Make more robust

mwmbl/historical.py

@@ -1,54 +0,0 @@
-from datetime import date, datetime
-
-import spacy
-
-from mwmbl.crawler.app import get_user_id_hashes_for_date, get_batches_for_date_and_user, get_batch_from_id, \
-    create_historical_batch, HashedBatch, get_batch_url
-from mwmbl.database import Database
-from mwmbl.indexdb import BatchInfo, BatchStatus, IndexDatabase
-from mwmbl.indexer.index import tokenize_document
-from mwmbl.indexer.paths import INDEX_PATH
-from mwmbl.tinysearchengine.indexer import TinyIndex, Document
-
-
-def run():
-    date_str = str(date.today())
-    users = get_user_id_hashes_for_date(date_str)
-    print("Users", users)
-    with Database() as db:
-        index_db = IndexDatabase(db.connection)
-        index_db.create_tables()
-        for user in users:
-            batches = get_batches_for_date_and_user(date_str, user)
-            print("Batches", batches)
-            batch_urls = [get_batch_url(batch_id, date_str, user) for batch_id in batches["batch_ids"]]
-            infos = [BatchInfo(url, user, BatchStatus.REMOTE) for url in batch_urls]
-            index_db.record_batches(infos)
-
-
-def index_batches(index_path: str):
-    nlp = spacy.load("en_core_web_sm")
-    with TinyIndex(Document, index_path, 'w') as indexer:
-        for batch_id in batch_ids["batch_ids"]:
-            start = datetime.now()
-            batch_dict = get_batch_from_id(date_str, user, batch_id)
-            get_batch_time = datetime.now()
-            print("Get batch time", get_batch_time - start)
-            batch = HashedBatch.parse_obj(batch_dict['batch'])
-            create_historical_batch(batch)
-            create_historical_time = datetime.now()
-            print("Create historical time", create_historical_time - get_batch_time)
-
-            for item in batch.items:
-                if item.content is None:
-                    continue
-
-                page = tokenize_document(item.url, item.content.title, item.content.extract, 1, nlp)
-                for token in page.tokens:
-                    indexer.index(token, Document(url=page.url, title=page.title, extract=page.extract, score=page.score))
-            tokenize_time = datetime.now()
-            print("Tokenize time", tokenize_time - create_historical_time)
-
-
-if __name__ == '__main__':
-    run()

mwmbl/indexer/historical.py

@@ -0,0 +1,33 @@
+from datetime import date, datetime, timedelta
+
+import spacy
+
+from mwmbl.crawler.app import get_user_id_hashes_for_date, get_batches_for_date_and_user, get_batch_from_id, \
+    create_historical_batch, HashedBatch, get_batch_url
+from mwmbl.database import Database
+from mwmbl.indexer.indexdb import BatchInfo, BatchStatus, IndexDatabase
+from mwmbl.indexer.index import tokenize_document
+from mwmbl.tinysearchengine.indexer import TinyIndex, Document
+
+
+DAYS = 10
+
+
+def run():
+    for day in range(DAYS):
+        date_str = str(date.today() - timedelta(days=day))
+        users = get_user_id_hashes_for_date(date_str)
+        print("Users", users)
+        with Database() as db:
+            index_db = IndexDatabase(db.connection)
+            index_db.create_tables()
+            for user in users:
+                batches = get_batches_for_date_and_user(date_str, user)
+                print("Batches", batches)
+                batch_urls = [get_batch_url(batch_id, date_str, user) for batch_id in batches["batch_ids"]]
+                infos = [BatchInfo(url, user, BatchStatus.REMOTE) for url in batch_urls]
+                index_db.record_batches(infos)
+
+
+if __name__ == '__main__':
+    run()

