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Merged
ekansh18 merged 8 commits into from
Jun 15, 2025
Merged

Frontend integration into declarative pql #74

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f399656
Added arrowheads in graphs where necessary
ekansh18 Jun 15, 2025
0a1ca3f
Implemented info buttons for all insights
ekansh18 Jun 15, 2025
1917b27
Added new button for Declarative
ekansh18 Jun 15, 2025
4a276c5
Updated info pages for temporal and resource based
ekansh18 Jun 15, 2025
920fdbc
Updated page for declarative and info buttons update
ekansh18 Jun 15, 2025
0a6aee3
Yash's Declarative constraints changes with PQL queries
ekansh18 Jun 15, 2025
a8e94e1
Updated url for declarative pql
ekansh18 Jun 15, 2025
e257df7
Merge branch 'declarative_PQL' into frontend-integration
ekansh18 Jun 15, 2025
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2 changes: 1 addition & 1 deletion backend/api/modules/declarative_router.py
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Original file line number Diff line number Diff line change
Expand Up @@ -369,7 +369,7 @@ def get_nonchainsuccession_violations(job_id: str, request: Request) -> ReturnGr
return request.app.state.jobs[job_id].result.get("nonchainsuccession", [])


# **************** Retrieving Declarative Model Attributes - PM4PY ****************
# **************** Retrieving Declarative Model Attributes - PQL Queries ****************


@router.get("/get_always_after_pql/")
Expand Down
136 changes: 86 additions & 50 deletions backend/pql_queries/declarative_queries.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,7 +19,8 @@

# **************** Formatting Function ****************

def format_graph_and_table (curr_df: pd.DataFrame) -> ReturnGraphType:

def format_graph_and_table(curr_df: pd.DataFrame) -> ReturnGraphType:
"""Formats the DataFrame into a graph and table structure.

Args:
Expand All @@ -28,44 +29,55 @@ def format_graph_and_table (curr_df: pd.DataFrame) -> ReturnGraphType:
Returns:
ReturnGraphType: A dictionary containing the formatted graph and table.
"""
output: ReturnGraphType = {"graphs": [], "tables": []}

if not curr_df.empty :
if curr_df.shape[1] == 3 :
output: ReturnGraphType = {"graphs": [], "tables": []}

if not curr_df.empty:
if curr_df.shape[1] == 3:
nodes = []
edges = []
for i, row in curr_df.iterrows(): # type: ignore
for i, row in curr_df.iterrows(): # type: ignore
nodes.append(str(row[curr_df.columns[0]])) # type: ignore
nodes.append(str(row[curr_df.columns[1]])) # type: ignore
edges.append({ # type: ignore
'from': str(row[curr_df.columns[0]]), # type: ignore
'to': str(row[curr_df.columns[1]]), # type: ignore
'label': str(row[curr_df.columns[2]]) # type: ignore
})

nodes = [{'id': str(ele)} for ele in list(set(list(nodes)))] # type: ignore
output["graphs"].append({
"nodes": nodes, # type: ignore
"edges": edges
})

headers = list(curr_df.columns)
rows = curr_df.values.tolist() # type: ignore
output["tables"].append({
"headers": headers, # type: ignore
"rows": [[str(ele) for ele in row] for row in rows] # type: ignore
})
else :
headers = list(curr_df.columns)
rows = curr_df.values.tolist() # type: ignore
output["tables"].append({
"headers": headers, # type: ignore
"rows": [[str(ele) for ele in row] for row in rows] # type: ignore
})
edges.append(
{ # type: ignore
"from": str(row[curr_df.columns[0]]), # type: ignore
"to": str(row[curr_df.columns[1]]), # type: ignore
"label": str(row[curr_df.columns[2]]), # type: ignore
}
)

nodes = [{"id": str(ele)} for ele in list(set(list(nodes)))] # type: ignore
output["graphs"].append(
{
"nodes": nodes, # type: ignore
"edges": edges,
}
)

headers = list(curr_df.columns)
rows = curr_df.values.tolist() # type: ignore
output["tables"].append(
{
"headers": headers, # type: ignore
"rows": [[str(ele) for ele in row] for row in rows], # type: ignore
}
)
else:
headers = list(curr_df.columns)
rows = curr_df.values.tolist() # type: ignore
output["tables"].append(
{
"headers": headers, # type: ignore
"rows": [[str(ele) for ele in row] for row in rows], # type: ignore
}
)
return output


