def home(request):
print "in uploader"
if request.method == "POST":
img = UploadForm(request.POST, request.FILES)
if img.is_valid():
img.save()
return HttpResponseRedirect(reverse('imageupload'))
else:
img = UploadForm()
images = Upload.objects.all()
print "img: ", img
print "images: ", images
return render(request, 'uploader/home.html', {
'form': img,
'images': images
})
def upload():
form = UploadForm()
if form.validate_on_submit():
f = form.file.data
file_name = secure_filename(f.filename)
f.save(os.path.join(UPLOAD_FOLDER, file_name))
current_user.score_card = os.path.join(UPLOAD_FOLDER, file_name)
flash("File uploaded successfully")
udisc_name = request.form.get("udisc")
current_user.udisc_name = udisc_name
db.session.commit()
return redirect(url_for("main.stats"))
if request.method == "POST":
if "pdga" in request.form:
pdga = str(request.form.get("pdga"))
current_user.pdga_rating = download(pdga, pdga=True)
db.session.commit()
flash(f"PDGA-rating {current_user.pdga_rating} saved!")
return redirect(request.url)
if "metrix" in request.form:
metrix = request.form.get("metrix")
current_user.metrix_rating = metrix
db.session.commit()
flash(f"Metrix-rating {current_user.metrix_rating} saved")
return redirect(request.url)
return render_template("new/upload.html", form=form)
def create_design(request):
if request.method == 'POST':
form = UploadForm(request.POST, request.FILES)
if form.is_valid():
slug = form.cleaned_data['slug']
form.save()
design = Design.objects.get(slug__iexact=slug)
design.owner = request.user
design.save()
return HttpResponseRedirect(WIKI_PREFIX_URL + 'accounts/')
else:
return render_to_response('wiki/create_design.html',
{'form': form})
else:
form = UploadForm()
return render_to_response('wiki/create_design.html', {'form': form})
def upload_handler(request):
view_url = reverse('upload.views.upload_handler')
if request.method == 'POST':
form = UploadForm(request.POST, request.FILE)
form.save()
return HttpResponseRedirect(view_url)
upload_url, upload_data = prepare_upload(request, view_url, private=True)
form = UploadForm()
return direct_to_template(
request, 'upload.html', {
'form': form,
'upload_url': upload_url,
'upload_data': upload_data,
'uploads': UploadMOdel.objects.all(),
'names': names
})
def upload_handler(request):
extra_data = request.user.social_auth.get()
print(extra_data.extra_data)
view_url = reverse('upload.views.upload_handler')
names = request.user.social_auth.values_list('provider', flat=True)
if request.method == 'POST':
form = UploadForm(request.POST, request.FILES)
form.save()
return HttpResponseRedirect(view_url)
upload_url, upload_data = prepare_upload(request, view_url, private=True)
form = UploadForm()
return direct_to_template(
request, 'upload.html', {
'form': form,
'upload_url': upload_url,
'upload_data': upload_data,
'uploads': UploadModel.objects.all(),
'names': names
})
def uploadsong():
form = UploadForm(request.form)
if request.method == 'POST' and form.validate_on_submit():
title = request.form['title']
author = request.form['author']
chords = request.form['chords']
chords = chords.replace(' ', ' ')
chords = chords.replace('\r\n', '<br />')
source = request.form['source']
songs.insert_one({'title': title, 'author': author, \
'chords': chords, 'source': source})
return render_template('uploadsongdone.html',
title=title,
author=author)
return render_template('uploadsong.html', form=form)
def UploadImg(request):
if request.method == "POST":
images = Upload.objects.all()
event = UploadForm(request.POST, request.FILES)
poll = UpPolls(request.POST, instance=Poll())
cforms = [
UpChoice(request.POST, prefix=str(x), instance=Choice())
for x in range(0, 4)
]
# choice1 = UpChoice1(request.POST, prefix='ch1')
# choice2 = UpChoice2(request.POST, prefix='ch2')
# choice3 = UpChoice3(request.POST, prefix='ch3')
# choice4 = UpChoice4(request.POST, prefix='ch4')
# # print "this is event",event
# choices = FormVoteChoices(request.POST, request.FILES)
for cf in cforms:
print cf
if event.is_valid() and poll.is_valid() and all(
[cf.is_valid() for cf in cforms]):
event.save()
a = poll.save()
for cf in cforms:
new_choice = cf.save(commit=False)
new_choice.poll = a
new_choice.save()
print "5555555555555555"
