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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)
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