I am new to Python.
I have this code in Python:
from netmiko import ConnectHandler
`sshCli = ConnectHandler(
device_type='Cisco_ios',
host='192.168.56.101',
port=22,
username='cisco',
password='cisco123!'
)
output = sshCli.send_command("show ip int brief")
print("show ip int brief:\n{}\n".format(output))
I get the following error:
========== RESTART: C:/Users/edanpc/AppData/Local/Programs/Python/Python38-32/Lab2.2.py =========
Traceback (most recent call last):
File "C:/Users/edanpc/AppData/Local/Programs/Python/Python38-32/Lab2.2.py", line 2, in <module>
sshCli = ConnectHandler(
File "C:\Users\edanpc\AppData\Local\Programs\Python\Python38-32\lib\site-packages\netmiko\ssh_dispatcher.py", line 297, in ConnectHandler
raise ValueError(
ValueError: Unsupported 'device_type' currently supported platforms are:
a10
accedian
adtran_os
alcatel_aos
alcatel_sros
apresia_aeos
arista_eos
aruba_os
avaya_ers
avaya_vsp
broadcom_icos
brocade_fastiron
brocade_netiron
brocade_nos
brocade_vdx
brocade_vyos
calix_b6
centec_os
checkpoint_gaia
ciena_saos
cisco_asa
cisco_ios
cisco_nxos
cisco_s300
cisco_tp
cisco_wlc
cisco_xe
cisco_xr
cloudgenix_ion
coriant
dell_dnos9
dell_force10
dell_isilon
dell_os10
dell_os6
dell_os9
dell_powerconnect
dlink_ds
eltex
eltex_esr
endace
enterasys
extreme
extreme_ers
extreme_exos
extreme_netiron
extreme_nos
extreme_slx
extreme_vdx
extreme_vsp
extreme_wing
f5_linux
f5_ltm
f5_tmsh
flexvnf
fortinet
generic
generic_termserver
hp_comware
hp_procurve
huawei
huawei_olt
huawei_smartax
huawei_vrpv8
ipinfusion_ocnos
juniper
juniper_junos
juniper_screenos
keymile
keymile_nos
linux
mellanox
mellanox_mlnxos
mikrotik_routeros
mikrotik_switchos
mrv_lx
mrv_optiswitch
netapp_cdot
netgear_prosafe
netscaler
nokia_sros
oneaccess_oneos
ovs_linux
paloalto_panos
pluribus
quanta_mesh
rad_etx
raisecom_roap
ruckus_fastiron
ruijie_os
sixwind_os
sophos_sfos
ubiquiti_edge
ubiquiti_edgeswitch
ubiquiti_unifiswitch
vyatta_vyos
vyos
watchguard_fireware
yamaha
zte_zxros
>>>
What is wrong with my code ?
This error is specific to netmiko. The error text says the list of supported device_type values. To solve the error, fix the below in your code.
device_type='cisco_ios'
The device type should contain small cisco_ios instead of Cisco_ios.
Related
I'm trying to make this version work on my CPU (Linux):
https://github.com/bes-dev/stable_diffusion.openvino
And it works fine without any initial image. But when I try to pass an initial image, I get this error:
Traceback (most recent call last):
File "/home/ideruga/workspace/stable_diffusion.openvino/demo.py", line 79, in <module>
main(args)
File "/home/ideruga/workspace/stable_diffusion.openvino/demo.py", line 39, in main
image = engine(
File "/home/ideruga/workspace/stable_diffusion.openvino/stable_diffusion_engine.py", line 188, in __call__
noise_pred = result(self.unet.infer_new_request({
File "/home/ideruga/anaconda3/lib/python3.9/site-packages/openvino/runtime/ie_api.py", line 266, in infer_new_request
return self.create_infer_request().infer(inputs)
......
File "/home/ideruga/anaconda3/lib/python3.9/site-packages/openvino/runtime/ie_api.py", line 31, in set_scalar_tensor
request.set_tensor(key, tensor)
RuntimeError: [ PARAMETER_MISMATCH ] Failed to set input blob with precision: I64, if CNNNetwork input blob precision is: FP64
It's bizarre, because I am not messing with any parameters. It's as if model that it downloads is not compatible with parsed input image.
