/runtime) to use it.\n\nTo add _Warp_ API to your project:\n\n```\n$ npm install warp\n```\n\n## How to use it\n\n_Warp_ offers two main functions starting a [_warp_ task](#warp-task): `warp.call` and `warp.callAsPromise`.\nWe say that they perform a _warp_ call. By extension, we also say that code\n_warps_ a function or that the function is _warped_.\n\nHere is a very simple illustrative code sample where a CPU intensive function (`computePrimeFactorization`)\nis executed in parallel by a _warp_ call keeping the event loop free for any other processing. If you\nwant to see complete code, browse the [repository](https://github.com/ScaleDynamics/warp/tree/bfca2213fcb2b20fdc651efa9501bb2b9f213741/example).\n\nThe first example uses a callback-based function, whereas the second uses a Promise-based function.\n\n### With callback\n\n``` javascript\nconst warp = require('warp');\n\nfunction computePrimeFactorization(n, done) {\n // Compute f\n done(f);\n}\n\nwarp.call(computePrimeFactorization, 9007199254740991,\n (a) => console.log(`Prime factors of ${a.value} are ${a.factors}`));\n```\n\nPrints out\n> Prime factors of 9007199254740991 are 6361,69431,20394401\n\n### With promise\n\n``` javascript\nconst warp = require('warp');\n\nfunction computePrimeFactorization(n) {\n // Compute f\n return f;\n}\n\nlet a = await warp.callAsPromise(computePrimeFactorization, 9007199254740991);\nconsole.log(`Prime factors of ${a.value} are ${a.factors}`);\n```\n\nPrints out\n> Prime factors of 9007199254740991 are 6361,69431,20394401\n\n## How it works\n\n\n\nWhen you _warp_ call a function, the [execution context](#execution-context) (i.e. everything\nreachable from the function scope) is captured, then this context and the _warped_ function are\nsent to a distinct and [parallel _warp_ thread](#parallel-thread) (see label `A` in the drawing).\n\nOnce the [_warp_ task](#warp-task) is finished, the parallel [context](#execution-context) is\ncaptured and sent back to the main JavaScript thread (see label `B` in the drawing). Then,\nin an event task of the main thread, the context is updated, and:\n\n- If the _warp_ call is `call`, the callback is executed in the main thread, with the arguments\ngiven to the callback in the parallel _warp_ thread.\n- If the _warp_ call is `callAsPromise`, the Promise returned by `callAsPromise` is resolved or\nrejected with the value or the exception obtained at the end of the parallel _warp_ thread.\n\n### Scope\n\nThe _warped_ functions can read and modify anything reachable from their\n[scope](https://developer.mozilla.org/en-US/docs/Glossary/Scope).\n\nIn the following sample, the variable `o` is defined as a free variable (outside of the function).\nThe _warped_ function can read it, and also modify the object. Modifications made to `o` in the parallel\n_warp_ thread are applied and visible in the main thread.\n\n``` javascript\nconst warp = require('warp');\n\nlet object = {};\nfunction computePrimeFactorization(n) {\n // Compute f\n o.result = f;\n}\n\nawait warp.callAsPromise(computePrimeFactorization, 9007199254740991);\nconsole.log(`Prime factors of ${object.value} are ${object.factors}`);\n```\n\nPrints out\n> Prime factors of 9007199254740991 are 6361,69431,20394401\n\n### Shared resources and concurrency\n\n_Warp_ offers no new synchronization or semaphore mechanism. If you need to manage concurrent access\nto a value, you'll have to keep the modifying code in the main thread.\n\nIn the following example, we compute several prime factorizations in parallel.\n\n``` javascript\nconst warp = require('warp');\n\nlet primeFactorizations = [];\n\nfunction computePrimeFactorization(index, n) {\n // Compute f\n primeFactorizations[index] = f;\n}\n\nlet promises = []\nfor(let i = 0; i < 8; i++) {\n promises.push(warp.callAsPromise(computePrimeFactorization, i, 9007174991 + i));\n}\n\nawait Promise.all(promises);\n\nconsole.log(`Prime factorizations: %j`, primeFactorizations);\n```\n\nPrints out\n> Prime factorizations: [{\"value\":9007174991,\"factors\":[17,131,4044533]},{\"value\":9007174997,\"factors\":{\"0\":59,\"1\":109,\"2\":1400587,\"value\":9007174993,\"factors\":[12071,746183]}},{\"0\":59,\"1\":109,\"2\":1400587,\"value\":9007174993,\"factors\":[12071,746183]},{\"0\":2,\"1\":2,\"2\":2251793749,\"value\":9007174994,\"factors\":[2,37,53,2296577]},{\"value\":9007174995,\"factors\":[3,5,7,13,41,227,709]},{\"value\":9007174997,\"factors\":{\"0\":59,\"1\":109,\"2\":1400587,\"value\":9007174993,\"factors\":[12071,746183]}},{\"value\":9007174997,\"factors\":{\"0\":59,\"1\":109,\"2\":1400587,\"value\":9007174993,\"factors\":[12071,746183]}},{\"value\":9007174998,\"factors\":[2,3,3,3,19,43,204161]}]\n\nBut you need to be carefull about parallel access to shared variables or properties.\n\nFor instance, the following example shows bad usage of a shared value causing indetermism. There, you\ndon't know in which order the additions will be made, but it is guaranteed that each `fnct` sees\nthe initial value of `v` as `4`. This means you don't know what the final value of `v` will be, you\njust know it will be either `7` or `8`.\n\n``` javascript\nconst warp = require('warp');\n\nlet v = 4;\nfunction fnct(num) {\n let inc = num;\n v += inc;\n return;\n}\n\nlet promises = []\npromises.push(warp.callAsPromise(fnct, 3));\npromises.push(warp.callAsPromise(fnct, 4));\n\nawait Promise.all(promises);\n\nconsole.log(`Value: ${v}`);\n```\n\nTo obtain the correct behavior in this example, you'll need to apply the changes to the shared\nvariable in the main thread by using the `.then` of the promise.\n\n``` javascript\nconst warp = require('warp');\n\nlet v = 4;\nfunction fnct(num) {\n let inc = num;\n return inc;\n}\n\nlet promises = []\npromises.push(warp.callAsPromise(fnct, 3).then((inc) => v += inc));\npromises.push(warp.callAsPromise(fnct, 4).then((inc) => v += inc));\n\nawait Promise.all(promises);\n\nconsole.log(`Value: ${v}`);\n```\n\nPrints out\n> Value: 11\n\nThis way it'll end up with `11` as the final value.\n\n# Definitions\n\n## Parallel thread\n\nA **parallel thread** is a JavaScript execution thread distinct from the main JavaScript execution thread. The\nmain thread and some parallel _warp_ threads are running at the same physical time. _Warp_ threads don't necessarily belong to the same process. It can come from the fork of a new process or even in a remote machine.\n\n## Warp task\n\nA **warp task** is started by a _warp_ call (a call to `warp.call` or `warp.callAsPromise`).\nThe task is executed in a [parallel thread](#parallel-thread). It starts by executing the given\nfunction and continues until the end of the task is detected.\n\nThe end of the task is detected when:\n- an exception is thrown by the task\n\n**or**\n\n- If the task was started by `warp.callAsPromise`: \n - the function given to `callAsPromise` has returned \n - **And**, if its returned value is a Promise, it is\n [fulfilled or rejected](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Promise#Description).\n\n- If the task was started by `warp.call` \n - The callback is called, \n - **And** the function given to `call` has returned. \n\nNote that this doesn't mean that `return` was executed, it means that the execution has\nreturned to its caller. For example in the following code the end is detected during the line\n`a = await 3` when `await` yields and `a` is still `2`.\n\n``` javascript\nlet a = 0;\nasync function fnct(done) {\n a = 1;\n done();\n a = 2;\n a = await 3; // End is here at `await` before assignation of `a`\n return;\n}\n```\n\n**Warning:** If the task were to attempt to execute code after the end of execution were detected\n(e.g. with a `setImmediate`, `setTimeout`, ...), then the behavior would be unspecified. This\nmeans that if the function given to `call` is starting any asynchronous processing, calling\nthe `callback` must be the very last thing done by the task.