as a Result File Format in OMNeT++ Rudolf Hornig ## OMNeT++ Result Files ## • Scalar and Vector files • Contents: ☐ Run description ☐ Scalar file: (module, scalar, value), histograms, result attributes #34; ## Using SQLite Result Files from OMNeT++ IDE ## SQLite Result Files can be used from the IDE just like the text based format ## I nput files Add or drag & drop result files (*.sca or *.vec) analysis. Wildcards (*,?) can also be used to specify multiple files. ## Data Here you can browse the result files and their contents. Physical: by file and run Physical: by run and file Logical: by experiment

## GCN ## I mproving Go Backend Developer Experience in Grab  Chew Chee Ming Grab Engineering Manager, Developer Experience Breaks flow of engineers, lag time leads to lower productivity ● 1 min increased build time could result in landing code 1 hour later ● Build times too long p50 ~15mins p90 ~38mins ● Start fixing the

• Task result backend settings • Database backend settings • AMQP backend settings • Cache backend settings • Tokyo Tyrant backend settings • Redis backend settings • MongoDB backend settings • Messaging settings • Task execution settings • Worker: celeryd • Periodic Task Server: celerybeat • Monitor Server: celerymon • Cookbook Subtasks and Callbacks - celery.task.sets - Executing Tasks - celery.execute - Task Result - celery.result - Task Information and Utilities - celery.task - Configuration - celery.conf - Remote

Foreign Function Interface ## Haskell FFI Note: This section currently only applies to the GHC backend. The FFI is controlled by five pragmas: • IMPORT • COMPILED TYPE • COMPILED DATA • COMPILED A _:_: A → List A → List A {-# COMPILED_DATA List [] [] (:) #-} ## Built-in Types The GHC backend compiles certain Agda built-ins to special Haskell types. The mapping between Agda built-in types Without this pragma, functions are compiled to Haskell functions with unpredictable names and, as a result, cannot be invoked from Haskell. The type of hsNameForF will be the translated type of f (see Translating

if k > INT_MAX-10, the result is undefined – “The program is not well-defined” language is also used - The standard imposes no requirements or restrictions on the result of $ f() $ - Only if if k > INT_MAX-10 (for any k <= INT_MAX-10, the result is well-defined) - The standard imposes no requirements or restrictions on the result of any program that calls $ f() $ with $ k > INT\_MAX-10 of UB: the result of the entire program is undefined if any operation exhibits UB (according to the standard) • "Undefined" means the standard imposes no requirements on such result ![Image](

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edited by a staff, or a client, or maybe just you – and you don’t want to have to deal with creating backend interfaces just to manage content. One typical workflow in creating Django apps is to create models how Django will load and render templates. The default settings file configures a DjangoTemplates backend whose APP_DIRS option is set to True. By convention DjangoTemplates looks for a "templates" a very common idiom to load a template, fill a context and return an HttpResponse object with the result of the rendered template. Django provides a shortcut. Here’s the full index() view, rewritten: ###

Concurrency • prefork (multiprocessing), o Eventlet, gevent ○ thread (multithreaded) ## • Result Stores ☐ solo (single threaded) o AMQP, Redis o Memcached, o SQLAlchemy, Django ORM o Apache using the librabbitmq C library. celery[redis]: for using Redis as a message transport or as a result backend. celery[sqs]: for using Amazon SQS as a message transport (experimental). celery[tlib]: for celery[memcache]: for using Memcached as a result backend (using pylibmc [https://pypi.python.org/pypi/pylibmc/]) celery[pymemcache]: for using Memcached as a result backend (pure-Python implementation). celery[candora]:

Concurrency • prefork (multiprocessing), o Eventlet, gevent ○ thread (multithreaded) ## • Result Stores ☐ solo (single threaded) o AMQP, Redis o Memcached, o SQLAlchemy, Django ORM o Apache using the librabbitmq C library. celery[redis]: for using Redis as a message transport or as a result backend. celery[sqs]: for using Amazon SQS as a message transport (experimental). celery[tlib]: for celery[memcache]: for using Memcached as a result backend (using pylibmc [https://pypi.python.org/pypi/pylibmc/]) celery[pymemcache]: for using Memcached as a result backend (pure-Python implementation). celery[candora]:

Concurrency • prefork (multiprocessing), o Eventlet, gevent ○ thread (multithreaded) ## • Result Stores ☐ solo (single threaded) o AMQP, Redis o Memcached, o SQLAlchemy, Django ORM o Apache using the librabbitmq C library. celery[redis]: for using Redis as a message transport or as a result backend. celery[sqs]: for using Amazon SQS as a message transport (experimental). celery[tlib]: for celery[memcache]: for using Memcached as a result backend (using pylibmc [https://pypi.python.org/pypi/pylibmc/]) celery[pymemcache]: for using Memcached as a result backend (pure-Python implementation). celery[candora]: