def sample_describe_graph():
"""this demonstrates use of cypher query and interpretation of result returned from the query"""
rows, cols = db.cypher_query(
"MATCH (t:TeamMember)-[p:PROFICIENCY_FOR]-(s:Skill) RETURN t, p, s")
# cols {0: TeamMember, 1: Proficiency, 2: Skill}
for r in rows:
team_member = TeamMember.inflate(r[0])
proficiency = ProficiencyRel.inflate(r[1])
skill = Skill.inflate(r[2])
print(
f"Team member {team_member.name} is proficient in skill {skill.name} with a score {proficiency.score} "
f"in year {proficiency.year}\n")
def sample_queries():
"""sample queries, using both techniques provided by neomodel and cypher query"""
# use object graph mapping (OGM) to query for information
print(f"Skill Python: {Skill.nodes.get_or_none(name='Python')}")
print(
f"Skill Java that doesn't exist: {Skill.nodes.get_or_none(name='Java')}"
)
print("All team members name that starts with T:\n")
team_members = TeamMember.nodes.filter(Q(first_name__startswith="T"))
for n in team_members:
print(f"\tTeam member: {n}\n")
print(
"All team members name that starts with T with proficiencies more than 3 in:\n"
)
excellencies = team_members.skill.match(score__gt=4.0)
for ex in excellencies:
print(f"\t Skills: {ex}\n")
# use cypher queries
print("Current graph description:")
sample_describe_graph()
print(
"The skills in which team member first name starting with T has score more than 3 in any year"
)
rows, cols = db.cypher_query(
"MATCH(t: TeamMember)-[p: PROFICIENCY_FOR]-(s:Skill) "
"WHERE t.first_name STARTS WITH 'T' AND p.score > 3.0 "
"RETURN DISTINCT (s)")
# cols: {0: Skill}
for r in rows:
skill = Skill.inflate(r[0])
print(f"Skill name {skill.name}")
print(
"For each of the available skills, find out the list of team members who has proficiency in it\n"
)
skills = Skill.nodes.all()
for skill in skills:
rows, cols = db.cypher_query(
"MATCH (s:Skill)-[p:PROFICIENCY_FOR]-(t:TeamMember) "
"WHERE s.name = $name RETURN DISTINCT (t)",
params={"name": skill.name})
print(f"\nSkill name: {skill.name}")
for r in rows:
team_member = TeamMember.inflate(r[0]) # cols: {0: TeamMember}
print(f"Team member name {team_member.name}")
print("Queried sample queries ...")
