From 30acfdd3f12c5709189b2c302ed3861497f16ba9 Mon Sep 17 00:00:00 2001
From: Jonas Winkler <jonas.winkler@jpwinkler.de>
Date: Thu, 26 Nov 2020 14:18:10 +0100
Subject: [PATCH 1/3] tests for the classifier and fixes for edge cases with
minimal data.
---
src/documents/classifier.py | 45 +++++--
src/documents/tests/test_classifier.py | 155 ++++++++++++++++++++++++-
2 files changed, 189 insertions(+), 11 deletions(-)
diff --git a/src/documents/classifier.py b/src/documents/classifier.py
index 6e0d6f946..b0d7d87bb 100755
--- a/src/documents/classifier.py
+++ b/src/documents/classifier.py
@@ -6,7 +6,8 @@ import re
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.neural_network import MLPClassifier
-from sklearn.preprocessing import MultiLabelBinarizer
+from sklearn.preprocessing import MultiLabelBinarizer, LabelBinarizer
+from sklearn.utils.multiclass import type_of_target
from documents.models import Document, MatchingModel
from paperless import settings
@@ -27,7 +28,7 @@ def preprocess_content(content):
class DocumentClassifier(object):
- FORMAT_VERSION = 5
+ FORMAT_VERSION = 6
def __init__(self):
# mtime of the model file on disk. used to prevent reloading when
@@ -54,6 +55,8 @@ class DocumentClassifier(object):
"Cannor load classifier, incompatible versions.")
else:
if self.classifier_version > 0:
+ # Don't be confused by this check. It's simply here
+ # so that we wont log anything on initial reload.
logger.info("Classifier updated on disk, "
"reloading classifier models")
self.data_hash = pickle.load(f)
@@ -122,9 +125,14 @@ class DocumentClassifier(object):
labels_tags_unique = set([tag for tags in labels_tags for tag in tags])
num_tags = len(labels_tags_unique)
+
# substract 1 since -1 (null) is also part of the classes.
- num_correspondents = len(set(labels_correspondent)) - 1
- num_document_types = len(set(labels_document_type)) - 1
+
+ # union with {-1} accounts for cases where all documents have
+ # correspondents and types assigned, so -1 isnt part of labels_x, which
+ # it usually is.
+ num_correspondents = len(set(labels_correspondent) | {-1}) - 1
+ num_document_types = len(set(labels_document_type) | {-1}) - 1
logging.getLogger(__name__).debug(
"{} documents, {} tag(s), {} correspondent(s), "
@@ -145,12 +153,23 @@ class DocumentClassifier(object):
)
data_vectorized = self.data_vectorizer.fit_transform(data)
- self.tags_binarizer = MultiLabelBinarizer()
- labels_tags_vectorized = self.tags_binarizer.fit_transform(labels_tags)
-
# Step 3: train the classifiers
if num_tags > 0:
logging.getLogger(__name__).debug("Training tags classifier...")
+
+ if num_tags == 1:
+ # Special case where only one tag has auto:
+ # Fallback to binary classification.
+ labels_tags = [label[0] if len(label) == 1 else -1
+ for label in labels_tags]
+ self.tags_binarizer = LabelBinarizer()
+ labels_tags_vectorized = self.tags_binarizer.fit_transform(
+ labels_tags).ravel()
+ else:
+ self.tags_binarizer = MultiLabelBinarizer()
+ labels_tags_vectorized = self.tags_binarizer.fit_transform(
+ labels_tags)
+
self.tags_classifier = MLPClassifier(tol=0.01)
self.tags_classifier.fit(data_vectorized, labels_tags_vectorized)
else:
@@ -222,6 +241,16 @@ class DocumentClassifier(object):
X = self.data_vectorizer.transform([preprocess_content(content)])
y = self.tags_classifier.predict(X)
tags_ids = self.tags_binarizer.inverse_transform(y)[0]
- return tags_ids
+ if type_of_target(y).startswith('multilabel'):
+ # the usual case when there are multiple tags.
+ return list(tags_ids)
+ elif type_of_target(y) == 'binary' and tags_ids != -1:
+ # This is for when we have binary classification with only one
+ # tag and the result is to assign this tag.
