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libtorrent python binding

building

Building the libtorrent python bindings will produce a shared library (DLL) which is a python module that can be imported in a python program.

building using boost build (windows)

Download and install Visual C++ 2015 Build Tools

Download Boost libraries Extract it to c:/Libraries/boost_1_63_0 and create these environmental vars:

  1. BOOST_BUILD_PATH: "c:/Libraries/boost_1_63_0/tools/build/"
  2. BOOST_ROOT: "c:/Libraries/boost_1_63_0/"

Navigate to BOOST_ROOT, execute "bootstrap.bat" and add to the path "c:/Libraries/boost_1_63_0/tools/build/src/engine/bin.ntx86/"

Move the file user-config.jam from %BOOST_BUILD_PATH%/example/ to %BOOST_BUILD_PATH%/user-config.jam and add this at the end:

using msvc : 14.0 : : /std:c++11 ;
using python : 3.5 : C:/Users/<UserName>/AppData/Local/Programs/Python/Python35 : C:/Users/<UserName>/AppData/Local/Programs/Python/Python35/include : C:/Users/<UserName>/AppData/Local/Programs/Python/Python35/libs ;

(change the python path for yours)

Navigate to bindings/python and execute::
python setup.py build --bjam

Note: If you are using 64 bits python you should edit setup.py and add this to the b2 command: address-model=64

This will create the file libtorrent.pyd inside build/lib/ that contains the binding.

building using boost build (others)

To set up your build environment, you need to add some settings to your $BOOST_BUILD_PATH/user-config.jam.

A similar line to this line should be in the file (could be another python version):

#using python : 2.3 ;

Uncomment it and change it with the version of python you have installed or want to use. If you've installed python in a non-standard location, you have to add the prefix path used when you installed python as a second option. Like this:

using python : 2.6 : /usr/bin/python2.6 : /usr/include/python2.6 : /usr/lib/python2.6 ;

The bindings require at least python version 2.2.

For more information on how to install and set up boost-build, see the building libtorrent section.

Once you have boost-build set up, you cd to the bindings/python directory and invoke bjam with the appropriate settings. For the available build variants, see libtorrent build options.

For example:

$ bjam dht-support=on link=static

On Mac OS X, this will produce the following python module:

bin/darwin-4.0/release/dht-support-on/link-static/logging-none/threading-multi/libtorrent.so

using libtorrent in python

The python interface is nearly identical to the C++ interface. Please refer to the library reference. The main differences are:

asio::tcp::endpoint
The endpoint type is represented as a tuple of a string (as the address) and an int for the port number. E.g. ("127.0.0.1", 6881) represents the localhost port 6881.
lt::time_duration
The time duration is represented as a number of seconds in a regular integer.

The following functions takes a reference to a container that is filled with entries by the function. The python equivalent of these functions instead returns a list of entries.

  • torrent_handle::get_peer_info
  • torrent_handle::file_progress
  • torrent_handle::get_download_queue
  • torrent_handle::piece_availability

create_torrent::add_node() takes two arguments, one string and one integer, instead of a pair. The string is the address and the integer is the port.

session::apply_settings() accepts a dictionary with keys matching the names of settings in settings_pack. When calling apply_settings, the dictionary does not need to have every settings set, keys that are not present are not updated.

To get a python dictionary of the settings, call session::get_settings.

Retrieving session statistics in Python is more convenient than that in C++. The statistics are stored as an array in session_stats_alert, which will be posted after calling post_session_stats() in the session object. In order to interpret the statistics array, in C++ it is required to call session_stats_metrics() to get the indices of these metrics, while in Python it can be done using session_stats_alert.values["NAME_OF_METRIC"], where NAME_OF_METRIC is the name of a metric.

For an example python program, see client.py in the bindings/python directory.

A very simple example usage of the module would be something like this: