def nemesis():
search = Search()
if search.validate_on_submit():
results = Superheroes.query.filter(
Superheroes.nemesis == search.nemesis.data.upper()).all()
p1 = 0
p2 = 0
p3 = 0
p1id = ""
p2id = ""
p3id = ""
for x in results:
p1 = int(x.__dict__['p1'])
p1id = Powers.query.filter(Powers.id == p1).first()
x.__dict__['p1'] = p1id.power
p2 = int(x.__dict__['p2'])
p2id = Powers.query.filter(Powers.id == p2).first()
x.__dict__['p2'] = p2id.power
p3 = int(x.__dict__['p3'])
p3id = Powers.query.filter(Powers.id == p3).first()
x.__dict__['p3'] = p3id.power
return render_template("show.html", superherodata=results)
return render_template("searchnemesis.html", search=search)
#publisher, name, alterego, power, team, sidekick, nemesis
def search():
form = Search()
if form.validate_on_submit():
search = lookup(form.search.data)
return render_template("search.html", form=form, search=search)
return render_template("search.html", form=form)
def name():
search = Search()
if search.validate_on_submit():
print(search.name.data)
results = Superheroes.query.filter(
Superheroes.name == search.name.data.upper()).all()
return render_template("show.html", superherodata=results)
return render_template("searchname.html", search=search)
def power():
search = Search()
if search.validate_on_submit():
#pquery=Powers.query.filter(Powers.power.in_(search.power.data.upper())).first()
pquery = Powers.query.filter(
Powers.power == search.power.data.upper()).first()
p1q = Superheroes.query.filter(Superheroes.p1 == pquery.id).all()
p2q = Superheroes.query.filter(Superheroes.p2 == pquery.id).all()
p3q = Superheroes.query.filter(Superheroes.p3 == pquery.id).all()
#results=Superheroes.query.filter(Superheroes.p1==pquery.id, Superheroes.p2==pquery.id, Superheroes.p3==pquery.id).all()
p1 = 0
p2 = 0
p3 = 0
p1id = ""
p2id = ""
p3id = ""
for x in p1q:
p1 = int(x.__dict__['p1'])
p1id = Powers.query.filter(Powers.id == p1).first()
x.__dict__['p1'] = p1id.power
p2 = int(x.__dict__['p2'])
p2id = Powers.query.filter(Powers.id == p2).first()
x.__dict__['p2'] = p2id.power
p3 = int(x.__dict__['p3'])
p3id = Powers.query.filter(Powers.id == p3).first()
x.__dict__['p3'] = p3id.power
for x in p2q:
p1 = int(x.__dict__['p1'])
p1id = Powers.query.filter(Powers.id == p1).first()
x.__dict__['p1'] = p1id.power
p2 = int(x.__dict__['p2'])
p2id = Powers.query.filter(Powers.id == p2).first()
x.__dict__['p2'] = p2id.power
p3 = int(x.__dict__['p3'])
p3id = Powers.query.filter(Powers.id == p3).first()
x.__dict__['p3'] = p3id.power
for x in p3q:
p1 = int(x.__dict__['p1'])
p1id = Powers.query.filter(Powers.id == p1).first()
x.__dict__['p1'] = p1id.power
p2 = int(x.__dict__['p2'])
p2id = Powers.query.filter(Powers.id == p2).first()
x.__dict__['p2'] = p2id.power
p3 = int(x.__dict__['p3'])
p3id = Powers.query.filter(Powers.id == p3).first()
x.__dict__['p3'] = p3id.power
return render_template("showpowers.html", p1=p1q, p2=p2q, p3=p3q)
return render_template("searchpower.html", search=search)
def sidekick():
search = Search()
if search.validate_on_submit():
results = Superheroes.query.filter(
Superheroes.sidekick == search.sidekick.data.upper()).all()
p1 = 0
p2 = 0
p3 = 0
p1id = ""
p2id = ""
p3id = ""
for x in results:
p1 = int(x.__dict__['p1'])
p1id = Powers.query.filter(Powers.id == p1).first()
x.__dict__['p1'] = p1id.power
p2 = int(x.__dict__['p2'])
p2id = Powers.query.filter(Powers.id == p2).first()
x.__dict__['p2'] = p2id.power
p3 = int(x.__dict__['p3'])
p3id = Powers.query.filter(Powers.id == p3).first()
