Simple and easy-to-use library for executing shell commands saving data to the file system without re-executing already executed tasks.
Project description
Ey - Radically simple task execution in Python scripts
A super-simple library for performing stepwise batch tasks (implemented as shell commands, or python functions) that saves things to files, such that outputs from already finished tasks are not needlessly re-computed. See the below for an example.
Ey does not have a scheduler or central worker pool or anything like that. Instead you simply execute your tasks manually in a procedural way. This way task executions can easily be mixed with other procedural python code.
Ey can work as an alternative to full-blown workflow frameworks like Luigi or Airflow for cases when you just have a single python script, where you want to do a few batch steps before starting your interactive analysis, such as downloading datasets, unpacking them, preprocessing et cetera.
Ey is small (not much more than 100 lines of code), and has no external dependencies, meaning that you can even copy the implementation into your own code repos if you want to ensure maximum future reproducibility.
'Ey' what?
For anyeone left confused by the name, 'Ey' is urban slang
meaning things like "Hey", "Hi", "Oh" or even "Hey, let's".
It reflects how relaxed you can be while using this library, as it is so simple
that to execute a shell command, you can just go: "Ey, shell ... yada yada", or
more precisely: ey.shell('yada yada...')
:)
Prerequisites
- Ey is so far only tested on unix-like environments.
Installation
Install from the Python Package Index using pip:
pip install ey
Usage
Ey works by specifying either a shell command, or a python function, to
be executed, as the first argument to ey.shell()
or ey.func()
respectively.
In shell commands, you need to replace input and output file paths with
placeholders on the form of [i:inputname]
and [o:outputname:outputpath]
respectively. You will also need to provide dicts which specify the paths to
the inputs and outputs, as appropriate, by providing them to the optional
inputs
and outputs
parameters of ey.shell()
and ey.func()
. See the
example below for a concrete example.
Inputs should always be provided via the input
-parameter, while output paths
are easiest to provide inline in the command, in the respective placeholder.
Note that you can re-use input placeholder values to produce the output path.
So, for example, if you want to name your output the same as the input, but
with an extra .txt
extension, you can specify it like this in the command:
somecommand > [o:myoutput:[i:myinput].txt]
.
Removing file extensions
If you have an existing extension in the input that you want to remove, you can
do it by adding |%.actual-extension-here
in the input placeholder. So, if you
have an input myinput
with the path myfile.txt.gz
, you can reuse just the
myfile.txt
part by writing [i:myinput|%.gz]
, to remove the .gz
part.
Putting that inside an output placeholder, you could for example do: zcat [i:archivefile] > [o:unpacked:[i:archivefile|%.gz]]
, in order to name the
unpacked file the same as the archive, but without the .gz
extension.
Removing parent directories from paths
Often it is the case that the input path contains a long folder path that you
don't want to re-use when re-using the input filename. To clean the path from
the parent directory structure, you can add the |basename
modifier inside any
path placeholder. So, if you have an input myinput
with the path
some/directory/structure/file.txt.gz
, you can reuse just the myfile.txt
part
by writing [i:myinput|basename]
, to remove the some/directory/structure
part. Modifiers can be compbined, so for example, given that you have an archive
file in another directory named some/directory/structure
, you could do
the following to extract the archive, removing the .gz
file extension and
putting the extracted file in a new directory named other-directory
:
zcat [i:archivefile] > other-directory/[o:unpacked:[i:archivefile|basename|%.gz]]
See the example below for how to use some of this in practice!
Example
Below is a small example that downloads a gzipped text file (in the so called FASTA format), un-gzips it, and then calculates the number of A:s, T:s, G:s and C:s and calculates the fraction of G and C:s in relation to all A, T, G, C:s (the so-called GC-fraction measure for DNA).
The two first tasks are done by executing shell commands, and the second one using a python function.
import ey
# ------------------------------------------------------------------------
# Download a gzipped fasta file and save it as chrmt.fa.gz
# ------------------------------------------------------------------------
url = 'ftp://ftp.ensembl.org/pub/release-100/fasta/'+
'homo_sapiens/dna/Homo_sapiens.GRCh38.dna.chromosome.MT.fa.gz'
download_task = ey.shell('wget -O [o:gz:chrmt.fa.gz] '+url)
# ------------------------------------------------------------------------
# Un-GZip the file, into a file named chrmt.fa
# ------------------------------------------------------------------------
ungzip_task = ey.shell('zcat [i:gz] > [o:fa:[i:gz|%.gz]]',
inputs={'gz': download_task.outputs['gz']})
# ------------------------------------------------------------------------
# Count the fraction of G+C, vs G+C+A+T
# ------------------------------------------------------------------------
# A function for Count GC fraction in DNA
def count_gcfrac_func(task):
gc_count = 0
at_count = 0
with open(task.inputs['fa']) as infile:
for line in infile:
if line[0] == '>':
continue
for char in line:
if char in ['A', 'T']:
at_count += 1
elif char in ['G', 'C']:
gc_count += 1
gc_fraction = gc_count/(gc_count+at_count)
with open(task.outputs['gcfrac'], 'w') as outfile:
outfile.write(str(gc_fraction) + '\n')
# Execute the function
count_task = ey.func(count_gcfrac_func,
inputs={'fa': ungzip_task.outputs['fa']},
outputs={'gcfrac': 'gcfrac.txt'})
Add this code to a file named gcfrac.py
and run it with:
python gcfrac.py
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