# if a:
# poll_list = Poll.objects.all()
# print "poll: ",poll_list
# print "Hello a: ",a
# print "choice", choice.data['choice_text']
# if choice.is_valid:
# c1 = Choice.objects.create(poll=a,choice_text=choice1.data['choice_text'],votes=0)
# c1.save()
# else:
# print"not valid"
# if choice2.is_valid:
# c2 = Choice.objects.create(poll=a,choice_text=choice2.data['choice_text'],votes=0)
# c2.save()
# else:
# print"not valid"
# if choice3.is_valid:
# c3 = Choice.objects.create(poll=a,choice_text=choice3.data['choice_text'],votes=0)
# c3.save()
# else:
# print"not valid"
# if choice4.is_valid:
# c4 = Choice.objects.create(poll=a,choice_text=choice4.data['choice_text'],votes=0)
# c4.save()
# else:
# print"not valid"
print "success"
print request.user.username
return HttpResponseRedirect('/')
else:
print "fail"
event = UploadForm()
poll = UpPolls(instance=Poll())
cforms = [
UpChoice(prefix=str(x), instance=Choice()) for x in range(0, 4)
]
# choice2 = UpChoice2()
# choice3 = UpChoice3()
# choice4 = UpChoice4()
# choices = FormVoteChoices()
images = Upload.objects.all()
return render(
request, 'addEvent.html', {
'form': event,
'images': images,
'username': request.user.username,
'poll': poll,
'choices': cforms
})
def index():
upload_form = UploadForm()
annotation_form = AnnotationForm()
uniprot_form = UniProtForm()
brenda_form = BrendaForm()
download_form = DownloadForm()
if request.method == "POST":
# print (upload_form.validate())
# print (annotation_form.validate())
# print (brenda_form.validate())
# print (uniprot_form.validate())
if upload_form.upload_submit.data:
saved_files = process_input.save_files(request.files)
session["data_generated"] = saved_files
session['filepath'] = saved_files['filepath']
return render_template("annotation.html",
form=annotation_form,
uniprot_form=uniprot_form,
brenda_form=brenda_form,
download_form=download_form,
current_file=saved_files['filepath'])
elif uniprot_form.uniprot_retrieve.data:
# Get list of columns we want to annotate
columns = request.form.getlist("uniprot_select")
# Retrieve them from UniProt
seq_array = process_input.get_ids_from_fasta(session['filepath'])
# seq_array = pd.read_msgpack(session['seq_array'])
id_list = seq_array['id'].values.tolist()
# print ('seq array ')
# print (seq_array)
# print ()
# seq_array = seq_array.set_index('id')
# # Check if user is specifically asking for organism and if it should be retained
# if 'organism' in columns:
# session['keep_organism'] = True
#
# # Check if we need to explicitly map to species (i.e. we haven't already or aren't just about to)
# if not 'organism' in seq_array and 'organism' not in columns:
# columns.insert(0, 'organism')
# Retrieve the UniProt annotations
master_uniprot_dict = {}
for chunk in process_input.chunks(id_list, 50):
uniprot_dict = src.webservice.getUniProtDict(chunk, columns)
master_uniprot_dict.update(uniprot_dict)
global uniprot_array
uniprot_array = pd.DataFrame.from_dict(master_uniprot_dict,
orient='index')
# # Split up the organism field (to try and maximise matches between this field and the BRENDA annotations)
# uniprot_array['organism_split'] = uniprot_array.apply(lambda row: " ".join(row.organism.split(" ")[0:2]), axis=1)
# print ('before rename')
#
# print (uniprot_array)
# print ()
uniprot_array.index.names = ['id']
#
# print ('after rename')
#
# print(uniprot_array)
# print ()
# uniprot_array.reindex(uniprot_array.index.rename(['ID']))
# uniprot_array = uniprot_array.rename(columns={uniprot_array.columns[0]: "ID"})
# session['uniprot_array'] = uniprot_array.to_msgpack()
# print ('uniprot dict ')
# for k,v in uniprot_dict.items():
# print (k,v)
# print()
# print ('uniprot array')
# print (uniprot_array)
# Add the species information to the seq array
# if not 'organism' in seq_array:
# seq_array = pd.DataFrame.from_dict(uniprot_dict, orient='index', columns = ['organism',
# 'organism_split'] )
#
# print ('problem area is here ')
# print (seq_array)
#
# # seq_array = seq_array.rename(columns={seq_array.columns[0]: "id"})
# seq_array.index.name = 'id'
#
# # seq_array.set_index('id')
#
# print ('problem was renamed ')
# print (seq_array)
# session['seq_array'] = seq_array.to_msgpack()
session['uniprot_array'] = True
flash(u'Retrieved UniProt annotations', 'success')
# Set UniProt as the default selected item
annotation_form.database.default = 'UniProt'