I've actually found a bug in the linked repository, I'll submit a fix later today. The used model expects f64 but is fed with i64 value. I'll post a comment with the PR when it's submitted.
I am trying to implement Hierarchical time series forecasting on azureautoml pipelines.
I followed this notebook for implementation
https://github.com/Azure/azureml-examples/blob/main/v1/python-sdk/tutorials/automl-with-azureml/forecasting-hierarchical-timeseries/auto-ml-forecasting-hierarchical-timeseries.ipynb
While I ran training pipeline on compute instance it worked, but when I am running the same on compute cluster it breaks at hts-proportion-calculation part.
This is the error I am getting,
system error:
Encountered an internal AutoML error. Error Message/Code: ClientException. Additional Info: ClientException:
Message: No objects to concatenate
InnerException: None
ErrorResponse
{
"error": {
"message": "No objects to concatenate"
}
}
logs :
Loading arguments for scenario proportions-calculation
adding argument --input-medatadata
adding argument --hts-graph
adding argument --enable-event-logger
Input arguments dict is {'--input-medatadata': '/mnt/azureml/cr/j/85509be625484b6caa3c1d97b7ab2e33/cap/data-capability/wd/INPUT_automl_training_workspaceblobstore/azureml/17ca5ae7-7269-4246-888f-e781071e3f5c/automl_training', '--hts-graph': '/mnt/azureml/cr/j/85509be625484b6caa3c1d97b7ab2e33/cap/data-capability/wd/INPUT_hts_graph_workspaceblobstore/azureml/a2c1b15a-c895-41e8-b6a6-1ca37ebe9e77/hts_graph', '--enable-event-logger': None}
Unknown file to proceed outputs.txt
processing: outputs.txt with type None.
Cleaning up all outstanding Run operations, waiting 300.0 seconds
3 items cleaning up...
Cleanup took 0.001676321029663086 seconds
Traceback (most recent call last):
File "proportions_calculation_wrapper.py", line 47, in <module>
runtime_wrapper.run()
File "/azureml-envs/azureml_e34d0633ffc4cb2fa25d91e3da5f59be/lib/python3.7/site-packages/azureml/train/automl/runtime/_many_models/automl_pipeline_step_wrapper.py", line 63, in run
self._run()
File "/azureml-envs/azureml_e34d0633ffc4cb2fa25d91e3da5f59be/lib/python3.7/site-packages/azureml/train/automl/runtime/_hts/proportions_calculation.py", line 44, in _run
proportions_calculation(self.arguments_dict, self.event_logger, script_run=self.step_run)
File "/azureml-envs/azureml_e34d0633ffc4cb2fa25d91e3da5f59be/lib/python3.7/site-packages/azureml/train/automl/runtime/_hts/proportions_calculation.py", line 173, in proportions_calculation
proportion_files_list, forecasting_parameters.time_column_name, graph.label_column_name
File "/azureml-envs/azureml_e34d0633ffc4cb2fa25d91e3da5f59be/lib/python3.7/site-packages/azureml/train/automl/runtime/_hts/proportions_calculation.py", line 92, in calculate_time_agg_sum_for_all_files
df = pd.concat(pool.map(concat_func, files_batches), ignore_index=True)
File "/azureml-envs/azureml_e34d0633ffc4cb2fa25d91e3da5f59be/lib/python3.7/site-packages/pandas/util/_decorators.py", line 311, in wrapper
return func(*args, **kwargs)
File "/azureml-envs/azureml_e34d0633ffc4cb2fa25d91e3da5f59be/lib/python3.7/site-packages/pandas/core/reshape/concat.py", line 304, in concat
sort=sort,
File "/azureml-envs/azureml_e34d0633ffc4cb2fa25d91e3da5f59be/lib/python3.7/site-packages/pandas/core/reshape/concat.py", line 351, in __init__
raise ValueError("No objects to concatenate")
ValueError: No objects to concatenate
Please let me know how can I resolve this issue ?
