Spaces:
Runtime error
Runtime error
File size: 8,531 Bytes
cca012f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 | import sqlite3
import json
import os
from typing import List, Optional, Dict, Any
from tech_radar.db.models import JobPosting
class DatabaseManager:
"""Thread-safe SQLite database manager for TechRadar-MCP across all domains & cities."""
def __init__(self, db_path: str = "tech_radar.db"):
self.db_path = db_path
self._init_db()
def _get_connection(self) -> sqlite3.Connection:
conn = sqlite3.connect(self.db_path)
conn.row_factory = sqlite3.Row
return conn
def _init_db(self):
with self._get_connection() as conn:
cursor = conn.cursor()
cursor.execute("""
CREATE TABLE IF NOT EXISTS job_postings (
id TEXT PRIMARY KEY,
title TEXT NOT NULL,
company TEXT NOT NULL,
tech_domain TEXT NOT NULL,
city TEXT NOT NULL,
area TEXT NOT NULL,
salary_min_lpa REAL NOT NULL,
salary_max_lpa REAL NOT NULL,
experience_min_years INTEGER NOT NULL,
experience_max_years INTEGER NOT NULL,
tech_stack TEXT NOT NULL, -- JSON List
requirements TEXT NOT NULL,
work_mode TEXT NOT NULL,
company_tier TEXT NOT NULL,
posted_date TEXT NOT NULL,
url TEXT
)
""")
conn.commit()
def save_job_posting(self, job: JobPosting) -> bool:
with self._get_connection() as conn:
cursor = conn.cursor()
cursor.execute("""
INSERT OR REPLACE INTO job_postings (
id, title, company, tech_domain, city, area, salary_min_lpa, salary_max_lpa,
experience_min_years, experience_max_years, tech_stack, requirements,
work_mode, company_tier, posted_date, url
) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
""", (
job.id, job.title, job.company, job.tech_domain, job.city, job.area,
job.salary_min_lpa, job.salary_max_lpa,
job.experience_min_years, job.experience_max_years,
json.dumps(job.tech_stack), job.requirements,
job.work_mode, job.company_tier, job.posted_date, job.url
))
conn.commit()
return True
def get_job_by_id(self, job_id: str) -> Optional[JobPosting]:
with self._get_connection() as conn:
cursor = conn.cursor()
cursor.execute("SELECT * FROM job_postings WHERE id = ?", (job_id,))
row = cursor.fetchone()
if not row:
return None
return self._row_to_job(row)
def search_jobs(
self,
domain: Optional[str] = None,
city: Optional[str] = None,
query: Optional[str] = None,
experience_level: Optional[int] = None,
min_salary_lpa: Optional[float] = None,
tech_stack_filter: Optional[List[str]] = None,
limit: int = 100
) -> List[JobPosting]:
with self._get_connection() as conn:
cursor = conn.cursor()
sql = "SELECT * FROM job_postings WHERE 1=1"
params = []
if domain and domain.lower() != "all":
sql += " AND LOWER(tech_domain) = LOWER(?)"
params.append(domain)
if city and city.lower() != "all":
sql += " AND LOWER(city) = LOWER(?)"
params.append(city)
if experience_level is not None:
sql += " AND experience_min_years <= ? AND experience_max_years >= ?"
params.extend([experience_level, experience_level])
if min_salary_lpa is not None:
sql += " AND salary_max_lpa >= ?"
params.append(min_salary_lpa)
if query:
sql += " AND (LOWER(title) LIKE LOWER(?) OR LOWER(company) LIKE LOWER(?) OR LOWER(requirements) LIKE LOWER(?) OR LOWER(area) LIKE LOWER(?))"
q = f"%{query}%"
params.extend([q, q, q, q])
sql += " ORDER BY salary_max_lpa DESC LIMIT ?"
params.append(limit)
cursor.execute(sql, params)
rows = cursor.fetchall()
jobs = [self._row_to_job(r) for r in rows]
if tech_stack_filter:
filter_set = {s.lower() for s in tech_stack_filter}
jobs = [
j for j in jobs
if any(ts.lower() in filter_set for ts in j.tech_stack)
]
return jobs
def get_all_jobs(self) -> List[JobPosting]:
return self.search_jobs(limit=500)
def get_market_analytics(self, city: str = "All", domain: str = "All") -> Dict[str, Any]:
with self._get_connection() as conn:
cursor = conn.cursor()
sql = "SELECT COUNT(*), AVG((salary_min_lpa + salary_max_lpa) / 2.0), MIN(salary_min_lpa), MAX(salary_max_lpa) FROM job_postings WHERE 1=1"
params = []
if city and city.lower() != "all":
sql += " AND LOWER(city) = LOWER(?)"
params.append(city)
if domain and domain.lower() != "all":
sql += " AND LOWER(tech_domain) = LOWER(?)"
params.append(domain)
cursor.execute(sql, params)
count, avg_sal, min_sal, max_sal = cursor.fetchone()
if not count or count == 0:
return {
"city": city,
"domain": domain,
"total_jobs": 0,
"avg_salary_lpa": 0,
"salary_range": "N/A",
"top_frameworks": [],
"top_hubs": [],
"top_companies": []
}
sql_details = "SELECT tech_stack, area, company FROM job_postings WHERE 1=1"
params_details = []
if city and city.lower() != "all":
sql_details += " AND LOWER(city) = LOWER(?)"
params_details.append(city)
if domain and domain.lower() != "all":
sql_details += " AND LOWER(tech_domain) = LOWER(?)"
params_details.append(domain)
cursor.execute(sql_details, params_details)
rows = cursor.fetchall()
skill_counts = {}
hub_counts = {}
company_set = set()
for r in rows:
stacks = json.loads(r["tech_stack"])
for s in stacks:
skill_counts[s] = skill_counts.get(s, 0) + 1
area = r["area"]
hub_counts[area] = hub_counts.get(area, 0) + 1
company_set.add(r["company"])
sorted_skills = [
{"skill": k, "count": v, "percentage": round((v / count) * 100, 1)}
for k, v in sorted(skill_counts.items(), key=lambda x: x[1], reverse=True)[:10]
]
sorted_hubs = [
{"hub": k, "count": v}
for k, v in sorted(hub_counts.items(), key=lambda x: x[1], reverse=True)[:5]
]
return {
"city": city,
"domain": domain,
"total_jobs": count,
"avg_salary_lpa": round(avg_sal or 0, 1),
"salary_range": f"₹{int(min_sal or 0)}L - ₹{int(max_sal or 0)}L PA",
"top_frameworks": sorted_skills,
"top_hubs": sorted_hubs,
"top_companies": list(company_set)[:10]
}
def _row_to_job(self, row: sqlite3.Row) -> JobPosting:
return JobPosting(
id=row["id"],
title=row["title"],
company=row["company"],
tech_domain=row["tech_domain"],
city=row["city"],
area=row["area"],
salary_min_lpa=row["salary_min_lpa"],
salary_max_lpa=row["salary_max_lpa"],
experience_min_years=row["experience_min_years"],
experience_max_years=row["experience_max_years"],
tech_stack=json.loads(row["tech_stack"]),
requirements=row["requirements"],
work_mode=row["work_mode"],
company_tier=row["company_tier"],
posted_date=row["posted_date"],
url=row["url"]
)
|