+ return [tags_ids]
+ else:
+ # Usually binary as well with -1 as the result, but we're
+ # going to catch everything else here as well.
+ return []
else:
return []
diff --git a/src/documents/tests/test_classifier.py b/src/documents/tests/test_classifier.py
index 4ae672ac2..0f421bb32 100644
--- a/src/documents/tests/test_classifier.py
+++ b/src/documents/tests/test_classifier.py
@@ -1,8 +1,10 @@
import tempfile
+from time import sleep
+from unittest import mock
from django.test import TestCase, override_settings
-from documents.classifier import DocumentClassifier
+from documents.classifier import DocumentClassifier, IncompatibleClassifierVersionError
from documents.models import Correspondent, Document, Tag, DocumentType
@@ -15,10 +17,12 @@ class TestClassifier(TestCase):
def generate_test_data(self):
self.c1 = Correspondent.objects.create(name="c1", matching_algorithm=Correspondent.MATCH_AUTO)
self.c2 = Correspondent.objects.create(name="c2")
+ self.c3 = Correspondent.objects.create(name="c3", matching_algorithm=Correspondent.MATCH_AUTO)
self.t1 = Tag.objects.create(name="t1", matching_algorithm=Tag.MATCH_AUTO, pk=12)
self.t2 = Tag.objects.create(name="t2", matching_algorithm=Tag.MATCH_ANY, pk=34, is_inbox_tag=True)
self.t3 = Tag.objects.create(name="t3", matching_algorithm=Tag.MATCH_AUTO, pk=45)
self.dt = DocumentType.objects.create(name="dt", matching_algorithm=DocumentType.MATCH_AUTO)
+ self.dt2 = DocumentType.objects.create(name="dt2", matching_algorithm=DocumentType.MATCH_AUTO)
self.doc1 = Document.objects.create(title="doc1", content="this is a document from c1", correspondent=self.c1, checksum="A", document_type=self.dt)
self.doc2 = Document.objects.create(title="doc1", content="this is another document, but from c2", correspondent=self.c2, checksum="B")
@@ -59,8 +63,8 @@ class TestClassifier(TestCase):
self.classifier.train()
self.assertEqual(self.classifier.predict_correspondent(self.doc1.content), self.c1.pk)
self.assertEqual(self.classifier.predict_correspondent(self.doc2.content), None)
- self.assertTupleEqual(self.classifier.predict_tags(self.doc1.content), (self.t1.pk,))
- self.assertTupleEqual(self.classifier.predict_tags(self.doc2.content), (self.t1.pk, self.t3.pk))
+ self.assertListEqual(self.classifier.predict_tags(self.doc1.content), [self.t1.pk])
+ self.assertListEqual(self.classifier.predict_tags(self.doc2.content), [self.t1.pk, self.t3.pk])
self.assertEqual(self.classifier.predict_document_type(self.doc1.content), self.dt.pk)
self.assertEqual(self.classifier.predict_document_type(self.doc2.content), None)
@@ -71,6 +75,42 @@ class TestClassifier(TestCase):
self.assertTrue(self.classifier.train())
self.assertFalse(self.classifier.train())
+ def testVersionIncreased(self):
+
+ self.generate_test_data()
+ self.assertTrue(self.classifier.train())
+ self.assertFalse(self.classifier.train())
+
+ classifier2 = DocumentClassifier()
+
+ current_ver = DocumentClassifier.FORMAT_VERSION
+ with mock.patch("documents.classifier.DocumentClassifier.FORMAT_VERSION", current_ver+1):
+ # assure that we won't load old classifiers.
+ self.assertRaises(IncompatibleClassifierVersionError, self.classifier.reload)
+
+ self.classifier.save_classifier()
+
+ # assure that we can load the classifier after saving it.
+ classifier2.reload()
+
+ def testReload(self):
+
+ self.generate_test_data()
+ self.assertTrue(self.classifier.train())
+ self.classifier.save_classifier()
+
+ classifier2 = DocumentClassifier()
+ classifier2.reload()
+ v1 = classifier2.classifier_version
+
+ # change the classifier after some time.
