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README.md
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# cjvt-vezljivost
## Components
### Database (2 containers)
Input:
* ssj500k.xml
* kres.xml
* kres_SRL.json
Intermediate:
* ssj500k.json
* kres.json
Output:
* DB containing both corpora (1:1 map of the intermediate json formats)
### Flask backend (1 container)
Input: see Database
API endpoints:
* GET word list (pre-cached)
* GET reduced frames (pre-cached)
* POST senses
* User auth logic
### Vue frontend (1 container)
* ngnix server

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src_diploma/README.md Normal file
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# Izdelava vezljivostnih vzorcev za slovenske glagole #
Študent: Kristjan Voje
Mentor: prof. Marko Robnik Šikonja
Somentorica: dr. Apolonija Gantar
### Requirements:
* Linux (built and tested on Ubuntu 16.04),
* python3
## Quick workspace preparation
```bash
# Clone the repo.
$ git clone https://voje@bitbucket.org/voje/diploma.git
# Prepare the data.
$ cd ./data
$ unzip data.zip
```
Virtualenv recommended. `$ sudo pip3 install virtualenv`.
```bash
$ cd ./script
$ virtualenv -p /usr/bin/python3 venv
# A folder venv with python libraries will appear.
# To activate the virtual environment:
$ source ./venv/bin/activate
# To deactivate:
$ deactivate
```
Now, to build the python packages:
```bash
# Polyglot dependencies
$ sudo apt-get install libicu-dev
# NOTE: installing this broke my Arch system.
# If on Arch, use the AUR version (it's supposed to be safe).
$ cd ./script
$ pip3 install -e .
# Polyglot downloads
$ polyglot download morph2.sl
```
To test the installation, fire up a python3 shell (while in virtualenv) and:
```python
import valency
```
## Nodejs environment
There's a compiled front end client in the git repo.
In case you want to change anything, you'll need to set up the development environment:
* install nodejs (default Ubuntu versions are usually behind),
* check `$ npm -v`, if you don't have it, install npm,
```
$ npm install vue-cli
$ cd ./vue_frontend
$ npm install
$ npm run dev # for development
$ npm run build # for production
```
You will also need to change some path variables if you'll want to access the backend api from vue development server.
See chapter "Web app deployment".
## MongoDB
### Set up the database on the system
[install MongoDB on Linux](https://docs.mongodb.com/manual/tutorial/install-mongodb-on-ubuntu/)
> The MongoDB instance stores its data files in /var/lib/mongodb and its log files in /var/log/mongodb by default, and runs using the mongodb user account. You can specify alternate log and data file directories in /etc/mongod.conf. See systemLog.path and storage.dbPath for additional information.
>
> If you change the user that runs the MongoDB process, you must modify the access control rights to the /var/lib/mongodb and /var/log/mongodb directories to give this user access to these directories.
#### Check if it's working.
```bash
$ sudo service mongod start / stop / restart
$ tail -n 30 /var/log/mongodb/mongod.log
# If you want the mongo shell on local machine:
$ mongo --host 127.0.0.1:<27017> # Check net.port in /etc/mongod.conf
```
#### Security
Create admin and user. Localhost only.
[sedurity man](https://docs.mongodb.com/v3.4/tutorial/enable-authentication/)
Basically, create an admin user then user that admin to create a normal user.
Something like this:
```
use admin
db.createUser(
{
user: "admin_name",
pwd: "admin_pass",
roles: [ { role: "userAdminAnyDatabase", db: "admin" } ]
}
)
# Restart mongod.
use texts
db.createUser(
{
user: "user_name",
pwd: "user_pass",
roles: [ { role: "readWrite", db: "texts" } ]
}
)
# Restart mongod.
# Also useful
db.dropUser("username")
```
Then go to `/etc/mongod.conf` and add this:
Do not use tabs! mongod won't start.
```bash
security:
authorization: enabled
```
You need to `use <db>`, `db.auth("username", "pass")` to have access.
#### DB migration
I installed mongo on remote with same user accounts as on local.
```bash
# On local.
$ mongodump --db texts --host mongodb1.example.net --port 3017 --username user --password "pass" --out ./file.db
# Rsync it over to remote.
# On remote.
# Need to turn off authorization for the drop part.
$ mongorestore --db texts --drop --port <port> ./<dbfolder>
```
#### DB collections, needed for web app
* v2_senses,
* v2_senses_map,
* v2_users,
* v2_user_tokens
* sskj
## Web app deployment
We need to set flask to serve the vuejs frontend:
```python
# in ./script/flask_app/app.py
app = Flask(
__name__,
static_folder="./vue/dist/static",
template_folder="./vue/dist"
)
```
Set the correct CORS options.
Might need to reinstall the package. Make sure you're in python virtualenv.
`$ pip3 install -e .`
We also need to tell vuejs client to look for the api on server's address.
```javascript
// in script/vue_frontend/src/main.js
api_addr: "http://<my_server_addr>:5004",
```
Compile frontend client:
```bash
$ cd ./script/vue_frontend
$ npm run build
$ rm ../flask_app/vue -rf
$ cp ./dist ../flask_app/vue -r
```
After preparing frontend, backend and database, run the command:
```bash
$ cd ./script
$ ./autostart.sh
```
## When fixing things in dev environment:
```bash
## Backend
# git clone everything
$ cd script
# unzip some zipped files
$ ./sherpa --unpack
# virtualenv
$ source venv/bin/activate
$ pip3 install -e .