\n\n## Execution context\n\nAn **execution context** is referring to everything accessible from the\n[scope](https://developer.mozilla.org/en-US/docs/Glossary/Scope) of the considered\nfunction at a given point of the execution. This includes \n- parameters of the call, \n- local, free and global variables accessed by the function called or by all functions potentially\n called directly or indirectly, \n- any reachable objects (objects, arrays, functions, symbols) from the above defined parameters/variables. \n","readmeFilename":"README.md","_id":"warp@1.1.0-dev.112","_npmVersion":"6.4.1","_nodeVersion":"8.15.1","_npmUser":{"name":"lcars","email":"welcome@scaledynamics.io"},"dist":{"integrity":"sha512-FCLUykNGnaMTNYUhe3mcDQe0MmXDOreghLy4FsTWBP3Vk/CjZjrlCbuxa+z/vGj6Jf/kyFtc4S2mpkLtVCzOYA==","shasum":"dbaafee33422e1978dada0d3129a0e0b212f123e","tarball":"https://registry.npmjs.org/warp/-/warp-1.1.0-dev.112.tgz","fileCount":4,"unpackedSize":15353,"npm-signature":"-----BEGIN PGP SIGNATURE-----\r\nVersion: OpenPGP.js v3.0.4\r\nComment: 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computations.","keywords":["node","starnode","parallel","concurrent","performance","speed","cpu","child_process","worker","workers","thread","threads","worker_threads","async","asynchronous"],"bugs":{"url":"https://github.com/ScaleDynamics/warp/issues"},"homepage":"https://scaledynamics.io/","dependencies":{},"build":{"date":"2019-08-02T13:53:06.702Z","user":"2834254","host":"dedi-03-ovh","sha":"95888a4ec1d0664bd68e8d45c4969b01a6ec356b","id":"74426115","branch":"master"},"_resolved":"","_integrity":"","_from":"file:dist/warp-1.1.0-dev.144.tgz","readme":"[](https://scaledynamics.io)\n\n# Warp\n\n_Warp_ is an API allowing easy parallel execution of JavaScript code, at the\nsame physical time as the main JavaScript thread and as other threads.\n\n```javascript\n// runs `fnct` in parallel\nwarp.call(fnct, , cb);\n```\n\nDiscover Warp in this short YouTube video:\n\n[](https://www.youtube.com/watch?v=d54AOpRgfg0)\n\n## Installing\n\n_Warp_ module is an API and is not providing support for execution. You will need\nto acquire a [**Warp runtime**](https://redirect.scaledynamics.io/warp/runtime) to use it.\n\nTo add _Warp_ API to your project:\n\n```\n$ npm install warp\n```\n\n## How to use it\n\n_Warp_ offers two main functions starting a [_warp_ task](#warp-task): `warp.call` and `warp.callAsPromise`.\nWe say that they perform a _warp_ call. By extension, we also say that code\n_warps_ a function or that the function is _warped_.\n\nHere is a very simple illustrative code sample where a CPU intensive function (`computePrimeFactorization`)\nis executed in parallel by a _warp_ call keeping the event loop free for any other processing. If you\nwant to see complete code, browse the [repository](https://github.com/ScaleDynamics/warp/tree/95888a4ec1d0664bd68e8d45c4969b01a6ec356b/example).\n\nThe first example uses a callback-based function, whereas the second uses a Promise-based function.\n\n### With callback\n\n``` javascript\nconst warp = require('warp');\n\nfunction computePrimeFactorization(n, done) {\n // Compute `f`\n done(f);\n}\n\nwarp.call(computePrimeFactorization, 9007199254740991,\n (a) => console.log(`Prime factors of ${a.value} are ${a.factors}`));\n```\n\nPrints out\n> Prime factors of 9007199254740991 are 6361,69431,20394401\n\n### With promise\n\n``` javascript\nconst warp = require('warp');\n\nfunction computePrimeFactorization(n) {\n // Compute `f`\n return f;\n}\n\nlet a = await warp.callAsPromise(computePrimeFactorization, 9007199254740991);\nconsole.log(`Prime factors of ${a.value} are ${a.factors}`);\n```\n\nPrints out\n> Prime factors of 9007199254740991 are 6361,69431,20394401\n\n## How it works\n\n\n\nWhen you _warp_ call a function, the [execution context](#execution-context) (i.e. everything\nreachable from the function scope) is captured, then this context and the _warped_ function are\nsent to a distinct and [parallel _warp_ thread](#parallel-thread) (see label `A` in the drawing).\n\nOnce the [_warp_ task](#warp-task) is finished, the parallel [context](#execution-context) is\ncaptured and sent back to the main JavaScript thread (see label `B` in the drawing). Then,\nin an event task of the main thread, the context is updated, and:\n\n- If the _warp_ call is `call`, the callback is executed in the main thread, with the arguments\ngiven to the callback in the parallel _warp_ thread.\n- If the _warp_ call is `callAsPromise`, the Promise returned by `callAsPromise` is resolved or\nrejected with the value or the exception obtained at the end of the parallel _warp_ thread.\n\n### Scope\n\nThe _warped_ functions can read and modify anything reachable from their\n[scope](https://developer.mozilla.org/en-US/docs/Glossary/Scope).\n\nIn the following sample, the variable `o` is defined as a free variable (outside of the function).\nThe _warped_ function can read it, and also modify the object. Modifications made to `o` in the parallel\n_warp_ thread are applied and visible in the main thread.\n\n``` javascript\nconst warp = require('warp');\n\nlet o = {};\nfunction computePrimeFactorization(n) {\n // Compute `f`\n o.result = f;\n}\n\nawait warp.callAsPromise(computePrimeFactorization, 9007199254740991);\nconsole.log(`Prime factors of ${o.value} are ${o.factors}`);\n```\n\nPrints out\n> Prime factors of 9007199254740991 are 6361,69431,20394401\n\n### Shared resources and concurrency\n\n_Warp_ offers no new synchronization or semaphore mechanism. If you need to manage concurrent access\nto a value, you'll have to keep the modifying code in the main thread.\n\nIn the following example, we compute several prime factorizations in parallel.\n\n``` javascript\nconst warp = require('warp');\n\nlet primeFactorizations = [];\n\nfunction computePrimeFactorization(index, n) {\n // Compute `f`\n primeFactorizations[index] = f;\n}\n\nlet promises = []\nfor(let i = 0; i < 8; i++) {\n promises.push(warp.callAsPromise(computePrimeFactorization, i, 9007174991 + i));\n}\n\nawait Promise.all(promises);\n\nconsole.log(`Prime factorizations: %j`, primeFactorizations);\n```\n\nPrints out\n> Prime factorizations: [{\"value\":9007174991,\"factors\":[17,131,4044533]},{\"value\":9007174997,\"factors\":{\"0\":59,\"1\":109,\"2\":1400587,\"value\":9007174993,\"factors\":[12071,746183]}},{\"0\":59,\"1\":109,\"2\":1400587,\"value\":9007174993,\"factors\":[12071,746183]},{\"0\":2,\"1\":2,\"2\":2251793749,\"value\":9007174994,\"factors\":[2,37,53,2296577]},{\"value\":9007174995,\"factors\":[3,5,7,13,41,227,709]},{\"value\":9007174997,\"factors\":{\"0\":59,\"1\":109,\"2\":1400587,\"value\":9007174993,\"factors\":[12071,746183]}},{\"value\":9007174997,\"factors\":{\"0\":59,\"1\":109,\"2\":1400587,\"value\":9007174993,\"factors\":[12071,746183]}},{\"value\":9007174998,\"factors\":[2,3,3,3,19,43,204161]}]\n\nBut you need to be carefull about parallel access to shared variables or properties.\n\nFor instance, the following example shows bad usage of a shared value causing indetermism. There, you\ndon't know in which order the additions will be made, but it is guaranteed that each `fnct` sees\nthe initial value of `v` as `4`. This means you don't know what the final value of `v` will be, you\njust know it will be either `7` or `8`.\n\n``` javascript\nconst warp = require('warp');\n\nlet v = 4;\nfunction fnct(num) {\n let inc = num;\n v += inc;\n return;\n}\n\nlet promises = []\npromises.push(warp.callAsPromise(fnct, 3));\npromises.push(warp.callAsPromise(fnct, 4));\n\nawait Promise.all(promises);\n\nconsole.log(`Value: ${v}`);\n```\n\nTo obtain the correct behavior in this example, you'll need to apply the changes to the shared\nvariable in the main thread by using the `.then` of the promise.\n\n``` javascript\nconst warp = require('warp');\n\nlet v = 4;\nfunction fnct(num) {\n let inc = num;\n return inc;\n}\n\nlet promises = []\npromises.push(warp.callAsPromise(fnct, 3).then((inc) => v += inc));\npromises.push(warp.callAsPromise(fnct, 4).then((inc) => v += inc));\n\nawait Promise.all(promises);\n\nconsole.log(`Value: ${v}`);\n```\n\nPrints out\n> Value: 11\n\nThis way it'll end up with `11` as the final value.\n\n# Definitions\n\n## Parallel thread\n\nA **parallel thread** is a JavaScript execution thread distinct from the main JavaScript execution thread. The\nmain thread and some parallel _warp_ threads are running at the same physical time. _Warp_ threads don't necessarily belong to the same process. It can come from the fork of a new process or even in a remote machine.\n\n## Warp task\n\nA **warp task** is started by a _warp_ call (a call to `warp.call` or `warp.callAsPromise`).\nThe task is executed in a [parallel thread](#parallel-thread). It starts by executing the given\nfunction and continues until the end of the task is detected.