Basic functions per columns

Author: EduardoJFigueroa

braininventory.egg-info/PKG-INFO

@@ -0,0 +1,15 @@
+Metadata-Version: 2.1
+Name: braininventory
+Version: 1.0.0
+Summary: A basic inventory management package
+Home-page: https://github.com/brain-image-library/py-bil-inventory
+Author: Ivan Cao-Berg, Eduardo Figueroa
+Author-email: [email protected]
+License: UNKNOWN
+Description: UNKNOWN
+Platform: UNKNOWN
+Classifier: Programming Language :: Python :: 3
+Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
+Classifier: Operating System :: OS Independent
+Requires-Python: >=3.6
+Description-Content-Type: text/markdown

braininventory.egg-info/SOURCES.txt

@@ -0,0 +1,8 @@
+README.md
+setup.py
+braininventory/__init__.py
+braininventory/get.py
+braininventory.egg-info/PKG-INFO
+braininventory.egg-info/SOURCES.txt
+braininventory.egg-info/dependency_links.txt
+braininventory.egg-info/top_level.txt

braininventory.egg-info/dependency_links.txt

@@ -0,0 +1 @@
+

braininventory.egg-info/top_level.txt

@@ -0,0 +1 @@
+braininventory

braininventory/get.py

@@ -33,6 +33,36 @@ def __get_completeness_score(df):
 def __get_metadata_version(df):
     return df['metadata_version'] .value_counts().to_dict()
 
+def __get_contributor(df):
+    return df['contributor'].value_counts().to_dict()
+
+def __get_affilation(df):
+    return df['affiliation'].value_counts().to_dict()
+
+def __get_award_number(df):
+    return df['award_number'].value_counts().to_dict()
+
+def __get_species(df):
+    return df['species'].value_counts().to_dict()
+
+def __ get_cnbtaxonomy(df):
+    return df['cnbtaxonomy'].value_counts().to_dict()
+
+def __get_samplelocalid(df):
+    return df['samplelocalid'].value_counts().to_dict()
+
+def __get_genotype(df):
+    return df['genotype'].value_counts().to_dict()
+
+def __get_generalmodality(df):
+    return df['generalmodality'].value_counts().to_dict()
+
+def __get_technique(df):
+    return df['technique'].value_counts().to_dict()
+
+def __get_locations(df):
+    return df['locations'].value_counts().to_dict()
+
 def report():
     # Get today's date
 	tdate = date.today()
@@ -47,5 +77,15 @@ def report():
 	report['number_of_datasets'] = __get_number_of_datasets(df)
 	report['completeness_score'] = __get_completeness_score(df)
 	report['metadata_version'] = __get_metadata_version(df)
-
+        report['contributor'] =  __get_contributor(df)
+        report['affiliation'] =  __get_affilation(df)
+        report['award_number'] = __get_award_number(df)
+        report['species'] = __get_species(df)
+        report['cnbtaxonomy'] = __ get_cnbtaxonomy(df)
+        report['samplelocalid'] = __get_samplelocalid(df)
+        report['genotype'] = __get_genotype(df)
+        report['generalmodality'] = __get_generalmodality(df)
+        report['technique'] = __get_technique(df)
+        report['locations'] = __get_locations(df)
+     
 	return report

build/lib/braininventory/__init__.py

@@ -0,0 +1 @@
+from .get import *

build/lib/braininventory/get.py

@@ -0,0 +1,51 @@
+import requests
+import pandas as pd
+import json
+from datetime import date
+
+def today():
+    """
+	Get today's snapshot of Brain Image Library.
+	"""
+
+    server = "https://download.brainimagelibrary.org/inventory/daily/reports/"
+    filename = "today.json"
+
+    response = requests.get(f"{server}{filename}")
+
+    # Check if the request was successful
+    if response.status_code == 200:
+        # Parse the JSON data into a dictionary
+        data = json.loads(response.text)
+        data = pd.DataFrame(data)
+        return data
+
+    else:
+        print("Error: Failed to fetch JSON data")
+        return pd.DataFrame()
+    
+def __get_number_of_datasets(df):
+     return len(df)
+
+def __get_completeness_score(df):
+      return df['score'].sum()/len(df)
+
+def __get_metadata_version(df):
+    return df['metadata_version'] .value_counts().to_dict()
+
+def report():
+    # Get today's date
+	tdate = date.today()
+
+	# Convert date to string
+	tdate = tdate.strftime("%Y-%m-%d")
+        
+	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)
+
+	return report