CHAPTER TWO PERFORMANCE To benchmark performance against a range of tasks a test suite with a fixed set of 8 PDFs with a total of 7,031 pages containing text & images is used to obtain performance timings installed: • On Windows: – Install Visual Studio 2019. If not installed in a standard location, set environmental variable PYMUPDF_SETUP_DEVENV to the location of the devenv.com binary. – Having other C:/Program Files/Tesseract-OCR/tessdata • Unix systems: /usr/share/tesseract-ocr/4.00/tessdata 2. Set the environment variable TESSDATA_PREFIX • Windows: setx TESSDATA_PREFIX "C:/Program Files/Tesseract-OCR/tessdata"

compatible with Tornado. Applications that use Tornado on Windows with Python 3.8 must call asyncio.set_event_loop_policy(asyncio.WindowsSelectorEventLoopPolicy()) at the beginning of their main file/function my_future = Future() fetch_future = http_client.fetch(url) def on_fetch(f): my_future.set_result(f.result().body) fetch_future.add_done_callback(on_fetch) return my_future Notice that that yields Queue.get pauses until there is an item in the queue. If the queue has a maximum size set, a coroutine that yields Queue.put pauses until there is room for another item. A Queue maintains

my_future = Future() fetch_future = http_client.fetch(url) def on_fetch(f): my_future.set_result(f.result().body) fetch_future.add_done_callback(on_fetch) return my_future Notice that that yields Queue.get pauses until there is an item in the queue. If the queue has a maximum size set, a coroutine that yields Queue.put pauses until there is room for another item. A Queue maintains async def main(): q = queues.Queue() start = time.time() fetching, fetched, dead = set(), set(), set() async def fetch_url(current_url): if current_url in fetching: return

AsyncHTTPClient() my_future = Future() fetch_future = http_client.fetch(url) def on_fetch(f): my_future.set_result(f.result().body) fetch_future.add_done_callback(on_fetch) return my_future Notice that the that yields Queue.get pauses until there is an item in the queue. If the queue has a maximum size set, a coroutine that yields Queue.put pauses until there is room for another item. A Queue maintains url_seeker.urls async def main(): q = queues.Queue() start = time.time() fetching, fetched, dead = set(), set(), set() async def fetch_url(current_url): if current_url in fetching: return print("fetching %s"

AsyncHTTPClient() my_future = Future() fetch_future = http_client.fetch(url) def on_fetch(f): my_future.set_result(f.result().body) fetch_future.add_done_callback(on_fetch) return my_future Notice that the that yields Queue.get pauses until there is an item in the queue. If the queue has a maximum size set, a coroutine that yields Queue.put pauses until there is room for another item. A Queue maintains url_seeker.urls async def main(): q = queues.Queue() start = time.time() fetching, fetched, dead = set(), set(), set() async def fetch_url(current_url): if current_url in fetching: return print("fetching %s"

compatible with Tornado. Applications that use Tornado on Windows with Python 3.8 must call asyncio.set_event_loop_policy(asyncio. WindowsSelectorEventLoopPolicy()) at the beginning of their main file/function AsyncHTTPClient() my_future = Future() fetch_future = http_client.fetch(url) def on_fetch(f): my_future.set_result(f.result().body) fetch_future.add_done_callback(on_fetch) return my_future Notice that the that yields Queue.get pauses until there is an item in the queue. If the queue has a maximum size set, a coroutine that yields Queue.put pauses until there is room for another item. A Queue maintains

AsyncHTTPClient() my_future = Future() fetch_future = http_client.fetch(url) def on_fetch(f): my_future.set_result(f.result().body) fetch_future.add_done_callback(on_fetch) return my_future Notice that the that yields Queue.get pauses until there is an item in the queue. If the queue has a maximum size set, a coroutine that yields Queue.put pauses until there is room for another item. A Queue maintains url_seeker.urls async def main(): q = queues.Queue() start = time.time() fetching, fetched, dead = set(), set(), set() async def fetch_url(current_url): if current_url in fetching: return print("fetching %s"

AsyncHTTPClient() my_future = Future() fetch_future = http_client.fetch(url) def on_fetch(f): my_future.set_result(f.result().body) fetch_future.add_done_callback(on_fetch) return my_future Notice that the that yields Queue.get pauses until there is an item in the queue. If the queue has a maximum size set, a coroutine that yields Queue.put pauses until there is room for another item. A Queue maintains url_seeker.urls async def main(): q = queues.Queue() start = time.time() fetching, fetched, dead = set(), set(), set() async def fetch_url(current_url): if current_url in fetching: return print("fetching %s"

AsyncHTTPClient() my_future = Future() fetch_future = http_client.fetch(url) def on_fetch(f): my_future.set_result(f.result().body) fetch_future.add_done_callback(on_fetch) return my_future Notice that the that yields Queue.get pauses until there is an item in the queue. If the queue has a maximum size set, a coroutine that yields Queue.put pauses until there is room for another item. A Queue maintains url_seeker.urls async def main(): q = queues.Queue() start = time.time() fetching, fetched, dead = set(), set(), set() async def fetch_url(current_url): if current_url in fetching: return print("fetching %s"

AsyncHTTPClient() my_future = Future() fetch_future = http_client.fetch(url) def on_fetch(f): my_future.set_result(f.result().body) fetch_future.add_done_callback(on_fetch) return my_future Notice that the that yields Queue.get pauses until there is an item in the queue. If the queue has a maximum size set, a coroutine that yields Queue.put pauses until there is room for another item. A Queue maintains url_seeker.urls async def main(): q = queues.Queue() start = time.time() fetching, fetched, dead = set(), set(), set() async def fetch_url(current_url): if current_url in fetching: return print("fetching %s"