+ sleep(1)
+ self.classifier.save_classifier()
+
+ classifier2.reload()
+ v2 = classifier2.classifier_version
+ self.assertNotEqual(v1, v2)
+
@override_settings(DATA_DIR=tempfile.mkdtemp())
def testSaveClassifier(self):
@@ -83,3 +123,112 @@ class TestClassifier(TestCase):
new_classifier = DocumentClassifier()
new_classifier.reload()
self.assertFalse(new_classifier.train())
+
+ def test_one_correspondent_predict(self):
+ c1 = Correspondent.objects.create(name="c1", matching_algorithm=Correspondent.MATCH_AUTO)
+ doc1 = Document.objects.create(title="doc1", content="this is a document from c1", correspondent=c1, checksum="A")
+
+ self.classifier.train()
+ self.assertEqual(self.classifier.predict_correspondent(doc1.content), c1.pk)
+
+ def test_one_correspondent_predict_manydocs(self):
+ c1 = Correspondent.objects.create(name="c1", matching_algorithm=Correspondent.MATCH_AUTO)
+ doc1 = Document.objects.create(title="doc1", content="this is a document from c1", correspondent=c1, checksum="A")
+ doc2 = Document.objects.create(title="doc2", content="this is a document from noone", checksum="B")
+
+ self.classifier.train()
+ self.assertEqual(self.classifier.predict_correspondent(doc1.content), c1.pk)
+ self.assertIsNone(self.classifier.predict_correspondent(doc2.content))
+
+ def test_one_type_predict(self):
+ dt = DocumentType.objects.create(name="dt", matching_algorithm=DocumentType.MATCH_AUTO)
+
+ doc1 = Document.objects.create(title="doc1", content="this is a document from c1",
+ checksum="A", document_type=dt)
+
+ self.classifier.train()
+ self.assertEqual(self.classifier.predict_document_type(doc1.content), dt.pk)
+
+ def test_one_type_predict_manydocs(self):
+ dt = DocumentType.objects.create(name="dt", matching_algorithm=DocumentType.MATCH_AUTO)
+
+ doc1 = Document.objects.create(title="doc1", content="this is a document from c1",
+ checksum="A", document_type=dt)
+
+ doc2 = Document.objects.create(title="doc1", content="this is a document from c2",
+ checksum="B")
+
+ self.classifier.train()
+ self.assertEqual(self.classifier.predict_document_type(doc1.content), dt.pk)
+ self.assertIsNone(self.classifier.predict_document_type(doc2.content))
+
+ def test_one_tag_predict(self):
+ t1 = Tag.objects.create(name="t1", matching_algorithm=Tag.MATCH_AUTO, pk=12)
+
+ doc1 = Document.objects.create(title="doc1", content="this is a document from c1", checksum="A")
+
+ doc1.tags.add(t1)
+ self.classifier.train()
+ self.assertListEqual(self.classifier.predict_tags(doc1.content), [t1.pk])
+
+ def test_one_tag_predict_unassigned(self):
+ t1 = Tag.objects.create(name="t1", matching_algorithm=Tag.MATCH_AUTO, pk=12)
+
+ doc1 = Document.objects.create(title="doc1", content="this is a document from c1", checksum="A")
+
+ self.classifier.train()
+ self.assertListEqual(self.classifier.predict_tags(doc1.content), [])
+
+ def test_two_tags_predict_singledoc(self):
+ t1 = Tag.objects.create(name="t1", matching_algorithm=Tag.MATCH_AUTO, pk=12)
+ t2 = Tag.objects.create(name="t2", matching_algorithm=Tag.MATCH_AUTO, pk=121)
+
+ doc4 = Document.objects.create(title="doc1", content="this is a document from c4", checksum="D")
+
+ doc4.tags.add(t1)
+ doc4.tags.add(t2)
+ self.classifier.train()
+ self.assertListEqual(self.classifier.predict_tags(doc4.content), [t1.pk, t2.pk])
+
+ def test_two_tags_predict(self):
+ t1 = Tag.objects.create(name="t1", matching_algorithm=Tag.MATCH_AUTO, pk=12)
