def store_record(self, metadata: Dict[str, str]) -> None:
"""Method to create and store an activity record
Args:
metadata(dict): A dictionary of data to start the activity monitor
Returns:
None
"""
if len(self.cell_data) > 0:
t_start = time.time()
# Process collected data and create an activity record
activity_record = self.process(ActivityType.CODE,
list(reversed(self.cell_data)),
{"path": metadata["path"]})
# Commit changes to the related Notebook file
commit = self.commit_labbook()
# Create note record
activity_commit = self.store_activity_record(
commit, activity_record)
logger.info(
f"Created auto-generated activity record {activity_commit} in {time.time() - t_start} seconds"
)
# Reset for next execution
self.can_store_activity_record = False
self.cell_data = list()
self.current_cell = ExecutionData()
def __init__(self,
user: str,
owner: str,
labbook_name: str,
monitor_key: str,
config_file: str = None,
author_name: Optional[str] = None,
author_email: Optional[str] = None) -> None:
"""Constructor requires info to load the lab book
Args:
user(str): current logged in user
owner(str): owner of the lab book
labbook_name(str): name of the lab book
monitor_key(str): Unique key for the activity monitor in redis
author_name(str): Name of the user starting this activity monitor
author_email(str): Email of the user starting this activity monitor
"""
# Call super constructor
ActivityMonitor.__init__(self,
user,
owner,
labbook_name,
monitor_key,
config_file,
author_name=author_name,
author_email=author_email)
# For now, register processors by default
self.register_processors()
# Let's call them cells as if they were Jupyter
self.current_cell = ExecutionData()
self.cell_data: List[ExecutionData] = list()
# variables that track the context of messages in the log
# am I in the console, or the notebook?
# what chunk is being executed?
# in what notebook?
self.is_console = False
self.is_notebook = False
self.chunk_id = None
self.nbname = None
def test_is_not_empty(self):
"""Test the constructor"""
ed = ExecutionData()
ed.code.append({"this": "thing"})
assert ed.is_empty() is False
ed = ExecutionData()
ed.result.append({"this": "thing"})
assert ed.is_empty() is False
ed = ExecutionData()
ed.tags.append("tag")
assert ed.is_empty() is False
def store_record(self) -> None:
"""Store R input/output/code to ActivityRecord / git commit
store_record() should be called after moving any data in self.current_cell to
self.cell_data. Any data remaining in self.current_cell will be removed.
Args:
None
"""
if len(self.cell_data) > 0:
t_start = time.time()
# Process collected data and create an activity record
if self.is_console:
codepath = "console"
else:
codepath = self.nbname if self.nbname else "Unknown notebook"
activity_record = self.process(ActivityType.CODE,
list(reversed(self.cell_data)),
{'path': codepath})
# Commit changes to the related Notebook file
commit = self.commit_labbook()
# Create note record
activity_commit = self.store_activity_record(
commit, activity_record)
logger.info(
f"Created auto-generated activity record {activity_commit} in {time.time() - t_start} seconds"
)
# Reset for next execution
self.current_cell = ExecutionData()
self.cell_data = list()
self.is_notebook = False
self.is_console = False
def __init__(self,
user: str,
owner: str,
labbook_name: str,
monitor_key: str,
config_file: str = None,
author_name: Optional[str] = None,
author_email: Optional[str] = None) -> None:
"""Constructor requires info to load the lab book
Args:
user(str): current logged in user
owner(str): owner of the lab book
labbook_name(str): name of the lab book
monitor_key(str): Unique key for the activity monitor in redis
author_name(str): Name of the user starting this activity monitor
author_email(str): Email of the user starting this activity monitor
"""
# Call super constructor
ActivityMonitor.__init__(self,
user,
owner,
labbook_name,
monitor_key,
config_file,
author_name=author_name,
author_email=author_email)
# For now, register processors by default
self.register_processors()
# Tracking variables during message processing
self.kernel_status = 'idle'
self.current_cell = ExecutionData()
self.cell_data: List[ExecutionData] = list()
