'volume' : volume }
if len(objects) >= chunk_size:
print(f"Running chunk {chunk}")
client.insert_document(objects,commit_msg = f"Inserting stock exchange ticker chunk {chunk}")
objects = []
chunk+=1
else:
objects.append(obj)
if not (objects == []):
client.insert_document(objects,commit_msg = "Adding initial schema")
load_file('indexData.csv')
branch = "second"
client.create_branch(branch)
client.branch = branch
load_file('other.csv')
print("About to rebase")
client.branch = "main"
client.rebase(f"{team}/{db}/local/branch/second")
print("About to query")
client.optimize(f"{team}/{db}")
documents = client.query_document({'@type' : 'IndexRecord',
'date' : '2021-07-01'})
print(list(documents))
# TODO: change the team name
team = "<TEAM_NAME>"
client = WOQLClient("https://cloud.terminusdb.com/"+team)
try:
client.connect(team=team, use_token=True)
client.create_database(db_id, label = "Netflix Graph", description = "Create a graph with Netflix data")
except Exception:
client.connect(db=db_id, team=team, use_token=True)
schema.commit(client, commit_msg = "Adding Netflix Schema")
insert_content_data(client, url)
contents = client.query_document({"@type" : "Content"}, count=50)
insert_user_data(list(contents))
print("\nQUERING DOCUMENTS\n")
query_documents(client)
print("\nBranches\n")
branches(client)
# Get the whole commit history:
commit_history = client.get_commit_history()
print("\nCOMMIT HISTORY\n",commit_history)
# Manipulate the commit history
print("\nTime Travel\n")
from terminusdb_client import WOQLClient
from terminusdb_client.woqlschema import WOQLSchema
from terminusdb_client.woqldataframe import result_to_df
# For Terminus X, use the following
# client = WOQLClient("https://cloud.terminusdb.com/<Your Team>/")
# client.connect(db="demo_workshop", team="<Your Team>", use_token=True)
client = WOQLClient("http://127.0.0.1:6363/")
client.connect(db="getting_started")
team_it_raw = client.query_document({"@type": "Employee", "team": "it"})
team_marketing_raw = client.query_document({
"@type": "Employee",
"team": "marketing"
})
team_it = result_to_df(team_it_raw)
team_marketing = result_to_df(team_marketing_raw)
team_it_avg = team_it["name"].apply(len).sum() / len(team_it)
team_marketing_avg = team_it["name"].apply(len).sum() / len(team_marketing)
print(f"Average name length of IT team is {team_it_avg}")
print(f"Average name length of Marketing team is {team_marketing_avg}")