+ t2 = Tag.objects.create(name="t2", matching_algorithm=Tag.MATCH_AUTO, pk=121)
+
+ doc1 = Document.objects.create(title="doc1", content="this is a document from c1", checksum="A")
+ doc2 = Document.objects.create(title="doc1", content="this is a document from c2", checksum="B")
+ doc3 = Document.objects.create(title="doc1", content="this is a document from c3", checksum="C")
+ doc4 = Document.objects.create(title="doc1", content="this is a document from c4", checksum="D")
+
+ doc1.tags.add(t1)
+ doc2.tags.add(t2)
+
+ doc4.tags.add(t1)
+ doc4.tags.add(t2)
+ self.classifier.train()
+ self.assertListEqual(self.classifier.predict_tags(doc1.content), [t1.pk])
+ self.assertListEqual(self.classifier.predict_tags(doc2.content), [t2.pk])
+ self.assertListEqual(self.classifier.predict_tags(doc3.content), [])
+ self.assertListEqual(self.classifier.predict_tags(doc4.content), [t1.pk, t2.pk])
+
+ def test_one_tag_predict_multi(self):
+ t1 = Tag.objects.create(name="t1", matching_algorithm=Tag.MATCH_AUTO, pk=12)
+
+ doc1 = Document.objects.create(title="doc1", content="this is a document from c1", checksum="A")
+ doc2 = Document.objects.create(title="doc2", content="this is a document from c2", checksum="B")
+
+ doc1.tags.add(t1)
+ doc2.tags.add(t1)
+ self.classifier.train()
+ self.assertListEqual(self.classifier.predict_tags(doc1.content), [t1.pk])
+ self.assertListEqual(self.classifier.predict_tags(doc2.content), [t1.pk])
+
+ def test_one_tag_predict_multi_2(self):
+ t1 = Tag.objects.create(name="t1", matching_algorithm=Tag.MATCH_AUTO, pk=12)
+
+ doc1 = Document.objects.create(title="doc1", content="this is a document from c1", checksum="A")
+ doc2 = Document.objects.create(title="doc2", content="this is a document from c2", checksum="B")
+
+ doc1.tags.add(t1)
+ self.classifier.train()
+ self.assertListEqual(self.classifier.predict_tags(doc1.content), [t1.pk])
+ self.assertListEqual(self.classifier.predict_tags(doc2.content), [])
From 43b473dc531d22e5de7ee62f0a98430630b64f31 Mon Sep 17 00:00:00 2001
From: Jonas Winkler <jonas.winkler@jpwinkler.de>
Date: Thu, 26 Nov 2020 15:55:13 +0100
Subject: [PATCH 2/3] Test cases for the API
---
src/documents/tests/samples/simple.pdf | Bin 0 -> 22926 bytes
src/documents/tests/samples/simple.zip | Bin 0 -> 17396 bytes
src/documents/tests/test_api.py | 39 +++++++++++++++++++++++++
3 files changed, 39 insertions(+)
create mode 100644 src/documents/tests/samples/simple.pdf
create mode 100644 src/documents/tests/samples/simple.zip
diff --git a/src/documents/tests/samples/simple.pdf b/src/documents/tests/samples/simple.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..e450de48269ce43785b8344c63e233a1794abae6
GIT binary patch
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diff --git a/src/documents/tests/test_api.py b/src/documents/tests/test_api.py
index b0318d2b3..c7e31e280 100644
--- a/src/documents/tests/test_api.py
+++ b/src/documents/tests/test_api.py
@@ -5,6 +5,7 @@ from unittest import mock
from django.contrib.auth.models import User
from django.test import override_settings
+from pathvalidate import ValidationError
from rest_framework.test import APITestCase
from documents.models import Document, Correspondent, DocumentType, Tag
@@ -215,3 +216,41 @@ class DocumentApiTest(APITestCase):
self.assertEqual(response.status_code, 200)
self.assertEqual(response.data['documents_total'], 3)
self.assertEqual(response.data['documents_inbox'], 1)
+