annotation_form.process()
return render_template(
"annotation.html",
form=annotation_form,
uniprot_form=uniprot_form,
brenda_form=brenda_form,
download_form=download_form,
selected='uniprot',
current_file=session['data_generated']['filepath'])
elif brenda_form.brenda_retrieve.data:
global brenda_array
# List of sequences to add annotations to
seq_array = process_input.get_ids_from_fasta(session['filepath'])
# seq_array = pd.read_msgpack(session['seq_array'])
# seq_array.index.names = ['id']
print('here is seq array ')
print(seq_array)
print()
# seq_array = seq_array.set_index('id')
id_list = seq_array['id'].values.tolist()
# id_list = seq_array['id'].values.tolist()
# id_list = seq_array.index.array
print('id list is ')
print(id_list)
print()
# Get list of columns we want to get annotations for
columns = request.form.getlist("brenda_select")
# Get dictionary mapping annotations to abbreviated form
annot_dict = brenda_annotations.get_brenda_dict(columns)
# Get user's preferences for parsing the file
print('choice is ')
print(request.form.get('brenda_select'))
brenda_species = True if request.form.get(
"brenda_species") == 'Organism name' else False
session['brenda_species'] = brenda_species
add_commonalities = True if 'brenda_ubiquitous' in request.form else False
add_comments = True if 'brenda_comments' in request.form else False
print('brenda species is ')
print(brenda_species)
print('add comments is ')
print(add_comments)
# Load BRENDA annotations file
brenda_path = process_input.save_brenda_annotations(request.files)
num_to_prot = brenda_parser.parse_brenda(brenda_path, annot_dict,
brenda_species,
add_commonalities,
add_comments)
brenda_dict = {}
for prot in num_to_prot.values():
print(prot.name)
print()
print(prot.prot_annots)
print()
# If we're mapping based on species, add everything
if brenda_species:
del prot.prot_annots['id']
brenda_dict[prot.name] = prot.prot_annots
# Else we need to check that our annotated ID from the BRENDA file is in our FASTA file
else:
del prot.prot_annots['organism_split']
if prot.id in id_list:
brenda_dict[prot.name] = prot.prot_annots
print('brenda dict is ')
for k, v in brenda_dict.items():
print(k, v)
print()
print()
brenda_array = pd.DataFrame.from_dict(brenda_dict, orient='index')
# If mapping based on species name
if brenda_species:
brenda_array = brenda_array.rename_axis(
'organism_brenda').reset_index()
# Split up the organism field (to try and maximise matches between this field and the UniProt
# annotations)
# brenda_array['organism_split'] = brenda_array.apply(
# lambda row: " ".join(row.organism.split(" ")[0:2]), axis=1)
# Check if we need to annotate the IDs from the FASTA with species names
# if not 'organism' in seq_array:
# print ('Organism was not in seq array')
master_uniprot_dict = {}
for chunk in process_input.chunks(id_list, 50):
uniprot_dict = src.webservice.getUniProtDict(
chunk, ['organism'])
master_uniprot_dict.update(uniprot_dict)
for k, v in master_uniprot_dict.items():
print(k, v)
seq_array = pd.DataFrame.from_dict(master_uniprot_dict,
orient='index',
columns=['organism'])
print('seq array before rename')
print(seq_array)
print()
# seq_array.index.names = ['id']
# seq_array.reset_index()
seq_array = seq_array.rename_axis('id').reset_index()
# Split up the organism field (to try and maximise matches between this field and the BRENDA annotations)
seq_array['organism_split'] = seq_array.apply(
lambda row: " ".join(row.organism.split(" ")[0:2])
if row.organism != None else None,
axis=1)
# seq_array = seq_array.rename(columns={seq_array.columns[0]: "ID"})
# seq_array['organism'] = 'str' + " ".join(seq_array['organism'].astype(str).split(" ")[0:2])
print('Seq array is now ')
print(seq_array)
print()
for k, v in seq_array.items():
print(k, v)
print()
# session['seq_array'] = seq_array.to_msgpack()
# else:
# print ('Organism WAS IN seq array\n')
print('brenda array is ')
print(brenda_array)
print()
for k, v in brenda_array.items():
print(k, v)
print()
#
# print()
# print ('seq array is ')
# print (seq_array)
# brenda_array = brenda_array.rename(columns={'organism': 'organism_brenda'})
seq_array = seq_array.rename(
columns={'organism': 'organism_uniprot'})
# Merge the species and the BRENDA annotations
brenda_array = pd.merge(brenda_array,
