upload/match pipeline refactor

notes

phone

columns

comment

Author: carlos-dominguez

src/client/src/pages/Admin.js

@@ -243,7 +243,7 @@ export default function Admin(props) {
                                         <Typography variant="h5" styles={{paddingBottom: 5}}>Run New Analysis</Typography>
                                         <form onSubmit={handleExecute}>
                                             <Button type="submit" variant="contained" color="primary"
-                                                    disabled={statistics === 'Running' || isNewFileExist === false}>
+                                                    disabled={statistics === 'Running'}>
                                                 Run Data Analysis
                                             </Button>
                                         </form>

src/server/api/API_ingest/ingest_sources_from_api.py

@@ -1,7 +1,7 @@
 from api.API_ingest import shelterluv_api_handler
 
-def start():
+def start(conn):
     print("Start Fetching raw data from different API sources")
     #Run each source to store the output in dropbox and in the container as a CSV
-    shelterluv_api_handler.store_shelterluv_people_all()
+    shelterluv_api_handler.store_shelterluv_people_all(conn)
     print("Finish Fetching raw data from different API sources")

src/server/api/API_ingest/shelterluv_api_handler.py

@@ -1,10 +1,12 @@
-import os
-import requests
 import csv
+import os
 import time
 
-from constants import RAW_DATA_PATH
+import requests
+import pandas as pd
 from api.API_ingest.dropbox_handler import upload_file_to_dropbox
+from constants import RAW_DATA_PATH
+from models import ShelterluvPeople
 
 try:
     from secrets_dict import SHELTERLUV_SECRET_TOKEN
@@ -60,7 +62,7 @@ def write_csv(json_data):
 
 ''' Iterate over all shelterlove people and store in json file in the raw data folder
 We fetch 100 items in each request, since that is the limit based on our research '''
-def store_shelterluv_people_all():
+def store_shelterluv_people_all(conn):
     offset = 0
     LIMIT = 100
     has_more = True
@@ -90,8 +92,9 @@ def store_shelterluv_people_all():
     file_path = write_csv(shelterluv_people)
     print("Finish storing latest shelterluvpeople results to container")
 
-
     print("Start storing " + '/shelterluv/' + "results to dropbox")
     upload_file_to_dropbox(file_path, '/shelterluv/' + file_path.split('/')[-1])
     print("Finish storing " + '/shelterluv/' + "results to dropbox")
 
+    print("Uploading shelterluvpeople csv to database")
+    ShelterluvPeople.insert_from_df(pd.read_csv(file_path, dtype="string"), conn)

src/server/api/file_uploader.py

@@ -1,101 +1,55 @@
-import os
-import time
 import pandas as pd
-import threading
-import io
-import re
-
-from werkzeug.utils import secure_filename
-from flask import flash, current_app
-from datasource_manager import CSV_HEADERS
-from datasource_manager import DATASOURCE_MAPPING
-from openpyxl import load_workbook
-from tempfile import NamedTemporaryFile
+from config import engine
 from donations_importer import validate_import_sfd
+from flask import current_app
+from models import ManualMatches, SalesForceContacts, ShelterluvPeople, Volgistics
 from shifts_importer import validate_import_vs
+from werkzeug.utils import secure_filename
 
-from constants import RAW_DATA_PATH
-
-SUCCESS_MSG = 'Uploaded Successfully!'
-lock = threading.Lock()
+SUCCESS_MSG = "Uploaded Successfully!"
 
 
 def validate_and_arrange_upload(file):
     current_app.logger.info("Start uploading file: " + file.filename)
     filename = secure_filename(file.filename)
-    file_extension = filename.rpartition('.')[2]
-    determine_upload_type(file, file_extension)
+    file_extension = filename.rpartition(".")[2]
+    with engine.begin() as conn:
+        determine_upload_type(file, file_extension, conn)
 
 
-def determine_upload_type(file, file_extension):
-    df = None
+def determine_upload_type(file, file_extension, conn):
+    # Yes, this method of discovering what kind of file we have by looking at
+    # the extension and columns is silly. We'd like to get more of our data from
+    # automatically pulling from vendor APIs directly, in which case we'd know
+    # what kind of data we had.
+    if file_extension == "csv":
+        df = pd.read_csv(file, dtype="string")
 
