agartland/fishersapi

A package that for applying a fast implementation of Fisher's exact test to observations in a pandas DataFrame.

fishersapi's Issues

Tricky conda install: working YAML attached

Hello!

Thanks so much for putting all of the effort into re-factoring tcrdist2! The pre-processing workflows are a lovely addition as well. While trying to follow the default installation instructions using conda, I ran into several minor issues. The first is that the pip install calls for fishersapi and fisher both kept failing out repeatedly. To circumvent this, I put together the following conda env which can be used with conda create -f tcrdist2.yaml:

name: tcrdist2
channels:
  - conda-forge
  - bioconda
  - defaults
dependencies:
  - _libgcc_mutex=0.1=conda_forge
  - _openmp_mutex=4.5=0_gnu
  - ca-certificates=2019.11.28=hecc5488_0
  - certifi=2019.11.28=py38_0
  - cycler=0.10.0=py_2
  - dbus=1.13.6=he372182_0
  - expat=2.2.9=he1b5a44_2
  - fisher=0.1.9=py38hc1659b7_0
  - fontconfig=2.13.1=h86ecdb6_1001
  - freetype=2.10.0=he983fc9_1
  - future=0.18.2=py38_0
  - gettext=0.19.8.1=hc5be6a0_1002
  - glib=2.58.3=py38h6f030ca_1002
  - gst-plugins-base=1.14.5=h0935bb2_1
  - gstreamer=1.14.5=h36ae1b5_1
  - icu=64.2=he1b5a44_1
  - joblib=0.14.1=py_0
  - jpeg=9c=h14c3975_1001
  - kiwisolver=1.1.0=py38hc9558a2_0
  - ld_impl_linux-64=2.33.1=h53a641e_8
  - libblas=3.8.0=14_openblas
  - libcblas=3.8.0=14_openblas
  - libclang=9.0.1=default_hde54327_0
  - libffi=3.2.1=he1b5a44_1006
  - libgcc-ng=9.2.0=h24d8f2e_2
  - libgfortran-ng=7.3.0=hdf63c60_4
  - libgomp=9.2.0=h24d8f2e_2
  - libiconv=1.15=h516909a_1005
  - liblapack=3.8.0=14_openblas
  - libllvm9=9.0.1=hc9558a2_0
  - libopenblas=0.3.7=h5ec1e0e_6
  - libpng=1.6.37=hed695b0_0
  - libstdcxx-ng=9.2.0=hdf63c60_2
  - libuuid=2.32.1=h14c3975_1000
  - libxcb=1.13=h14c3975_1002
  - libxkbcommon=0.9.1=hebb1f50_0
  - libxml2=2.9.10=hee79883_0
  - matplotlib=3.1.2=py38_1
  - matplotlib-base=3.1.2=py38h250f245_1
  - ncurses=6.1=hf484d3e_1002
  - nspr=4.24=he1b5a44_0
  - nss=3.47=he751ad9_0
  - numpy=1.17.5=py38h95a1406_0
  - openssl=1.1.1d=h516909a_0
  - pandas=1.0.0=py38hb3f55d8_0
  - patsy=0.5.1=py_0
  - pcre=8.43=he1b5a44_0
  - pip=20.0.2=py38_1
  - pthread-stubs=0.4=h14c3975_1001
  - pyparsing=2.4.6=py_0
  - pyqt=5.12.3=py38hcca6a23_1
  - python=3.8.1=h357f687_2
  - python-dateutil=2.8.1=py_0
  - pytz=2019.3=py_0
  - qt=5.12.5=hd8c4c69_1
  - readline=8.0=hf8c457e_0
  - scikit-learn=0.22.1=py38hcdab131_1
  - scipy=1.4.1=py38h921218d_0
  - seaborn=0.9.0=py_2
  - setuptools=45.1.0=py38_0
  - six=1.14.0=py38_0
  - sqlite=3.30.1=hcee41ef_0
  - statsmodels=0.11.0=py38h516909a_0
  - tk=8.6.10=hed695b0_0
  - tornado=6.0.3=py38h516909a_0
  - wheel=0.34.2=py38_0
  - xorg-libxau=1.0.9=h14c3975_0
  - xorg-libxdmcp=1.1.3=h516909a_0
  - xz=5.2.4=h14c3975_1001
  - zlib=1.2.11=h516909a_1006
  - pip:
    - fishersapi==0.1.dev0
    - parasail==1.1.19
    - pyqt5-sip==4.19.18
    - pyqtwebengine==5.12.1
    - tcrdist2==2.0.dev0
prefix: /path/to/anaconda3/envs/tcrdist2

I hope this will help other conda users get off the ground and running quickly!