Ryan Dale daler

## PWMSearch.py
"""
PWMSearch

Searches through a fasta sequence for the relevant Position Weight Matrices
from the Jaspar Database.

"""
from __future__ import division

from optparse import OptionParser

## .1.miniconda.md

      
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                dan-blanchard
                / .1.miniconda.md
            
            
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              December 11, 2019 22:38
            
              
                Quicker Travis builds that rely on numpy and scipy using Miniconda
              
          
    For ETS's SKLL project, we found out the hard way that Travis-CI's support for numpy and scipy is pretty abysmal. There are pre-installed versions of numpy for some versions of Python, but those are seriously out of date, and scipy is not there are at all. The two most popular approaches for working around this are to (1) build everything from scratch, or (2) use apt-get to install more recent (but still out of date) versions of numpy and scipy. Both of these approaches lead to longer build times, and with the second approach, you still don't have the most recent versions of anything. To circumvent these issues, we've switched to using Miniconda (Anaconda's lightweight cousin) to install everything.
A template for installing a simple Python package that relies on numpy and scipy using Miniconda is provided below. Since it's a common s

  
## jupyterTunnel
#!/bin/bash
# This is a little bash script to create a tunnel for running jupyter
# notebooks.
#
# You can run the script like so:
#
#   $ jupyterTunnel start remote1
#
# This will create an ssh tunnel on port 7000 to remote 1, and create a control
# socket 'jupyter-ctrl-socket' in the current working direcotry. To stop the
	"""
	PWMSearch

	Searches through a fasta sequence for the relevant Position Weight Matrices
	from the Jaspar Database.

	"""
	from __future__ import division

	from optparse import OptionParser
	#!/bin/bash
	# This is a little bash script to create a tunnel for running jupyter
	# notebooks.
	#
	# You can run the script like so:
	#
	# $ jupyterTunnel start remote1
	#
	# This will create an ssh tunnel on port 7000 to remote 1, and create a control
	# socket 'jupyter-ctrl-socket' in the current working direcotry. To stop the