python-bladerf 1.4.0

This is a wrapper for bladerf.

python_bladerf

python_bladerf is a cython wrapper for bladerf. It also contains some additional tools.

Before installing python_bladerf library, you must have bladerf host software installed. Because this library uses dynamic linking with an existing library file. Minimum libbladeRF version: 2.6.0, FX3 version: 2.6.0, FPGA version: 0.16.0!

For windows users please use additional steps to install python_bladerf You can install this library using

pip install git+https://github.com/GvozdevLeonid/python_bladerf.git

If your bladerf files are in non-standard paths and during installation the python_bladerf cannot find libbladeRF.h and bladeRF2.h or the library files, you can specify the paths via environment variables

LINUX/MACOS:
export PYTHON_BLADERF_CFLAGS=path_to_libbladeRF.h and bladeRF2.h
export PYTHON_BLADERF_LDFLAGS=path_to_libbladerf.(so, dylib)
WINDOWS:
set PYTHON_BLADERF_INCLUDE_PATH=path_to_libbladeRF.h and bladeRF2.h
set PYTHON_BLADERF_LIB_PATH=path_to_libbladerf.dll

If you notice smeared frequencies in sweep mode please increase the time between sweeps. export pybladerf_sweep_await_time=1.5-3 or more await_time is the delay time between different frequencies in milliseconds

Requirements:

• Numpy>=2.2.1
• Cython>=3.1.0,<3.2
• Scipy (optional, for faster work)
• pyFFTW (optional, for faster work)
• pyjnius and android (only for android)

bladerf:

The library supports all bladerf2 functions, some of the functions can also work on the first versions. If there is a demand for full support of the first version, I will add it.

pybladerf tools:

• pybladerf_info.py - Reading information about found devices.
• pybladerf_sweep.pyx - a function that allows you to obtain a sweep over a given frequency range (same as hackrf_sweep)
• pybladerf_transfer.pyx - a function that allows you to record and play back samples (np.complex64)

usage

usage: python_bladerf [-h] {info, sweep, transfer} ...

python_bladerf is a Python wrapper for libbladerf. It also contains some additional tools.

options:
  -h, --help    show this help message and exit

Available commands:
  {info,sweep,transfer}
    info        Read device information from Bladerf such as serial number and FPGA version.
    sweep       Spectrum analyzer.
    transfer    Send and receive signals using BladeRF. Input/output files consist of complex64 quadrature samples.

usage: python_bladerf info [-h] [-f] [-s]

options:
  -h, --help            show this help message and exit
  -f, --full            show full info
  -s, --serial_numbers  show only founded serial_numbers

usage: python_bladerf sweep [-h] [-d] [-f] [-g] [-w] [-c] [-1] [-N] [-o] [-B] [-S] [-s] [-b] [-r]

options:
  -h, --help  show this help message and exit
  -d          serial number of desired BladeRF
  -f          freq_min:freq_max. minimum and maximum frequencies in MHz start:stop or start1:stop1,start2:stop2. Default
  -g          RX gain, -15 - 60dB, 1dB steps
  -w          FFT bin width (frequency resolution) in Hz
  -c          RX channel. which channel to use (0, 1). Default is 0
  -1          one shot mode. If specified = Enable
  -N          Number of sweeps to perform
  -o          oversample. If specified = Enable
  -B          binary output. If specified = Enable
  -S          sweep style ("L" - LINEAR, "I" - INTERLEAVED). Default is INTERLEAVED
  -s          sample rate in MHz  (0.5 MHz - 122 MHz). Default is 61. To use a sample rate higher than 61, specify oversample
  -b          baseband filter bandwidth in MHz (0.2 MHz - 56 MHz). Default .75 * sample rate
  -r          filename. output file

python_bladerf transfer [-h] [-d] [-r] [-t] [-f] [-p] [-c] [-g] [-N] [-R] [-s] -[b] [-H] -[o]

options:
  -d                  serial number of desired BladeRF
  -r                  <filename> receive data into file (use "-" for stdout)
  -t                  <filename> transmit data from file (use "-" for stdout)
  -f, --freq_hz       frequency in Hz (0MHz to 6000MHz supported). Default is 900MHz
  -p                  antenna port power. If specified = Enable
  -c                  RX or TX channel. which channel to use (0, 1). Default is 0
  -g                  RX or TX gain, RX: -15 - 60dB, 1dB steps, TX: -24 - 66 dB, 1dB steps
  -N                  number of samples to transfer (default is unlimited)
  -R                  repeat TX mode. Fefault is off
  -s                  sample rate in MHz  (0.5 MHz - 122 MHz). Default is 61. To use a sample rate higher than 61, specify oversample'
  -b                  baseband filter bandwidth in MHz (0.2 MHz - 56 MHz). Default .75 * sample rate
  -H                  synchronize RX/TX to external trigger input
  -o                  oversample. If specified = Enable

Android

This library can work on android. To do this, go to the android directory and download 3 recipes for p4a.

buildozer.spec

requirements = python3,android,pyjnius,numpy,libusb,libbladerf,python_bladerf
p4a.local_recipes = path_to_pythonforandroidrecipes_folder

Your recipes folder should contain at least the following files:

pythonforandroidrecipes/
    __init__.py
    libusb/
        __init__.py
    python_bladerf/
        __init__.py
    libbladerf/
        __init__.py
        bladerf_android.patch
        pre_install.cmake
        jni/
            Android.mk
            Application.mk
            libbladerf.mk
            libad936x.mk
        src/
            libusb.c
            log.c

Examples

Please use the original bladerf documentation

Installation on Windows

To install python_bladerf, you must first install the BladeRF software. Official installation instructions are available on the BladeRF documentation site. Alternatively, you can download the ZIP archive from the Releases tab of this repository. Extract the archive and move its contents to the standard location: C:\Program Files\BladeRF

The BladeRF directory should contain the following subfolders and files:

├── include
│ └── libbladeRF.h
│ └── bladeRF2.h
│ └── bladeRF1.h
│ └── pthread.h
├── lib
│ └── bladeRF.dll
│ └── bladeRF.lib ← for MSVC
│ └── libbladeRF.a ← for MinGW
│ └── libusb-1.0.dll
│ └── pthreadVC2.dll
│ └── msvcr100.dll

In addition, the archive includes other required DLLs and dependencies to ensure proper operation of HackRF on Windows. libusb-1.0.dll pthreadVC2.dll msvcr100.dll

If you install bladerf yourself or via another path, set the following environment variables

MSVC | MinGW:

  set PYTHON_BLADERF_INCLUDE_PATH={path to .h file directory}
  set PYTHON_BLADERF_LIB_PATH={path to .dll and .lib file directory}
  set BLADERF_LIB_DIR="{path to .dll and .lib file directory}"