\n\nThe end of the task is detected when:\n- an exception is thrown by the task\n\n**or**\n\n- If the task was started by `warp.callAsPromise`: \n - the function given to `callAsPromise` has returned \n - **And**, if its returned value is a Promise, it is\n [fulfilled or rejected](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Promise#Description).\n\n- If the task was started by `warp.call` \n - The callback is called, \n - **And** the function given to `call` has returned. \n\nNote that this doesn't mean that `return` was executed, it means that the execution has\nreturned to its caller. For example in the following code the end is detected during the line\n`a = await 3` when `await` yields and `a` is still `2`.\n\n``` javascript\nlet a = 0;\nasync function fnct(done) {\n a = 1;\n done();\n a = 2;\n a = await 3; // End is here at `await` before assignation of `a`\n return;\n}\n```\n\n**Warning:** If the task were to attempt to execute code after the end of execution were detected\n(e.g. with a `setImmediate`, `setTimeout`, ...), then the behavior would be unspecified. This\nmeans that if the function given to `call` is starting any asynchronous processing, calling\nthe `callback` must be the very last thing done by the task.\n\n## Execution context\n\nAn **execution context** is referring to everything accessible from the\n[scope](https://developer.mozilla.org/en-US/docs/Glossary/Scope) of the considered\nfunction at a given point of the execution. This includes \n- parameters of the call, \n- local, free and global variables accessed by the function called or by all functions potentially\n called directly or indirectly, \n- any reachable objects (objects, arrays, functions, symbols) from the above defined parameters/variables. \n","readmeFilename":"README.md","_id":"warp@1.1.0-dev.144","_npmVersion":"6.4.1","_nodeVersion":"8.16.0","_npmUser":{"name":"lcars","email":"welcome@scaledynamics.io"},"dist":{"integrity":"sha512-CwaM4Sl9H8Vtn0KSj40ZCJ/luCgcexM6W1FQ5Sb8WpeGnH/vNT6M0K6okWPGNK2LfqgTkqJJEY68rVmoBmQM2A==","shasum":"7be19ea60702dd8deef8dfa71637b16bd0fde24c","tarball":"https://registry.npmjs.org/warp/-/warp-1.1.0-dev.144.tgz","fileCount":4,"unpackedSize":16514,"npm-signature":"-----BEGIN PGP SIGNATURE-----\r\nVersion: OpenPGP.js v3.0.4\r\nComment: https://openpgpjs.org\r\n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\nBKqI\r\n=/Jop\r\n-----END PGP SIGNATURE-----\r\n","signatures":[{"keyid":"SHA256:jl3bwswu80PjjokCgh0o2w5c2U4LhQAE57gj9cz1kzA","sig":"MEQCIGXTYa3X1HXVK5y2xNDZHW8v68uKCkolS07hHWlaQqwJAiAV2bORi6VS9s4rGHGlZLqNO/K756xCGGXY3UwrjWPrWQ=="}]},"maintainers":[{"email":"jpl@scaledynamics.io","name":"jpl-scale"},{"email":"welcome@scaledynamics.io","name":"lcars"},{"email":"gc@scaledynamics.io","name":"scalejs"}],"directories":{},"_npmOperationalInternal":{"host":"s3://npm-registry-packages","tmp":"tmp/warp_1.1.0-dev.144_1564754286519_0.3244063778831663"},"_hasShrinkwrap":false},"1.2.0-dev.149":{"name":"warp","version":"1.2.0-dev.149","author":{"name":"ScaleDynamics SAS"},"license":"MIT","main":"warp.js","repository":{"type":"git","url":"git+https://github.com/ScaleDynamics/warp.git"},"description":"Warp is an API to run JavaScript functions in parallel: get the most of multi-core systems, shorten response time & intensive computations.","keywords":["node","starnode","parallel","concurrent","performance","speed","cpu","child_process","worker","workers","thread","threads","worker_threads","async","asynchronous"],"bugs":{"url":"https://github.com/ScaleDynamics/warp/issues"},"homepage":"https://scaledynamics.io/","dependencies":{},"build":{"date":"2019-08-09T14:25:55.464Z","user":"2834254","host":"dedi-02-ovh","sha":"d600e20784b2253b846f0301adb2f31aca328256","id":"75630920","branch":"master"},"_resolved":"","_integrity":"","_from":"file:dist/warp-1.2.0-dev.149.tgz","readme":"[](https://scaledynamics.io)\n\n# Warp\n\n_Warp_ is an API allowing easy parallel execution of JavaScript code, at the\nsame physical time as the main JavaScript thread and as other threads.\n\n```javascript\n// runs `fnct` in parallel\nwarp.call(fnct, , cb);\n```\n\nDiscover Warp in this short YouTube video:\n\n[](https://www.youtube.com/watch?v=d54AOpRgfg0)\n\n## Installing\n\n_Warp_ module is an API and is not providing support for execution. You will need\nto acquire a [**Warp runtime**](https://redirect.scaledynamics.io/warp/runtime) to use it.\n\nTo add _Warp_ API to your project:\n\n```\n$ npm install warp\n```\n\n## How to use it\n\n_Warp_ offers two main functions starting a [_warp_ task](#warp-task): `warp.call` and `warp.callAsPromise`.\nWe say that they perform a _warp_ call. By extension, we also say that code\n_warps_ a function or that the function is _warped_.\n\nHere is a very simple illustrative code sample where a CPU intensive function (`computePrimeFactorization`)\nis executed in parallel by a _warp_ call keeping the event loop free for any other processing. If you\nwant to see complete code, browse the [repository](https://github.com/ScaleDynamics/warp/tree/d600e20784b2253b846f0301adb2f31aca328256/example).\n\nThe first example uses a callback-based function, whereas the second uses a Promise-based function.\n\n### With callback\n\n``` javascript\nconst warp = require('warp');\n\nfunction computePrimeFactorization(n, done) {\n // Compute `f`\n done(f);\n}\n\nwarp.call(computePrimeFactorization, 9007199254740991,\n (a) => console.log(`Prime factors of ${a.value} are ${a.factors}`));\n```\n\nPrints out\n> Prime factors of 9007199254740991 are 6361,69431,20394401\n\n### With promise\n\n``` javascript\nconst warp = require('warp');\n\nfunction computePrimeFactorization(n) {\n // Compute `f`\n return f;\n}\n\nlet a = await warp.callAsPromise(computePrimeFactorization, 9007199254740991);\nconsole.log(`Prime factors of ${a.value} are ${a.factors}`);\n```\n\nPrints out\n> Prime factors of 9007199254740991 are 6361,69431,20394401\n\n## How it works\n\n\n\nWhen you _warp_ call a function, the [execution context](#execution-context) (i.e. everything\nreachable from the function scope) is captured, then this context and the _warped_ function are\nsent to a distinct and [parallel _warp_ thread](#parallel-thread) (see label `A` in the drawing).\n\nOnce the [_warp_ task](#warp-task) is finished, the parallel [context](#execution-context) is\ncaptured and sent back to the main JavaScript thread (see label `B` in the drawing). Then,\nin an event task of the main thread, the context is updated, and:\n\n- If the _warp_ call is `call`, the callback is executed in the main thread, with the arguments\ngiven to the callback in the parallel _warp_ thread.\n- If the _warp_ call is `callAsPromise`, the Promise returned by `callAsPromise` is resolved or\nrejected with the value or the exception obtained at the end of the parallel _warp_ thread.\n\n### Scope\n\nThe _warped_ functions can read and modify anything reachable from their\n[scope](https://developer.mozilla.org/en-US/docs/Glossary/Scope).\n\nIn the following sample, the variable `o` is defined as a free variable (outside of the function).\nThe _warped_ function can read it, and also modify the object. Modifications made to `o` in the parallel\n_warp_ thread are applied and visible in the main thread.\n\n``` javascript\nconst warp = require('warp');\n\nlet o = {};\nfunction computePrimeFactorization(n) {\n // Compute `f`\n o.result = f;\n}\n\nawait warp.callAsPromise(computePrimeFactorization, 9007199254740991);\nconsole.log(`Prime factors of ${o.value} are ${o.factors}`);\n```\n\nPrints out\n> Prime factors of 9007199254740991 are 6361,69431,20394401\n\n### Shared resources and concurrency\n\n_Warp_ offers no new synchronization or semaphore mechanism. If you need to manage concurrent access\nto a value, you'll have to keep the modifying code in the main thread.\n\nIn the following example, we compute several prime factorizations in parallel.\n\n``` javascript\nconst warp = require('warp');\n\nlet primeFactorizations = [];\n\nfunction computePrimeFactorization(index, n) {\n // Compute `f`\n primeFactorizations[index] = f;\n}\n\nlet promises = []\nfor(let i = 0; i < 8; i++) {\n promises.push(warp.callAsPromise(computePrimeFactorization, i, 9007174991 + i));\n}\n\nawait Promise.all(promises);\n\nconsole.log(`Prime factorizations: %j`, primeFactorizations);\n```\n\nPrints out\n> Prime factorizations: [{\"value\":9007174991,\"factors\":[17,131,4044533]},{\"value\":9007174997,\"factors\":{\"0\":59,\"1\":109,\"2\":1400587,\"value\":9007174993,\"factors\":[12071,746183]}},{\"0\":59,\"1\":109,\"2\":1400587,\"value\":9007174993,\"factors\":[12071,746183]},{\"0\":2,\"1\":2,\"2\":2251793749,\"value\":9007174994,\"factors\":[2,37,53,2296577]},{\"value\":9007174995,\"factors\":[3,5,7,13,41,227,709]},{\"value\":9007174997,\"factors\":{\"0\":59,\"1\":109,\"2\":1400587,\"value\":9007174993,\"factors\":[12071,746183]}},{\"value\":9007174997,\"factors\":{\"0\":59,\"1\":109,\"2\":1400587,\"value\":9007174993,\"factors\":[12071,746183]}},{\"value\":9007174998,\"factors\":[2,3,3,3,19,43,204161]}]\n\nBut you need to be carefull about parallel access to shared variables or properties.\n\nFor instance, the following example shows bad usage of a shared value causing indetermism. There, you\ndon't know in which order the additions will be made, but it is guaranteed that each `fnct` sees\nthe initial value of `v` as `4`. This means you don't know what the final value of `v` will be, you\njust know it will be either `7` or `8`.\n\n``` javascript\nconst warp = require('warp');\n\nlet v = 4;\nfunction fnct(num) {\n let inc = num;\n v += inc;\n return;\n}\n\nlet promises = []\npromises.push(warp.callAsPromise(fnct, 3));\npromises.push(warp.callAsPromise(fnct, 4));\n\nawait Promise.all(promises);\n\nconsole.log(`Value: ${v}`);\n```\n\nTo obtain the correct behavior in this example, you'll need to apply the changes to the shared\nvariable in the main thread by using the `.then` of the promise.\n\n``` javascript\nconst warp = require('warp');\n\nlet v = 4;\nfunction fnct(num) {\n let inc = num;\n return inc;\n}\n\nlet promises = []\npromises.push(warp.callAsPromise(fnct, 3).then((inc) => v += inc));\npromises.push(warp.callAsPromise(fnct, 4).then((inc) => v += inc));\n\nawait Promise.all(promises);\n\nconsole.log(`Value: ${v}`);\n```\n\nPrints out\n> Value: 11\n\nThis way it'll end up with `11` as the final value.\n\n### Use transferable objects\n\n``` javascript\nlet arrayBuffer = new ArrayBuffer(8);\nwarp.markTransferable(arrayBuffer);\n```\n\nAs for the Worker.postMessage method, some objects can be identified as transferable. You must pass all your Transferable objects to _warp_ markTransferable function to transfer these objects. In that case, it becomes unusable (neutered) in the main thread and becomes available only to the parallel thread it was sent to.\nTransferable objects are instances of classes like ArrayBuffer, MessagePort, OffSceenCanvas or ImageBitmap objects.\nArrayBuffer can be transferred conventionally but this type of transfer is faster.\n\n# Definitions\n\n## Parallel thread\n\nA **parallel thread** is a JavaScript execution thread distinct from the main JavaScript execution thread. The\nmain thread and some parallel _warp_ threads are running at the same physical time. _Warp_ threads don't necessarily belong to the same process. It can come from the fork of a new process or even in a remote machine.\n\n## Warp task\n\nA **warp task** is started by a _warp_ call (a call to `warp.call` or `warp.callAsPromise`).\nThe task is executed in a [parallel thread](#parallel-thread). It starts by executing the given\nfunction and continues until the end of the task is detected.\n\nThe end of the task is detected when:\n- an exception is thrown by the task\n\n**or**\n\n- If the task was started by `warp.callAsPromise`: \n - the function given to `callAsPromise` has returned \n - **And**, if its returned value is a Promise, it is\n [fulfilled or rejected](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Promise#Description).\n\n- If the task was started by `warp.call` \n - The callback is called, \n - **And** the function given to `call` has returned. \n\nNote that this doesn't mean that `return` was executed, it means that the execution has\nreturned to its caller. For example in the following code the end is detected during the line\n`a = await 3` when `await` yields and `a` is still `2`.\n\n``` javascript\nlet a = 0;\nasync function fnct(done) {\n a = 1;\n done();\n a = 2;\n a = await 3; // End is here at `await` before assignation of `a`\n return;\n}\n```\n\n**Warning:** If the task were to attempt to execute code after the end of execution were detected\n(e.g. with a `setImmediate`, `setTimeout`, ...), then the behavior would be unspecified. This\nmeans that if the function given to `call` is starting any asynchronous processing, calling\nthe `callback` must be the very last thing done by the task.\n\n## Execution context\n\nAn **execution context** is referring to everything accessible from the\n[scope](https://developer.mozilla.org/en-US/docs/Glossary/Scope) of the considered\nfunction at a given point of the execution. This includes \n- parameters of the call, \n- local, free and global variables accessed by the function called or by all functions potentially\n called directly or indirectly, \n- any reachable objects (objects, arrays, functions, symbols) from the above defined parameters/variables. \n","readmeFilename":"README.md","_id":"warp@1.2.0-dev.149","_npmVersion":"6.4.1","_nodeVersion":"8.16.0","_npmUser":{"name":"lcars","email":"welcome@scaledynamics.io"},"dist":{"integrity":"sha512-f71INzw0XSzxG8cwJY90ATnzyZM8Z1KaYCJIK0cm6c3VUkSfB4823vqxW5c//S21QKMNFgVV+odpPJYi4ywVjw==","shasum":"472e5472d13b6e8de5e7ed07a5de78806a3d6121","tarball":"https://registry.npmjs.org/warp/-/warp-1.2.0-dev.149.tgz","fileCount":4,"unpackedSize":17537,"npm-signature":"-----BEGIN PGP SIGNATURE-----\r\nVersion: OpenPGP.js v3.0.4\r\nComment: https://openpgpjs.org\r\n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\nl3yv\r\n=0PgE\r\n-----END PGP SIGNATURE-----\r\n","signatures":[{"keyid":"SHA256:jl3bwswu80PjjokCgh0o2w5c2U4LhQAE57gj9cz1kzA","sig":"MEQCIA1SlCmDX2Y1GQQAUXNUfJcemSuYwJsvpN39yU3z/wnzAiAYHP8CUa//wokB7w0avviFe14jNgHaON3a/8hFVk67Hg=="}]},"maintainers":[{"email":"jpl@scaledynamics.io","name":"jpl-scale"},{"email":"welcome@scaledynamics.io","name":"lcars"},{"email":"gc@scaledynamics.io","name":"scalejs"}],"directories":{},"_npmOperationalInternal":{"host":"s3://npm-registry-packages","tmp":"tmp/warp_1.2.0-dev.149_1565361638213_0.8129423835541667"},"_hasShrinkwrap":false},"1.2.0-dev.161":{"name":"warp","version":"1.2.0-dev.161","author":{"name":"ScaleDynamics SAS"},"license":"MIT","main":"warp.js","repository":{"type":"git","url":"git+https://github.com/ScaleDynamics/warp.git"},"description":"Warp is an API to run JavaScript functions in parallel: get the most of multi-core systems, shorten response time & intensive computations.","keywords":["node","starnode","parallel","concurrent","performance","speed","cpu","child_process","worker","workers","thread","threads","worker_threads","async","asynchronous"],"bugs":{"url":"https://github.com/ScaleDynamics/warp/issues"},"homepage":"https://scaledynamics.io/","dependencies":{},"build":{"date":"2019-09-18T15:48:07.869Z","user":"2834254","host":"dedi-02-ovh","sha":"ea9ce1b983ead05aacdeddf1891c6e09bf5cd396","id":"82996231","branch":"master"},"_resolved":"","_integrity":"","_from":"file:dist/warp-1.2.0-dev.161.tgz","readme":"[](https://warpjs.com)\n\n# Warp\n\n_Warp_ is an API allowing easy parallel execution of JavaScript code, at the\nsame physical time as the main JavaScript thread and as other threads.\n\n```javascript\n// runs `fnct` in parallel\nwarp.call(fnct, , cb);\n```\n\nDiscover Warp in this short YouTube video:\n\n[](https://www.youtube.com/watch?v=d54AOpRgfg0)\n\n## Installing\n\n_Warp_ module is an API and is not providing support for execution. You will need\nto acquire a [**Warp runtime**](https://redirect.scaledynamics.io/warp/runtime) to use it.\n\nTo add _Warp_ API to your project:\n\n```\n$ npm install warp\n```\n\n## How to use it\n\n_Warp_ offers two main functions starting a [_warp_ task](#warp-task): `warp.call` and `warp.callAsPromise`.\nWe say that they perform a _warp_ call. By extension, we also say that code\n_warps_ a function or that the function is _warped_.\n\nHere is a very simple illustrative code sample where a CPU intensive function (`computePrimeFactorization`)\nis executed in parallel by a _warp_ call keeping the event loop free for any other processing. If you\nwant to see complete code, browse the [repository](https://github.com/ScaleDynamics/warp/tree/ea9ce1b983ead05aacdeddf1891c6e09bf5cd396/example).