# start a mongod instance
$ sudo systemctl start mongod
# start the backend server
$ ./autostart.sh --debug
# you can watch the logs with
$ tail -f log/main.log
## Frontend
# set the right config file (path to api)
$ ./sherpa --frontend_config dev
$ cd vue_frontend
$ npm run dev
## Done making changes
# build frontend for production with the right config files
$ ./sherpa --build_vue
# if you've made changes to static .pickle files
$ ./sherpa --pack
```

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#!/bin/bash
# prepare args for app.py
datapath="../data"
logpath="./log"
function echo_help() {
echo "arguments:
--help
--rm_pickles (removes .pickle files from ./data/tmp_pickles)
--prepare_for_shipment (build frontend, zip some data)
--reload_sskj_senses (removes author: SSKJ from db.v2_senses
and inserts senses from ./data/no_del_pickles/sskj_sense.pickle)
--debug"
}
function rm_pickles () {
pickles_path="${datapath}/tmp_pickles"
nfiles=$(ls "${pickles_path}" | grep ".pickle" | wc -l)
if [[ $nfiles -gt 0 ]]; then
echo "Removing:"
ls "${pickles_path}"/*.pickle
rm "${pickles_path}"/*.pickle
else
echo "No .pickle files to remove."
fi
}
function prepare_for_shipment () {
./sherpa.sh --pack
./sherpa.sh --build_vue
}
args=""
# Parse arguments
while [[ "$#" -gt 0 ]]; do
key="$1"
case "$key" in
--help)
echo_help
exit 0
;;
--rm_pickles)
rm_pickles
exit 0
;;
--prepare_for_shipment)
prepare_for_shipment
exit 0
;;
--reload_sskj_senses)
args="$args --reload_sskj_senses"
shift
;;
--debug)
args="$args --debug"
shift
;;
*)
echo "Unknown argument: $key"
exit 1
;;
esac
done
args="${args} --datapath=${datapath} --logpath=${logpath}"
python3 ./flask_app/app.py "$args"

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src_diploma/flask_app/app.py Normal file
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# -*- coding: utf-8 -*-
from flask import Flask, render_template, request, url_for, redirect
from valency import k_utils
from valency.ssj_struct import *
from valency.val_struct import *
from valency.reduce_functions import *
import logging
import sys
import json
from flask_cors import CORS
import hashlib
import uuid
import datetime
import string
import random
import smtplib
from email.mime.text import MIMEText
from copy import deepcopy as DC
log = logging.getLogger(__name__)
PORT = 5004
args = []
def get_arg(argname):
for arg in args:
if "--{}".format(argname) in arg:
spl = arg.split("=")
if len(spl) == 2:
return spl[1]
else:
return True
else:
return False
vallex = None
# app = Flask(__name__)
# v2 (serving vuejs frontend)
# change api path in vue to localhost:5004
app = Flask(
__name__,
static_folder="./vue/dist/static",
template_folder="./vue/dist"
)
# when running vuejs via webpack
# CORS(app)
CORS(app, resources={r"/api/*": {
"origins": "*",
}})
# for testing functions
@app.route("/test_dev")
def test_dev():
ret = vallex.test_dev()
return(str(ret) or "edit val_struct.py: test_dev()")
@app.route("/")
def index():
return(render_template("index.html"))
@app.route("/home", defaults={"pathname": ""})
@app.route("/home/<path:pathname>")
def home(pathname):
return redirect(url_for("index"), code=302)
@app.route("/api/words")
def api_words():
return json.dumps({
"sorted_words": vallex.sorted_words,
"has_se": vallex.has_se
})
@app.route("/api/functors")
def api_functors():
res = []
for key in sorted(vallex.functors_index.keys()):
res.append((key, len(vallex.functors_index[key])))
return json.dumps(res)
@app.route("/api/register", methods=["POST"])
def api_register():
USERS_COLL = "v2_users"
b = request.get_data()
data = json.loads(b.decode())
username = data["username"]
password = data["password"]
email = data["email"]
if (
username == "" or
password == "" or
email == ""
):
return "ERR"
existing = list(vallex.db[USERS_COLL].find({
"$or": [{"username": username}, {"email": email}]
}))
if len(existing) > 0:
return "ERR: Username or email already exists."
entry = {
"username": username,
"hpass": hashlib.sha256(
password.encode("utf-8")).hexdigest(),
"email": hashlib.sha256(
email.encode("utf-8")).hexdigest()
}
vallex.db[USERS_COLL].insert(entry)
return "OK"
@app.route("/api/login", methods=["POST"])
def api_login():
USERS_COLL = "v2_users"
TOKENS_COLL = "v2_user_tokens"
b = request.get_data()
data = json.loads(b.decode())
username = data["username"]
password = data["password"]
hpass = hashlib.sha256(password.encode("utf-8")).hexdigest()
db_user = list(vallex.db[USERS_COLL].find({
"username": username,
"hpass": hpass
}))
if len(db_user) == 0:
return json.dumps({"token": None})
# update or create token
token = uuid.uuid4().hex
token_entry = {
"username": username,
"date": datetime.datetime.utcnow(),
"token": token
}
vallex.db[TOKENS_COLL].update(
{"username": token_entry["username"]},
token_entry,
upsert=True
)
return json.dumps({"token": token})
def send_new_pass_mail(recipient, new_pass):
# dtime = str(datetime.datetime.now())
SENDER = "valencaglagolov@gmail.com"
msg = MIMEText(
"Pošiljamo vam novo geslo za "
"vstop v aplikacijo Vezljivostni vzorci slovenskih glagolov.\n"
"Geslo: {}.".format(new_pass)
)
msg["Subject"] = "Pozabljeno geslo"
msg["From"] = SENDER
msg["To"] = recipient
try:
server = smtplib.SMTP("smtp.gmail.com", 587)
server.ehlo()
server.starttls()
server.login(
SENDER,
"rapid limb soapy fermi"
)
server.sendmail(SENDER, [recipient], msg.as_string())
server.close()
log.info("Sent new password.")
