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2 changed files with 69 additions and 102 deletions

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@@ -1,4 +1,5 @@
import os
import datetime
from dotenv import load_dotenv
from flask import Flask, jsonify, request
@@ -42,7 +43,6 @@ auth_manager = AuthManager(db, bcrypt)
stat_gen = StatGen()
@app.route("/register", methods=["POST"])
def register_user():
data = request.get_json()
@@ -112,7 +112,7 @@ def upload_data():
post_file = request.files["posts"]
topic_file = request.files["topics"]
if post_file.filename == "" or topic_file == "":
if post_file.filename == "" or topic_file.filename == "":
return jsonify({"error": "Empty filename"}), 400
if not post_file.filename.endswith(".jsonl") or not topic_file.filename.endswith(
@@ -280,75 +280,34 @@ def get_interaction_analysis(dataset_id):
return jsonify({"error": f"An unexpected error occurred: {str(e)}"}), 500
# @app.route("/filter/query", methods=["POST"])
# def filter_query():
# if stat_obj is None:
# return jsonify({"error": "No data uploaded"}), 400
@app.route("/dataset/query", methods=["POST"])
@jwt_required()
def filter_query():
data = request.get_json()
# data = request.get_json(silent=True) or {}
if "query" in data:
stat_gen.set_search_query(data["query"])
# if "query" not in data:
# return jsonify(stat_obj.df.to_dict(orient="records")), 200
if "start" in data:
start_timestamp = datetime.datetime.fromisoformat(data["start"])
stat_gen.set_start_date(start_timestamp)
# query = data["query"]
# filtered_df = stat_obj.filter_by_query(query)
if "end" in data:
end_timestamp = datetime.datetime.fromisoformat(data["end"])
stat_gen.set_end_date(end_timestamp)
# return jsonify(filtered_df), 200
if "sources" in data:
data_sources = set(data["sources"])
stat_gen.set_data_sources(data_sources)
return jsonify({"message": "Filters set successfully"}), 200
# @app.route("/filter/time", methods=["POST"])
# def filter_time():
# if stat_obj is None:
# return jsonify({"error": "No data uploaded"}), 400
# data = request.get_json(silent=True)
# if not data:
# return jsonify({"error": "Invalid or missing JSON body"}), 400
# if "start" not in data or "end" not in data:
# return jsonify({"error": "Please include both start and end dates"}), 400
# try:
# start = pd.to_datetime(data["start"], utc=True)
# end = pd.to_datetime(data["end"], utc=True)
# filtered_df = stat_obj.set_time_range(start, end)
# return jsonify(filtered_df), 200
# except Exception:
# return jsonify({"error": "Invalid datetime format"}), 400
# @app.route("/filter/sources", methods=["POST"])
# def filter_sources():
# if stat_obj is None:
# return jsonify({"error": "No data uploaded"}), 400
# data = request.get_json(silent=True)
# if not data:
# return jsonify({"error": "Invalid or missing JSON body"}), 400
# if "sources" not in data:
# return jsonify({"error": "Ensure sources hash map is in 'sources' key"}), 400
# try:
# filtered_df = stat_obj.filter_data_sources(data["sources"])
# return jsonify(filtered_df), 200
# except ValueError:
# return jsonify({"error": "Please enable at least one data source"}), 400
# except Exception as e:
# return jsonify({"error": "An unexpected server error occured: " + str(e)}), 500
# @app.route("/filter/reset", methods=["GET"])
# def reset_dataset():
# if stat_obj is None:
# return jsonify({"error": "No data uploaded"}), 400
# try:
# stat_obj.reset_dataset()
# return jsonify({"success": "Dataset successfully reset"})
# except Exception as e:
# print(traceback.format_exc())
# return jsonify({"error": f"An unexpected error occurred: {str(e)}"}), 500
@app.route("/database/query/reset", methods=["GET"])
@jwt_required()
def reset_dataset():
stat_gen.reset_filters()
return jsonify({"message": "Filters reset successfully"}), 200
if __name__ == "__main__":

View File

@@ -39,6 +39,37 @@ class StatGen:
self.linguistic_analysis = LinguisticAnalysis(EXCLUDE_WORDS)
self.cultural_analysis = CulturalAnalysis()
self.search_query = ""
self.start_date_filter = None
self.end_date_filter = None
self.data_source_filters = set()
## Private Methods
def _prepare_filtered_df(self, df: pd.DataFrame) -> pd.DataFrame:
filtered_df = df.copy()
if self.search_query:
mask = (
filtered_df["content"].str.contains(self.search_query, case=False, na=False)
| filtered_df["author"].str.contains(self.search_query, case=False, na=False).fillna(False)
| filtered_df["title"].str.contains(self.search_query, case=False, na=False, regex=False).fillna(False)
)
filtered_df = filtered_df[mask]
if self.start_date_filter and self.end_date_filter:
filtered_df = filtered_df[
(filtered_df["dt"] >= self.start_date_filter) & (filtered_df["dt"] <= self.end_date_filter)
]
if self.data_source_filters:
enabled_sources = [src for src, enabled in self.data_source_filters.items() if enabled]
if enabled_sources:
filtered_df = filtered_df[filtered_df["source"].isin(enabled_sources)]
return filtered_df
## Public Methods
def get_time_analysis(self, df: pd.DataFrame) -> dict:
return {
"events_per_day": self.temporal_analysis.posts_per_day(df),
@@ -93,43 +124,20 @@ class StatGen:
"sources": df["source"].dropna().unique().tolist(),
}
# def filter_by_query(self, df: pd.DataFrame, search_query: str) -> dict:
# filtered_df = df[df["content"].str.contains(search_query, na=False)]
def set_search_query(self, search_query: str) -> None:
self.search_query = search_query
# return {
# "rows": len(filtered_df),
# "data": filtered_df.to_dict(orient="records"),
# }
def set_start_date(self, start: datetime.datetime) -> None:
self.start_date_filter = start
# def set_time_range(
# self,
# original_df: pd.DataFrame,
# start: datetime.datetime,
# end: datetime.datetime,
# ) -> dict:
# df = self._prepare_df(original_df)
# filtered_df = df[(df["dt"] >= start) & (df["dt"] <= end)]
def set_end_date(self, end: datetime.datetime) -> None:
self.end_date_filter = end
# return {
# "rows": len(filtered_df),
# "data": filtered_df.to_dict(orient="records"),
# }
# def filter_data_sources(
# self, original_df: pd.DataFrame, data_sources: dict
# ) -> dict:
# df = self._prepare_df(original_df)
# enabled_sources = [src for src, enabled in data_sources.items() if enabled]
# if not enabled_sources:
# raise ValueError("Please choose at least one data source")
# filtered_df = df[df["source"].isin(enabled_sources)]
# return {
# "rows": len(filtered_df),
# "data": filtered_df.to_dict(orient="records"),
# }
# def reset_dataset(self, original_df: pd.DataFrame) -> pd.DataFrame:
# return self._prepare_df(original_df)
def set_data_sources(self, data_sources: set) -> None:
self.data_source_filters = data_sources
def reset_filters(self) -> None:
self.search_query = ""
self.start_date_filter = None
self.end_date_filter = None
self.data_source_filters = set()