self.execution_count = 0
def handle_message(self, msg: Dict[str, Dict]):
"""Method to handle processing an IOPub Message from a JupyterLab kernel
Args:
msg(dict): An IOPub message
Returns:
None
"""
# Initialize can_process to False. This variable is used to indicate if the cell data should be processed into
# an ActivityRecord and saved
if msg['msg_type'] == 'status':
# If status was busy and transitions to idle store cell since execution has completed
if self.kernel_status == 'busy' and msg['content'][
'execution_state'] == 'idle':
self.set_busy_state(False)
if self.current_cell.cell_error is False and self.current_cell.is_empty(
) is False:
# Current cell did not error and has content
# Add current cell to collection of cells ready to process
self.cell_data.append(self.current_cell)
# Reset current_cell attribute for next execution
self.current_cell = ExecutionData()
# Indicate record COULD be processed if timeout occurs
self.can_store_activity_record = True
elif self.kernel_status == 'idle' and msg['content'][
'execution_state'] == 'busy':
# Starting to process new cell execution
self.set_busy_state(True)
self.can_store_activity_record = False
# Update status
self.kernel_status = msg['content']['execution_state']
elif msg['msg_type'] == 'execute_input':
# A message containing the input to kernel has been received
self.current_cell.code.append({'code': msg['content']['code']})
self.execution_count = msg['content']['execution_count']
self.current_cell.tags.append(
f"ex:{msg['content']['execution_count']}")
elif msg['msg_type'] == 'execute_result':
# A message containing the output of a cell execution has been received
if self.execution_count != msg['content']['execution_count']:
logger.error("Execution count mismatch detected {},{}".format(
self.execution_count, msg['content']['execution_count']))
self.current_cell.result.append({
'data':
msg['content']['data'],
'metadata':
msg['content']['metadata']
})
elif msg['msg_type'] == 'stream':
# A message containing plaintext output of a cell execution has been received
self.current_cell.result.append({
'data': {
"text/plain": msg['content']['text']
},
'metadata': {
'source': 'stream'
}
})
elif msg['msg_type'] == 'display_data':
# A message containing rich output of a cell execution has been received
self.current_cell.result.append({
'data': msg['content']['data'],
'metadata': {
'source': 'display_data'
}
})
elif msg['msg_type'] == 'error':
# An error occurred, so don't save this cell by resetting the current cell attribute.
self.current_cell.cell_error = True
else:
logger.info("Received and ignored IOPUB Message of type {}".format(
msg['msg_type']))
class JupyterLabNotebookMonitor(ActivityMonitor):
"""Class to monitor a notebook kernel for activity to be processed."""
def __init__(self,
user: str,
owner: str,
labbook_name: str,
monitor_key: str,
config_file: str = None,
author_name: Optional[str] = None,
author_email: Optional[str] = None) -> None:
"""Constructor requires info to load the lab book
Args:
user(str): current logged in user
owner(str): owner of the lab book
labbook_name(str): name of the lab book
monitor_key(str): Unique key for the activity monitor in redis
author_name(str): Name of the user starting this activity monitor
author_email(str): Email of the user starting this activity monitor
"""
# Call super constructor
ActivityMonitor.__init__(self,
user,
owner,
labbook_name,
monitor_key,
config_file,
author_name=author_name,
author_email=author_email)
# For now, register processors by default
self.register_processors()
# Tracking variables during message processing
self.kernel_status = 'idle'
self.current_cell = ExecutionData()
self.cell_data: List[ExecutionData] = list()
self.execution_count = 0
def register_processors(self) -> None:
"""Method to register processors
Returns:
None
"""
self.add_processor(JupyterLabCodeProcessor())
self.add_processor(GenericFileChangeProcessor())
self.add_processor(JupyterLabPlaintextProcessor())
self.add_processor(JupyterLabImageExtractorProcessor())
self.add_processor(JupyterLabCellVisibilityProcessor())
self.add_processor(ActivityDetailLimitProcessor())
self.add_processor(ActivityShowBasicProcessor())