\n\nThe first example uses a callback-based function, whereas the second uses a Promise-based function.\n\n### With callback\n\n``` javascript\nconst warp = require('warp');\n\nfunction computePrimeFactorization(n, done) {\n // Compute `f`\n done(f);\n}\n\nwarp.call(computePrimeFactorization, 9007199254740991,\n (a) => console.log(`Prime factors of ${a.value} are ${a.factors}`));\n```\n\nPrints out\n> Prime factors of 9007199254740991 are 6361,69431,20394401\n\n### With promise\n\n``` javascript\nconst warp = require('warp');\n\nfunction computePrimeFactorization(n) {\n // Compute `f`\n return f;\n}\n\nlet a = await warp.callAsPromise(computePrimeFactorization, 9007199254740991);\nconsole.log(`Prime factors of ${a.value} are ${a.factors}`);\n```\n\nPrints out\n> Prime factors of 9007199254740991 are 6361,69431,20394401\n\n## How it works\n\n\n\nWhen you _warp_ call a function, the [execution context](#execution-context) (i.e. everything\nreachable from the function scope) is captured, then this context and the _warped_ function are\nsent to a distinct and [parallel _warp_ thread](#parallel-thread) (see label `A` in the drawing).\n\nOnce the [_warp_ task](#warp-task) is finished, the parallel [context](#execution-context) is\ncaptured and sent back to the main JavaScript thread (see label `B` in the drawing). Then,\nin an event task of the main thread, the context is updated, and:\n\n- If the _warp_ call is `call`, the callback is executed in the main thread, with the arguments\ngiven to the callback in the parallel _warp_ thread.\n- If the _warp_ call is `callAsPromise`, the Promise returned by `callAsPromise` is resolved or\nrejected with the value or the exception obtained at the end of the parallel _warp_ thread.\n\n### Scope\n\nThe _warped_ functions can read and modify anything reachable from their\n[scope](https://developer.mozilla.org/en-US/docs/Glossary/Scope).\n\nIn the following sample, the variable `o` is defined as a free variable (outside of the function).\nThe _warped_ function can read it, and also modify the object. Modifications made to `o` in the parallel\n_warp_ thread are applied and visible in the main thread.\n\n``` javascript\nconst warp = require('warp');\n\nlet o = {};\nfunction computePrimeFactorization(n) {\n // Compute `f`\n o.result = f;\n}\n\nawait warp.callAsPromise(computePrimeFactorization, 9007199254740991);\nconsole.log(`Prime factors of ${o.value} are ${o.factors}`);\n```\n\nPrints out\n> Prime factors of 9007199254740991 are 6361,69431,20394401\n\n### Shared resources and concurrency\n\n_Warp_ offers no new synchronization or semaphore mechanism. If you need to manage concurrent access\nto a value, you'll have to keep the modifying code in the main thread.\n\nIn the following example, we compute several prime factorizations in parallel.\n\n``` javascript\nconst warp = require('warp');\n\nlet primeFactorizations = [];\n\nfunction computePrimeFactorization(index, n) {\n // Compute `f`\n primeFactorizations[index] = f;\n}\n\nlet promises = []\nfor(let i = 0; i < 8; i++) {\n promises.push(warp.callAsPromise(computePrimeFactorization, i, 9007174991 + i));\n}\n\nawait Promise.all(promises);\n\nconsole.log(`Prime factorizations: %j`, primeFactorizations);\n```\n\nPrints out\n> Prime factorizations: [{\"value\":9007174991,\"factors\":[17,131,4044533]},{\"value\":9007174997,\"factors\":{\"0\":59,\"1\":109,\"2\":1400587,\"value\":9007174993,\"factors\":[12071,746183]}},{\"0\":59,\"1\":109,\"2\":1400587,\"value\":9007174993,\"factors\":[12071,746183]},{\"0\":2,\"1\":2,\"2\":2251793749,\"value\":9007174994,\"factors\":[2,37,53,2296577]},{\"value\":9007174995,\"factors\":[3,5,7,13,41,227,709]},{\"value\":9007174997,\"factors\":{\"0\":59,\"1\":109,\"2\":1400587,\"value\":9007174993,\"factors\":[12071,746183]}},{\"value\":9007174997,\"factors\":{\"0\":59,\"1\":109,\"2\":1400587,\"value\":9007174993,\"factors\":[12071,746183]}},{\"value\":9007174998,\"factors\":[2,3,3,3,19,43,204161]}]\n\nBut you need to be carefull about parallel access to shared variables or properties.\n\nFor instance, the following example shows bad usage of a shared value causing indetermism. There, you\ndon't know in which order the additions will be made, but it is guaranteed that each `fnct` sees\nthe initial value of `v` as `4`. This means you don't know what the final value of `v` will be, you\njust know it will be either `7` or `8`.\n\n``` javascript\nconst warp = require('warp');\n\nlet v = 4;\nfunction fnct(num) {\n let inc = num;\n v += inc;\n return;\n}\n\nlet promises = []\npromises.push(warp.callAsPromise(fnct, 3));\npromises.push(warp.callAsPromise(fnct, 4));\n\nawait Promise.all(promises);\n\nconsole.log(`Value: ${v}`);\n```\n\nTo obtain the correct behavior in this example, you'll need to apply the changes to the shared\nvariable in the main thread by using the `.then` of the promise.\n\n``` javascript\nconst warp = require('warp');\n\nlet v = 4;\nfunction fnct(num) {\n let inc = num;\n return inc;\n}\n\nlet promises = []\npromises.push(warp.callAsPromise(fnct, 3).then((inc) => v += inc));\npromises.push(warp.callAsPromise(fnct, 4).then((inc) => v += inc));\n\nawait Promise.all(promises);\n\nconsole.log(`Value: ${v}`);\n```\n\nPrints out\n> Value: 11\n\nThis way it'll end up with `11` as the final value.\n\n### Use transferable objects\n\n``` javascript\nlet arrayBuffer = new ArrayBuffer(8);\nwarp.markTransferable(arrayBuffer);\n```\n\nAs for the Worker.postMessage method, some objects can be identified as [transferable](https://developer.mozilla.org/en-US/docs/Web/API/Transferable). You must pass all your Transferable objects to _warp_ markTransferable function to transfer these objects. In that case, they may become unusable ([neutered](https://www.w3.org/TR/html50/infrastructure.html#concept-transferable-neutered)) in the main thread and become available only to the parallel thread they were sent to, but this way the transfer is much faster. But, this behavior is not guaranteed, because this is not supported by all protocols that can be used by the runtime.\n\n# Definitions\n\n## Parallel thread\n\nA **parallel thread** is a JavaScript execution thread distinct from the main JavaScript execution thread. The\nmain thread and some parallel _warp_ threads are running at the same physical time. _Warp_ threads don't necessarily belong to the same process. It can come from the fork of a new process or even in a remote machine.\n\n## Warp task\n\nA **warp task** is started by a _warp_ call (a call to `warp.call` or `warp.callAsPromise`).\nThe task is executed in a [parallel thread](#parallel-thread). It starts by executing the given\nfunction and continues until the end of the task is detected.\n\nThe end of the task is detected when:\n- an exception is thrown by the task\n\n**or**\n\n- If the task was started by `warp.callAsPromise`: \n - the function given to `callAsPromise` has returned \n - **And**, if its returned value is a Promise, it is\n [fulfilled or rejected](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Promise#Description).\n\n- If the task was started by `warp.call` \n - The callback is called, \n - **And** the function given to `call` has returned. \n\nNote that this doesn't mean that `return` was executed, it means that the execution has\nreturned to its caller. For example in the following code the end is detected during the line\n`a = await 3` when `await` yields and `a` is still `2`.\n\n``` javascript\nlet a = 0;\nasync function fnct(done) {\n a = 1;\n done();\n a = 2;\n a = await 3; // End is here at `await` before assignation of `a`\n return;\n}\n```\n\n**Warning:** If the task were to attempt to execute code after the end of execution were detected\n(e.g. with a `setImmediate`, `setTimeout`, ...), then the behavior would be unspecified. This\nmeans that if the function given to `call` is starting any asynchronous processing, calling\nthe `callback` must be the very last thing done by the task.