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Diffstat (limited to 'python/mainthread.py')
| -rw-r--r-- | python/mainthread.py | 35 |
1 files changed, 35 insertions, 0 deletions
diff --git a/python/mainthread.py b/python/mainthread.py index 14698b6a..9064a666 100644 --- a/python/mainthread.py +++ b/python/mainthread.py @@ -18,6 +18,41 @@ # FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS # IN THE SOFTWARE. +""" +.. py:module:: mainthread + +This module provides two ways to execute "jobs": + +1. On the Binary Ninja main thread (the UI event thread when running in the GUI application): + * :py:func:`.execute_on_main_thread` + * :py:func:`.execute_on_main_thread_and_wait` +2. On a worker thread + +Any manipulation of the GUI should be performed on the main thread, but any +non-GUI work is generally better to be performed using a worker. This is +especially true for any longer-running work, as the user interface will +be unable to update itself while a job is executing on the main thread. + +There are three worker queues, in order of decreasing priority: + + 1. The Interactive Queue (:py:func:`.worker_interactive_enqueue`) + 2. The Priority Queue (:py:func:`.worker_priority_enqueue`) + 3. The Worker Queue (:py:func:`.worker_enqueue`) + +All of these queues are serviced by the same pool of worker threads. The +difference between the queues is basically one of priority: one queue must +be empty of jobs before a worker thread will execute a job from a lower +priority queue. + +The default maximum number of concurrent worker threads is controlled by the +`analysis.limits.workerThreadCount` setting but can be adjusted at runtime via +:py:func:`.set_worker_thread_count`. + +The worker threads are native threads, managed by the Binary Ninja core. If +more control over the thread is required, consider using the +:py:class:`~binaryninja.plugin.BackgroundTaskThread` class. +""" + # Binary Ninja components from . import _binaryninjacore as core from . import scriptingprovider |