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Plugin: python.d.plugin Module: tor


This collector monitors Tor bandwidth traffic .

It connects to the Tor control port to collect traffic statistics.

This collector is supported on all platforms.

This collector supports collecting metrics from multiple instances of this integration, including remote instances.

Default Behavior


If no configuration is provided the collector will try to connect to to detect a running tor instance.


The default configuration for this integration does not impose any limits on data collection.

Performance Impact

The default configuration for this integration is not expected to impose a significant performance impact on the system.


Metrics grouped by scope.

The scope defines the instance that the metric belongs to. An instance is uniquely identified by a set of labels.

Per Tor instance

These metrics refer to the entire monitored application.

This scope has no labels.


tor.trafficread, writeKiB/s


There are no alerts configured by default for this integration.



Required python module

The stem python library needs to be installed.

Required Tor configuration

Add to /etc/tor/torrc:

ControlPort 9051

For more options please read the manual.



The configuration file name for this integration is python.d/tor.conf.

You can edit the configuration file using the edit-config script from the Netdata config directory.

cd /etc/netdata 2>/dev/null || cd /opt/netdata/etc/netdata
sudo ./edit-config python.d/tor.conf


There are 2 sections:

  • Global variables
  • One or more JOBS that can define multiple different instances to monitor.

The following options can be defined globally: priority, penalty, autodetection_retry, update_every, but can also be defined per JOB to override the global values.

Additionally, the following collapsed table contains all the options that can be configured inside a JOB definition.

Every configuration JOB starts with a job_name value which will appear in the dashboard, unless a name parameter is specified.

Config options
update_everySets the default data collection frequency.5no
priorityControls the order of charts at the netdata dashboard.60000no
autodetection_retrySets the job re-check interval in seconds.0no
penaltyIndicates whether to apply penalty to update_every in case of failures.yesno
nameJob name. This value will overwrite the job_name value. JOBS with the same name are mutually exclusive. Only one of them will be allowed running at any time. This allows autodetection to try several alternatives and pick the one that
control_addrTor control IP address127.0.0.1no
control_portTor control port. Can be either a tcp port, or a path to a socket file.9051no
passwordTor control passwordno


Local TCP

A basic TCP configuration. local_addr is ommited and will default to

name: 'local'
control_port: 9051
password: <password> # if required

Local socket

A basic local socket configuration

name: 'local'
control_port: '/var/run/tor/control'
password: <password> # if required


Debug Mode

To troubleshoot issues with the tor collector, run the python.d.plugin with the debug option enabled. The output should give you clues as to why the collector isn't working.

  • Navigate to the plugins.d directory, usually at /usr/libexec/netdata/plugins.d/. If that's not the case on your system, open netdata.conf and look for the plugins setting under [directories].

    cd /usr/libexec/netdata/plugins.d/
  • Switch to the netdata user.

    sudo -u netdata -s
  • Run the python.d.plugin to debug the collector:

    ./python.d.plugin tor debug trace

Do you have any feedback for this page? If so, you can open a new issue on our netdata/learn repository.