def handle_message(self, msg: Dict[str, Dict]):
"""Method to handle processing an IOPub Message from a JupyterLab kernel
Args:
msg(dict): An IOPub message
Returns:
None
"""
# Initialize can_process to False. This variable is used to indicate if the cell data should be processed into
# an ActivityRecord and saved
if msg['msg_type'] == 'status':
# If status was busy and transitions to idle store cell since execution has completed
if self.kernel_status == 'busy' and msg['content'][
'execution_state'] == 'idle':
self.set_busy_state(False)
if self.current_cell.cell_error is False and self.current_cell.is_empty(
) is False:
# Current cell did not error and has content
# Add current cell to collection of cells ready to process
self.cell_data.append(self.current_cell)
# Reset current_cell attribute for next execution
self.current_cell = ExecutionData()
# Indicate record COULD be processed if timeout occurs
self.can_store_activity_record = True
elif self.kernel_status == 'idle' and msg['content'][
'execution_state'] == 'busy':
# Starting to process new cell execution
self.set_busy_state(True)
self.can_store_activity_record = False
# Update status
self.kernel_status = msg['content']['execution_state']
elif msg['msg_type'] == 'execute_input':
# A message containing the input to kernel has been received
self.current_cell.code.append({'code': msg['content']['code']})
self.execution_count = msg['content']['execution_count']
self.current_cell.tags.append(
f"ex:{msg['content']['execution_count']}")
elif msg['msg_type'] == 'execute_result':
# A message containing the output of a cell execution has been received
if self.execution_count != msg['content']['execution_count']:
logger.error("Execution count mismatch detected {},{}".format(
self.execution_count, msg['content']['execution_count']))
self.current_cell.result.append({
'data':
msg['content']['data'],
'metadata':
msg['content']['metadata']
})
elif msg['msg_type'] == 'stream':
# A message containing plaintext output of a cell execution has been received
self.current_cell.result.append({
'data': {
"text/plain": msg['content']['text']
},
'metadata': {
'source': 'stream'
}
})
elif msg['msg_type'] == 'display_data':
# A message containing rich output of a cell execution has been received
self.current_cell.result.append({
'data': msg['content']['data'],
'metadata': {
'source': 'display_data'
}
})
elif msg['msg_type'] == 'error':
# An error occurred, so don't save this cell by resetting the current cell attribute.
self.current_cell.cell_error = True
else:
logger.info("Received and ignored IOPUB Message of type {}".format(
msg['msg_type']))
def store_record(self, metadata: Dict[str, str]) -> None:
"""Method to create and store an activity record
Args:
metadata(dict): A dictionary of data to start the activity monitor
Returns:
None
"""
if len(self.cell_data) > 0:
t_start = time.time()
# Process collected data and create an activity record
activity_record = self.process(ActivityType.CODE,
list(reversed(self.cell_data)),
{"path": metadata["path"]})
# Commit changes to the related Notebook file
commit = self.commit_labbook()
# Create note record
activity_commit = self.store_activity_record(
commit, activity_record)
logger.info(
f"Created auto-generated activity record {activity_commit} in {time.time() - t_start} seconds"
)
# Reset for next execution
self.can_store_activity_record = False
self.cell_data = list()
self.current_cell = ExecutionData()
def start(self, metadata: Dict[str, str], database: int = 1) -> None:
"""Method called in a periodically scheduled async worker that should check the dev env and manage Activity
Monitor Instances as needed
Args:
metadata(dict): A dictionary of data to start the activity monitor
database(int): The database ID to use
Returns:
None
"""
# Connect to the kernel
cf = jupyter_client.find_connection_file(
metadata["kernel_id"], path=os.environ['JUPYTER_RUNTIME_DIR'])
km = jupyter_client.BlockingKernelClient()
with open(cf, 'rt') as cf_file:
cf_data = json.load(cf_file)
# Get IP address of lab book container on the bridge network
container_ip = self.get_container_ip()
if not container_ip:
raise ValueError("Failed to find LabBook container IP address.")