\n\n## Execution context\n\nAn **execution context** is referring to everything accessible from the\n[scope](https://developer.mozilla.org/en-US/docs/Glossary/Scope) of the considered\nfunction at a given point of the execution. This includes \n- parameters of the call, \n- local, free and global variables accessed by the function called or by all functions potentially\n called directly or indirectly, \n- any reachable objects (objects, arrays, functions, symbols) from the above defined parameters/variables. \n","readmeFilename":"README.md","_id":"warp@1.2.0-dev.161","_npmVersion":"6.4.1","_nodeVersion":"8.16.1","_npmUser":{"name":"lcars","email":"welcome@scaledynamics.io"},"dist":{"integrity":"sha512-Kbjs8m3d9Kd6oDiDcyWGwRr/W1WNZicMFrM/ABQecjQvIoRCFxBGv6cAU1b26KmTFpnZeRfYeekZAH+l/p+raw==","shasum":"b143411c2da59c63fe36ccd456e02e4f309895c6","tarball":"https://registry.npmjs.org/warp/-/warp-1.2.0-dev.161.tgz","fileCount":4,"unpackedSize":18005,"npm-signature":"-----BEGIN PGP SIGNATURE-----\r\nVersion: OpenPGP.js v3.0.4\r\nComment: https://openpgpjs.org\r\n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\n5KNa\r\n=YE8V\r\n-----END PGP SIGNATURE-----\r\n","signatures":[{"keyid":"SHA256:jl3bwswu80PjjokCgh0o2w5c2U4LhQAE57gj9cz1kzA","sig":"MEYCIQDu83PxAUar0/bAH3opxe5/pFPLA0ocATN3e0KluwEfJwIhAOKPQDFUId5S/oOYVrSbhXjgQzvNj3T5ITgMwp137nuA"}]},"maintainers":[{"email":"jpl@scaledynamics.io","name":"jpl-scale"},{"email":"welcome@scaledynamics.io","name":"lcars"},{"email":"gc@scaledynamics.io","name":"scalejs"}],"directories":{},"_npmOperationalInternal":{"host":"s3://npm-registry-packages","tmp":"tmp/warp_1.2.0-dev.161_1568879252979_0.06926116580554709"},"_hasShrinkwrap":false},"1.2.0-dev.163":{"name":"warp","version":"1.2.0-dev.163","author":{"name":"ScaleDynamics SAS"},"license":"MIT","main":"warp.js","repository":{"type":"git","url":"git+https://github.com/ScaleDynamics/warp.git"},"description":"Warp is an API to run JavaScript functions in parallel: get the most of multi-core systems, shorten response time & intensive computations.","keywords":["node","starnode","parallel","concurrent","performance","speed","cpu","child_process","worker","workers","thread","threads","worker_threads","async","asynchronous"],"bugs":{"url":"https://github.com/ScaleDynamics/warp/issues"},"homepage":"https://scaledynamics.io/","dependencies":{},"build":{"date":"2019-09-19T08:30:11.736Z","user":"2834254","host":"dedi-02-ovh","sha":"ec73f702412dfc4c6282fb96ea2fd7e7ff444515","id":"83125500","branch":"master"},"_resolved":"","_integrity":"","_from":"file:dist/warp-1.2.0-dev.163.tgz","readme":"[](https://warpjs.com)\n\n# Warp\n\n_Warp_ is an API allowing easy parallel execution of JavaScript code, at the\nsame physical time as the main JavaScript thread and as other threads.\n\n```javascript\n// runs `fnct` in parallel\nwarp.call(fnct, , cb);\n```\n\nDiscover Warp in this short YouTube video:\n\n[](https://www.youtube.com/watch?v=d54AOpRgfg0)\n\n## Installing\n\n_Warp_ module is an API and is not providing support for execution. You will need\nto acquire a [**Warp runtime**](https://redirect.scaledynamics.io/warp/runtime) to use it.\n\nTo add _Warp_ API to your project:\n\n```\n$ npm install warp\n```\n\n## How to use it\n\n_Warp_ offers two main functions starting a [_warp_ task](#warp-task): `warp.call` and `warp.callAsPromise`.\nWe say that they perform a _warp_ call. By extension, we also say that code\n_warps_ a function or that the function is _warped_.\n\nHere is a very simple illustrative code sample where a CPU intensive function (`computePrimeFactorization`)\nis executed in parallel by a _warp_ call keeping the event loop free for any other processing. If you\nwant to see complete code, browse the [repository](https://github.com/ScaleDynamics/warp/tree/ec73f702412dfc4c6282fb96ea2fd7e7ff444515/example).\n\nThe first example uses a callback-based function, whereas the second uses a Promise-based function.\n\n### With callback\n\n``` javascript\nconst warp = require('warp');\n\nfunction computePrimeFactorization(n, done) {\n // Compute `f`\n done(f);\n}\n\nwarp.call(computePrimeFactorization, 9007199254740991,\n (a) => console.log(`Prime factors of ${a.value} are ${a.factors}`));\n```\n\nPrints out\n> Prime factors of 9007199254740991 are 6361,69431,20394401\n\n### With promise\n\n``` javascript\nconst warp = require('warp');\n\nfunction computePrimeFactorization(n) {\n // Compute `f`\n return f;\n}\n\nlet a = await warp.callAsPromise(computePrimeFactorization, 9007199254740991);\nconsole.log(`Prime factors of ${a.value} are ${a.factors}`);\n```\n\nPrints out\n> Prime factors of 9007199254740991 are 6361,69431,20394401\n\n## How it works\n\n\n\nWhen you _warp_ call a function, the [execution context](#execution-context) (i.e. everything\nreachable from the function scope) is captured, then this context and the _warped_ function are\nsent to a distinct and [parallel _warp_ thread](#parallel-thread) (see label `A` in the drawing).\n\nOnce the [_warp_ task](#warp-task) is finished, the parallel [context](#execution-context) is\ncaptured and sent back to the main JavaScript thread (see label `B` in the drawing). Then,\nin an event task of the main thread, the context is updated, and:\n\n- If the _warp_ call is `call`, the callback is executed in the main thread, with the arguments\ngiven to the callback in the parallel _warp_ thread.\n- If the _warp_ call is `callAsPromise`, the Promise returned by `callAsPromise` is resolved or\nrejected with the value or the exception obtained at the end of the parallel _warp_ thread.\n\n### Scope\n\nThe _warped_ functions can read and modify anything reachable from their\n[scope](https://developer.mozilla.org/en-US/docs/Glossary/Scope).\n\nIn the following sample, the variable `o` is defined as a free variable (outside of the function).\nThe _warped_ function can read it, and also modify the object. Modifications made to `o` in the parallel\n_warp_ thread are applied and visible in the main thread.\n\n``` javascript\nconst warp = require('warp');\n\nlet o = {};\nfunction computePrimeFactorization(n) {\n // Compute `f`\n o.result = f;\n}\n\nawait warp.callAsPromise(computePrimeFactorization, 9007199254740991);\nconsole.log(`Prime factors of ${o.value} are ${o.factors}`);\n```\n\nPrints out\n> Prime factors of 9007199254740991 are 6361,69431,20394401\n\n### Shared resources and concurrency\n\n_Warp_ offers no new synchronization or semaphore mechanism. If you need to manage concurrent access\nto a value, you'll have to keep the modifying code in the main thread.\n\nIn the following example, we compute several prime factorizations in parallel.\n\n``` javascript\nconst warp = require('warp');\n\nlet primeFactorizations = [];\n\nfunction computePrimeFactorization(index, n) {\n // Compute `f`\n primeFactorizations[index] = f;\n}\n\nlet promises = []\nfor(let i = 0; i < 8; i++) {\n promises.push(warp.callAsPromise(computePrimeFactorization, i, 9007174991 + i));\n}\n\nawait Promise.all(promises);\n\nconsole.log(`Prime factorizations: %j`, primeFactorizations);\n```\n\nPrints out\n> Prime factorizations: [{\"value\":9007174991,\"factors\":[17,131,4044533]},{\"value\":9007174997,\"factors\":{\"0\":59,\"1\":109,\"2\":1400587,\"value\":9007174993,\"factors\":[12071,746183]}},{\"0\":59,\"1\":109,\"2\":1400587,\"value\":9007174993,\"factors\":[12071,746183]},{\"0\":2,\"1\":2,\"2\":2251793749,\"value\":9007174994,\"factors\":[2,37,53,2296577]},{\"value\":9007174995,\"factors\":[3,5,7,13,41,227,709]},{\"value\":9007174997,\"factors\":{\"0\":59,\"1\":109,\"2\":1400587,\"value\":9007174993,\"factors\":[12071,746183]}},{\"value\":9007174997,\"factors\":{\"0\":59,\"1\":109,\"2\":1400587,\"value\":9007174993,\"factors\":[12071,746183]}},{\"value\":9007174998,\"factors\":[2,3,3,3,19,43,204161]}]\n\nBut you need to be carefull about parallel access to shared variables or properties.\n\nFor instance, the following example shows bad usage of a shared value causing indetermism. There, you\ndon't know in which order the additions will be made, but it is guaranteed that each `fnct` sees\nthe initial value of `v` as `4`. This means you don't know what the final value of `v` will be, you\njust know it will be either `7` or `8`.\n\n``` javascript\nconst warp = require('warp');\n\nlet v = 4;\nfunction fnct(num) {\n let inc = num;\n v += inc;\n return;\n}\n\nlet promises = []\npromises.push(warp.callAsPromise(fnct, 3));\npromises.push(warp.callAsPromise(fnct, 4));\n\nawait Promise.all(promises);\n\nconsole.log(`Value: ${v}`);\n```\n\nTo obtain the correct behavior in this example, you'll need to apply the changes to the shared\nvariable in the main thread by using the `.then` of the promise.