except Error as e:
log.error("Sending new password failed")
log.error(e)
@app.route("/api/new_pass", methods=["POST"])
def api_new_pass():
b = request.get_data()
data = json.loads(b.decode())
username = data["username"]
email = data["email"]
hemail = hashlib.sha256(email.encode("utf-8")).hexdigest()
db_res = list(vallex.db.v2_users.find({
"username": username,
"email": hemail
}))
# check if user is valid
if len(db_res) == 0:
return json.dumps({"confirmation": False})
# create a new password
new_pass = "".join([random.choice(
string.ascii_letters + string.digits) for i in range(10)])
# update locally
hpass = hashlib.sha256(new_pass.encode("utf-8")).hexdigest()
vallex.db.v2_users.update(
{
"username": username,
"email": hemail
},
{"$set": {
"hpass": hpass
}}
)
# send via mail
send_new_pass_mail(email, new_pass)
return json.dumps({"confirmation": True})
def prepare_frames(ret_frames):
# append sentences
for frame in ret_frames:
frame.sentences = []
unique_sids = {".".join(x.split(".")[:-1]): x for x in frame.tids}
log.debug(str(unique_sids))
frame.sentences = []
frame.aggr_sent = {}
for sid, tid in unique_sids.items():
hwl = vallex.get_token(tid)["lemma"]
tmp_idx = len(frame.sentences)
if hwl not in frame.aggr_sent:
frame.aggr_sent[hwl] = []
frame.aggr_sent[hwl].append(tmp_idx)
frame.sentences.append(
vallex.get_tokenized_sentence(tid)
)
# return (n-frames, rendered template)
# json frames
json_ret = {"frames": []}
for frame in ret_frames:
json_ret["frames"].append(DC(frame.to_json()))
return json.dumps(json_ret)
@app.route("/api/frames")
def api_get_frames():
hw = request.args.get("hw")
if hw is None:
return json.dumps({"error": "Headword not found."})
rf_name = request.args.get("rf", "reduce_0") # 2nd is default
RF = reduce_functions[rf_name]["f"]
entry = vallex.entries[hw]
ret_frames = RF(entry.raw_frames, vallex)
return prepare_frames(ret_frames)
@app.route("/api/functor-frames")
def api_get_functor_frames():
functor = request.args.get("functor")
if functor is None:
return json.dumps({"error": "Missing argument: functor."})
rf_name = request.args.get("rf", "reduce_0") # 2nd is default
RF = reduce_functions[rf_name]["f"]
raw_frames = vallex.functors_index[functor]
ret_frames = RF(raw_frames, vallex)
return prepare_frames(ret_frames)
def token_to_username(token):
COLLNAME = "v2_user_tokens"
key = {
"token": token
}
res = list(vallex.db[COLLNAME].find(key))
if len(res) != 1:
return None
username = res[0]["username"]
# update deletion interval
vallex.db[COLLNAME].update(
key, {"$set": {"date": datetime.datetime.utcnow()}})
return username
@app.route("/api/token", methods=["POST"])
def api_token():
# check if token is valid
b = request.get_data()
data = json.loads(b.decode())
token = data.get("token")
# user = data.get("user")
user = token_to_username(token)
confirm = (user is not None)
return json.dumps({
"confirmation": confirm,
"username": user
})
@app.route("/api/senses/get")
def api_senses_get():
# returns senses and mapping for hw
hw = request.args.get("hw")
senses = list(vallex.db["v2_senses"].find({
"hw": hw
}))
sense_map_query = list(vallex.db["v2_sense_map"].find({
"hw": hw
}))
# aggregation by max date possible on DB side
# but no simple way of returning full entries
# aggregate hw and ssj_id by max date
sense_map_aggr = {}
for sm in sense_map_query:
key = sm["hw"] + sm["ssj_id"]
if key in sense_map_aggr:
sense_map_aggr[key] = max(
[sm, sense_map_aggr[key]], key=lambda x: x["date"])
else:
sense_map_aggr[key] = sm
sense_map_list = [x[1] for x in sense_map_aggr.items()]
sense_map = {}
for el in sense_map_list:
sense_map[el["ssj_id"]] = el
for k, e in sense_map.items():
del(e["_id"])
del(e["date"])
for e in senses:
del(e["_id"])
if "date" in e:
del(e["date"])
# sort senses: user defined first, sskj second
# sskj senses sorted by sskj sense_id
user_senses = [s for s in senses if s["author"] != "SSKJ"]
sskj_senses = [s for s in senses if s["author"] == "SSKJ"]
def sorting_helper(sense):
arr = sense["sense_id"].split("-")
return "{:03d}-{:03d}-{:03d}".format(
int(arr[1]), int(arr[2]), int(arr[3]))
sskj_senses = sorted(sskj_senses, key=sorting_helper)
senses = user_senses + sskj_senses
return json.dumps({
"senses": senses,
"sense_map": sense_map,
})
@app.route("/api/senses/update", methods=["POST"])
def api_senses_update():
b = request.get_data()
data = json.loads(b.decode())
token = data.get("token")
hw = data.get("hw")
sense_map = data.get("sense_map")
new_senses = data.get("new_senses")
username = token_to_username(token)
if username is None:
log.debug("Not a user.")
return "Not a user."