cf_data['ip'] = container_ip
km.load_connection_info(cf_data)
# Get connection to the DB
redis_conn = redis.Redis(db=database)
try:
while True:
try:
# Check for messages, waiting up to 1 second. This is the rate that records will be merged
msg = km.get_iopub_msg(timeout=1)
self.handle_message(msg)
except queue.Empty:
# if queue is empty and the record is ready to store, save it!
if self.can_store_activity_record is True:
self.store_record(metadata)
# Check if you should exit
if redis_conn.hget(self.monitor_key,
"run").decode() == "False":
logger.info(
"Received Activity Monitor Shutdown Message for {}".
format(metadata["kernel_id"]))
break
except Exception as err:
logger.error(
"Error in JupyterLab Activity Monitor: {}".format(err))
finally:
# Delete the kernel monitor key so the dev env monitor will spin up a new process
# You may lose some activity if this happens, but the next action will sweep up changes
redis_conn.delete(self.monitor_key)
def process_activity(self, mitmlog):
"""Collect tail of the activity log and turn into an activity record.
Args:
mitmlog(file): open file object
Returns:
ar(): activity record
"""
# get an fstream generator object
fstream = mitmio.FlowReader(mitmlog).stream()
# no context yet. not a notebook or console
self.is_console = False
self.is_notebook = False
while True:
try:
f = next(fstream)
except StopIteration:
break
except FlowReadException as e:
logger.info("MITM Flow file corrupted: {}. Exiting.".format(e))
break
st: Dict = f.get_state()
is_png = False
is_gzip = False
is_json = False
# Check response types for images and json
for header in st['response']['headers']:
# png images
if header[0] == b'Content-Type':
if header[1] == b'image/png':
is_png = True
# json
if header[0] == b'Content-Type':
if header[1] == b'application/json':
is_json = True
if header[0] == b'Content-Encoding':
if header[1] == b'gzip':
is_gzip = True
else:
# Not currently used, but useful for debugging and potentially in future
encoding = header[1]
# process images
if is_png:
if is_gzip:
self._parse_image(st)
else:
logger.error(
f"RSERVER Found image/png that was not gzip encoded.")
if is_json:
self._parse_json(st, is_gzip)
# Flush cell data IFF anything happened
if self.current_cell.code:
self.cell_data.append(self.current_cell)
self.store_record()
self.current_cell = ExecutionData()
self.cell_data = list()
self.chunk_id = None
def _parse_json_record(self, json_record: Dict) -> None:
"""Extract code and data from the record.
When context switches between console <-> notebook, we store a record for
the previous execution and start a new record.
Args:
json_record: dictionary parsed from mitmlog
"""
result = json_record.get('result')
# No result ignore
if not result:
return
# execution of new notebook cell
if result[0]['type'] == 'chunk_exec_state_changed':
if self.is_console:
# switch from console to notebook. store record
if self.current_cell.code:
self.cell_data.append(self.current_cell)
self.store_record()
elif self.is_notebook and self.current_cell.code:
self.cell_data.append(self.current_cell)
self.current_cell = ExecutionData()
self.chunk_id = None
self.is_notebook = True
self.is_console = False
# Reset current_cell attribute for next execution
self.current_cell.tags.append('notebook')