+ @mock.patch("documents.forms.async_task")
+ def test_upload(self, m):
+
+ with open(os.path.join(os.path.dirname(__file__), "samples", "simple.pdf"), "rb") as f:
+ response = self.client.post("/api/documents/post_document/", {"document": f})
+
+ self.assertEqual(response.status_code, 200)
+
+ m.assert_called_once()
+
+ self.assertEqual(m.call_args.kwargs['override_filename'], "simple.pdf")
+
+ @mock.patch("documents.forms.async_task")
+ def test_upload_invalid_form(self, m):
+
+ with open(os.path.join(os.path.dirname(__file__), "samples", "simple.pdf"), "rb") as f:
+ response = self.client.post("/api/documents/post_document/", {"documenst": f})
+ self.assertEqual(response.status_code, 400)
+ m.assert_not_called()
+
+ @mock.patch("documents.forms.async_task")
+ def test_upload_invalid_file(self, m):
+
+ with open(os.path.join(os.path.dirname(__file__), "samples", "simple.zip"), "rb") as f:
+ response = self.client.post("/api/documents/post_document/", {"document": f})
+ self.assertEqual(response.status_code, 400)
+ m.assert_not_called()
+
+ @mock.patch("documents.forms.async_task")
+ @mock.patch("documents.forms.validate_filename")
+ def test_upload_invalid_filename(self, validate_filename, async_task):
+ validate_filename.side_effect = ValidationError()
+ with open(os.path.join(os.path.dirname(__file__), "samples", "simple.pdf"), "rb") as f:
+ response = self.client.post("/api/documents/post_document/", {"document": f})
+ self.assertEqual(response.status_code, 400)
+
+ async_task.assert_not_called()
From 75390693b900f51ffd53283f2c5a07b0e58f668a Mon Sep 17 00:00:00 2001
From: jonaswinkler <jonas.winkler@jpwinkler.de>
Date: Thu, 26 Nov 2020 17:41:50 +0100
Subject: [PATCH 3/3] Apparently there was a very good reason to use inotify.
fixes #46 complete with test cases for inotify and polling.
---
Pipfile | 1 +
Pipfile.lock | 22 +-
.../management/commands/document_consumer.py | 124 ++++++++----
.../tests/test_management_consumer.py | 188 ++++++++++++++++++
4 files changed, 293 insertions(+), 42 deletions(-)
create mode 100644 src/documents/tests/test_management_consumer.py
diff --git a/Pipfile b/Pipfile
index ad60e0905..a6169a2ba 100644
--- a/Pipfile
+++ b/Pipfile
@@ -35,6 +35,7 @@ scikit-learn="~=0.23.2"
whitenoise = "~=5.2.0"
watchdog = "*"
whoosh="~=2.7.4"
+inotify-simple = "*"
[dev-packages]
coveralls = "*"
diff --git a/Pipfile.lock b/Pipfile.lock
index 6ecca3c34..b10c414ed 100644
--- a/Pipfile.lock
+++ b/Pipfile.lock
@@ -1,7 +1,7 @@
{
"_meta": {
"hash": {
- "sha256": "ae2643b9cf0cf5741ae149fb6bc0c480de41329ce48e773eb4b5d760bc5e2244"
+ "sha256": "e9792119f687757dd388e73827ddd4216910327d5b65a8b950d4b202679c36eb"
},
"pipfile-spec": 6,
"requires": {},
@@ -129,6 +129,14 @@
"index": "pypi",
"version": "==0.32.0"
},
+ "inotify-simple": {
+ "hashes": [
+ "sha256:8440ffe49c4ae81a8df57c1ae1eb4b6bfa7acb830099bfb3e305b383005cc128",
+ "sha256:854f9ac752cc1fcff6ca34e9d3d875c9a94c9b7d6eb377f63be2d481a566c6ee"
+ ],
+ "index": "pypi",
+ "version": "==1.3.5"
+ },
"joblib": {
"hashes": [
"sha256:698c311779f347cf6b7e6b8a39bb682277b8ee4aba8cf9507bc0cf4cd4737b72",
@@ -663,11 +671,11 @@
},
"faker": {
"hashes": [
- "sha256:3f5d379e4b5ce92a8afe3c2ce59d7c43886370dd3bf9495a936b91888debfc81",
- "sha256:8c0e8a06acef4b9312902e2ce18becabe62badd3a6632180bd0680c6ee111473"
+ "sha256:5398268e1d751ffdb3ed36b8a790ed98659200599b368eec38a02eed15bce997",
+ "sha256:d4183b8f57316de3be27cd6c3b40e9f9343d27c95c96179f027316c58c2c239e"