\n\n``` javascript\nconst warp = require('warp');\n\nlet v = 4;\nfunction fnct(num) {\n let inc = num;\n return inc;\n}\n\nlet promises = []\npromises.push(warp.callAsPromise(fnct, 3).then((inc) => v += inc));\npromises.push(warp.callAsPromise(fnct, 4).then((inc) => v += inc));\n\nawait Promise.all(promises);\n\nconsole.log(`Value: ${v}`);\n```\n\nPrints out\n> Value: 11\n\nThis way it'll end up with `11` as the final value.\n\n### Use transferable objects\n\n``` javascript\nlet arrayBuffer = new ArrayBuffer(8);\nwarp.markTransferable(arrayBuffer);\n```\n\nAs for the Worker.postMessage method, some objects can be identified as [transferable](https://developer.mozilla.org/en-US/docs/Web/API/Transferable). You must pass all your Transferable objects to _warp_ markTransferable function to transfer these objects. In that case, they may become unusable ([neutered](https://www.w3.org/TR/html50/infrastructure.html#concept-transferable-neutered)) in the main thread and become available only to the parallel thread they were sent to, but this way the transfer is much faster. But, this behavior is not guaranteed, because this is not supported by all protocols that can be used by the runtime.\n\n# Definitions\n\n## Parallel thread\n\nA **parallel thread** is a JavaScript execution thread distinct from the main JavaScript execution thread. The\nmain thread and some parallel _warp_ threads are running at the same physical time. _Warp_ threads don't necessarily belong to the same process. It can come from the fork of a new process or even in a remote machine.\n\n## Warp task\n\nA **warp task** is started by a _warp_ call (a call to `warp.call` or `warp.callAsPromise`).\nThe task is executed in a [parallel thread](#parallel-thread). It starts by executing the given\nfunction and continues until the end of the task is detected.\n\nThe end of the task is detected when:\n- an exception is thrown by the task\n\n**or**\n\n- If the task was started by `warp.callAsPromise`: \n - the function given to `callAsPromise` has returned \n - **And**, if its returned value is a Promise, it is\n [fulfilled or rejected](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Promise#Description).\n\n- If the task was started by `warp.call` \n - The callback is called, \n - **And** the function given to `call` has returned. \n\nNote that this doesn't mean that `return` was executed, it means that the execution has\nreturned to its caller. For example in the following code the end is detected during the line\n`a = await 3` when `await` yields and `a` is still `2`.\n\n``` javascript\nlet a = 0;\nasync function fnct(done) {\n a = 1;\n done();\n a = 2;\n a = await 3; // End is here at `await` before assignation of `a`\n return;\n}\n```\n\n**Warning:** If the task were to attempt to execute code after the end of execution were detected\n(e.g. with a `setImmediate`, `setTimeout`, ...), then the behavior would be unspecified. This\nmeans that if the function given to `call` is starting any asynchronous processing, calling\nthe `callback` must be the very last thing done by the task.\n\n## Execution context\n\nAn **execution context** is referring to everything accessible from the\n[scope](https://developer.mozilla.org/en-US/docs/Glossary/Scope) of the considered\nfunction at a given point of the execution. This includes \n- parameters of the call, \n- local, free and global variables accessed by the function called or by all functions potentially\n called directly or indirectly, \n- any reachable objects (objects, arrays, functions, symbols) from the above defined parameters/variables. \n","readmeFilename":"README.md","_id":"warp@1.2.0-dev.163","_npmVersion":"6.4.1","_nodeVersion":"8.16.1","_npmUser":{"name":"lcars","email":"welcome@scaledynamics.io"},"dist":{"integrity":"sha512-0xfSrvX+lZ0/j6Jf6pck4qX1SlTsKFHfIbJ/S8AZZJHCMVnOfSNYfcnLIcaJrX7Nw9+jM4EA87zr6g+HqJ9LYQ==","shasum":"1fdb9f192f32759d74d8a35ae107b8fae645a7b6","tarball":"https://registry.npmjs.org/warp/-/warp-1.2.0-dev.163.tgz","fileCount":4,"unpackedSize":18005,"npm-signature":"-----BEGIN PGP SIGNATURE-----\r\nVersion: OpenPGP.js v3.0.4\r\nComment: https://openpgpjs.org\r\n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\nZxQz\r\n=gt5j\r\n-----END PGP SIGNATURE-----\r\n","signatures":[{"keyid":"SHA256:jl3bwswu80PjjokCgh0o2w5c2U4LhQAE57gj9cz1kzA","sig":"MEQCIFNwqN4ke7y4ZqDCB1z01/UKllEVwX0JDOo/PLbsu3YKAiBZD7kZHZ3tQ+fDw8pkkVv89EN7AOwmP1su+yknEClg7A=="}]},"maintainers":[{"email":"jpl@scaledynamics.io","name":"jpl-scale"},{"email":"welcome@scaledynamics.io","name":"lcars"},{"email":"gc@scaledynamics.io","name":"scalejs"}],"directories":{},"_npmOperationalInternal":{"host":"s3://npm-registry-packages","tmp":"tmp/warp_1.2.0-dev.163_1568890371835_0.7134514595209125"},"_hasShrinkwrap":false},"1.1.0-dev.61":{"name":"warp","version":"1.1.0-dev.61","author":{"name":"ScaleDynamics SAS"},"license":"MIT","main":"warp.js","repository":{"type":"git","url":"git+https://github.com/ScaleDynamics/warp.git"},"description":"Warp is an API to run JavaScript functions in parallel: get the most of multi-core systems, shorten response time & intensive computations.","keywords":["node","starnode","parallel","concurrent","performance","speed","cpu","child_process","worker","workers","thread","threads","worker_threads","async","asynchronous"],"bugs":{"url":"https://github.com/ScaleDynamics/warp/issues"},"homepage":"https://scaledynamics.io/","dependencies":{},"build":{"date":"2020-01-07T13:41:08.989Z","user":"2834254","host":"shared-runners-manager-5.gitlab.com","sha":"02738e84d738c80606d9e43a7cccf9633a472a01","id":"107543961","branch":"warp-v1"},"_resolved":"","_integrity":"","_from":"file:dist/warp-1.1.0-dev.61.tgz","readme":"[](https://warpjs.com)\n\n# Warp\n\n_Warp_ is an API allowing easy parallel execution of JavaScript code, at the\nsame physical time as the main JavaScript thread and as other threads.\n\n```javascript\n// runs `fnct` in parallel\nwarp.call(fnct, , cb);\n```\n\nDiscover Warp in this short YouTube video:\n\n[](https://www.youtube.com/watch?v=d54AOpRgfg0)\n\n## Installing\n\n_Warp_ module is an API and is not providing support for execution. You will need\nto acquire a [**Warp runtime**](https://redirect.scaledynamics.io/warp/runtime) to use it.\n\nTo add _Warp_ API to your project:\n\n```\n$ npm install warp\n```\n\n## How to use it\n\n_Warp_ offers two main functions starting a [_warp_ task](#warp-task): `warp.call` and `warp.callAsPromise`.\nWe say that they perform a _warp_ call. By extension, we also say that code\n_warps_ a function or that the function is _warped_.\n\nHere is a very simple illustrative code sample where a CPU intensive function (`computePrimeFactorization`)\nis executed in parallel by a _warp_ call keeping the event loop free for any other processing. If you\nwant to see complete code, browse the [repository](https://github.com/ScaleDynamics/warp/tree/02738e84d738c80606d9e43a7cccf9633a472a01/example).\n\nThe first example uses a callback-based function, whereas the second uses a Promise-based function.\n\n### With callback\n\n``` javascript\nconst warp = require('warp');\n\nfunction computePrimeFactorization(n, done) {\n // Compute `f`\n done(f);\n}\n\nwarp.call(computePrimeFactorization, 9007199254740991,\n (a) => console.log(`Prime factors of ${a.value} are ${a.factors}`));\n```\n\nPrints out\n> Prime factors of 9007199254740991 are 6361,69431,20394401\n\n### With promise\n\n``` javascript\nconst warp = require('warp');\n\nfunction computePrimeFactorization(n) {\n // Compute `f`\n return f;\n}\n\nlet a = await warp.callAsPromise(computePrimeFactorization, 9007199254740991);\nconsole.log(`Prime factors of ${a.value} are ${a.factors}`);\n```\n\nPrints out\n> Prime factors of 9007199254740991 are 6361,69431,20394401\n\n## How it works\n\n\n\nWhen you _warp_ call a function, the [execution context](#execution-context) (i.e. everything\nreachable from the function scope) is captured, then this context and the _warped_ function are\nsent to a distinct and [parallel _warp_ thread](#parallel-thread) (see label `A` in the drawing).\n\nOnce the [_warp_ task](#warp-task) is finished, the parallel [context](#execution-context) is\ncaptured and sent back to the main JavaScript thread (see label `B` in the drawing). Then,\nin an event task of the main thread, the context is updated, and:\n\n- If the _warp_ call is `call`, the callback is executed in the main thread, with the arguments\ngiven to the callback in the parallel _warp_ thread.