[#69] Added begging of function for connection all together, decorato…

…r for params and func to get regex which need to be fixed to concatenate lists

src/shmir/data/models.py

@@ -90,6 +90,10 @@ def generate_regexp_all(cls):
 
         db_session.commit()
 
+    @classmethod
+    def get_all_regexp(cls):
+        return [bone.regex for bone in db_session.query(cls).all()]
+
     @classmethod
     def get_mirna(cls, name=None):
         if name:

src/shmir/decorators.py

@@ -10,6 +10,7 @@
 import json
 
 from shmir.utils import json_error
+from shmir.designer import errors
 
 
 def require_json(require_data=True, required_data_words=None,
@@ -63,3 +64,15 @@ def jsonify(f):
     def wrapped(*args, **kwargs):
         return dumps(f(*args, **kwargs))
     return wrapped
+
+
+def param(name, g_type, description, default=None, required=False):
+    def wrapper(func):
+        def wrapped(**kwargs):
+            if not kwargs[name]:
+                if required:
+                    raise errors.InputException('{} is required'.format(name))
+                kwargs[name] = g_type(default)
+            return func(**kwargs)
+        return wrapped
+    return wrapper

src/shmir/designer/connection.py

@@ -0,0 +1,45 @@
+from shmir import cache
+from shmir.data import (
+    models,
+    ncbi_api,
+)
+from shmir.decorators import param
+from shmir.designer.validators import calculate_gc_content
+
+
+def create_cache_key(*args):
+    return ':'.join(args)
+
+
+@param('transcript_name', str, 'Name of transcript', required=True)
+@param('min_gc', int, 'Minimum of GC content', default=40)
+@param('max_gc', int, 'Maximum of GC content', default=60)
+@param('max_offtarget', int, 'Maximum offtarget, minimum is 0', default=10)
+@param('mirna_name', str, 'miRNA name of Backbone', default=None)
+@param(
+    'stymulators', bool, 'Bool if immuno stimulators are wanted', default=False
+)
+def connection(
+    transcript_name, min_gc, max_gc, max_offtarget, mirna_name, stymulators
+):
+    sequence = '?'
+    cg_content = calculate_gc_content(sequence)
+
+    cache_key = create_cache_key(
+        transcript_name,
+        cg_content,
+        mirna_name,
+        max_offtarget,
+        str(stymulators)
+    )
+
+    sequence = cache.get(cache_key)  # TODO: check if get take cache by key xD
+
+    if not sequence:
+        sequence = ncbi_api.get_mRNA(transcript_name)
+
+    backbones = models.Backbone.get_mirna(mirna_name)
+    if not isinstance(backbones, list):
+        backbones = [backbones]
+
+    all_regex = models.Backbone.get_all_regexp()