1 files changed, 62 insertions, 0 deletions
diff --git a/gn2/wqflask/gsearch.py b/gn2/wqflask/gsearch.py
new file mode 100644
index 00000000..cad6db94
--- /dev/null
+++ b/gn2/wqflask/gsearch.py
@@ -0,0 +1,62 @@
+from urllib.parse import urlencode, urljoin
+
+from pymonad.maybe import Just, Maybe
+from pymonad.tools import curry
+import requests
+
+from gn3.monads import MonadicDict
+from gn2.utility.hmac import hmac_creation
+from gn2.utility.tools import GN3_LOCAL_URL
+from gn2.base import webqtlConfig
+
+# KLUDGE: Due to the lack of pagination, we hard-limit the maximum
+# number of search results.
+MAX_SEARCH_RESULTS = 10000
+
+class GSearch:
+    def __init__(self, kwargs):
+        if ("type" not in kwargs) or ("terms" not in kwargs):
+            raise ValueError
+        self.type = kwargs["type"]
+        self.terms = kwargs["terms"]
+
+        # FIXME: Handle presentation (that is, formatting strings for
+        # display) in the template rendering, not when retrieving
+        # search results.
+        chr_mb = curry(2, lambda chr, mb: f"Chr{chr}: {mb:.6f}")
+        format3f = lambda x: f"{x:.3f}"
+        hmac = curry(3, lambda trait_name, dataset, data_hmac: f"{trait_name}:{dataset}:{data_hmac}")
+        convert_lod = lambda x: x / 4.61
+        self.trait_list = []
+        for i, trait in enumerate(requests.get(
+                urljoin(GN3_LOCAL_URL, "/api/search?" + urlencode({"query": self.terms,
+                                                                   "type": self.type,
+                                                                   "per_page": MAX_SEARCH_RESULTS}))).json()):
+            trait = MonadicDict(trait)
+            trait["index"] = Just(i)
+            trait["location_repr"] = (Maybe.apply(chr_mb)
+                                      .to_arguments(trait.pop("chr"), trait.pop("mb")))
+            trait["LRS_score_repr"] = trait.pop("lrs").map(convert_lod).map(format3f)
+            trait["additive"] = trait["additive"].map(format3f)
+            trait["mean"] = trait["mean"].map(format3f)
+            trait["max_lrs_text"] = (Maybe.apply(chr_mb)
+                                     .to_arguments(trait.pop("geno_chr"), trait.pop("geno_mb")))
+            if self.type == "gene":
+                trait["hmac"] = (Maybe.apply(hmac)
+                                 .to_arguments(trait['name'], trait['dataset'], Just(hmac_creation(f"{trait['name']}:{trait['dataset']}"))))
+            elif self.type == "phenotype":
+                trait["display_name"] = trait["name"]
+                inbredsetcode = trait.pop("inbredsetcode")
+                if inbredsetcode.map(len) == Just(3):
+                    trait["display_name"] = (Maybe.apply(
+                        curry(2, lambda inbredsetcode, name: f"{inbredsetcode}_{name}"))
+                                             .to_arguments(inbredsetcode, trait["name"]))
+
+                trait["hmac"] = (Maybe.apply(hmac)
+                                 .to_arguments(trait['name'], trait['dataset'], Just(hmac_creation(f"{trait['name']}:{trait['dataset']}"))))
+                trait["authors_display"] = (trait.pop("authors").map(
+                    lambda authors:
+                    ", ".join(authors[:2] + ["et al."] if len(authors) >=2 else authors)))
+                trait["pubmed_text"] = trait["year"].map(str)
+            self.trait_list.append(trait.data)
+        self.trait_count = len(self.trait_list)