A Python (2 and 3) wrapper for fplll.

>>> from fpylll import *

>>> A = IntegerMatrix(50, 50)
>>> A.randomize("ntrulike", bits=50, q=127)
>>> A[0].norm()
3564748886669202.5

>>> M = GSO.Mat(A)
>>> M.update_gso()
>>> M.get_mu(1,0)
0.815748944429783

>>> L = LLL.Reduction(M)
>>> L()
>>> M.get_mu(1,0)
0.41812865497076024
>>> A[0].norm()
24.06241883103193

The basic BKZ algorithm can be implemented in about 60 pretty readable lines of Python code (cf. simple_bkz.py).

fpylll relies on the following C/C++ libraries:

• GMP or MPIR for arbitrary precision integer arithmetic.
• MPFR for arbitrary precision floating point arithmetic.
• QD for double double and quad double arithmetic (optional).
• fpLLL for pretty much everything.

fpylll also relies on

• Cython for linking Python and C/C++.
• cysignals for signal handling such as interrupting C++ code.
• py.test for testing Python.
• flake8 for linting.

We also suggest

• IPython for interacting with Python
• Numpy for numerical computations (e.g. with Gram-Schmidt values)

We recommend virtualenv for isolating Python build environments and virtualenvwrapper to manage virtual environments.

1. Create a new virtualenv and activate it:

   $ virtualenv env
   $ source ./env/bin/activate

We indicate active virtualenvs by the prefix (fpylll).

2. Install the required libraries – GMP or MPIR and MPFR – if not available already. You may also want to install QD.

3. Install fplll:

   $ (fpylll) ./install-dependencies.sh $VIRTUAL_ENV

4. Then, execute:

   $ (fpylll) pip install Cython
   $ (fpylll) pip install -r requirements.txt

to install the required Python packages (see above).

5. If you are so inclined, run:

   $ (fpylll) pip install -r suggestions.txt

to install suggested Python packages as well (optional).

6. Build the Python extension:

   $ (fpylll) export PKG_CONFIG_PATH="$VIRTUAL_ENV/lib/pkgconfig:$PKG_CONFIG_PATH"
   $ (fpylll) python setup.py build_ext
   $ (fpylll) python setup.py install

7. To run fpylll, you will need to:

   $ (fpylll) export LD_LIBRARY_PATH="$VIRTUAL_ENV/lib"

so that Python can find fplll and friends.

8. Start Python:

   $ (fpylll) ipython

To reactivate the virtual environment later, simply run:

$ source ./env/bin/activate

Note that you can also patch activate to set LD_LIBRRY_PATH. For this, add:

### LD_LIBRARY_HACK
_OLD_LD_LIBRARY_PATH="$LD_LIBRARY_PATH"
LD_LIBRARY_PATH="$VIRTUAL_ENV/lib:$LD_LIBRARY_PATH"
export LD_LIBRARY_PATH
### END_LD_LIBRARY_HACK

### PKG_CONFIG_HACK
_OLD_PKG_CONFIG_PATH="$PKG_CONFIG_PATH"
PKG_CONFIG_PATH="$VIRTUAL_ENV/lib/pkgconfig:$PKG_CONFIG_PATH"
export PKG_CONFIG_PATH
### END_PKG_CONFIG_HACK

towards the end and:

### LD_LIBRARY_HACK
if ! [ -z ${_OLD_LD_LIBRARY_PATH+x} ] ; then
    LD_LIBRARY_PATH="$_OLD_LD_LIBRARY_PATH"
    export LD_LIBRARY_PATH
    unset _OLD_LD_LIBRARY_PATH
fi
### END_LD_LIBRARY_HACK

### PKG_CONFIG_HACK
if ! [ -z ${_OLD_PKG_CONFIG_PATH+x} ] ; then
    PKG_CONFIG_PATH="$_OLD_PKG_CONFIG_PATH"
    export PKG_CONFIG_PATH
    unset _OLD_PKG_CONFIG_PATH
fi
### END_PKG_CONFIG_HACK

in the deactivate function in the activate script.

To contribute to fpylll, clone this repository, commit your code on a separate branch and send a pull request. Please write tests for your code. You can run them by calling:

$ (fpylll) py.test

from the top-level directory which runs all tests in tests/test_*.py. We run flake8 on every commit automatically, In particular, we run:

$ (fpylll) flake8 --max-line-length=120 --max-complexity=16 --ignore=E22,E241 src

Note that fpylll supports Python 2 and 3. In particular, tests are run using Python 2.7 and 3.5. See .travis.yml for details on automated testing.

We copied a decent bit of code over from Sage, mostly from it’s fpLLL interface.

fpylll is licensed under the GPLv2+.