def routeNextTask(task, document, task_extras=None):
if not hasattr(task, 'no_continue') or not task.no_continue:
next_task_path = None
from lib.Worker.Models.uv_task import UnveillanceTask
if hasattr(task, 'next_task_path'):
next_task_path = task.next_task_path
else:
from vars import MIME_TYPE_TASKS
if document.mime_type in MIME_TYPE_TASKS.keys():
try:
next_task_path = MIME_TYPE_TASKS[document.mime_type][1]
except Exception as e:
if DEBUG: print e
if next_task_path is not None:
inflate = {
'task_path' : next_task_path,
'doc_id' : document._id,
'queue' : task.queue
}
if task_extras is not None: inflate.update(task_extras)
next_task = UnveillanceTask(inflate=inflate)
next_task.run()
def evaluateFile(task):
task_tag = "EVALUATING DOCUMENT (INFORMACAM)"
print "\n\n************** %s [START] ******************\n" % task_tag
print "image preprocessing at %s" % task.doc_id
task.setStatus(302)
from lib.Worker.Models.uv_document import UnveillanceDocument
from conf import DEBUG
from vars import ASSET_TAGS
document = UnveillanceDocument(_id=task.doc_id)
if document is None:
print "DOC IS NONE"
print "\n\n************** %s [ERROR] ******************\n" % task_tag
task.fail()
return
if not document.getFile(task.file_name):
print "NO FILE CONTENT"
print "\n\n************** %s [ERROR] ******************\n" % task_tag
task.fail()
return
from lib.Worker.Models.uv_task import UnveillanceTask
from lib.Worker.Utils.funcs import getFileType
from vars import MIME_TYPE_TASKS
from conf import ANNEX_DIR
try:
mime_type = getFileType(os.path.join(ANNEX_DIR, task.file_name))
new_task = UnveillanceTask(inflate={
'task_path' : MIME_TYPE_TASKS[mime_type][0],
'doc_id' : document._id,
'file_name' : task.file_name
})
document.addCompletedTask(task.task_path)
new_task.run()
except IndexError as e:
print "NO NEXT TASK: %s" % e
print "\n\n************** %s [ERROR] ******************\n" % task_tag
task.fail()
return
task.finish()
print "\n\n************** %s [END] ******************\n" % task_tag
def startElasticsearch(self, catch=True):
cmd = [ELS_ROOT, '-Des.max-open-files=true',
'-Des.config=%s' % os.path.join(CONF_ROOT, "els.settings.yaml")]
print "elasticsearch running in daemon."
print cmd
p = Popen(cmd, stdout=PIPE, close_fds=True)
data = p.stdout.readline()
while data:
print data
if re.match(r'.*started$', data):
print "STARTED: %s" % data
with open(self.els_status_file, 'wb+') as f: f.write("True")
sleep(1)
if self.first_use: self.initElasticsearch()
break
data = p.stdout.readline()
p.stdout.close()
#if self.first_use:
startDaemon(self.els_log_file, self.els_pid_file)
self.startCronJobs()
try:
with open(os.path.join(CONF_ROOT, "initial_tasks.json"), 'rb') as IT:
from lib.Worker.Models.uv_task import UnveillanceTask
for i_task in json.loads(IT.read()):
task = UnveillanceTask(inflate=i_task)
try:
task.run()
except Exception as e:
if DEBUG:
print "TASK ERROR: %s" % e
except Exception as e:
if DEBUG:
print "No initial tasks...\n%s" % e
if catch:
while True: sleep(1)
def do_reindex(self, request):
print "DOING REINDEX"
query = parseRequestEntity(request.query)
if query is None: return None
if '_id' not in query.keys(): return None
document = self.get(_id=query['_id'])
if document is None:
return None
document = UnveillanceDocument(_id=document['_id'])
inflate={
'doc_id' : document._id,
'queue' : UUID
}
del query['_id']
if 'task_path' not in query.keys() and 'task_queue' not in query.keys():
document.reset()
inflate.update({
'task_path' : "Documents.evaluate_document.evaluateDocument"
})
else:
inflate.update(query)
if 'task_queue' in inflate.keys():
inflate.update({
'task_path' : inflate['task_queue'][0],
'task_queue' : inflate['task_queue']
})
else:
inflate.update({
'no_continue' : True
})
uv_task = UnveillanceTask(inflate=inflate)
uv_task.run()
return uv_task.emit()
def runTask(self, handler): try: args = parseRequestEntity(handler.request.body) except AttributeError as e: if DEBUG: print "No body?\n%s" % e return None uv_task = None if len(args.keys()) == 1 and '_id' in args.keys(): uv_task = UnveillanceTask(_id=args['_id']) else: # TODO: XXX: IF REFERER IS LOCALHOST ONLY (and other auth TBD)! if 'task_path' in args.keys(): args['queue'] = UUID uv_task = UnveillanceTask(inflate=args) if uv_task is None: return None uv_task.run() return uv_task.emit()
def initSource(task):
task_tag = "INITING SOURCE"
print "\n\n************** %s [START] ******************\n" % task_tag
task.setStatus(302)
from lib.Worker.Models.ic_source import InformaCamSource
from conf import DEBUG
from vars import ASSET_TAGS
source = InformaCamSource(_id=task.doc_id)
if source is None:
print "SOURCE DOCUMENT DOES NOT EXIST"
print "\n\n************** %s [ERROR] ******************\n" % task_tag
task.fail()
return
if not hasattr(task, "assets"):