# store new senses,
# create new sense_ids
id_map = {}
for ns in new_senses:
tmp_dt = datetime.datetime.utcnow()
new_sense_id = "{}-{}".format(
username,
hashlib.sha256("{}{}{}".format(
username,
ns["desc"],
str(tmp_dt)
).encode("utf-8")).hexdigest()[:10]
)
frontend_sense_id = ns["sense_id"]
ns["sense_id"] = new_sense_id
ns["date"] = tmp_dt
id_map[frontend_sense_id] = new_sense_id
# insert into db
vallex.db["v2_senses"].insert(ns)
# replace tmp_id with mongo's _id
for ssj_id, el in sense_map.items():
sense_id = el["sense_id"]
if sense_id in id_map.keys():
sense_id = id_map[sense_id]
data = {
"user": username,
"hw": hw,
"ssj_id": ssj_id,
"sense_id": sense_id,
"date": datetime.datetime.utcnow()
}
# vallex.db["v2_sense_map"].update(key, data, upsert=True)
vallex.db["v2_sense_map"].insert(data)
return "OK"
if __name__ == "__main__":
# Files needed to run:
# pre-generated .pickle files in /data/no_del_pickles
# temporary .pickle files can speed up startup (/data/tmp_pickles)
# main input file: annotated sentences (ssj.xml)
ANNOTATED_SSJ_XML_PATH = "/ssj500k-sl.TEI/ssj500k-sl.body.xml"
# Read arguments from autostart.sh script.
for arg in sys.argv:
args.extend(arg.split())
app.debug = get_arg("debug")
# Set up logging
logfile = get_arg("logpath") + "/main.log"
logging.basicConfig(filename=logfile, level=logging.DEBUG)
datapath = get_arg("datapath")
if datapath is None:
log.error("No path to data.")
exit(1)
# Prepare vallex.
vallex = Vallex()
vallex_pickle_path = datapath + "/tmp_pickles/vallex.pickle"
vallex_data = k_utils.pickle_load(vallex_pickle_path)
if vallex_data is None:
log.info("No pickle found, creating vallex_data.")
# get ssj data from pickle
ssj_pickle_path = datapath + "/tmp_pickles/ssj.pickle"
ssj = k_utils.pickle_load(ssj_pickle_path)
if ssj is None:
ssj_path = datapath + ANNOTATED_SSJ_XML_PATH
log.info("No pickle found, creating ssj pickle from {}.".format(
ssj_path))
ssj = SsjDict()
ssj.read_xml_v2(ssj_path)
# create fresh pickle
k_utils.pickle_dump(ssj, ssj_pickle_path)
vallex.read_ssj(ssj)
vallex_data = {
"entries": vallex.entries,
"tokens": vallex.tokens
}
k_utils.pickle_dump(vallex_data, vallex_pickle_path)
vallex.entries = DC(vallex_data["entries"])
vallex.tokens = DC(vallex_data["tokens"])
# Generate senses and se_list after we've built the vallex object.
seqparser_sskj_path = datapath + "/no_del_pickles/sskj_senses.pickle"
seqparser_se_list_path = datapath + "/no_del_pickles/se_list.pickle"
vallex.process_after_read(
seqparser_sskj_path, seqparser_se_list_path,
reload_sskj_senses=get_arg("reload_sskj_senses")
)
log.info(
"\n[*] Starting the app." +
"\n[*] args: {}".format(args) +
"\n[*] | logfile: {}".format(logfile) +
"\n[*] | debug: {}".format(str(app.debug))
)
# Run the app.
if app.debug:
app.run(port=PORT)
else:
app.run(host="0.0.0.0", port=PORT)

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/*!
* Bootstrap v3.3.7 (http://getbootstrap.com)
* Copyright 2011-2016 Twitter, Inc.
* Licensed under MIT (https://github.com/twbs/bootstrap/blob/master/LICENSE)
*/
.btn-default,
.btn-primary,
.btn-success,
.btn-info,
.btn-warning,
.btn-danger {
text-shadow: 0 -1px 0 rgba(0, 0, 0, .2);
-webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, .15), 0 1px 1px rgba(0, 0, 0, .075);
box-shadow: inset 0 1px 0 rgba(255, 255, 255, .15), 0 1px 1px rgba(0, 0, 0, .075);
}
.btn-default:active,
.btn-primary:active,
.btn-success:active,
.btn-info:active,
.btn-warning:active,
.btn-danger:active,
.btn-default.active,
.btn-primary.active,
.btn-success.active,
.btn-info.active,
.btn-warning.active,
.btn-danger.active {
-webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, .125);
box-shadow: inset 0 3px 5px rgba(0, 0, 0, .125);
}
.btn-default.disabled,
.btn-primary.disabled,
.btn-success.disabled,
.btn-info.disabled,
.btn-warning.disabled,
.btn-danger.disabled,
.btn-default[disabled],
.btn-primary[disabled],
.btn-success[disabled],
.btn-info[disabled],
.btn-warning[disabled],
.btn-danger[disabled],
fieldset[disabled] .btn-default,
fieldset[disabled] .btn-primary,
fieldset[disabled] .btn-success,
fieldset[disabled] .btn-info,
fieldset[disabled] .btn-warning,
fieldset[disabled] .btn-danger {
-webkit-box-shadow: none;
box-shadow: none;
}
.btn-default .badge,
.btn-primary .badge,
.btn-success .badge,
.btn-info .badge,
.btn-warning .badge,
.btn-danger .badge {
text-shadow: none;
}
.btn:active,
.btn.active {
background-image: none;
}
.btn-default {
text-shadow: 0 1px 0 #fff;
background-image: -webkit-linear-gradient(top, #fff 0%, #e0e0e0 100%);
background-image: -o-linear-gradient(top, #fff 0%, #e0e0e0 100%);
background-image: -webkit-gradient(linear, left top, left bottom, from(#fff), to(#e0e0e0));
background-image: linear-gradient(to bottom, #fff 0%, #e0e0e0 100%);
filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ffffffff', endColorstr='#ffe0e0e0', GradientType=0);
filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
background-repeat: repeat-x;
border-color: #dbdbdb;
border-color: #ccc;
}
.btn-default:hover,
.btn-default:focus {
background-color: #e0e0e0;
background-position: 0 -15px;
}
.btn-default:active,
.btn-default.active {
background-color: #e0e0e0;
border-color: #dbdbdb;
