added api and display for analyzing department for specific artworks

.gitignore

@@ -1 +1,2 @@
-venv
+venv
+final_project

main.py

@@ -1,5 +1,6 @@
 import streamlit as st
-
+import met_api
+import pandas as pd
 # Page setup
 st.set_page_config(page_title="The METrics", layout="centered")
 
@@ -62,6 +63,25 @@ st.markdown("""
 </div>
 """, unsafe_allow_html=True)
 
+# Department analytic
+st.write("")
+st.subheader("Departments for your search")
+
+query = st.text_input("Search term (for images only)", value="cats", key="dept_query")
+max_ids = st.slider("How many results to analyze", 20, 400, 150, 10, key="dept_max")
+
+if st.button("Run department analytic", key="dept_run"):
+    with st.spinner("Fetching and tallying departments…"):
+        rows = met_api.department_counts(q=query, max_ids=max_ids)
+
+    if not rows:
+        st.info("No results found (or the API call failed). Try another term.")
+    else:
+        df = pd.DataFrame(rows, columns=["Department", "Count"])
+        # show a quick bar chart + table
+        st.bar_chart(df.set_index("Department"))
+        st.dataframe(df, use_container_width=True)
+
 st.write("")
 
 # Footer

met_api.py

@@ -0,0 +1,61 @@
+import requests
+import random
+
+URL = "https://collectionapi.metmuseum.org/public/collection/v1/"
+
+'''
+Need to add error handling
+'''
+
+# gets information on a single object
+def get_object(objectID):
+    return requests.get(f"{URL}/objects/{objectID}").json()
+
+# gets all the objects that have some sort of image
+def get_objectsWithImages():
+    response = requests.get(f"{URL}search?hasImages=true&q=*").json()
+    total = response["total"]
+    objectIDs = response["objectIDs"]
+    return total, objectIDs
+
+# gets the urls for random objects with images
+def get_images(totalObjects, objectIDs, limit):
+    images = []
+    # grabbing extra in case a primary image is blank (Works best on small limits)
+    rand_indexes = random.sample(range(totalObjects), limit + 20)
+    for i in rand_indexes:
+        obj = get_object(objectIDs[i])
+        if obj["primaryImage"]:
+            images.append((obj["primaryImage"], obj["title"]))
+        if len(images) == limit:
+            break
+
+    return images
+
+def department_counts(q="*", max_ids=200):
+    """
+    Analytic: return a list of (department, count) for search results.
+    - q: search query (default '*' = anything)
+    - max_ids: cap how many object IDs to inspect (keeps it fast)
+
+    Uses the Met search endpoint (images only), then tallies the 'department'
+    field from each object's metadata.
+    """
+    try:
+        resp = requests.get(f"{URL}search", params={"q": q, "hasImages": True}, timeout=15)
+        resp.raise_for_status()
+        ids = (resp.json().get("objectIDs") or [])[:max_ids]
+    except Exception:
+        return []
+
+    counts = {}
+    for oid in ids:
+        try:
+            obj = get_object(oid)  # uses your existing helper
+            dep = obj.get("department") or "(unknown)"
+            counts[dep] = counts.get(dep, 0) + 1
+        except Exception:
+            continue
+
+    # return sorted (department, count) pairs, highest first
+    return sorted(counts.items(), key=lambda x: x[1], reverse=True)

requirements.txt

@@ -1 +1,3 @@
-streamlit==1.48.1
+streamlit==1.48.1
+pandas
+requests