This error was incurred as Iteration timeout was not less than experiment timeout , but the system error & logs are a kind of misleading.
df = pd.concat(pool.map(concat_func, files_batches), ignore_index=True)
logs was pointing to pandas "No objects to concatenate"
This error can be overcome by setting iterationtimeout value less than experimenttime out value.
I had set iteration_timeout_minutes=60 which caused the error.
automl_settings = AutoMLConfig(
task="forecasting",
primary_metric="normalized_root_mean_squared_error",
experiment_timeout_hours=1,
label_column_name=label_column_name,
track_child_runs=False,
forecasting_parameters=forecasting_parameters,
pipeline_fetch_max_batch_size=15,
model_explainability=model_explainability,
n_cross_validations="auto", # Feel free to set to a small integer (>=2) if runtime is an issue.
cv_step_size="auto",
# The following settings are specific to this sample and should be adjusted according to your own needs.
iteration_timeout_minutes=10,
iterations=15,
)
We are able to run the sample successfully using the compute cluster as given below.
from azureml.core.compute import ComputeTarget, AmlCompute
# Name your cluster
compute_name = "hts-compute"
if compute_name in ws.compute_targets:
compute_target = ws.compute_targets[compute_name]
if compute_target and type(compute_target) is AmlCompute:
print("Found compute target: " + compute_name)
else:
print("Creating a new compute target...")
provisioning_config = AmlCompute.provisioning_configuration(
vm_size="STANDARD_D16S_V3", max_nodes=20
)
# Create the compute target
compute_target = ComputeTarget.create(ws, compute_name, provisioning_config)
# Can poll for a minimum number of nodes and for a specific timeout.
# If no min node count is provided it will use the scale settings for the cluster
compute_target.wait_for_completion(
show_output=True, min_node_count=None, timeout_in_minutes=20
)
# For a more detailed view of current cluster status, use the 'status' property
print(compute_target.status.serialize())
I'm trying to use the ansible strategy mitogen_linear. Once I try to run a playbook with more then one maschine its crashes as follows.
I'm running this on a Debian 11 over WSL v2 with kernel version 5.10.102.1.
ERROR! [mux 12903] 17:51:03.129739 E mitogen: <Stream ssh.proxyserver02 #5730> crashed
Traceback (most recent call last):
File "/usr/lib/python3/dist-packages/mitogen/core.py", line 3488, in _call
func(self)
File "/usr/lib/python3/dist-packages/mitogen/core.py", line 1726, in on_transmit
self.protocol.on_transmit(broker)
File "/usr/lib/python3/dist-packages/mitogen/core.py", line 2174, in on_transmit
self._writer.on_transmit(broker)
File "/usr/lib/python3/dist-packages/mitogen/core.py", line 1914, in on_transmit
written = self._protocol.stream.transmit_side.write(buf)
File "/usr/lib/python3/dist-packages/mitogen/core.py", line 2040, in write
written, disconnected = io_op(os.write, self.fd, s)
File "/usr/lib/python3/dist-packages/mitogen/core.py", line 553, in io_op
return func(*args), None
BlockingIOError: [Errno 11] Resource temporarily unavailable
fatal: [proxyserver02]: UNREACHABLE! => changed=false
msg: Channel was disconnected while connection attempt was in progress; this may be caused by an abnormal Ansible exit, or due to an unreliable target.
unreachable: true
I'm writing a program that should respond to file changes using inotify. The below skeleton program works as I expect...
# test.py
import asyncio
import ctypes
import os
IN_CLOSE_WRITE = 0x00000008
async def main(loop):
libc = ctypes.cdll.LoadLibrary('libc.so.6')
fd = libc.inotify_init()
os.mkdir('directory-to-watch')
wd = libc.inotify_add_watch(fd, 'directory-to-watch'.encode('utf-8'), IN_CLOSE_WRITE)
loop.add_reader(fd, handle, fd)
with open(f'directory-to-watch/file', 'wb') as file:
pass
def handle(fd):
event_bytes = os.read(fd, 32)
print(event_bytes)
loop = asyncio.get_event_loop()
loop.run_until_complete(main(loop))
... in that it outputs...
b'\x01\x00\x00\x00\x08\x00\x00\x00\x00\x00\x00\x00\x10\x00\x00\x00file\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
However, if I change it to attempt to read 31 bytes...
event_bytes = os.read(fd, 31)
... then it raises an exception...