}
.btn-default.disabled,
.btn-default[disabled],
fieldset[disabled] .btn-default,
.btn-default.disabled:hover,
.btn-default[disabled]:hover,
fieldset[disabled] .btn-default:hover,
.btn-default.disabled:focus,
.btn-default[disabled]:focus,
fieldset[disabled] .btn-default:focus,
.btn-default.disabled.focus,
.btn-default[disabled].focus,
fieldset[disabled] .btn-default.focus,
.btn-default.disabled:active,
.btn-default[disabled]:active,
fieldset[disabled] .btn-default:active,
.btn-default.disabled.active,
.btn-default[disabled].active,
fieldset[disabled] .btn-default.active {
background-color: #e0e0e0;
background-image: none;
}
.btn-primary {
background-image: -webkit-linear-gradient(top, #337ab7 0%, #265a88 100%);
background-image: -o-linear-gradient(top, #337ab7 0%, #265a88 100%);
background-image: -webkit-gradient(linear, left top, left bottom, from(#337ab7), to(#265a88));
background-image: linear-gradient(to bottom, #337ab7 0%, #265a88 100%);
filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff337ab7', endColorstr='#ff265a88', GradientType=0);
filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
background-repeat: repeat-x;
border-color: #245580;
}
.btn-primary:hover,
.btn-primary:focus {
background-color: #265a88;
background-position: 0 -15px;
}
.btn-primary:active,
.btn-primary.active {
background-color: #265a88;
border-color: #245580;
}
.btn-primary.disabled,
.btn-primary[disabled],
fieldset[disabled] .btn-primary,
.btn-primary.disabled:hover,
.btn-primary[disabled]:hover,
fieldset[disabled] .btn-primary:hover,
.btn-primary.disabled:focus,
.btn-primary[disabled]:focus,
fieldset[disabled] .btn-primary:focus,
.btn-primary.disabled.focus,
.btn-primary[disabled].focus,
fieldset[disabled] .btn-primary.focus,
.btn-primary.disabled:active,
.btn-primary[disabled]:active,
fieldset[disabled] .btn-primary:active,
.btn-primary.disabled.active,
.btn-primary[disabled].active,
fieldset[disabled] .btn-primary.active {
background-color: #265a88;
background-image: none;
}
.btn-success {
background-image: -webkit-linear-gradient(top, #5cb85c 0%, #419641 100%);
background-image: -o-linear-gradient(top, #5cb85c 0%, #419641 100%);
background-image: -webkit-gradient(linear, left top, left bottom, from(#5cb85c), to(#419641));
background-image: linear-gradient(to bottom, #5cb85c 0%, #419641 100%);
filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff5cb85c', endColorstr='#ff419641', GradientType=0);
filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
background-repeat: repeat-x;
border-color: #3e8f3e;
}
.btn-success:hover,
.btn-success:focus {
background-color: #419641;
background-position: 0 -15px;
}
.btn-success:active,
.btn-success.active {
background-color: #419641;
border-color: #3e8f3e;
}
.btn-success.disabled,
.btn-success[disabled],
fieldset[disabled] .btn-success,
.btn-success.disabled:hover,
.btn-success[disabled]:hover,
fieldset[disabled] .btn-success:hover,
.btn-success.disabled:focus,
.btn-success[disabled]:focus,
fieldset[disabled] .btn-success:focus,
.btn-success.disabled.focus,
.btn-success[disabled].focus,
fieldset[disabled] .btn-success.focus,
.btn-success.disabled:active,
.btn-success[disabled]:active,
fieldset[disabled] .btn-success:active,
.btn-success.disabled.active,
.btn-success[disabled].active,
fieldset[disabled] .btn-success.active {
background-color: #419641;
background-image: none;
}
.btn-info {
background-image: -webkit-linear-gradient(top, #5bc0de 0%, #2aabd2 100%);
background-image: -o-linear-gradient(top, #5bc0de 0%, #2aabd2 100%);
background-image: -webkit-gradient(linear, left top, left bottom, from(#5bc0de), to(#2aabd2));
background-image: linear-gradient(to bottom, #5bc0de 0%, #2aabd2 100%);
filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff5bc0de', endColorstr='#ff2aabd2', GradientType=0);
filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
background-repeat: repeat-x;
border-color: #28a4c9;
}
.btn-info:hover,
.btn-info:focus {
background-color: #2aabd2;
background-position: 0 -15px;
}
.btn-info:active,
.btn-info.active {
background-color: #2aabd2;
border-color: #28a4c9;
}
.btn-info.disabled,
.btn-info[disabled],
fieldset[disabled] .btn-info,
.btn-info.disabled:hover,
.btn-info[disabled]:hover,
fieldset[disabled] .btn-info:hover,
.btn-info.disabled:focus,
.btn-info[disabled]:focus,
fieldset[disabled] .btn-info:focus,
.btn-info.disabled.focus,
.btn-info[disabled].focus,
fieldset[disabled] .btn-info.focus,
.btn-info.disabled:active,
.btn-info[disabled]:active,
fieldset[disabled] .btn-info:active,
.btn-info.disabled.active,
.btn-info[disabled].active,
fieldset[disabled] .btn-info.active {
background-color: #2aabd2;
background-image: none;
}
.btn-warning {
background-image: -webkit-linear-gradient(top, #f0ad4e 0%, #eb9316 100%);
background-image: -o-linear-gradient(top, #f0ad4e 0%, #eb9316 100%);
background-image: -webkit-gradient(linear, left top, left bottom, from(#f0ad4e), to(#eb9316));
background-image: linear-gradient(to bottom, #f0ad4e 0%, #eb9316 100%);
filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#fff0ad4e', endColorstr='#ffeb9316', GradientType=0);
filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