print "NO ASSETS FOR THIS SOURCE"
print "\n\n************** %s [ERROR] ******************\n" % task_tag
task.fail()
return
import re, json, os
from conf import ANNEX_DIR
next_task = None
for asset in task.assets:
description = None
tags = None
sync = False
if re.match(r'publicKey', asset):
# import key
description = "Source's public pgp key"
tags = [ASSET_TAGS['PGP_KEY']]
from lib.Worker.Models.uv_task import UnveillanceTask
next_task = UnveillanceTask(inflate={
'doc_id' : source._id,
'task_path' : "PGP.import_key.importKey",
'queue' : task.queue
})
sync = True
elif re.match(r'credentials', asset):
# parse creds
with open(os.path.join(ANNEX_DIR, source.base_path, asset), 'rb') as C:
try:
credentials = json.loads(C.read())
if DEBUG: print credentials
for field in ['email','alias']:
if field in credentials.keys() and credentials[field] != "":
setattr(source, field, credentials[field])
source.save()
except Exception as e:
if DEBUG: print e
pass
asset_path = source.addAsset(None, asset, description=description, tags=tags)
print "ASSET PATH: %s" % asset_path
if asset_path is None: continue
if sync:
print "ADDING %s AS FILE AS WELL:" % asset_path
source.addFile(asset_path, None)
if next_task is None:
print "NO PUBLIC KEY FOR SOURCE."
print "\n\n************** %s [ERROR] ******************\n" % task_tag
task.fail()
return
source.addCompletedTask(task.task_path)
from time import sleep
sleep(10)
next_task.run()
task.finish()
print "\n\n************** %s [END] ******************\n" % task_tag
def unpackJ3MLog(uv_task):
task_tag = "UNPACKING J3M LOG"
print "\n\n************** %s [START] ******************\n" % task_tag
uv_task.setStatus(302)
from lib.Worker.Models.ic_j3mlog import InformaCamLog
from conf import DEBUG
if not hasattr(uv_task, "assets"):
print "NO ASSETS FOR THIS J3M LOG"
print "\n\n************** %s [ERROR] ******************\n" % task_tag
uv_task.fail()
return
j3m_log = InformaCamLog(_id=uv_task.doc_id)
if j3m_log is None:
print "J3M LOG DOES NOT EXIST"
print "\n\n************** %s [ERROR] ******************\n" % task_tag
uv_task.fail()
return
import re, os
from fabric.api import local, settings
from fabric.context_managers import hide
from lib.Worker.Models.uv_task import UnveillanceTask
from lib.Worker.Models.uv_document import UnveillanceDocument
from conf import ANNEX_DIR
from vars import MIME_TYPES
j3m_log.original_mime_type = j3m_log.mime_type
j3m_log.mime_type = MIME_TYPES['j3mlog']
j3m_log.save()
for asset in uv_task.assets:
if re.match(r'log.j3m(?:\.json)?', asset):
# is the j3m
try:
j3m_name = j3m_log.addAsset(None, asset)
except Exception as e:
print "WE COULD NOT ADD ASSET %s?" % asset
print e
print "\n\n************** %s [WARN] ******************\n" % task_tag
continue
if j3m_name is None:
print "COULD NOT ADD J3M."
print "\n\n************** %s [WARN] ******************\n" % task_tag
continue
uv_task.routeNext(inflate={'j3m_name' : j3m_name})
elif re.match(r'.+\.(?:jpg|mkv)$', asset):
# is a submission; create it, but move asset over into ANNEX_DIR first
asset_path = os.path.join(ANNEX_DIR, j3m_log.base_path, asset)
if DEBUG:
print "MOVING ASSET FROM %s" % asset_path
with settings(hide('everything'), warn_only=True):
local("mv %s %s" % (asset_path, ANNEX_DIR))
media = UnveillanceDocument(inflate={
'file_name' : asset,
'attached_to' : j3m_log._id
})
if not hasattr(j3m_log, "documents"):
j3m_log.documents = []
j3m_log.documents.append(media)
media_task = UnveillanceTask(inflate={
'task_path' : "Documents.evaluate_document.evaluateDocument",
'doc_id' : media._id,
'queue' : uv_task.queue,
'file_name' : asset
})
media_task.run()
uv_task.finish()
print "\n\n************** %s [END] ******************\n" % task_tag
def splitPDFPages(task):
print "\n\n************** SPLITTING PDF PAGES [START] ******************\n"
print "splitting pdf at %s into pages" % task.doc_id
task.setStatus(412)
from copy import deepcopy
from lib.Worker.Models.cp_pdf import CompassPDF
from conf import DEBUG
from vars import ASSET_TAGS
pdf = CompassPDF(_id=task.doc_id)
if pdf is None:
print "PDF IS NONE"
print "\n\n************** SPLITTING PDF PAGES [ERROR] ******************\n"
return
from cStringIO import StringIO
from PyPDF2 import PdfFileWriter
from lib.Worker.Models.uv_task import UnveillanceTask
from vars import MIME_TYPE_TASKS
MAX_PAGES = 200
next_task = {
'task_path' : MIME_TYPE_TASKS['application/pdf'][1],
'doc_id' : task.doc_id,
'queue' : task.queue
}
pdf_reader = pdf.loadFile(pdf.file_name)
if pdf_reader is None:
print "PDF READER IS NONE"
print "\n\n************** SPLITTING PDF PAGES [ERROR] ******************\n"
return
# get num pages
total_pages = pdf_reader.getNumPages()
if not hasattr(task, "num_pages"): task.num_pages = MAX_PAGES
if total_pages > task.num_pages:
print "THIS SHOULD BE SPLIT BEFORE CONTINUING!"
count = done = 0
out = PdfFileWriter()
for x in xrange(0, total_pages):
page = pdf_reader.getPage(x)
if x != 0 and x % num_pages == 0:
if DEBUG:
print "max reached... let's close this doc (done = %d)" % done
print "merging pages %d to %d to PDF" % (count, x)
count = x
done += 1
new_pdf = StringIO()
out.write(new_pdf)
new_pdf.close()
if pdf.addAsset(new_pdf.getvalue(), "doc_split_%d.pdf" % done,
tags=[ASSET_TAGS['D_S'], ASSET_TAGS['AS_PDF']], description="Chunk %d of original document" % done):
doc_split_task = deepcopy(next_task)
doc_split_task.update({
'split_file' : "doc_split_%d.pdf" % done,
'split_index' : done
})
new_task = UnveillanceTask(inflate=doc_split_task)
new_task.run()
else:
pdf.addCompletedTask(task.task_path)
new_task = UnveillanceTask(inflate=deepcopy(next_task))
new_task.run()
task.finish()
print "\n\n************** SPLITTING PDF PAGES [END] ******************\n"
def extractPDFText(task):
task_tag = "PDF TEXT EXTRACTION"
print "\n\n************** %s [START] ******************\n" % task_tag
print "extracting text from pdf at %s" % task.doc_id
task.setStatus(412)
from lib.Worker.Models.cp_pdf import CompassPDF
from conf import DEBUG
from vars import ASSET_TAGS
pdf = CompassPDF(_id=task.doc_id)
if pdf is None:
print "PDF IS NONE"
print "\n\n************** PDF TEXT EXTRACTION [ERROR] ******************\n"
return
"""
In this task, we might be asked to extract from a broken-up sub-group of documents.
if so, that should be set in the task's properties.
"""
pdf_reader = pdf.loadFile(pdf.file_name)
total_pages = pdf_reader.getNumPages()
if hasattr(task, "split_file"):
pdf_reader = pdf.loadAsset(task.split_file)
if pdf_reader is None:
print "PDF READER IS NONE"
print "\n\n************** PDF TEXT EXTRACTION [ERROR] ******************\n"
return
from json import loads
lower_bound = 0
t = pdf.getAsset("doc_texts.json")
if t is None:
texts = [None] * total_pages
else:
try:
texts = loads(t[0])
except TypeError as e:
texts = [None] * total_pages
if hasattr(task, "split_index") : lower_bound = task.split_index
upper_bound = lower_bound + pdf_reader.getNumPages()
for x in xrange(lower_bound, upper_bound):
texts[x] = pdf_reader.getPage(x).extractText()
if DEBUG: print "EXTRACTED TEXT from page %d of %d:\n%s" % (x, upper_bound, texts[x])
asset_path = pdf.addAsset(texts, "doc_texts.json", as_literal=False,
description="jsonified texts in document; page-by-page, segment-by-segment. uncleaned. (Not OCR)", tags=[ASSET_TAGS['TXT_JSON']])
if asset_path is not None:
pdf.addFile(asset_path, None, sync=True)
from lib.Worker.Models.uv_text import UnveillanceText
uv_text = UnveillanceText(inflate={
'media_id' : pdf._id,
'searchable_text' : texts,
'file_name' : asset_path
})
pdf.text_id = uv_text._id
pdf.save()
pdf.addCompletedTask(task.task_path)
if not hasattr(task, "no_continue"):
from lib.Worker.Models.uv_task import UnveillanceTask
next_task = UnveillanceTask(inflate={
'task_path' : 'Text.preprocess_nlp.preprocessNLP',
'doc_id' : task.doc_id,
'queue' : task.queue,
'text_file' : asset_path
})
next_task.run()
if DEBUG: print "WHERE ARE THE F*****G S TEXTS? %d" % len(pdf.searchable_texts)
task.finish()
print "\n\n************** PDF TEXT EXTRACTION [END] ******************\n"
