<jupyter_start><jupyter_text>Testing AssertionForm/NewForm.html with standalone Blazegraph and Docker images:In Docker container jermnelson/semantic-server-core:new:|-------- formTest [Time Log Calculation]-----------------|StartDiff       LastNodeDiff    NodeName0.0             0.0             form render start for: AssertionForm/NewForm8402.0          8402.0          End test form path8402.0          0.0             initial form creation start8402.5          0.5             initial form creation end8402.5          0.0             start non post testing8402.5          0.0             end non post testing8402.5          0.0             create form class start8403.0          0.5             create form class end8403.0          0.0             start query options load8409.5          6.5             ----Sending query to triplestore9437.7          1028.1          ----Recieved query from triplestore9444.2          6.5             ----Sending query to triplestore10493.3         1049.1          ----Recieved query from triplestore10493.3         0.0             end query options load10564.3         71.0            template rendered|------------------------------------------------------------|Standalone Blazegraph server:Name,', ',?givenName) AS ?name) } ORDER BY ?name|-------- formTest [Time Log Calculation]-----------------|StartDiff       LastNodeDiff    NodeName0.0             0.0             form render start for: AssertionForm/NewForm6109.0          6109.0          End test form path6109.0          0.0             initial form creation start6109.5          0.5             initial form creation end6109.5          0.0             start non post testing6109.5          0.0             end non post testing6109.5          0.0             create form class start6110.0          0.5             create form class end6110.0          0.0             start query options load6111.0          1.0             ----Sending query to triplestore6147.5          36.5            ----Recieved query from triplestore6154.5          7.0             ----Sending query to triplestore6199.0          44.5            ----Recieved query from triplestore6199.5          0.5             end query options load6360.5          161.0           template rendered|------------------------------------------------------------|  Testing  Using Windows 7 running Docker on Linux through VirtualBox<jupyter_code>import timeit
timeit.timeit(stmt="""requests.post(
	"http://li-b82p6v1-1208:9999/blazegraph/sparql",
	data={"query": "SELECT DISTINCT ?s ?p ?o WHERE { ?s ?p ?o .}",
	      "format": "json"})""",
	      setup="import requests",
	      number=100)
import timeit
timeit.timeit(stmt="""requests.post(
	"http://li-b82p6v1-1208:8080/bigdata/sparql",
	data={"query": "SELECT DISTINCT ?s ?p ?o WHERE { ?s ?p ?o .}",
	      "format": "json"})""",
	      setup="import requests",
	      number=100)
print("Using Blazegraph 2.0 in a standalone Docker container")
timeit.timeit(stmt="""requests.post(
	"http://li-b82p6v1-1208:9999/blazegraph/sparql",
	data={"query": "SELECT DISTINCT ?s ?p ?o WHERE { ?s ?p ?o .}",
	      "format": "json"})""",
	      setup="import requests",
	      number=100)<jupyter_output>Using Blazegraph 2.0 in a standalone Docker container<jupyter_text>Testing on MacOS X with Docker running Kitematic<jupyter_code>import timeit
print("Using Blazegraph 2.0 in a standalone Docker container")
timeit.timeit(stmt="""requests.post(
	"http://192.168.99.100:9999//blazegraph/sparql",
	data={"query": "SELECT DISTINCT ?s ?p ?o WHERE { ?s ?p ?o .}",
	      "format": "json"})""",
	      setup="import requests",
	      number=100)
import timeit
print("Using Blazegraph 2.0 as a Tomcat war in Semantic Server Docker container")
timeit.timeit(stmt="""requests.post(
	"http://localhost:8080/bigdata/sparql",
	data={"query": "SELECT DISTINCT ?s ?p ?o WHERE { ?s ?p ?o .}",
	      "format": "json"})""",
	      setup="import requests",
	      number=100)<jupyter_output>Using Blazegraph 2.0 as a Tomcat war in Semantic Server Docker container
{'fraction_non_alphanumeric': 0.14688427299703263, 'fraction_numerical': 0.07542037586547973, 'mean_word_length': 1.8606789250353606, 'pattern_counts': {'":': 10, '<': 7, '<?xml version=': 0, '>': 7, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 1, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 2, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '46059', 'license': 'Apache-2.0', 'n_tokens_mistral': 1347, 'n_tokens_neox': 1184, 'n_words': 333, 'path': 'blazegraph-testing.ipynb', 'repo_name': 'KnowledgeLinks/notebooks', 'size': '4044'}