background-repeat: repeat-x;
border-color: #e38d13;
}
.btn-warning:hover,
.btn-warning:focus {
background-color: #eb9316;
background-position: 0 -15px;
}
.btn-warning:active,
.btn-warning.active {
background-color: #eb9316;
border-color: #e38d13;
}
.btn-warning.disabled,
.btn-warning[disabled],
fieldset[disabled] .btn-warning,
.btn-warning.disabled:hover,
.btn-warning[disabled]:hover,
fieldset[disabled] .btn-warning:hover,
.btn-warning.disabled:focus,
.btn-warning[disabled]:focus,
fieldset[disabled] .btn-warning:focus,
.btn-warning.disabled.focus,
.btn-warning[disabled].focus,
fieldset[disabled] .btn-warning.focus,
.btn-warning.disabled:active,
.btn-warning[disabled]:active,
fieldset[disabled] .btn-warning:active,
.btn-warning.disabled.active,
.btn-warning[disabled].active,
fieldset[disabled] .btn-warning.active {
background-color: #eb9316;
background-image: none;
}
.btn-danger {
background-image: -webkit-linear-gradient(top, #d9534f 0%, #c12e2a 100%);
background-image: -o-linear-gradient(top, #d9534f 0%, #c12e2a 100%);
background-image: -webkit-gradient(linear, left top, left bottom, from(#d9534f), to(#c12e2a));
background-image: linear-gradient(to bottom, #d9534f 0%, #c12e2a 100%);
filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ffd9534f', endColorstr='#ffc12e2a', GradientType=0);
filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
background-repeat: repeat-x;
border-color: #b92c28;
}
.btn-danger:hover,
.btn-danger:focus {
background-color: #c12e2a;
background-position: 0 -15px;
}
.btn-danger:active,
.btn-danger.active {
background-color: #c12e2a;
border-color: #b92c28;
}
.btn-danger.disabled,
.btn-danger[disabled],
fieldset[disabled] .btn-danger,
.btn-danger.disabled:hover,
.btn-danger[disabled]:hover,
fieldset[disabled] .btn-danger:hover,
.btn-danger.disabled:focus,
.btn-danger[disabled]:focus,
fieldset[disabled] .btn-danger:focus,
.btn-danger.disabled.focus,
.btn-danger[disabled].focus,
fieldset[disabled] .btn-danger.focus,
.btn-danger.disabled:active,
.btn-danger[disabled]:active,
fieldset[disabled] .btn-danger:active,
.btn-danger.disabled.active,
.btn-danger[disabled].active,
fieldset[disabled] .btn-danger.active {
background-color: #c12e2a;
background-image: none;
}
.thumbnail,
.img-thumbnail {
-webkit-box-shadow: 0 1px 2px rgba(0, 0, 0, .075);
box-shadow: 0 1px 2px rgba(0, 0, 0, .075);
}
.dropdown-menu > li > a:hover,
.dropdown-menu > li > a:focus {
background-color: #e8e8e8;
background-image: -webkit-linear-gradient(top, #f5f5f5 0%, #e8e8e8 100%);
background-image: -o-linear-gradient(top, #f5f5f5 0%, #e8e8e8 100%);
background-image: -webkit-gradient(linear, left top, left bottom, from(#f5f5f5), to(#e8e8e8));
background-image: linear-gradient(to bottom, #f5f5f5 0%, #e8e8e8 100%);
filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#fff5f5f5', endColorstr='#ffe8e8e8', GradientType=0);
background-repeat: repeat-x;
}
.dropdown-menu > .active > a,
.dropdown-menu > .active > a:hover,
.dropdown-menu > .active > a:focus {
background-color: #2e6da4;
background-image: -webkit-linear-gradient(top, #337ab7 0%, #2e6da4 100%);
background-image: -o-linear-gradient(top, #337ab7 0%, #2e6da4 100%);
background-image: -webkit-gradient(linear, left top, left bottom, from(#337ab7), to(#2e6da4));
background-image: linear-gradient(to bottom, #337ab7 0%, #2e6da4 100%);
filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff337ab7', endColorstr='#ff2e6da4', GradientType=0);
background-repeat: repeat-x;
}
.navbar-default {
background-image: -webkit-linear-gradient(top, #fff 0%, #f8f8f8 100%);
background-image: -o-linear-gradient(top, #fff 0%, #f8f8f8 100%);
background-image: -webkit-gradient(linear, left top, left bottom, from(#fff), to(#f8f8f8));
background-image: linear-gradient(to bottom, #fff 0%, #f8f8f8 100%);
filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ffffffff', endColorstr='#fff8f8f8', GradientType=0);
filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
background-repeat: repeat-x;
border-radius: 4px;
-webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, .15), 0 1px 5px rgba(0, 0, 0, .075);
box-shadow: inset 0 1px 0 rgba(255, 255, 255, .15), 0 1px 5px rgba(0, 0, 0, .075);
}
.navbar-default .navbar-nav > .open > a,
.navbar-default .navbar-nav > .active > a {
background-image: -webkit-linear-gradient(top, #dbdbdb 0%, #e2e2e2 100%);
background-image: -o-linear-gradient(top, #dbdbdb 0%, #e2e2e2 100%);
background-image: -webkit-gradient(linear, left top, left bottom, from(#dbdbdb), to(#e2e2e2));
background-image: linear-gradient(to bottom, #dbdbdb 0%, #e2e2e2 100%);
filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ffdbdbdb', endColorstr='#ffe2e2e2', GradientType=0);
background-repeat: repeat-x;
-webkit-box-shadow: inset 0 3px 9px rgba(0, 0, 0, .075);
box-shadow: inset 0 3px 9px rgba(0, 0, 0, .075);
}
.navbar-brand,
.navbar-nav > li > a {
text-shadow: 0 1px 0 rgba(255, 255, 255, .25);
}
.navbar-inverse {
background-image: -webkit-linear-gradient(top, #3c3c3c 0%, #222 100%);
background-image: -o-linear-gradient(top, #3c3c3c 0%, #222 100%);
background-image: -webkit-gradient(linear, left top, left bottom, from(#3c3c3c), to(#222));