# **************** PQL Functions ****************


# Always before
def get_always_before_relation(celonis: CelonisConnectionManager) -> ReturnGraphType:
"""Compute Always-Before summary using PQL.
Expand All @@ -76,23 +88,37 @@ def get_always_before_relation(celonis: CelonisConnectionManager) -> ReturnGraph
Returns:
ReturnGraphType: A dictionary containing the formatted graph and table.
"""
target_df: pd.DataFrame = DataFrame(columns=["Activity A", "Activity B", "# Occurrences"])
act_table = get_activities(celonis) # type: ignore
activitiy_pairs = list(combinations(act_table["Activity"].to_list(), 2)) # type: ignore
for i, pair in enumerate(activitiy_pairs): # type: ignore
target_df: pd.DataFrame = DataFrame(
columns=["Activity A", "Activity B", "# Occurrences"]
)
act_table = get_activities(celonis) # type: ignore
activitiy_pairs = list(combinations(act_table["Activity"].to_list(), 2)) # type: ignore
for i, pair in enumerate(activitiy_pairs): # type: ignore
query = {
"A before B": f"""MATCH_PROCESS ("ACTIVITIES"."concept:name", NODE ['{pair[0]}'] as src,
NODE ['{pair[1]}'] as tgt CONNECTED BY EVENTUALLY [src , tgt])""",
"B before A": f"""MATCH_PROCESS ("ACTIVITIES"."concept:name", NODE ['{pair[1]}'] as src,
NODE ['{pair[0]}'] as tgt CONNECTED BY EVENTUALLY [src , tgt])""",
}
pair_df = celonis.get_dataframe_from_celonis(query) # type: ignore
if (pair_df["B before A"] == 1).any() and not (pair_df["A before B"] == 1).any(): # type: ignore
target_df.loc[i] = [pair[1], pair[0], int((pair_df["B before A"] == 1).sum())] # type: ignore
elif (pair_df["A before B"] == 1).any() and not (pair_df["B before A"] == 1).any(): # type: ignore
target_df.loc[i] = [pair[0], pair[1], int((pair_df["A before B"] == 1).sum())] # type: ignore
output = format_graph_and_table(target_df)
return output
pair_df = celonis.get_dataframe_from_celonis(query) # type: ignore
if (pair_df["B before A"] == 1).any() and not (
pair_df["A before B"] == 1
).any(): # type: ignore
target_df.loc[i] = [
pair[1],
pair[0],
int((pair_df["B before A"] == 1).sum()),
] # type: ignore
elif (pair_df["A before B"] == 1).any() and not (
pair_df["B before A"] == 1
).any(): # type: ignore
target_df.loc[i] = [
pair[0],
pair[1],
int((pair_df["A before B"] == 1).sum()),
] # type: ignore
output = format_graph_and_table(target_df)
return output


# Always after
Expand All @@ -107,18 +133,28 @@ def get_always_after_relation(celonis: CelonisConnectionManager) -> ReturnGraphT
"""
target_df = DataFrame(columns=["Activity A", "Activity B", "# Occurrences"])
act_table = get_activities(celonis)
activitiy_pairs = list(combinations(act_table["Activity"].to_list(), 2)) # type: ignore
for i, pair in enumerate(activitiy_pairs): # type: ignore
activitiy_pairs = list(combinations(act_table["Activity"].to_list(), 2)) # type: ignore
for i, pair in enumerate(activitiy_pairs): # type: ignore
query = {
"A after B": f"""MATCH_PROCESS ("ACTIVITIES"."concept:name", NODE ['{pair[1]}'] as src,
NODE ['{pair[0]}'] as tgt CONNECTED BY EVENTUALLY [src , tgt])""",
"B after A": f"""MATCH_PROCESS ("ACTIVITIES"."concept:name", NODE ['{pair[0]}'] as src,
NODE ['{pair[1]}'] as tgt CONNECTED BY EVENTUALLY [src , tgt])""",
}
pair_df = celonis.get_dataframe_from_celonis(query) # type: ignore
if (pair_df["B after A"] == 1).any() and not (pair_df["A after B"] == 1).any(): # type: ignore
target_df.loc[i] = [pair[1], pair[0], int((pair_df["B after A"] == 1).sum())] # type: ignore
elif (pair_df["A after B"] == 1).any() and not (pair_df["B after A"] == 1).any(): # type: ignore
target_df.loc[i] = [pair[0], pair[1], int((pair_df["A after B"] == 1).sum())] # type: ignore
output = format_graph_and_table(target_df)
return output
pair_df = celonis.get_dataframe_from_celonis(query) # type: ignore
if (pair_df["B after A"] == 1).any() and not (pair_df["A after B"] == 1).any(): # type: ignore
target_df.loc[i] = [
pair[1],
pair[0],
int((pair_df["B after A"] == 1).sum()),
] # type: ignore
elif (pair_df["A after B"] == 1).any() and not (
pair_df["B after A"] == 1
).any(): # type: ignore
target_df.loc[i] = [
pair[0],
pair[1],
int((pair_df["A after B"] == 1).sum()),
] # type: ignore
output = format_graph_and_table(target_df)
return output
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