# execution of console code. you get a message for every line.
if result[0]['type'] == 'console_write_prompt':
if self.is_notebook:
# switch to console. store record
if self.current_cell.code:
self.cell_data.append(self.current_cell)
self.store_record()
self.current_cell.tags.append('console')
# add a tag is this is first line of console code
elif not self.is_console:
self.current_cell.tags.append('console')
self.is_console = True
self.is_notebook = False
# parse the entries in this message
for edata, etype in [(entry.get('data'), entry.get('type'))
for entry in result]:
if etype == 'chunk_output':
outputs = edata.get('chunk_outputs')
if outputs:
for oput in outputs:
result = format_output(oput)
if result:
self.current_cell.result.append(result)
oput = edata.get('chunk_output')
if oput:
result = format_output(oput)
if result:
self.current_cell.result.append(result)
# get notebook code
if self.is_notebook and etype == 'notebook_range_executed':
# new cell advance cell
if self.chunk_id is None or self.chunk_id != edata['chunk_id']:
if self.current_cell.code:
self.cell_data.append(self.current_cell)
self.current_cell = ExecutionData()
self.chunk_id = edata['chunk_id']
self.current_cell.tags.append('notebook')
# take code in current cell
self.current_cell.code.append({'code': edata['code']})
# console code
if self.is_console and etype == 'console_write_input':
# remove trailing whitespace -- specificially \n
if edata['text'] != "\n" or self.current_cell.code != []:
self.current_cell.code.append(
{'code': edata['text'].rstrip()})
# this happens in both notebooks and console
# ignore if no context (that's the R origination message
if etype == 'console_output' and (self.is_console
or self.is_notebook):
self.current_cell.result.append(
{'data': {
'text/plain': edata['text']
}})
class RStudioServerMonitor(ActivityMonitor):
"""Class to monitor an rstudio server for activity to be processed."""
def __init__(self,
user: str,
owner: str,
labbook_name: str,
monitor_key: str,
config_file: str = None,
author_name: Optional[str] = None,
author_email: Optional[str] = None) -> None:
"""Constructor requires info to load the lab book
Args:
user(str): current logged in user
owner(str): owner of the lab book
labbook_name(str): name of the lab book
monitor_key(str): Unique key for the activity monitor in redis
author_name(str): Name of the user starting this activity monitor
author_email(str): Email of the user starting this activity monitor
"""
# Call super constructor
ActivityMonitor.__init__(self,
user,
owner,
labbook_name,
monitor_key,
config_file,
author_name=author_name,
author_email=author_email)
# For now, register processors by default
self.register_processors()
# Let's call them cells as if they were Jupyter
self.current_cell = ExecutionData()
self.cell_data: List[ExecutionData] = list()
# variables that track the context of messages in the log
# am I in the console, or the notebook?
# what chunk is being executed?
# in what notebook?
self.is_console = False
self.is_notebook = False
self.chunk_id = None
self.nbname = None
def register_processors(self) -> None:
"""Method to register processors
Returns:
None
"""
self.add_processor(RStudioServerCodeProcessor())
self.add_processor(GenericFileChangeProcessor())
self.add_processor(RStudioServerPlaintextProcessor())
self.add_processor(RStudioServerImageExtractorProcessor())
self.add_processor(ActivityDetailLimitProcessor())
self.add_processor(ActivityShowBasicProcessor())
def start(self, metadata: Dict[str, str], database: int = 1) -> None:
"""Method called in a periodically scheduled async worker that should check the dev env and manage Activity
Monitor Instances as needed
Args:
metadata(dict): A dictionary of data to start the activity monitor
database(int): The database ID to use
Returns:
None
"""
# Get connection to the DB
redis_conn = redis.Redis(db=database)
# TODO DC: Dean asks why we need to use a regex here.
# This will get hoisted by https://github.com/gigantum/gigantum-client/issues/453
m = re.match(r".*:activity_monitor:(\w+)$", self.monitor_key)
if m is not None:
filename = f"/mnt/share/mitmproxy/{m.group(1)}.rserver.dump"
else:
logger.error(f"No active monitor matching {self.monitor_key}")
# TODO RB will need to open in write mode later to sparsify parts of the file that have already been read
# https://github.com/gigantum/gigantum-client/issues/434
# open the log file
mitmlog = open(filename, "rb")
if not mitmlog:
logger.info(f"Failed to open RStudio log {self.monitor_key}")
return
try:
while True:
still_running = redis_conn.hget(self.monitor_key, "run")