background-image: linear-gradient(to bottom, #3c3c3c 0%, #222 100%);
filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff3c3c3c', endColorstr='#ff222222', GradientType=0);
filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
background-repeat: repeat-x;
border-radius: 4px;
}
.navbar-inverse .navbar-nav > .open > a,
.navbar-inverse .navbar-nav > .active > a {
background-image: -webkit-linear-gradient(top, #080808 0%, #0f0f0f 100%);
background-image: -o-linear-gradient(top, #080808 0%, #0f0f0f 100%);
background-image: -webkit-gradient(linear, left top, left bottom, from(#080808), to(#0f0f0f));
background-image: linear-gradient(to bottom, #080808 0%, #0f0f0f 100%);
filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff080808', endColorstr='#ff0f0f0f', GradientType=0);
background-repeat: repeat-x;
-webkit-box-shadow: inset 0 3px 9px rgba(0, 0, 0, .25);
box-shadow: inset 0 3px 9px rgba(0, 0, 0, .25);
}
.navbar-inverse .navbar-brand,
.navbar-inverse .navbar-nav > li > a {
text-shadow: 0 -1px 0 rgba(0, 0, 0, .25);
}
.navbar-static-top,
.navbar-fixed-top,
.navbar-fixed-bottom {
border-radius: 0;
}
@media (max-width: 767px) {
.navbar .navbar-nav .open .dropdown-menu > .active > a,
.navbar .navbar-nav .open .dropdown-menu > .active > a:hover,
.navbar .navbar-nav .open .dropdown-menu > .active > a:focus {
color: #fff;
background-image: -webkit-linear-gradient(top, #337ab7 0%, #2e6da4 100%);
background-image: -o-linear-gradient(top, #337ab7 0%, #2e6da4 100%);
background-image: -webkit-gradient(linear, left top, left bottom, from(#337ab7), to(#2e6da4));
background-image: linear-gradient(to bottom, #337ab7 0%, #2e6da4 100%);
filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff337ab7', endColorstr='#ff2e6da4', GradientType=0);
background-repeat: repeat-x;
}
}
.alert {
text-shadow: 0 1px 0 rgba(255, 255, 255, .2);
-webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, .25), 0 1px 2px rgba(0, 0, 0, .05);
box-shadow: inset 0 1px 0 rgba(255, 255, 255, .25), 0 1px 2px rgba(0, 0, 0, .05);
}
.alert-success {
background-image: -webkit-linear-gradient(top, #dff0d8 0%, #c8e5bc 100%);
background-image: -o-linear-gradient(top, #dff0d8 0%, #c8e5bc 100%);
background-image: -webkit-gradient(linear, left top, left bottom, from(#dff0d8), to(#c8e5bc));
background-image: linear-gradient(to bottom, #dff0d8 0%, #c8e5bc 100%);
filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ffdff0d8', endColorstr='#ffc8e5bc', GradientType=0);
background-repeat: repeat-x;
border-color: #b2dba1;
}
.alert-info {
background-image: -webkit-linear-gradient(top, #d9edf7 0%, #b9def0 100%);
background-image: -o-linear-gradient(top, #d9edf7 0%, #b9def0 100%);
background-image: -webkit-gradient(linear, left top, left bottom, from(#d9edf7), to(#b9def0));
background-image: linear-gradient(to bottom, #d9edf7 0%, #b9def0 100%);
filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ffd9edf7', endColorstr='#ffb9def0', GradientType=0);
background-repeat: repeat-x;
border-color: #9acfea;
}
.alert-warning {
background-image: -webkit-linear-gradient(top, #fcf8e3 0%, #f8efc0 100%);
background-image: -o-linear-gradient(top, #fcf8e3 0%, #f8efc0 100%);
background-image: -webkit-gradient(linear, left top, left bottom, from(#fcf8e3), to(#f8efc0));
background-image: linear-gradient(to bottom, #fcf8e3 0%, #f8efc0 100%);
filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#fffcf8e3', endColorstr='#fff8efc0', GradientType=0);
background-repeat: repeat-x;
border-color: #f5e79e;
}
.alert-danger {
background-image: -webkit-linear-gradient(top, #f2dede 0%, #e7c3c3 100%);
background-image: -o-linear-gradient(top, #f2dede 0%, #e7c3c3 100%);
background-image: -webkit-gradient(linear, left top, left bottom, from(#f2dede), to(#e7c3c3));
background-image: linear-gradient(to bottom, #f2dede 0%, #e7c3c3 100%);
filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#fff2dede', endColorstr='#ffe7c3c3', GradientType=0);
background-repeat: repeat-x;
border-color: #dca7a7;
}
.progress {
background-image: -webkit-linear-gradient(top, #ebebeb 0%, #f5f5f5 100%);
background-image: -o-linear-gradient(top, #ebebeb 0%, #f5f5f5 100%);
background-image: -webkit-gradient(linear, left top, left bottom, from(#ebebeb), to(#f5f5f5));
background-image: linear-gradient(to bottom, #ebebeb 0%, #f5f5f5 100%);
filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ffebebeb', endColorstr='#fff5f5f5', GradientType=0);
background-repeat: repeat-x;
}
.progress-bar {
background-image: -webkit-linear-gradient(top, #337ab7 0%, #286090 100%);
background-image: -o-linear-gradient(top, #337ab7 0%, #286090 100%);
background-image: -webkit-gradient(linear, left top, left bottom, from(#337ab7), to(#286090));
background-image: linear-gradient(to bottom, #337ab7 0%, #286090 100%);
filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff337ab7', endColorstr='#ff286090', GradientType=0);
background-repeat: repeat-x;
}
.progress-bar-success {
background-image: -webkit-linear-gradient(top, #5cb85c 0%, #449d44 100%);
background-image: -o-linear-gradient(top, #5cb85c 0%, #449d44 100%);
background-image: -webkit-gradient(linear, left top, left bottom, from(#5cb85c), to(#449d44));
