How to: use Python with sqlalchemy into postgresql

env.yml

name: sqlalchemy
channels:
  - conda-forge
dependencies:
  - pandas=2.0.2
  - pip=22.3.1
  - python=3.10.9
  - sqlalchemy=1.4.39
  - pip:
      - psychopg2-binary==2.9.6

quick_connect.py

from sqlalchemy import create_engine
from sqlalchemy.engine import URL
import pandas as pd

p = {
    "drivername": "postgresql+psycopg2",
    "username": "",
    "password": "",
    "database": "",
    "host": "",
    "port": "",
}
url = URL.create(**p)
engine = create_engine(url)
conn = engine.connect()

df = pd.read_sql_query("SELECT COUNT(*) FROM jobs.info", conn)
print(df.loc[0, "count"])

That is much more concise. The reason I didn't use SQLalchemy before was because I saw it struggles much more with large dataframes that the code I have in the postgres.py file. But for exploratory stuff on our end, that will work well