function blocks, at least a little bit, while it is running and using the CPU (for an extreme example that demonstrates why CPU blocking must be taken as seriously as other kinds of blocking, consider password functions like bcrypt [http://bcrypt.sourceforge.net/], which by design use hundreds of milliseconds of CPU time, far more than a typical network or disk access). A function can be blocking in some respects necessary to run multiple Python processes to take full advantage of multi-CPU machines. Typically it is best to run one process per CPU. Tornado includes a built-in multi-process mode to start several processes

function blocks, at least a little bit, while it is running and using the CPU (for an extreme example that demonstrates why CPU blocking must be taken as seriously as other kinds of blocking, consider password functions like bcrypt [http://bcrypt.sourceforge.net/], which by design use hundreds of milliseconds of CPU time, far more than a typical network or disk access). A function can be blocking in some respects necessary to run multiple Python processes to take full advantage of multi-CPU machines. Typically it is best to run one process per CPU. Tornado includes a built-in multi-process mode to start several processes

function blocks, at least a little bit, while it is running and using the CPU (for an extreme example that demonstrates why CPU blocking must be taken as seriously as other kinds of blocking, consider password functions like bcrypt [http://bcrypt.sourceforge.net/], which by design use hundreds of milliseconds of CPU time, far more than a typical network or disk access). A function can be blocking in some respects necessary to run multiple Python processes to take full advantage of multi-CPU machines. Typically it is best to run one process per CPU. Tornado includes a built-in multi-process mode to start several processes

function blocks, at least a little bit, while it is running and using the CPU (for an extreme example that demonstrates why CPU blocking must be taken as seriously as other kinds of blocking, consider password password hashing functions like bcrypt, which by design use hundreds of milliseconds of CPU time, far more than a typical network or disk access). A function can be blocking in some respects and non-blocking necessary to run multiple Python processes to take full advantage of multi-CPU machines. Typically it is best to run one process per CPU. Tornado includes a built-in multi-process mode to start several processes

function blocks, at least a little bit, while it is running and using the CPU (for an extreme example that demonstrates why CPU blocking must be taken as seriously as other kinds of blocking, consider password password hashing functions like bcrypt, which by design use hundreds of milliseconds of CPU time, far more than a typical network or disk access). A function can be blocking in some respects and non-blocking necessary to run multiple Python processes to take full advantage of multi-CPU machines. Typically it is best to run one process per CPU. Tornado includes a built-in multi-process mode to start several processes

function blocks, at least a little bit, while it is running and using the CPU (for an extreme example that demonstrates why CPU blocking must be taken as seriously as other kinds of blocking, consider password password hashing functions like bcrypt, which by design use hundreds of milliseconds of CPU time, far more than a typical network or disk access). A function can be blocking in some respects and non-blocking necessary to run multiple Python processes to take full advantage of multi-CPU machines. Typically it is best to run one process per CPU. Tornado includes a built-in multi-process mode to start several processes

function blocks, at least a little bit, while it is running and using the CPU (for an extreme example that demonstrates why CPU blocking must be taken as seriously as other kinds of blocking, consider password password hashing functions like bcrypt, which by design use hundreds of milliseconds of CPU time, far more than a typical network or disk access). A function can be blocking in some respects and non-blocking necessary to run multiple Python processes to take full advantage of multi-CPU machines. Typically it is best to run one process per CPU. Tornado includes a built-in multi-process mode to start several processes

function blocks, at least a little bit, while it is running and using the CPU (for an extreme example that demonstrates why CPU blocking must be taken as seriously as other kinds of blocking, consider password functions like bcrypt [http://bcrypt.sourceforge.net/], which by design use hundreds of milliseconds of CPU time, far more than a typical network or disk access). A function can be blocking in some respects necessary to run multiple Python processes to take full advantage of multi-CPU machines. Typically it is best to run one process per CPU. Tornado includes a built-in multi-process mode to start several processes

function blocks, at least a little bit, while it is running and using the CPU (for an extreme example that demonstrates why CPU blocking must be taken as seriously as other kinds of blocking, consider password password hashing functions like bcrypt, which by design use hundreds of milliseconds of CPU time, far more than a typical network or disk access). A function can be blocking in some respects and non-blocking necessary to run multiple Python processes to take full advantage of multi-CPU machines. Typically it is best to run one process per CPU. The simplest way to do this is to add reuse_port=True to your listen()

function blocks, at least a little bit, while it is running and using the CPU (for an extreme example that demonstrates why CPU blocking must be taken as seriously as other kinds of blocking, consider password password hashing functions like bcrypt, which by design use hundreds of milliseconds of CPU time, far more than a typical network or disk access). A function can be blocking in some respects and non-blocking necessary to run multiple Python processes to take full advantage of multi-CPU machines. Typically it is best to run one process per CPU. The simplest way to do this is to add reuse_port=True to your listen()