\n- If the _warp_ call is `callAsPromise`, the Promise returned by `callAsPromise` is resolved or\nrejected with the value or the exception obtained at the end of the parallel _warp_ thread.\n\n### Scope\n\nThe _warped_ functions can read and modify anything reachable from their\n[scope](https://developer.mozilla.org/en-US/docs/Glossary/Scope).\n\nIn the following sample, the variable `o` is defined as a free variable (outside of the function).\nThe _warped_ function can read it, and also modify the object. Modifications made to `o` in the parallel\n_warp_ thread are applied and visible in the main thread.\n\n``` javascript\nconst warp = require('warp');\n\nlet o = {};\nfunction computePrimeFactorization(n) {\n // Compute `f`\n o.result = f;\n}\n\nawait warp.callAsPromise(computePrimeFactorization, 9007199254740991);\nconsole.log(`Prime factors of ${o.value} are ${o.factors}`);\n```\n\nPrints out\n> Prime factors of 9007199254740991 are 6361,69431,20394401\n\n### Shared resources and concurrency\n\n_Warp_ offers no new synchronization or semaphore mechanism. If you need to manage concurrent access\nto a value, you'll have to keep the modifying code in the main thread.\n\nIn the following example, we compute several prime factorizations in parallel.\n\n``` javascript\nconst warp = require('warp');\n\nlet primeFactorizations = [];\n\nfunction computePrimeFactorization(index, n) {\n // Compute `f`\n primeFactorizations[index] = f;\n}\n\nlet promises = []\nfor(let i = 0; i < 8; i++) {\n promises.push(warp.callAsPromise(computePrimeFactorization, i, 9007174991 + i));\n}\n\nawait Promise.all(promises);\n\nconsole.log(`Prime factorizations: %j`, primeFactorizations);\n```\n\nPrints out\n> Prime factorizations: [{\"value\":9007174991,\"factors\":[17,131,4044533]},{\"value\":9007174997,\"factors\":{\"0\":59,\"1\":109,\"2\":1400587,\"value\":9007174993,\"factors\":[12071,746183]}},{\"0\":59,\"1\":109,\"2\":1400587,\"value\":9007174993,\"factors\":[12071,746183]},{\"0\":2,\"1\":2,\"2\":2251793749,\"value\":9007174994,\"factors\":[2,37,53,2296577]},{\"value\":9007174995,\"factors\":[3,5,7,13,41,227,709]},{\"value\":9007174997,\"factors\":{\"0\":59,\"1\":109,\"2\":1400587,\"value\":9007174993,\"factors\":[12071,746183]}},{\"value\":9007174997,\"factors\":{\"0\":59,\"1\":109,\"2\":1400587,\"value\":9007174993,\"factors\":[12071,746183]}},{\"value\":9007174998,\"factors\":[2,3,3,3,19,43,204161]}]\n\nBut you need to be carefull about parallel access to shared variables or properties.\n\nFor instance, the following example shows bad usage of a shared value causing indetermism. There, you\ndon't know in which order the additions will be made, but it is guaranteed that each `fnct` sees\nthe initial value of `v` as `4`. This means you don't know what the final value of `v` will be, you\njust know it will be either `7` or `8`.\n\n``` javascript\nconst warp = require('warp');\n\nlet v = 4;\nfunction fnct(num) {\n let inc = num;\n v += inc;\n return;\n}\n\nlet promises = []\npromises.push(warp.callAsPromise(fnct, 3));\npromises.push(warp.callAsPromise(fnct, 4));\n\nawait Promise.all(promises);\n\nconsole.log(`Value: ${v}`);\n```\n\nTo obtain the correct behavior in this example, you'll need to apply the changes to the shared\nvariable in the main thread by using the `.then` of the promise.\n\n``` javascript\nconst warp = require('warp');\n\nlet v = 4;\nfunction fnct(num) {\n let inc = num;\n return inc;\n}\n\nlet promises = []\npromises.push(warp.callAsPromise(fnct, 3).then((inc) => v += inc));\npromises.push(warp.callAsPromise(fnct, 4).then((inc) => v += inc));\n\nawait Promise.all(promises);\n\nconsole.log(`Value: ${v}`);\n```\n\nPrints out\n> Value: 11\n\nThis way it'll end up with `11` as the final value.\n\n# Definitions\n\n## Parallel thread\n\nA **parallel thread** is a JavaScript execution thread distinct from the main JavaScript execution thread. The\nmain thread and some parallel _warp_ threads are running at the same physical time. _Warp_ threads don't necessarily belong to the same process. It can come from the fork of a new process or even in a remote machine.\n\n## Warp task\n\nA **warp task** is started by a _warp_ call (a call to `warp.call` or `warp.callAsPromise`).\nThe task is executed in a [parallel thread](#parallel-thread). It starts by executing the given\nfunction and continues until the end of the task is detected.\n\nThe end of the task is detected when:\n- an exception is thrown by the task\n\n**or**\n\n- If the task was started by `warp.callAsPromise`: \n - the function given to `callAsPromise` has returned \n - **And**, if its returned value is a Promise, it is\n [fulfilled or rejected](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Promise#Description).\n\n- If the task was started by `warp.call` \n - The callback is called, \n - **And** the function given to `call` has returned. \n\nNote that this doesn't mean that `return` was executed, it means that the execution has\nreturned to its caller. For example in the following code the end is detected during the line\n`a = await 3` when `await` yields and `a` is still `2`.\n\n``` javascript\nlet a = 0;\nasync function fnct(done) {\n a = 1;\n done();\n a = 2;\n a = await 3; // End is here at `await` before assignation of `a`\n return;\n}\n```\n\n**Warning:** If the task were to attempt to execute code after the end of execution were detected\n(e.g. with a `setImmediate`, `setTimeout`, ...), then the behavior would be unspecified. This\nmeans that if the function given to `call` is starting any asynchronous processing, calling\nthe `callback` must be the very last thing done by the task.\n\n## Execution context\n\nAn **execution context** is referring to everything accessible from the\n[scope](https://developer.mozilla.org/en-US/docs/Glossary/Scope) of the considered\nfunction at a given point of the execution. This includes \n- parameters of the call, \n- local, free and global variables accessed by the function called or by all functions potentially\n called directly or indirectly, \n- any reachable objects (objects, arrays, functions, symbols) from the above defined parameters/variables. \n","readmeFilename":"README.md","_id":"warp@1.1.0-dev.61","_nodeVersion":"8.17.0","_npmVersion":"6.13.4","dist":{"integrity":"sha512-Idpo7LPLQCZ0kpPrDdYR3ChDWsrNqH9CtAsjgWz7H0TFc8GfZT4IugJvp7IDUKgKVHmaj0BBQ5tStdVdLZXPhw==","shasum":"9ef82707860dbcd509597ce05f36a8d92a6347ea","tarball":"https://registry.npmjs.org/warp/-/warp-1.1.0-dev.61.tgz","fileCount":4,"unpackedSize":16608,"npm-signature":"-----BEGIN PGP SIGNATURE-----\r\nVersion: OpenPGP.js v3.0.4\r\nComment: 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beta. If you would like to test WarpJS, you need to know someone who is in the program to get an invitation link or to [request an invitation on WarpJS.com](https://warpjs.com/).\n\n# Philosophy\n\nIn a nutshell, the developer writes the back-end logic in Node.js module then the **warp** command line turns it into deployed serverless functions on the server-side and generates a JavaScript API module wrapping the functions calls on the client-side.\n\nThis way, developers can call scalable server-side functions in the most natural way from the client codebase, without coding any HTTP request or response.\n\nThe **warp** command line carries out three simple operations: **warp build**, **warp deploy** and **warp start-emulator**.\n\n\n\n# Quick start\n### Clone an existing project\n```bash\n$ git clone https://github.com/WarpJS/warpjs-starter-template\n$ cd warpjs-starter-template\n$ npm install\n```\n\n### Login to WarpJS\nWarpJS comes with cloud hosting. Run the warp login command-line to install Warp and to authenticate to your [WarpJS account](https://starbase.warpjs.com/signin) at once.\n```bash\n$ npx warp login\n```\n\n### Run locally\n```bash\n# launches 'npx warp start-emulator' to emulate the FaaS locally and starts an HTTP server for the front\n$ npm run dev\n```\n\n### Deploy on a cloud (GCP, AWS, Azure)\n```bash\n# build the serverless functions and a module exposing the API\n$ npx warp build --output umd:dist/client.js .\n# deploys the functions as FaaS, and the client assets optionally\n$ npx warp deploy --asset-dir dist/ .\n```\n\n# How it works\nOut of a module, **warp build** generates (1) the FaaS back-end code for each function and (2) an API script exposing the back-end functions calls. 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