x.__dict__['p3'] = p3id.power
return render_template("show.html", superherodata=results)
return render_template("searchsidekick.html", search=search)
def fileResult(process_id, ref_genome, file_name):
form = Search()
intervalform = intervalForm()
fileform = fileForm(CombinedMultiDict((request.files, request.form)))
if request.method == 'POST' and fileform.validate_on_submit():
filename = secure_filename(fileform.file.data.filename)
# check if the post request has the file part
if 'file' not in request.files:
return home("No selected file")
result = request.form
ref_genome = result['reference genome']
file = request.files['file']
if file.filename == '':
return home("No selected file")
if ref_genome == "":
return home("No reference genome")
if file:
file_name = secure_filename(file.filename)
process_id = str(random.randint(0, sys.maxsize))
file.save(app.config["SERVER_PATH"] + "/uploads/" +
str(process_id) + file_name.split(".", 1)[-1])
return redirect("/search/{}/{}/{}".format(process_id, ref_genome,
file_name))
out = utility.file_search(process_id, ref_genome, file_name)
print("INITIATING SEARCH")
start_total = time.time()
start_task = time.time()
if isinstance(out, str): # parsing error occured
return home(out)
else:
result_df = out
end_task = time.time()
print("#####")
print("SEARCH COMPLETED ({} seconds)".format(end_task - start_task))
# make array of links for pages
start_task = time.time()
# out = utility.retrieve_metadata(ref_genome) #generic function to handle data information gathering
# if isinstance(out, str): # parsing error occured
# return home(out)
# else:
# metadata_df = out
# result_df = pd.merge(result_df,
# metadata_df,
# left_on ="name",
# right_on ="NAME",
# how ="left")
# print(result_df)
result_df.sort_values("overlaps", inplace=True)
end_task = time.time()
print("########")
print("DATA SOURCE INFOMATION COLLECTED ({} seconds)".format(end_task -
start_task))
#Pagination
# determining results displayed on current page
current_page = 1
number_pages = int(math.ceil(len(result_df.index) / 10.0))
if current_page < 7 or number_pages < 10:
if number_pages < 10:
displayed_page_numbers = list(range(1, number_pages + 1))
else:
displayed_page_numbers = list(range(1, 11))
else:
if number_pages < (page + 4):
displayed_page_numbers = list(
range(current_page - 5, number_pages + 1))
else:
displayed_page_numbers = list(
range(current_page - 5, current_page + 5))
# EDIT BELOW
current_page_results = result_df.iloc[(current_page * 10 -
10):(current_page * 10)]
print("Pagination", displayed_page_numbers, current_page, number_pages)
end_total = time.time()
print("##########")
print("TOTAL SEARCH TIME ELAPSED {}".format(end_total - start_total))
print("####################")
print("RENDERING RESULTS {}-{}".format(current_page * 10 - 10,
current_page * 10))
print("########################################")
# [0 filename, 1 total region, 2 overlap, 3 short name, 4 long name, 5 description, 6 short description, 7 ID]
result_df.reset_index(inplace=True)
print(result_df.columns)
result_df = result_df.fillna("").sort_values(
"combo_score", ascending=False) # FIX ME SHOULD this be asc
results = result_df[[
"FILEID", "SIZE", "overlaps", "SHORTNAME", "LONGNAME", "LONGINFO",
"SHORTINFO", "index", "combo_score"
]].to_numpy()
return render_template('file_result.html',
form=fileform,
results=results.tolist(),
searchtime=end_total - start_total,
file_name=file_name,
ref_genome=ref_genome,
numresults=len(result_df.index),
source=ref_genome,
page=1,
pageNums=displayed_page_numbers)