-    if file_extension == 'csv':
-        dfs = [pd.read_csv(io.BytesIO(file.stream.read()), encoding='iso-8859-1')]
-        file.close()
-    else:
-        
-        match = re.search('donat', file.filename, re.I)
-
-        if match:   # It's a SalesForce Donations file
-            validate_import_sfd(file)
+        if {"salesforcecontacts", "volgistics", "shelterluvpeople"}.issubset(df.columns):
+            ManualMatches.insert_from_df(df, conn)
+            return
+        elif {"Animal_ids", "Internal-ID"}.issubset(df.columns):
+            ShelterluvPeople.insert_from_df(df, conn)
             return
-        else:
-            match = re.search('volunteer', file.filename, re.I)
-            if match:    # It's a Volgistics file
-                validate_import_vs(file)  
-                dfs = excel_to_dataframes(file)  # Also need to run Volgistics through match processing
-            else:
-                dfs = excel_to_dataframes(file)   #  It's a non-Volgistics, non-Shelterluv XLS? file 
-
-
-  
-
-    found_sources = 0
-    for df in dfs:
-        for src_type in CSV_HEADERS:
-            if set(CSV_HEADERS[src_type]).issubset(df.columns):
-                with lock:
-                    found_sources += 1
-                    filename = secure_filename(file.filename)
-                    now = time.localtime()
-                    now_date = time.strftime("%Y-%m-%d--%H-%M-%S", now)
-                    current_app.logger.info("  -File: " + filename + " Matches files type: " + src_type)
-                    df.to_csv(os.path.join(RAW_DATA_PATH, src_type + '-' + now_date + '.csv'))
-                    clean_current_folder(src_type)
-                    df.to_csv(os.path.join(RAW_DATA_PATH, src_type + '-' + now_date + '.csv'))
-                    current_app.logger.info("  -Uploaded successfully as : " + src_type + '-' + now_date + '.' + file_extension)
-                    flash(src_type + " {0} ".format(SUCCESS_MSG), 'info')
-    if found_sources == 0:
-        current_app.logger.error("\n\n          !!!!!!! No sources found in upload !!!!  \n                Uploaded file " + file.filename + " is probably from wrong report \n          !!!!!!!!!!!")
-
-
-def excel_to_dataframes(xls):
-    df = []
-    wb = load_workbook(xls)
-
-    if len(wb.sheetnames) > 1:
-        with NamedTemporaryFile() as tmp:
-            wb.save(tmp.name)
-            for sheetname in wb.sheetnames:
-                for item in DATASOURCE_MAPPING:
-                    if 'sheetname' in DATASOURCE_MAPPING[item]:
-                        if DATASOURCE_MAPPING[item]['sheetname'] == sheetname:
-                            tmp.seek(0)
-                            df.append(pd.read_excel(tmp.read(), sheetname))
-    else:
-        df.append(pd.read_excel(xls))
-
-    return df
 
+    if file_extension == "xlsx":
+        excel_file = pd.ExcelFile(file)
+        if {"Master", "Service"}.issubset(excel_file.sheet_names):
+            # Volgistics
+            validate_import_vs(file, conn)
+            Volgistics.insert_from_file(excel_file, conn)
+            return
 
-def clean_current_folder(src_type):
-    if os.listdir(RAW_DATA_PATH):
-        for file_name in os.listdir(RAW_DATA_PATH):
-            file_path = os.path.join(RAW_DATA_PATH, file_name)
-            file_name_striped = file_path.split('-')[0].split('/')[-1]
+        df = pd.read_excel(excel_file)
+        if "Contact ID 18" in df.columns:
+            # Salesforce something-or-other
+            if "Amount" in df.columns:
+                # Salesforce donations
+                validate_import_sfd(file, conn)
+                return
+            else:
+                # Salesforce contacts
+                SalesForceContacts.insert_from_file_df(df, conn)
+                return
 
-            if file_name_striped == src_type:
-                current_app.logger.info('File to remove: ' + file_path)
-                os.remove(file_path)
-                current_app.logger.info("  -Removed file: " + file_name + " from Current files folder")
+    current_app.logger.error(f"Don't know how to process file {file.filename}")

src/server/api/internal_api.py

@@ -1,4 +1,5 @@
 from api.api import internal_api
+from config import engine
 from flask import jsonify, current_app
 from datetime import datetime
 from api.API_ingest import ingest_sources_from_api
@@ -24,7 +25,8 @@ def user_test2():
 @internal_api.route("/api/ingestRawData", methods=["GET"])
 def ingest_raw_data():
     try:
-        ingest_sources_from_api.start()
+        with engine.begin() as conn:
+            ingest_sources_from_api.start(conn)
     except Exception as e:
         current_app.logger.exception(e)