seq_array,
on='organism_split',
how='right')
# brenda_array = pd.merge(seq_array, brenda_array, on='organism', how='outer')
print('merged array is now ')
print(brenda_array)
# Otherwise we're mapping based on ID
else:
print('Mapping based on ID')
print('seq array')
print(seq_array)
print(brenda_array)
# Merge the FASTA IDs and the BRENDA annotations
brenda_array = pd.merge(seq_array,
brenda_array,
on='id',
how='outer')
print('BRENDA array is ')
print(brenda_array)
# Drop any entries without an ID
brenda_array = brenda_array[pd.notnull(brenda_array['id'])]
print('And after dropping entries without an ID ')
print(brenda_array)
brenda_array = brenda_array.set_index('id')
print('brenda array before packing is ')
print(brenda_array)
session['brenda_array'] = brenda_array.to_msgpack()
flash('Retrieved BRENDA annotations', 'success')
# Set BRENDA as the default selected item
annotation_form.database.default = 'BRENDA'
annotation_form.process()
return render_template(
"annotation.html",
form=annotation_form,
uniprot_form=uniprot_form,
brenda_form=brenda_form,
download_form=download_form,
selected='brenda',
current_file=session['data_generated']['filepath'])
# Downloading the annotations file
elif download_form.download.data:
print('Download the data')
if 'uniprot_array' in session:
print('uniprot array was in session')
print(uniprot_array)
# uniprot_array = pd.read_msgpack(session['uniprot_array'])
uniprot_array.columns = uniprot_array.columns.map(
lambda x: x + '_uniprot'
if x != 'id' and x != 'Name' else x)
else:
uniprot_array = pd.DataFrame()
if 'brenda_array' in session:
print('brenda array was in session')
print('brenda after unpacking is ')
# brenda_array = pd.read_msgpack(session['brenda_array'])
print(brenda_array)
brenda_array.columns = brenda_array.columns.map(
lambda x: x + '_brenda' if x not in [
'id', 'organism_brenda', 'organism_split',
'organism_uniprot'
] else x)
else:
brenda_array = pd.DataFrame()
if uniprot_array.empty:
if brenda_array.empty:
flash(u'Annotation file ended up being empty', 'error')
return render_template("upload.html", form=upload_form)
else:
final_array = brenda_array
else:
if brenda_array.empty:
final_array = uniprot_array
else:
# if session['brenda_species']:
# final_array = pd.merge(brenda_array, uniprot_array, on='organism_split', how='outer')
# else:
final_array = pd.merge(brenda_array,
uniprot_array,
on='id',
how='outer')
print('Final array is ')
print(final_array)
# If there are there, shift the columns related to organism splitting to the front of the data frame
cols = list(final_array.columns.values)
shift_list = []
for colname in [
'organism_split', 'organism_uniprot', 'organism_brenda'
]:
if colname in final_array.columns:
cols.pop(cols.index(colname))
shift_list.append(colname)
if shift_list:
final_array = final_array[shift_list + cols]
# droplist = []
# dropcheck = ['organism_split_uniprot','organism_brenda', 'organism_split_brenda', 'organism_x_brenda',
# 'organism_y_brenda', 'organism_x_uniprot', 'organism_y_uniprot']
#
#
# if 'brenda_species' in session:
# print ('brenda species in session')
# if not session['brenda_species']:
# droplist = [i for i in final_array.columns if i in dropcheck]
# else:
# droplist = [i for i in final_array.columns if i in dropcheck]
#
# if 'keep_organism' in session:
# print ('keep organism in session')
# if not session['keep_organism']:
# droplist += (i for i in ['organism_uniprot', 'organism_split_uniprot'] if i not in droplist and i
# in final_array.columns)
# else:
# droplist += (i for i in ['organism_uniprot', 'organism_split_uniprot'] if i not in droplist and i in
# final_array.columns)
#
# print (droplist)
# print (type(droplist))
#
# final_array.drop(droplist, axis=1, inplace=True)
# Drop any records that don't have at least 2 columns annotated (ID will always be annotated)
# final_array = final_array.dropna(thresh=2)
resp = make_response(final_array.to_csv(sep='\t', index=True))
resp.headers[
"Content-Disposition"] = "attachment; filename=export.tsv"
resp.headers["Content-Type"] = "text/tsv"
return resp
elif request.method == "GET":
# Clear out any old annotations from previous sessions (good idea!)
session.clear()
return render_template("upload.html", form=upload_form)