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Bump version and enhance prospects init #29

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Merged
goldlabelapps merged 1 commit into from
Mar 27, 2026
Merged

Bump version and enhance prospects init #29

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2 changes: 1 addition & 1 deletion app/__init__.py
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Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
"""NX AI - FastAPI/Python/Postgres/tsvector"""

# Current Version
__version__ = "1.1.5"
__version__ = "1.1.6"
23 changes: 15 additions & 8 deletions app/api/prospects/prospects.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,13 +5,14 @@
from app.utils.db import get_db_connection

router = APIRouter()


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Copilot AI Mar 27, 2026

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There’s trailing whitespace on this blank line, which tends to cause avoidable diffs/lint noise. Please remove the extra spaces.

Suggested change

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base_url = os.getenv("BASE_URL", "http://localhost:8000")

@router.get("/prospects")
def root() -> dict:
"""Return a placeholder message for prospects endpoint."""
meta = make_meta("success", "Prospects placeholder")
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base_url is read at import time, while make_meta() reads BASE_URL at request time. This can lead to inconsistent URLs between meta.base_url and the data.init link (and can also produce double slashes if BASE_URL ends with /). Consider deriving the init link from meta["base_url"] and normalizing with rstrip("/") before concatenating the path.

Suggested change
meta = make_meta("success", "Prospects placeholder")
meta = make_meta("success", "Prospects placeholder")
base_url = meta.get("base_url", "").rstrip("/") # Derive from meta to keep URLs consistent

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data = {"message": "This is a placeholder for the /prospects endpoint."}
data = {"init": f"{base_url}/prospects/init"}
return {"meta": meta, "data": data}


Expand All @@ -38,24 +39,30 @@ def prospects_init() -> dict:
# Get unique titles and their counts (column is 'title')
cur.execute('SELECT title, COUNT(*) FROM prospects WHERE title IS NOT NULL GROUP BY title ORDER BY COUNT(*) DESC;')
title_rows = cur.fetchall()
def slugify(text):
import re
text = str(text).lower()
text = re.sub(r'[^a-z0-9]+', '-', text)
return text.strip('-')
Comment on lines +42 to +46
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Defining slugify() inside the request handler (and importing re inside the helper) adds per-request overhead and makes the helper harder to reuse/test. Consider moving slugify (and the re import) to module scope, outside the try: block.

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title = [
{"label": t[0], "count": t[1]} for t in title_rows if t[0] is not None
{"label": f"{t[0]} ({t[1]})", "value": slugify(t[0])} for t in title_rows if t[0] is not None
]
total_unique_title = len(title)

# Get unique seniority and their counts (column is 'seniority')
cur.execute('SELECT seniority, COUNT(*) FROM prospects WHERE seniority IS NOT NULL GROUP BY seniority ORDER BY COUNT(*) DESC;')
seniority_rows = cur.fetchall()
seniority = [
{"label": s[0], "count": s[1]} for s in seniority_rows if s[0] is not None
{"label": f"{s[0]} ({s[1]})", "value": slugify(s[0])} for s in seniority_rows if s[0] is not None
]
total_unique_seniority = len(seniority)

# Get unique sub_departments and their counts (column is 'sub_departments')
cur.execute('SELECT sub_departments, COUNT(*) FROM prospects WHERE sub_departments IS NOT NULL GROUP BY sub_departments ORDER BY COUNT(*) DESC;')
sub_department_rows = cur.fetchall()
sub_departments = [
{"label": sd[0], "count": sd[1]} for sd in sub_department_rows if sd[0] is not None
{"label": f"{sd[0]} ({sd[1]})", "value": slugify(sd[0])} for sd in sub_department_rows if sd[0] is not None
]
total_unique_sub_departments = len(sub_departments)
except Exception:
Expand All @@ -73,15 +80,15 @@ def prospects_init() -> dict:
"total_prospects": total,
"title": {
"total_unique": total_unique_title,
"values": title
"values": title[:3]
},
"seniority": {
"total_unique": total_unique_seniority,
"values": seniority
"values": seniority[:3]
},
"departments": {
"total_unique": total_unique_sub_departments,
"values": sub_departments
"values": sub_departments[:3]
Comment on lines +83 to +91
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The response now slices to the top 3 values, but the queries still fetch all grouped rows (fetchall()), which can be expensive with many distinct titles/seniority/departments. Consider using LIMIT 3 for the top lists and a separate COUNT(DISTINCT ...) query for total_unique to avoid transferring/processing large result sets.

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}
}
return {"meta": meta, "data": data}
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