# Check if you should exit
# sometimes this runs after key has been deleted. None is shutdown too.
if not still_running or still_running.decode() == "False":
logger.info(
f"Received Activity Monitor Shutdown Message for {self.monitor_key}"
)
break
previous_cells = len(self.cell_data)
# Read activity and update aggregated "cell" data
self.process_activity(mitmlog)
# We are processing every second, then aggregating activity records when idle
if previous_cells == len(
self.cell_data) and self.current_cell.is_empty():
# there are no new cells in the last second, and no cells are in-process
self.store_record()
# Check for new records every second
time.sleep(1)
except Exception as e:
logger.error(
f"Fatal error in RStudio Server Activity Monitor: {e}")
raise
finally:
# Delete the kernel monitor key so the dev env monitor will spin up a new process
# You may lose some activity if this happens, but the next action will sweep up changes
logger.info(f"Shutting down RStudio monitor {self.monitor_key}")
redis_conn.delete(self.monitor_key)
def store_record(self) -> None:
"""Store R input/output/code to ActivityRecord / git commit
store_record() should be called after moving any data in self.current_cell to
self.cell_data. Any data remaining in self.current_cell will be removed.
Args:
None
"""
if len(self.cell_data) > 0:
t_start = time.time()
# Process collected data and create an activity record
if self.is_console:
codepath = "console"
else:
codepath = self.nbname if self.nbname else "Unknown notebook"
activity_record = self.process(ActivityType.CODE,
list(reversed(self.cell_data)),
{'path': codepath})
# Commit changes to the related Notebook file
commit = self.commit_labbook()
# Create note record
activity_commit = self.store_activity_record(
commit, activity_record)
logger.info(
f"Created auto-generated activity record {activity_commit} in {time.time() - t_start} seconds"
)
# Reset for next execution
self.current_cell = ExecutionData()
self.cell_data = list()
self.is_notebook = False
self.is_console = False
def _parse_json_record(self, json_record: Dict) -> None:
"""Extract code and data from the record.
When context switches between console <-> notebook, we store a record for
the previous execution and start a new record.
Args:
json_record: dictionary parsed from mitmlog
"""
result = json_record.get('result')
# No result ignore
if not result:
return
# execution of new notebook cell
if result[0]['type'] == 'chunk_exec_state_changed':
if self.is_console:
# switch from console to notebook. store record
if self.current_cell.code:
self.cell_data.append(self.current_cell)
self.store_record()
elif self.is_notebook and self.current_cell.code:
self.cell_data.append(self.current_cell)
self.current_cell = ExecutionData()
self.chunk_id = None
self.is_notebook = True
self.is_console = False
# Reset current_cell attribute for next execution
self.current_cell.tags.append('notebook')
# execution of console code. you get a message for every line.
if result[0]['type'] == 'console_write_prompt':
if self.is_notebook:
# switch to console. store record
if self.current_cell.code:
self.cell_data.append(self.current_cell)
self.store_record()
self.current_cell.tags.append('console')
# add a tag is this is first line of console code
elif not self.is_console:
self.current_cell.tags.append('console')
self.is_console = True
self.is_notebook = False
# parse the entries in this message
for edata, etype in [(entry.get('data'), entry.get('type'))
for entry in result]:
if etype == 'chunk_output':
outputs = edata.get('chunk_outputs')
if outputs:
for oput in outputs:
result = format_output(oput)
if result:
self.current_cell.result.append(result)
oput = edata.get('chunk_output')
if oput:
result = format_output(oput)
if result:
self.current_cell.result.append(result)
# get notebook code
if self.is_notebook and etype == 'notebook_range_executed':
# new cell advance cell
if self.chunk_id is None or self.chunk_id != edata['chunk_id']:
if self.current_cell.code:
self.cell_data.append(self.current_cell)
self.current_cell = ExecutionData()
self.chunk_id = edata['chunk_id']
self.current_cell.tags.append('notebook')
# take code in current cell
self.current_cell.code.append({'code': edata['code']})
# console code
if self.is_console and etype == 'console_write_input':
# remove trailing whitespace -- specificially \n
if edata['text'] != "\n" or self.current_cell.code != []:
self.current_cell.code.append(
{'code': edata['text'].rstrip()})
# this happens in both notebooks and console
# ignore if no context (that's the R origination message
if etype == 'console_output' and (self.is_console
or self.is_notebook):
self.current_cell.result.append(
{'data': {
'text/plain': edata['text']
}})
def _is_error(self, result: Dict) -> bool:
"""Check if there's an error in the message"""
for entry in result:
if entry['type'] == 'console_error':
return True
else:
return False
def _parse_image(self, st: Dict):
# These are from notebooks
m = re.match(r"/chunk_output/(([\w]+)/)+([\w]+.png)",
st['request']['path'].decode())
if m:
img_data = zlib.decompress(st['response']['content'],
16 + zlib.MAX_WBITS)
# if we actually wanted to work with the image, could do so like this:
# img = Image.open(io.BytesIO(img_data))
eimg_data = base64.b64encode(img_data)
self.current_cell.result.append({'data': {'image/png': eimg_data}})