mwmbl/indexer/preprocess.py

@@ -0,0 +1,41 @@
+"""
+Preprocess local documents for indexing.
+"""
+import traceback
+from time import sleep
+
+import spacy
+
+from mwmbl.database import Database
+from mwmbl.indexer.indexdb import IndexDatabase
+from mwmbl.indexer.index import tokenize_document
+from mwmbl.tinysearchengine.indexer import TinyIndex, Document
+
+
+def run(index_path):
+    while True:
+        try:
+            run_preprocessing(index_path)
+        except Exception as e:
+            print("Exception preprocessing")
+            traceback.print_exception(type(e), e, e.__traceback__)
+            sleep(10)
+
+
+def run_preprocessing(index_path):
+    nlp = spacy.load("en_core_web_sm")
+    with Database() as db:
+        index_db = IndexDatabase(db.connection)
+        documents = index_db.get_documents_for_preprocessing()
+        print(f"Got {len(documents)} documents")
+        if len(documents) == 0:
+            sleep(10)
+        with TinyIndex(Document, index_path, 'w') as indexer:
+            for document in documents:
+                tokenized = tokenize_document(document.url, document.title, document.extract, 1, nlp)
+                page_indexes = [indexer.get_key_page_index(token) for token in tokenized.tokens]
+                index_db.queue_documents_for_page([(tokenized.url, i) for i in page_indexes])
+
+
+if __name__ == '__main__':
+    run('data/index.tinysearch')

mwmbl/retrieve.py → mwmbl/indexer/retrieve.py

@@ -3,6 +3,7 @@ Retrieve remote batches and store them in Postgres locally
 """
 import gzip
 import json
+import traceback
 from multiprocessing.pool import ThreadPool
 from time import sleep
 
@@ -10,10 +11,11 @@ import requests
 
 from mwmbl.crawler.app import HashedBatch
 from mwmbl.database import Database
-from mwmbl.indexdb import IndexDatabase, BatchStatus
+from mwmbl.indexer.indexdb import IndexDatabase, BatchStatus
+from mwmbl.retry import retry_requests
 from mwmbl.tinysearchengine.indexer import Document
 
-NUM_THREADS = 10
+NUM_THREADS = 5
 
 
 def retrieve_batches():
@@ -25,7 +27,7 @@ def retrieve_batches():
         index_db = IndexDatabase(db.connection)
         batches = index_db.get_batches_by_status(BatchStatus.REMOTE)
         print("Batches", batches)
-        urls = [batch.url for batch in batches][:10]
+        urls = [batch.url for batch in batches]
         pool = ThreadPool(NUM_THREADS)
         results = pool.imap_unordered(retrieve_batch, urls)
         for result in results:
@@ -37,13 +39,13 @@ def retrieve_batches():
 
 
 def retrieve_batch(url):
-    data = json.loads(gzip.decompress(requests.get(url).content))
+    data = json.loads(gzip.decompress(retry_requests.get(url).content))
     batch = HashedBatch.parse_obj(data)
-    queue_batch(url, batch)
+    queue_batch(batch)
     return len(batch.items)
 
 
-def queue_batch(batch_url: str, batch: HashedBatch):
+def queue_batch(batch: HashedBatch):
     # TODO get the score from the URLs database
     documents = [Document(item.content.title, item.url, item.content.extract, 1)
                  for item in batch.items if item.content is not None]
@@ -54,7 +56,11 @@ def queue_batch(batch_url: str, batch: HashedBatch):
 
 def run():
     while True:
-        retrieve_batches()
+        try:
+            retrieve_batches()
+        except Exception as e:
+            print("Exception retrieving batch")
+            traceback.print_exception(type(e), e, e.__traceback__)
         sleep(10)
 
 

mwmbl/update_pages.py → mwmbl/indexer/update_pages.py

@@ -1,12 +1,15 @@
 """
 Iterate over each page in the index and update it based on what is in the index database.
 """
+import traceback
+from time import sleep
+
 from mwmbl.database import Database
-from mwmbl.indexdb import IndexDatabase
+from mwmbl.indexer.indexdb import IndexDatabase
 from mwmbl.tinysearchengine.indexer import TinyIndex, Document
 
 
-def run(index_path):
+def run_update(index_path):
     with Database() as db:
         index_db = IndexDatabase(db.connection)
         index_db.create_tables()
@@ -33,5 +36,15 @@ def run(index_path):
                 index_db.clear_queued_documents_for_page(i)
 
