offset in each dimension into the final index. However, all the information we need for the loop is embedded in the type information of the arguments. Thus, we can utilize generated functions to move the package called Sockets. Let's first create a simple server: julia> using Sockets julia> @async begin server = listen(2000) while true sock = accept(server) println("Hello World\n") end end Task (runnable) usage is some- what simpler than the raw Unix socket API. The first call to listen will create a server waiting for incoming connections on the specified port (2000) in this case. The same function may

offset in each dimension into the final index. However, all the information we need for the loop is embedded in the type information of the arguments. Thus, we can utilize generated functions to move the package called Sockets. Let's first create a simple server: julia> using Sockets julia> @async begin server = listen(2000) while true sock = accept(server) println("Hello World\n") end end Task (runnable) usage is some- what simpler than the raw Unix socket API. The first call to listen will create a server waiting for incoming connections on the specified port (2000) in this case. The same function may

offset in each dimension into the final index. However, all the information we need for the loop is embedded in the type information of the arguments. Thus, we can utilize generated functions to move the package called Sockets. Let's first create a simple server: julia> using Sockets julia> @async begin server = listen(2000) while true sock = accept(server) println("Hello World\n") end end Task (runnable) usage is some- what simpler than the raw Unix socket API. The first call to listen will create a server waiting for incoming connections on the specified port (2000) in this case. The same function may

offset in each dimension into the final index. However, all the information we need for the loop is embedded in the type information of the arguments. Thus, we can utilize generated functions to move the package called Sockets. Let's first create a simple server: julia> using Sockets julia> @async begin server = listen(2000) while true sock = accept(server) println("Hello World\n") end end Task (runnable) usage is some- what simpler than the raw Unix socket API. The first call to listen will create a server waiting for incoming connections on the specified port (2000) in this case. The same function may

offset in each dimension into the final index. However, all the information we need for the loop is embedded in the type information of the arguments. Thus, we can utilize generated functions to move the package called Sockets. Let's first create a simple server: julia> using Sockets julia> @async begin server = listen(2000) while true sock = accept(server) println("Hello World\n") end end Task (runnable) usage is some- what simpler than the raw Unix socket API. The first call to listen will create a server waiting for incoming connections on the specified port (2000) in this case. The same function may

offset in each dimension into the final index. However, all the information we need for the loop is embedded in the type information of the arguments. Thus, we can utilize generated functions to move the package called Sockets. Let's first create a simple server: julia> using Sockets julia> @async begin server = listen(2000) while true sock = accept(server) println("Hello World\n") end end Task (runnable) usage is some- what simpler than the raw Unix socket API. The first call to listen will create a server waiting for incoming connections on the specified port (2000) in this case. The same function may

offset in each dimension into the final index. However, all the information we need for the loop is embedded in the type information of the arguments. Thus, we can utilize generated functions to move the package called Sockets. Let's first create a simple server: julia> using Sockets julia> @async begin server = listen(2000) while true sock = accept(server) println("Hello World\n") end end Task (runnable) usage is some- what simpler than the raw Unix socket API. The first call to listen will create a server waiting for incoming connections on the specified port (2000) in this case. The same function may

offset in each dimension into the final index. However, all the information we need for the loop is embedded in the type information of the arguments. Thus, we can utilize generated functions to move the package called Sockets. Let's first create a simple server: julia> using Sockets julia> @async begin server = listen(2000) while true sock = accept(server) println("Hello World\n") end end Task (runnable) usage is some- what simpler than the raw Unix socket API. The first call to listen will create a server waiting for incoming connections on the specified port (2000) in this case. The same function may

offset in each dimension into the final index. However, all the information we need for the loop is embedded in the type information of the arguments. Thus, we can utilize generated functions to move the package called Sockets. Let's first create a simple server: julia> using Sockets julia> @async begin server = listen(2000) while true sock = accept(server) println("Hello World\n") end end Task (runnable) usage is some- what simpler than the raw Unix socket API. The first call to listen will create a server waiting for incoming connections on the specified port (2000) in this case. The same function may

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333 JULIA_PKG_SERVER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333 29.2 External offset in each dimension into the final index. However, all the information we need for the loop is embedded in the type information of the arguments. Thus, we can utilize generated functions to move the package called Sockets. Let's first create a simple server: julia> using Sockets julia> @async begin server = listen(2000) while true sock = accept(server) println("Hello World\n") end end Task (runnable)