def setUp(self):
version = container.Version(1, 1, "pyaff4")
with data_store.MemoryDataStore() as resolver:
resolver.Set(lexicon.transient_graph, self.filename_urn,
lexicon.AFF4_STREAM_WRITE_MODE,
rdfvalue.XSDString("truncate"))
with zip.ZipFile.NewZipFile(resolver, version,
self.filename_urn) as zip_file:
self.volume_urn = zip_file.urn
self.image_urn = self.volume_urn.Append(self.image_name)
# Write Map image sequentially (Seek/Write method).
with aff4_map.AFF4Map.NewAFF4Map(resolver, self.image_urn,
self.volume_urn) as image:
# Maps are written in random order.
image.SeekWrite(50)
image.Write(b"XX - This is the position.")
image.SeekWrite(0)
image.Write(b"00 - This is the position.")
# We can "overwrite" data by writing the same range again.
image.SeekWrite(50)
image.Write(b"50")
# Test the Stream method.
with resolver.CachePut(
aff4_file.AFF4MemoryStream(resolver)) as source:
# Fill it with data.
source.Write(b"AAAABBBBCCCCDDDDEEEEFFFFGGGGHHHH")
# Make a temporary map that defines our plan.
helper_map = aff4_map.AFF4Map(resolver)
helper_map.AddRange(4, 0, 4, source.urn) # 0000AAAA
helper_map.AddRange(0, 12, 4, source.urn) # DDDDAAAA
helper_map.AddRange(12, 16, 4,
source.urn) # DDDDAAAA0000EEEE
image_urn_2 = self.volume_urn.Append(
self.image_name).Append("streamed")
with aff4_map.AFF4Map.NewAFF4Map(resolver, image_urn_2,
self.volume_urn) as image:
# Now we create the real map by copying the temporary
# map stream.
image.WriteStream(helper_map)
def _WriteToTarget(self, resolver, source_as, image_stream):
# Prepare a temporary map to control physical memory acquisition.
helper_map = aff4_map.AFF4Map(resolver)
with resolver.CachePut(
AddressSpaceWrapper(resolver=resolver,
address_space=source_as)) as source_aff4:
total_length = 0
for run in source_as.get_address_ranges():
total_length += run.length
helper_map.AddRange(run.start, run.start, run.length,
source_aff4.urn)
progress = aff4.ProgressContext(length=total_length)
image_stream.WriteStream(helper_map, progress=progress)
return total_length