],
"markers": "python_version >= '3.5'",
- "version": "==4.17.0"
+ "version": "==4.17.1"
},
"filelock": {
"hashes": [
@@ -999,11 +1007,11 @@
},
"virtualenv": {
"hashes": [
- "sha256:b0011228208944ce71052987437d3843e05690b2f23d1c7da4263fde104c97a2",
- "sha256:b8d6110f493af256a40d65e29846c69340a947669eec8ce784fcf3dd3af28380"
+ "sha256:07cff122e9d343140366055f31be4dcd61fd598c69d11cd33a9d9c8df4546dd7",
+ "sha256:e0aac7525e880a429764cefd3aaaff54afb5d9f25c82627563603f5d7de5a6e5"
],
"markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'",
- "version": "==20.1.0"
+ "version": "==20.2.1"
}
}
}
diff --git a/src/documents/management/commands/document_consumer.py b/src/documents/management/commands/document_consumer.py
index 05711ebd8..4bfd78e8f 100644
--- a/src/documents/management/commands/document_consumer.py
+++ b/src/documents/management/commands/document_consumer.py
@@ -1,11 +1,11 @@
import logging
import os
+from time import sleep
from django.conf import settings
from django.core.management.base import BaseCommand
from django_q.tasks import async_task
from watchdog.events import FileSystemEventHandler
-from watchdog.observers import Observer
from watchdog.observers.polling import PollingObserver
try:
@@ -13,25 +13,54 @@ try:
except ImportError:
INotify = flags = None
+logger = logging.getLogger(__name__)
+
+
+def _consume(file):
+ try:
+ if os.path.isfile(file):
+ async_task("documents.tasks.consume_file",
+ file,
+ task_name=os.path.basename(file)[:100])
+ else:
+ logger.debug(
+ f"Not consuming file {file}: File has moved.")
+
+ except Exception as e:
+ # Catch all so that the consumer won't crash.
+ # This is also what the test case is listening for to check for
+ # errors.
+ logger.error(
+ "Error while consuming document: {}".format(e))
+
+
+def _consume_wait_unmodified(file, num_tries=20, wait_time=1):
+ mtime = -1
+ current_try = 0
+ while current_try < num_tries:
+ try:
+ new_mtime = os.stat(file).st_mtime
+ except FileNotFoundError:
+ logger.debug(f"File {file} moved while waiting for it to remain "
+ f"unmodified.")
+ return
+ if new_mtime == mtime:
+ _consume(file)
+ return
+ mtime = new_mtime
+ sleep(wait_time)
+ current_try += 1
+
+ logger.error(f"Timeout while waiting on file {file} to remain unmodified.")
+
class Handler(FileSystemEventHandler):
- def _consume(self, file):
- if os.path.isfile(file):
- try:
- async_task("documents.tasks.consume_file",
- file,
- task_name=os.path.basename(file)[:100])
- except Exception as e:
- # Catch all so that the consumer won't crash.
- logging.getLogger(__name__).error(
- "Error while consuming document: {}".format(e))
-
def on_created(self, event):
- self._consume(event.src_path)
+ _consume_wait_unmodified(event.src_path)
def on_moved(self, event):
- self._consume(event.src_path)
+ _consume_wait_unmodified(event.dest_path)
class Command(BaseCommand):
@@ -40,12 +69,15 @@ class Command(BaseCommand):
consumption directory.
"""
+ # This is here primarily for the tests and is irrelevant in production.
+ stop_flag = False
+
def __init__(self, *args, **kwargs):
- self.verbosity = 0
self.logger = logging.getLogger(__name__)
BaseCommand.__init__(self, *args, **kwargs)
+ self.observer = None
def add_arguments(self, parser):
parser.add_argument(
@@ -54,38 +86,60 @@ class Command(BaseCommand):
nargs="?",
help="The consumption directory."
)
+ parser.add_argument(
+ "--oneshot",
+ action="store_true",
+ help="Run only once."
