Remove scripts for now

script/mhcflurry-class1-web-server.py

-#!/usr/bin/env python
-
-# Copyright (c) 2016. Mount Sinai School of Medicine
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-from __future__ import (
-    print_function,
-    division,
-    absolute_import,
-)
-import argparse
-
-from bottle import post, request, run, get
-
-from mhcflurry.common import (
-    split_uppercase_sequences,
-    split_allele_names,
-)
-from mhcflurry.predict import predict, supported_alleles
-
-
-parser = argparse.ArgumentParser()
-
-parser.add_argument("--host", default="0.0.0.0")
-parser.add_argument("--port", default=80, type=int)
-parser.add_argument("--debug", default=False, action="store_true")
-
-
-@post('/')
-def get_binding_value():
-    peptides_string = request.forms.get('peptide')
-    if peptides_string is None:
-        return "ERROR: no peptide given"
-    peptides_list = split_uppercase_sequences(peptides_string)
-    alleles_string = request.forms.get('allele')
-    if alleles_string is None:
-        return "ERROR: no allele given"
-    alleles_list = split_allele_names(alleles_string)
-    try:
-        result_df = predict(alleles=alleles_list, peptides=peptides_list)
-    except ValueError as e:
-        return "ERROR: %s" % e.args[0]
-    return result_df.to_csv(sep="\t", index=False, float_format="%0.4f")
-
-
-@get('/alleles')
-def get_supported_alleles():
-    peptide_lengths = "8,9,10,11,12"
-    strings = [
-        "%s\t%s" % (allele, peptide_lengths)
-        for allele in supported_alleles()
-    ]
-    return "\n".join(strings)
-
-
-if __name__ == "__main__":
-    args = parser.parse_args()
-    run(host=args.host, port=args.port, debug=args.debug, server="cherrypy")

script/mhcflurry-predict-class1.py

-#!/usr/bin/env python
-
-# Copyright (c) 2016. Mount Sinai School of Medicine
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-
-from __future__ import (
-    print_function,
-    division,
-    absolute_import,
-)
-import argparse
-
-from mhcflurry.common import (
-    parse_int_list,
-    split_uppercase_sequences,
-    split_allele_names,
-)
-from mhcflurry.predict import predict
-from six import string_types
-
-parser = argparse.ArgumentParser()
-
-parser.add_argument(
-    "--mhc",
-    default="HLA-A*02:01",
-    type=split_allele_names,
-    help="Comma separated list of MHC alleles")
-
-parser.add_argument(
-    "--sequence",
-    required=True,
-    type=split_uppercase_sequences,
-    help="Comma separated list of protein sequences")
-
-parser.add_argument(
-    "--fasta-file",
-    help="FASTA file of protein sequences to chop up into peptides")
-
-parser.add_argument(
-    "--peptide-lengths",
-    default=[9],
-    type=parse_int_list,
-    help="Comma separated list of peptide length, e.g. 8,9,10,11")
-
-if __name__ == "__main__":
-    args = parser.parse_args()
-    if len(args.peptide_lengths) == 0:
-        raise ValueError("Must specify at least one peptide length")
-
-    long_sequences = args.sequence
-    if isinstance(long_sequences, string_types):
-        long_sequences = [long_sequences]
-
-    peptides = []
-    for peptide_length in args.peptide_lengths:
-        for long_sequence in long_sequences:
-            total_length = len(long_sequence)
-            for i in range(total_length - peptide_length):
-                peptides.append(long_sequence[i:i + peptide_length])
-    print("Running predictor over %d sub-sequences" % len(peptides))
-    df = predict(alleles=args.mhc, peptides=peptides)
-    print(df.to_csv(sep="\t", index=False), end="")

setup.py

@@ -88,8 +88,4 @@ if __name__ == '__main__':
         ],
         long_description=readme,
         packages=['mhcflurry', 'mhcflurry.class1_allele_specific'],
-        scripts=[
-            "script/mhcflurry-predict-class1.py",
-            "script/mhcflurry-class1-web-server.py",
-        ],
     )