From 3fcf3574e6419359fee0d7a0f8caf8b69fbaa2c6 Mon Sep 17 00:00:00 2001
From: "georg.sinn-schirwitz" <georg.sinn-schirwitz@in-factory.com>
Date: Fri, 29 Aug 2025 23:01:46 +0200
Subject: [PATCH] remove analytics

---
 analytics.py     | 82 ------------------------------------------------
 requirements.txt |  1 -
 2 files changed, 83 deletions(-)
 delete mode 100644 analytics.py

diff --git a/analytics.py b/analytics.py
deleted file mode 100644
index d17c1ee..0000000
--- a/analytics.py
+++ /dev/null
@@ -1,82 +0,0 @@
-import pandas as pd
-from sqlalchemy import create_engine, text
-from web.utils import get_mysql_config
-
-
-def get_engine():
-    cfg = get_mysql_config()
-    url = f"mysql+pymysql://{cfg['user']}:{cfg['password']}@{cfg['host']}:{cfg['port']}/{cfg['database']}?charset=utf8mb4"
-    return create_engine(url, future=True)
-
-
-def get_all_jobs():
-    query = """
-SELECT l.job_id
-,l.title
-,d.description
-,l.region
-,l.keyword
-,d.company
-,l.location
-,l.timestamp
-,d.posted_time
-,l.url
-,c.file_path
-,c.last_modified
-,c.url_guess
-,CASE WHEN c.url_guess != l.url THEN 1 ELSE 0 END AS url_guess_stale
-FROM job_listings AS l
-INNER JOIN job_descriptions AS d 
-ON l.job_id = d.job_id
-AND l.url = d.url
-LEFT JOIN cached_pages AS c ON l.job_id = c.job_id
-ORDER BY d.posted_time DESC
-    """
-    engine = get_engine()
-    with engine.begin() as conn:
-        rows = conn.execute(text(query)).fetchall()
-    return [
-        {
-            "job_id": row[0],
-            "title": row[1],
-            "description": row[2],
-            "region": row[3],
-            "keyword": row[4],
-            "company": row[5],
-            "location": row[6],
-            "timestamp": row[7],
-            "posted_time": row[8],
-            "url": row[9],
-            "file_path": row[10],
-            "last_modified": row[11],
-            "url_guess": row[12],
-            "url_guess_stale": row[13],
-        }
-        for row in rows
-    ]
-
-
-def main():
-    """Main function to load and display job postings."""
-    jobs_df = pd.DataFrame(get_all_jobs())
-
-    print(jobs_df.head())
-    print(f"Total postings: {len(jobs_df)}")
-
-    print("Regions:")
-    print(jobs_df['region'].value_counts())
-
-    print("Keywords:")
-    print(jobs_df['keyword'].value_counts())
-
-    # print("Sample Job Postings:")
-    # print("-" * 40)
-    # for sample in jobs_df[['region', 'keyword', 'title', 'location', 'description']].sample(5).itertuples():
-    #     print(
-    #         f"Region: {sample.region}, Keyword: {sample.keyword}, Title: {sample.title}, Location: {sample.location}")
-    #     print(sample.description)
-    #     print("-" * 40)
-
-
-if __name__ == "__main__":
-    main()
diff --git a/requirements.txt b/requirements.txt
index 0dc108d..91e7e36 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,7 +1,6 @@
 beautifulsoup4
 flask
 flask-wtf
-pandas
 pytest
 requests
 sqlalchemy