 
+def run(index_path):
+    while True:
+        try:
+            run_update(index_path)
+        except Exception as e:
+            print("Exception updating pages in index")
+            traceback.print_exception(type(e), e, e.__traceback__)
+            sleep(10)
+
+
 if __name__ == '__main__':
-    run('data/index.tinysearch')
+    run_update('data/index.tinysearch')

mwmbl/local.py

@@ -1,31 +0,0 @@
-"""
-Preprocess local documents for indexing.
-"""
-from time import sleep
-
-import spacy
-
-from mwmbl.database import Database
-from mwmbl.indexdb import IndexDatabase
-from mwmbl.indexer.index import tokenize_document
-from mwmbl.tinysearchengine.indexer import TinyIndex, Document
-
-
-def run(index_path):
-    nlp = spacy.load("en_core_web_sm")
-    while True:
-        with Database() as db:
-            index_db = IndexDatabase(db.connection)
-            documents = index_db.get_documents_for_preprocessing()
-            print(f"Got {len(documents)} documents")
-            if len(documents) == 0:
-                sleep(10)
-            with TinyIndex(Document, index_path, 'w') as indexer:
-                for document in documents:
-                    tokenized = tokenize_document(document.url, document.title, document.extract, 1, nlp)
-                    page_indexes = [indexer.get_key_page_index(token) for token in tokenized.tokens]
-                    index_db.queue_documents_for_page([(tokenized.url, i) for i in page_indexes])
-
-
-if __name__ == '__main__':
-    run('data/index.tinysearch')

mwmbl/main.py

@@ -1,11 +1,12 @@
 import argparse
 import logging
+import os
 from multiprocessing import Process
 
 import uvicorn
 from fastapi import FastAPI
 
-from mwmbl import historical
+from mwmbl.indexer import historical, retrieve, preprocess
 from mwmbl.crawler.app import router as crawler_router
 from mwmbl.tinysearchengine import search
 from mwmbl.tinysearchengine.completer import Completer
@@ -23,23 +24,25 @@ def setup_args():
 
 
 def run():
-    """Main entrypoint for tinysearchengine.
-
-    * Parses CLI args
-    * Parses and validates config
-    * Initializes TinyIndex
-    * Initialize a FastAPI app instance
-    * Starts uvicorn server using app instance
-    """
     args = setup_args()
 
     try:
+        existing_index = TinyIndex(item_factory=Document, index_path=args.index)
+        if existing_index.page_size != PAGE_SIZE or existing_index.num_pages != NUM_PAGES:
+            print(f"Existing index page sizes ({existing_index.page_size}) and number of pages "
+                  f"({existing_index.num_pages}) does not match - removing.")
+            os.remove(args.index)
+            existing_index = None
+    except FileNotFoundError:
+        existing_index = None
+
+    if existing_index is None:
+        print("Creating a new index")
         TinyIndex.create(item_factory=Document, index_path=args.index, num_pages=NUM_PAGES, page_size=PAGE_SIZE)
-    except FileExistsError:
-        print("Index already exists")
 
-    historical_batch_process = Process(target=historical.run, args=(args.index,))
-    historical_batch_process.start()
+    Process(target=historical.run).start()
+    Process(target=retrieve.run).start()
+    Process(target=preprocess.run, args=(args.index,)).start()
 
     completer = Completer()
 

mwmbl/retry.py

@@ -0,0 +1,17 @@
+import requests
+from requests.adapters import HTTPAdapter
+from urllib3.util.retry import Retry
+
+
+MAX_RETRY = 2
+MAX_RETRY_FOR_SESSION = 2
+BACK_OFF_FACTOR = 0.3
+TIME_BETWEEN_RETRIES = 1000
+ERROR_CODES = (500, 502, 504)
+
+
+retry_requests = requests.Session()
+retry = Retry(total=5, backoff_factor=1)
+adapter = HTTPAdapter(max_retries=retry)
+retry_requests.mount('http://', adapter)
+retry_requests.mount('https://', adapter)

mwmbl/tinysearchengine/indexer.py

@@ -12,7 +12,7 @@ VERSION = 1
 METADATA_CONSTANT = b'mwmbl-tiny-search'
 METADATA_SIZE = 4096
 
-NUM_PAGES = 128000
+NUM_PAGES = 512000
 PAGE_SIZE = 4096