def intervalResult(ref_genome, chrom, lower, upper):
form = Search()
intervalform = intervalForm()
fileform = fileForm(CombinedMultiDict((request.files, request.form)))
current_interval = [
str(chrom) + ":" + str(lower) + "-" + str(upper), ref_genome
]
if session.get('intervals', None) == None:
session["intervals"] = [[chrom, lower, upper, ref_genome]]
print("Result recieved:", session.get('intervals', None))
print("#")
if form.validate_on_submit():
out = utility.parse_interval_input(form.Input.data)
if isinstance(out, str): # parsing error occured
return home(error=out)
else:
session['intervals'] = [[
int(i[0].split(":")[0]),
int(i[0].split(":")[1].split("-")[0]),
int(i[0].split(":")[1].split("-")[1]), i[1]
] for i in out]
return redirect("/result/{}/{}".format(out[0][1], out[0][0]))
print("INITIATING SEARCH")
start_total = time.time()
start_task = time.time()
out = utility.interval_search(ref_genome, chrom, lower, upper)
if isinstance(out, str): # parsing error occured
return render_template('home.html',
fileform=fileform,
intervalform=intervalform,
error=out)
else:
result_df = out
end_task = time.time()
print("#####")
print("SEARCH COMPLETED ({} seconds)".format(end_task - start_task))
# make array of links for pages
start_task = time.time()
# out = utility.retrieve_metadata(ref_genome) #generic function to handle data information gathering
# if isinstance(out, str): # parsing error occured
# return render_template('home.html', fileform = fileform, intervalform = intervalform, error = out)
# else:
# metadata_df = out
# result_df = pd.merge(result_df,
# metadata_df,
# left_on ="name",
# right_on ="NAME",
# how ="left")
print(result_df)
result_df.sort_values("overlaps", ascending=False, inplace=True)
end_task = time.time()
print("########")
print("DATA SOURCE INFOMATION COLLECTED ({} seconds)".format(end_task -
start_task))
#Pagination
# determining results displayed on current page
current_page = 1
number_pages = int(math.ceil(len(result_df.index) / 10.0))
if current_page < 7 or number_pages < 10:
if number_pages < 10:
displayed_page_numbers = list(range(1, number_pages + 1))
else:
displayed_page_numbers = list(range(1, 11))
else:
if number_pages < (page + 4):
displayed_page_numbers = list(
range(current_page - 5, number_pages + 1))
else:
displayed_page_numbers = list(
range(current_page - 5, current_page + 5))
# EDIT BELOW
current_page_results = result_df.iloc[(current_page * 10 -
10):(current_page * 10)]
print("Pagination", displayed_page_numbers, current_page, number_pages)
end_total = time.time()
print("##########")
print("TOTAL SEARCH TIME ELAPSED {}".format(end_total - start_total))
print("####################")
print("RENDERING RESULTS {}-{}".format(current_page * 10 - 10,
current_page * 10))
print("########################################")
# [0 filename, 1 total region, 2 overlap, 3 short name, 4 long name, 5 description, 6 short description, 7 ID]
result_df.reset_index(inplace=True)
print(result_df.columns)
result_df = result_df.fillna("")
results = result_df[[
"FILEID", "size", "overlaps", "SHORTNAME", "LONGNAME", "LONGINFO",
"SHORTINFO", "index"
]].to_numpy()
print(session.get('intervals', None))
return render_template(
'interval_result.html',
current_interval=current_interval,
current_interval_split=[chrom, lower, upper, ref_genome],
form=form,
results=results.tolist(),
searchtime=end_total - start_total,
sessionIntervals=session['intervals'],
numresults=len(result_df.index),
source=ref_genome,
page=1,
pageNums=displayed_page_numbers)