# Updated code to import and use the pandarallel library for parallel processing.

# Created a new function to check if a URL is reachable.
# Created a new function to compute the percentage of datasets that are reachable.
# Updated function names for better clarity.
# Added new functions to extract and count various metadata values from the dataset.
# Added new keys to the report dictionary to include the extracted metadata values.

Author: icaoberg

braininventory/get.py

@@ -2,11 +2,15 @@
 import pandas as pd
 import json
 from datetime import date
+from pandarallel import pandarallel
+
+pandarallel.initialize(nb_workers=8, progress_bar=True)
+
 
 def today():
     """
-	Get today's snapshot of Brain Image Library.
-	"""
+    Get today's snapshot of Brain Image Library.
+    """
 
     server = "https://download.brainimagelibrary.org/inventory/daily/reports/"
     filename = "today.json"
@@ -23,38 +27,84 @@ def today():
     else:
         print("Error: Failed to fetch JSON data")
         return pd.DataFrame()
-    
+
+
 def __get_number_of_datasets(df):
-     return len(df)
+    return len(df)
+
 
 def __get_completeness_score(df):
-      return df['score'].sum()/len(df)
+    return df["score"].sum() / len(df)
+
 
-def __is_reachable(url):
-	response = requests.get(url)
+def __is_it_reachable(url):
+    response = requests.get(url)
+
+    if response.status_code == 200:
+        return True
+    else:
+        return False
+
+
+def __are_reachable(df):
+    print("Computing what datasets are reachable")
+    df["is_reachable"] = df["URL"].parallel_apply(__is_it_reachable)
+    return df["is_reachable"].sum() / len(df)
 
-	if response.status_code == 200:
-		return True
-	else:
-		return False
 
 def __get_metadata_version(df):
-    return df['metadata_version'] .value_counts().to_dict()
+    return df["metadata_version"].value_counts().to_dict()
+
+
+def __get_genotypes(df):
+    return df["genotype"].value_counts().to_dict()
+
+
+def __get_modalities(df):
+    return df["generalmodality"].value_counts().to_dict()
+
+
+def __get_techniques(df):
+    return df["technique"].value_counts().to_dict()
+
+
+def __get_award_numbers(df):
+    return df["award_number"].value_counts().to_dict()
+
+
+def __get_affiliations(df):
+    return df["affiliation"].value_counts().to_dict()
+
+
+def __get_contributors(df):
+    return df["contributorname"].value_counts().to_dict()
+
+
+def __get_projects(df):
+    return df["project"].value_counts().to_dict()
+
 
 def report():
     # Get today's date
-	tdate = date.today()
+    tdate = date.today()
+
+    # Convert date to string
+    tdate = tdate.strftime("%Y-%m-%d")
 
-	# Convert date to string
-	tdate = tdate.strftime("%Y-%m-%d")
-        
-	df = today()
+    df = today()
 
-	report = {}
-	report['date'] = tdate
-	report['number_of_datasets'] = __get_number_of_datasets(df)
-	report['completeness_score'] = __get_completeness_score(df)
-	report['metadata_version'] = __get_metadata_version(df)
-	report['is_reachable'] = df['URL'].apply(__is_reachable)
+    report = {}
+    report["date"] = tdate
+    report["number_of_datasets"] = __get_number_of_datasets(df)
+    report["completeness_score"] = __get_completeness_score(df)
+    report["metadata_version"] = __get_metadata_version(df)
+    # report['are_reachable'] = __are_reachable(df)
+    report["genotypes"] = __get_genotypes(df)
+    report["modalities"] = __get_modalities(df)
+    report["award_numbers"] = __get_award_numbers(df)
+    report["tecniques"] = __get_techniques(df)
+    report["affiliations"] = __get_affiliations(df)
+    report["contributors"] = __get_contributors(df)
+    report["projects"] = __get_projects(df)
 
-	return report
+    return report