+ )
def handle(self, *args, **options):
-
- self.verbosity = options["verbosity"]
directory = options["directory"]
logging.getLogger(__name__).info(
- "Starting document consumer at {}".format(
- directory
- )
- )
+ f"Starting document consumer at {directory}")
- # Consume all files as this is not done initially by the watchdog
for entry in os.scandir(directory):
if entry.is_file():
async_task("documents.tasks.consume_file",
entry.path,
task_name=os.path.basename(entry.path)[:100])
- # Start the watchdog. Woof!
- if settings.CONSUMER_POLLING > 0:
- logging.getLogger(__name__).info(
- "Using polling instead of file system notifications.")
- observer = PollingObserver(timeout=settings.CONSUMER_POLLING)
+ if options["oneshot"]:
+ return
+
+ if settings.CONSUMER_POLLING == 0 and INotify:
+ self.handle_inotify(directory)
else:
- observer = Observer()
- event_handler = Handler()
- observer.schedule(event_handler, directory, recursive=True)
- observer.start()
+ self.handle_polling(directory)
+
+ logger.debug("Consumer exiting.")
+
+ def handle_polling(self, directory):
+ logging.getLogger(__name__).info(
+ f"Polling directory for changes: {directory}")
+ self.observer = PollingObserver(timeout=settings.CONSUMER_POLLING)
+ self.observer.schedule(Handler(), directory, recursive=False)
+ self.observer.start()
try:
- while observer.is_alive():
- observer.join(1)
+ while self.observer.is_alive():
+ self.observer.join(1)
+ if self.stop_flag:
+ self.observer.stop()
except KeyboardInterrupt:
- observer.stop()
- observer.join()
+ self.observer.stop()
+ self.observer.join()
+
+ def handle_inotify(self, directory):
+ logging.getLogger(__name__).info(
+ f"Using inotify to watch directory for changes: {directory}")
+
+ inotify = INotify()
+ inotify.add_watch(directory, flags.CLOSE_WRITE | flags.MOVED_TO)
+ try:
+ while not self.stop_flag:
+ for event in inotify.read(timeout=1000, read_delay=1000):
+ file = os.path.join(directory, event.name)
+ if os.path.isfile(file):
+ _consume(file)
+ except KeyboardInterrupt:
+ pass
diff --git a/src/documents/tests/test_management_consumer.py b/src/documents/tests/test_management_consumer.py
new file mode 100644
index 000000000..bfb7520ee
--- /dev/null
+++ b/src/documents/tests/test_management_consumer.py
@@ -0,0 +1,188 @@
+import filecmp
+import os
+import shutil
+import tempfile
+from threading import Thread
+from time import sleep
+from unittest import mock
+
+from django.conf import settings
+from django.test import TestCase, override_settings
+
+from documents.consumer import ConsumerError
+from documents.management.commands import document_consumer
+
+
+class ConsumerThread(Thread):
+
+ def __init__(self):
+ super().__init__()
+ self.cmd = document_consumer.Command()
+
+ def run(self) -> None:
+ self.cmd.handle(directory=settings.CONSUMPTION_DIR, oneshot=False)
+
+ def stop(self):
+ # Consumer checks this every second.
+ self.cmd.stop_flag = True
+
+
+def chunked(size, source):
+ for i in range(0, len(source), size):
+ yield source[i:i+size]
+
+
+class TestConsumer(TestCase):
+
+ sample_file = os.path.join(os.path.dirname(__file__), "samples", "simple.pdf")
+
+ def setUp(self) -> None:
+ patcher = mock.patch("documents.management.commands.document_consumer.async_task")
+ self.task_mock = patcher.start()
+ self.addCleanup(patcher.stop)
+
+ self.consume_dir = tempfile.mkdtemp()
+
+ override_settings(CONSUMPTION_DIR=self.consume_dir).enable()
+
+ def t_start(self):
+ self.t = ConsumerThread()
+ self.t.start()
+ # give the consumer some time to do initial work
+ sleep(1)
+
+ def tearDown(self) -> None:
+ if self.t:
+ self.t.stop()
+
+ def wait_for_task_mock_call(self):
+ n = 0
+ while n < 100:
+ if self.task_mock.call_count > 0:
+ # give task_mock some time to finish and raise errors
+ sleep(1)
+ return
+ n += 1
+ sleep(0.1)
+ self.fail("async_task was never called")
+
+ # A bogus async_task that will simply check the file for
+ # completeness and raise an exception otherwise.
