pyr0ball
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LinkedIn's unauthenticated public profile only exposes name, summary (truncated), current employer name, and certifications. Past roles, education, and skills are blurred server-side behind a login wall — not a scraper limitation. - Update selectors: data-section='summary' (was 'about'), .profile-section-card for certs, .visible-list for current experience entry - Strip login-wall noise injected into summary text after 'see more' - Skip aria-hidden blurred placeholder experience items - Add info callout in UI directing users to data export zip for full history
192 lines
7.7 KiB
Python
192 lines
7.7 KiB
Python
# app/components/linkedin_import.py
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"""
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Shared LinkedIn import widget.
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Usage in a page:
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from app.components.linkedin_import import render_linkedin_tab
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# At top of page render — check for pending import:
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_li_data = st.session_state.pop("_linkedin_extracted", None)
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if _li_data:
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st.session_state["_parsed_resume"] = _li_data
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st.rerun()
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# Inside the LinkedIn tab:
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with tab_linkedin:
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render_linkedin_tab(config_dir=CONFIG_DIR, tier=tier)
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"""
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from __future__ import annotations
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import json
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import re
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from datetime import datetime, timezone
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from pathlib import Path
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import streamlit as st
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_LINKEDIN_PROFILE_RE = re.compile(r"https?://(www\.)?linkedin\.com/in/", re.I)
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def _stage_path(config_dir: Path) -> Path:
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return config_dir / "linkedin_stage.json"
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def _load_stage(config_dir: Path) -> dict | None:
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path = _stage_path(config_dir)
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if not path.exists():
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return None
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try:
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return json.loads(path.read_text())
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except Exception:
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return None
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def _days_ago(iso_ts: str) -> str:
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try:
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dt = datetime.fromisoformat(iso_ts)
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delta = datetime.now(timezone.utc) - dt
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days = delta.days
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if days == 0:
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return "today"
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if days == 1:
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return "yesterday"
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return f"{days} days ago"
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except Exception:
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return "unknown"
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def _do_scrape(url: str, config_dir: Path) -> None:
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"""Validate URL, run scrape, update state."""
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if not _LINKEDIN_PROFILE_RE.match(url):
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st.error("Please enter a LinkedIn profile URL (linkedin.com/in/…)")
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return
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with st.spinner("Fetching LinkedIn profile… (10–20 seconds)"):
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try:
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from scripts.linkedin_scraper import scrape_profile
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scrape_profile(url, _stage_path(config_dir))
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st.success("Profile imported successfully.")
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st.rerun()
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except ValueError as e:
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st.error(str(e))
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except RuntimeError as e:
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st.warning(str(e))
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except Exception as e:
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st.error(f"Unexpected error: {e}")
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def render_linkedin_tab(config_dir: Path, tier: str) -> None:
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"""
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Render the LinkedIn import UI.
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When the user clicks "Use this data", writes the extracted dict to
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st.session_state["_linkedin_extracted"] and calls st.rerun().
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Caller reads: data = st.session_state.pop("_linkedin_extracted", None)
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"""
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stage = _load_stage(config_dir)
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# ── Staged data status bar ────────────────────────────────────────────────
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if stage:
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scraped_at = stage.get("scraped_at", "")
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source_label = "LinkedIn export" if stage.get("source") == "export_zip" else "LinkedIn profile"
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col_info, col_refresh = st.columns([4, 1])
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col_info.caption(f"Last imported from {source_label}: {_days_ago(scraped_at)}")
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if col_refresh.button("🔄 Refresh", key="li_refresh"):
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url = stage.get("url")
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if url:
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_do_scrape(url, config_dir)
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else:
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st.info("Original URL not available — paste the URL below to re-import.")
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# ── URL import ────────────────────────────────────────────────────────────
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st.markdown("**Import from LinkedIn profile URL**")
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url_input = st.text_input(
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"LinkedIn profile URL",
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placeholder="https://linkedin.com/in/your-name",
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label_visibility="collapsed",
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key="li_url_input",
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)
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if st.button("🔗 Import from LinkedIn", key="li_import_btn", type="primary"):
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if not url_input.strip():
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st.warning("Please enter your LinkedIn profile URL.")
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else:
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_do_scrape(url_input.strip(), config_dir)
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st.caption(
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"Imports from your public LinkedIn profile. No login or credentials required. "
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"Scraping typically takes 10–20 seconds."
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)
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st.info(
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"**LinkedIn limits public profile data.** Without logging in, LinkedIn only "
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"exposes your name, About summary, current employer, and certifications — "
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"past roles, education, and skills are hidden behind their login wall. "
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"For your full career history use the **data export zip** option below.",
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icon="ℹ️",
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)
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# ── Section preview + use button ─────────────────────────────────────────
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if stage:
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from scripts.linkedin_parser import parse_stage
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extracted, err = parse_stage(_stage_path(config_dir))
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if err:
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st.warning(f"Could not read staged data: {err}")
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else:
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st.divider()
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st.markdown("**Preview**")
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col1, col2, col3 = st.columns(3)
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col1.metric("Experience entries", len(extracted.get("experience", [])))
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col2.metric("Skills", len(extracted.get("skills", [])))
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col3.metric("Certifications", len(extracted.get("achievements", [])))
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if extracted.get("career_summary"):
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with st.expander("Summary"):
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st.write(extracted["career_summary"])
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if extracted.get("experience"):
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with st.expander(f"Experience ({len(extracted['experience'])} entries)"):
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for exp in extracted["experience"]:
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st.markdown(f"**{exp.get('title')}** @ {exp.get('company')} · {exp.get('date_range', '')}")
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if extracted.get("education"):
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with st.expander("Education"):
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for edu in extracted["education"]:
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st.markdown(f"**{edu.get('school')}** — {edu.get('degree')} {edu.get('field', '')}".strip())
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if extracted.get("skills"):
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with st.expander("Skills"):
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st.write(", ".join(extracted["skills"]))
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st.divider()
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if st.button("✅ Use this data", key="li_use_btn", type="primary"):
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st.session_state["_linkedin_extracted"] = extracted
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st.rerun()
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# ── Advanced: data export ─────────────────────────────────────────────────
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with st.expander("⬇️ Import from LinkedIn data export (advanced)", expanded=False):
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st.caption(
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"Download your LinkedIn data: **Settings & Privacy → Data Privacy → "
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"Get a copy of your data → Request archive → Fast file**. "
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"The Fast file is available immediately and contains your profile, "
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"experience, education, and skills."
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)
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zip_file = st.file_uploader(
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"Upload LinkedIn export zip", type=["zip"], key="li_zip_upload"
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)
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if zip_file is not None:
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if st.button("📦 Parse export", key="li_parse_zip"):
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with st.spinner("Parsing export archive…"):
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try:
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from scripts.linkedin_scraper import parse_export_zip
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extracted = parse_export_zip(
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zip_file.read(), _stage_path(config_dir)
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)
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st.success(
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f"Imported {len(extracted.get('experience', []))} experience entries, "
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f"{len(extracted.get('skills', []))} skills. "
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"Click 'Use this data' above to apply."
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)
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st.rerun()
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except Exception as e:
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st.error(f"Failed to parse export: {e}")
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