# These are from scripts.
m = re.match(r"/graphics/(?:[^[\\/:\"*?<>|]+])*([\w-]+).png",
st['request']['path'].decode())
if m:
img_data = zlib.decompress(st['response']['content'],
16 + zlib.MAX_WBITS)
eimg_data = base64.b64encode(img_data)
self.current_cell.result.append({'data': {'image/png': eimg_data}})
def _parse_json(self, st: Dict, is_gzip: bool):
# get the filename
m = re.match(r"/rpc/refresh_chunk_output.*",
st['request']['path'].decode())
if m:
# A new chunk, so potentially a new notebook.
if self.current_cell.code:
self.cell_data.append(self.current_cell)
# RB was always storing a record here
# with new logic, running cells in two notebooks within a second seems unlikely
# self.store_record()
# strict=False allows control codes, as used in tidyverse output
jdata = json.loads(st['request']['content'], strict=False)
fullname = jdata['params'][0]
# pull out the name relative to the "code" directory
m1 = re.match(r".*/code/(.*)$", fullname)
if m1:
self.nbname = m1.group(1)
else:
m2 = re.match(r"/mnt/labbook/(.*)$", fullname)
if m2:
self.nbname = m2.group(1)
else:
self.nbname = fullname
# code or output event
m = re.match(r"/events/get_events", st['request']['path'].decode())
if m:
if is_gzip:
jdata = zlib.decompress(st['response']['content'],
16 + zlib.MAX_WBITS)
else:
jdata = st['response']['content']
# get text/code fields out of dictionary
try:
# strict=False allows control codes, as used in tidyverse output
self._parse_json_record(json.loads(jdata, strict=False))
except json.JSONDecodeError as je:
logger.info(
f"Ignoring JSON Decoder Error in process_activity {je}.")
return False
return True
def process_activity(self, mitmlog):
"""Collect tail of the activity log and turn into an activity record.
Args:
mitmlog(file): open file object
Returns:
ar(): activity record
"""
# get an fstream generator object
fstream = mitmio.FlowReader(mitmlog).stream()
# no context yet. not a notebook or console
self.is_console = False
self.is_notebook = False
while True:
try:
f = next(fstream)
except StopIteration:
break
except FlowReadException as e:
logger.info("MITM Flow file corrupted: {}. Exiting.".format(e))
break
st: Dict = f.get_state()
is_png = False
is_gzip = False
is_json = False
# Check response types for images and json
for header in st['response']['headers']:
# png images
if header[0] == b'Content-Type':
if header[1] == b'image/png':
is_png = True
# json
if header[0] == b'Content-Type':
if header[1] == b'application/json':
is_json = True
if header[0] == b'Content-Encoding':
if header[1] == b'gzip':
is_gzip = True
else:
# Not currently used, but useful for debugging and potentially in future
encoding = header[1]
# process images
if is_png:
if is_gzip:
self._parse_image(st)
else:
logger.error(
f"RSERVER Found image/png that was not gzip encoded.")
if is_json:
self._parse_json(st, is_gzip)
# Flush cell data IFF anything happened
if self.current_cell.code:
self.cell_data.append(self.current_cell)
self.store_record()
self.current_cell = ExecutionData()
self.cell_data = list()
self.chunk_id = None
def test_is_empty(self):
"""Test the constructor"""
ed = ExecutionData()
assert ed.is_empty() is True