+ def bogus_task(self, func, filename, **kwargs):
+ eq = filecmp.cmp(filename, self.sample_file, shallow=False)
+ if not eq:
+ print("Consumed an INVALID file.")
+ raise ConsumerError("Incomplete File READ FAILED")
+ else:
+ print("Consumed a perfectly valid file.")
+
+ def slow_write_file(self, target, incomplete=False):
+ with open(self.sample_file, 'rb') as f:
+ pdf_bytes = f.read()
+
+ if incomplete:
+ pdf_bytes = pdf_bytes[:len(pdf_bytes) - 100]
+
+ with open(target, 'wb') as f:
+ # this will take 2 seconds, since the file is about 20k.
+ print("Start writing file.")
+ for b in chunked(1000, pdf_bytes):
+ f.write(b)
+ sleep(0.1)
+ print("file completed.")
+
+ def test_consume_file(self):
+ self.t_start()
+
+ f = os.path.join(self.consume_dir, "my_file.pdf")
+ shutil.copy(self.sample_file, f)
+
+ self.wait_for_task_mock_call()
+
+ self.task_mock.assert_called_once()
+ self.assertEqual(self.task_mock.call_args.args[1], f)
+
+ @override_settings(CONSUMER_POLLING=1)
+ def test_consume_file_polling(self):
+ self.test_consume_file()
+
+ def test_consume_existing_file(self):
+ f = os.path.join(self.consume_dir, "my_file.pdf")
+ shutil.copy(self.sample_file, f)
+
+ self.t_start()
+ self.task_mock.assert_called_once()
+ self.assertEqual(self.task_mock.call_args.args[1], f)
+
+ @override_settings(CONSUMER_POLLING=1)
+ def test_consume_existing_file_polling(self):
+ self.test_consume_existing_file()
+
+ @mock.patch("documents.management.commands.document_consumer.logger.error")
+ def test_slow_write_pdf(self, error_logger):
+
+ self.task_mock.side_effect = self.bogus_task
+
+ self.t_start()
+
+ fname = os.path.join(self.consume_dir, "my_file.pdf")
+
+ self.slow_write_file(fname)
+
+ self.wait_for_task_mock_call()
+
+ error_logger.assert_not_called()
+
+ self.task_mock.assert_called_once()
+
+ self.assertEqual(self.task_mock.call_args.args[1], fname)
+
+ @override_settings(CONSUMER_POLLING=1)
+ def test_slow_write_pdf_polling(self):
+ self.test_slow_write_pdf()
+
+ @mock.patch("documents.management.commands.document_consumer.logger.error")
+ def test_slow_write_and_move(self, error_logger):
+
+ self.task_mock.side_effect = self.bogus_task
+
+ self.t_start()
+
+ fname = os.path.join(self.consume_dir, "my_file.~df")
+ fname2 = os.path.join(self.consume_dir, "my_file.pdf")
+
+ self.slow_write_file(fname)
+ shutil.move(fname, fname2)
+
+ self.wait_for_task_mock_call()
+
+ self.task_mock.assert_called_once()
+ self.assertEqual(self.task_mock.call_args.args[1], fname2)
+
+ error_logger.assert_not_called()
+
+ @override_settings(CONSUMER_POLLING=1)
+ def test_slow_write_and_move_polling(self):
+ self.test_slow_write_and_move()
+
+ @mock.patch("documents.management.commands.document_consumer.logger.error")
+ def test_slow_write_incomplete(self, error_logger):
+
+ self.task_mock.side_effect = self.bogus_task
+
+ self.t_start()
+
+ fname = os.path.join(self.consume_dir, "my_file.pdf")
+ self.slow_write_file(fname, incomplete=True)
+
+ self.wait_for_task_mock_call()
+
+ self.task_mock.assert_called_once()
+ self.assertEqual(self.task_mock.call_args.args[1], fname)
+
+ # assert that we have an error logged with this invalid file.
+ error_logger.assert_called_once()
+
+ @override_settings(CONSUMER_POLLING=1)
+ def test_slow_write_incomplete_polling(self):
+ self.test_slow_write_incomplete()