Traceback (most recent call last):
File "/usr/lib/python3.7/asyncio/events.py", line 88, in _run
self._context.run(self._callback, *self._args)
File "/t.py", line 19, in handle
event_bytes = os.read(fd, 31)
OSError: [Errno 22] Invalid argument
... and similarly for all numbers smaller than 31 that I have tried, including 1 byte.
Why is this? I would have thought it should be able to attempt to read any number of bytes, and just return whatever is in the buffer, up to the length given by the second argument of os.read.
I'm running this in Alpine linux 3.10 in a docker container on Mac OS, with very basic Dockerfile:
FROM alpine:3.10
RUN apk add --no-cache python3
COPY test.py /
and running it by
docker build . -t test && docker run -it --rm test python3 /test.py
It's because it's written to only allow reads that can return information about the next event. From http://man7.org/linux/man-pages/man7/inotify.7.html
The behavior when the buffer given to read(2) is too small to return
information about the next event depends on the kernel version: in
kernels before 2.6.21, read(2) returns 0; since kernel 2.6.21,
read(2) fails with the error EINVAL.
and from https://github.com/torvalds/linux/blob/f1a3b43cc1f50c6ee5ba582f2025db3dea891208/include/uapi/asm-generic/errno-base.h#L26
#define EINVAL 22 /* Invalid argument */
which presumably maps to the Python OSError with Errno 22.
I am dealing with the following error
Traceback (most recent call last):
File "once.py", line 1757, in <module>
once()
File "once.py", line 55, in once
stripe.Charge.all()
File "/Library/Python/2.7/site-packages/stripe/resource.py", line 438, in all
return cls.list(*args, **params)
File "/Library/Python/2.7/site-packages/stripe/resource.py", line 450, in list
response, api_key = requestor.request('get', url, params)
File "/Library/Python/2.7/site-packages/stripe/api_requestor.py", line 150, in request
method.lower(), url, params, headers)
File "/Library/Python/2.7/site-packages/stripe/api_requestor.py", line 281, in request_raw
method, abs_url, headers, post_data)
File "/Library/Python/2.7/site-packages/stripe/http_client.py", line 139, in request
self._handle_request_error(e)
File "/Library/Python/2.7/site-packages/stripe/http_client.py", line 159, in _handle_request_error
raise error.APIConnectionError(msg)
stripe.error.APIConnectionError: Unexpected error communicating with Stripe. If this problem persists,
let us know at support#stripe.com.
I get this error when running a simple test program which stripe suggested
import stripe
stripe.api_key = "blah bla"
stripe.api_base = "https://api-tls12.stripe.com"
print "stripe.VERSION = ", stripe.VERSION
if stripe.VERSION in ("1.13.0", "1.14.0", "1.14.1", "1.15.1", "1.16.0", "1.17.0", "1.18.0", "1.19.0"):
print "Bindings update required."
try:
stripe.Charge.all()
print "TLS 1.2 supported, no action required."
except stripe.error.APIConnectionError:
print "TLS 1.2 is not supported. You will need to upgrade your integration."
raise
I do not understand why I get this error, since my stripe version is high enough
stripe.VERSION = 1.55.2
and my openssl version does support TLS?
>>$ openssl version
OpenSSL 1.0.2k 26 Jan 2017
>>$ which openssl
/usr/bin/openssl
any ideas how to debug this further? I am lost...
ok I don't know what exactly caused the problem, but I got it working by changing the client
client = stripe.http_client.PycurlClient()
stripe.default_http_client = client
I think the requests package is the default. pycurl seems to work in my case...