background-image: linear-gradient(to bottom, #5cb85c 0%, #449d44 100%);
filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff5cb85c', endColorstr='#ff449d44', GradientType=0);
background-repeat: repeat-x;
}
.progress-bar-info {
background-image: -webkit-linear-gradient(top, #5bc0de 0%, #31b0d5 100%);
background-image: -o-linear-gradient(top, #5bc0de 0%, #31b0d5 100%);
background-image: -webkit-gradient(linear, left top, left bottom, from(#5bc0de), to(#31b0d5));
background-image: linear-gradient(to bottom, #5bc0de 0%, #31b0d5 100%);
filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff5bc0de', endColorstr='#ff31b0d5', GradientType=0);
background-repeat: repeat-x;
}
.progress-bar-warning {
background-image: -webkit-linear-gradient(top, #f0ad4e 0%, #ec971f 100%);
background-image: -o-linear-gradient(top, #f0ad4e 0%, #ec971f 100%);
background-image: -webkit-gradient(linear, left top, left bottom, from(#f0ad4e), to(#ec971f));
background-image: linear-gradient(to bottom, #f0ad4e 0%, #ec971f 100%);
filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#fff0ad4e', endColorstr='#ffec971f', GradientType=0);
background-repeat: repeat-x;
}
.progress-bar-danger {
background-image: -webkit-linear-gradient(top, #d9534f 0%, #c9302c 100%);
background-image: -o-linear-gradient(top, #d9534f 0%, #c9302c 100%);
background-image: -webkit-gradient(linear, left top, left bottom, from(#d9534f), to(#c9302c));
background-image: linear-gradient(to bottom, #d9534f 0%, #c9302c 100%);
filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ffd9534f', endColorstr='#ffc9302c', GradientType=0);
background-repeat: repeat-x;
}
.progress-bar-striped {
background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, .15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, .15) 50%, rgba(255, 255, 255, .15) 75%, transparent 75%, transparent);
background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, .15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, .15) 50%, rgba(255, 255, 255, .15) 75%, transparent 75%, transparent);
background-image: linear-gradient(45deg, rgba(255, 255, 255, .15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, .15) 50%, rgba(255, 255, 255, .15) 75%, transparent 75%, transparent);
}
.list-group {
border-radius: 4px;
-webkit-box-shadow: 0 1px 2px rgba(0, 0, 0, .075);
box-shadow: 0 1px 2px rgba(0, 0, 0, .075);
}
.list-group-item.active,
.list-group-item.active:hover,
.list-group-item.active:focus {
text-shadow: 0 -1px 0 #286090;
background-image: -webkit-linear-gradient(top, #337ab7 0%, #2b669a 100%);
background-image: -o-linear-gradient(top, #337ab7 0%, #2b669a 100%);
background-image: -webkit-gradient(linear, left top, left bottom, from(#337ab7), to(#2b669a));
background-image: linear-gradient(to bottom, #337ab7 0%, #2b669a 100%);
filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff337ab7', endColorstr='#ff2b669a', GradientType=0);
background-repeat: repeat-x;
border-color: #2b669a;
}
.list-group-item.active .badge,
.list-group-item.active:hover .badge,
.list-group-item.active:focus .badge {
text-shadow: none;
}
.panel {
-webkit-box-shadow: 0 1px 2px rgba(0, 0, 0, .05);
box-shadow: 0 1px 2px rgba(0, 0, 0, .05);
}
.panel-default > .panel-heading {
background-image: -webkit-linear-gradient(top, #f5f5f5 0%, #e8e8e8 100%);
background-image: -o-linear-gradient(top, #f5f5f5 0%, #e8e8e8 100%);
background-image: -webkit-gradient(linear, left top, left bottom, from(#f5f5f5), to(#e8e8e8));
background-image: linear-gradient(to bottom, #f5f5f5 0%, #e8e8e8 100%);
filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#fff5f5f5', endColorstr='#ffe8e8e8', GradientType=0);
background-repeat: repeat-x;
}
.panel-primary > .panel-heading {
background-image: -webkit-linear-gradient(top, #337ab7 0%, #2e6da4 100%);
background-image: -o-linear-gradient(top, #337ab7 0%, #2e6da4 100%);
background-image: -webkit-gradient(linear, left top, left bottom, from(#337ab7), to(#2e6da4));
background-image: linear-gradient(to bottom, #337ab7 0%, #2e6da4 100%);
filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff337ab7', endColorstr='#ff2e6da4', GradientType=0);
background-repeat: repeat-x;
}
.panel-success > .panel-heading {
background-image: -webkit-linear-gradient(top, #dff0d8 0%, #d0e9c6 100%);
background-image: -o-linear-gradient(top, #dff0d8 0%, #d0e9c6 100%);
background-image: -webkit-gradient(linear, left top, left bottom, from(#dff0d8), to(#d0e9c6));
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// This file is autogenerated via the `commonjs` Grunt task. You can require() this file in a CommonJS environment.
require('../../js/transition.js')
require('../../js/alert.js')
require('../../js/button.js')
require('../../js/carousel.js')
require('../../js/collapse.js')
require('../../js/dropdown.js')
require('../../js/modal.js')
require('../../js/tooltip.js')
require('../../js/popover.js')
require('../../js/scrollspy.js')
require('../../js/tab.js')
require('../../js/affix.js')

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var hover_emph = [];
var highlight_lock = false;
var last_sense_group = "";
$(document).ready(function() {
$.get("/letters", function(data, status) {
$("#letters").html(data);
});
$.get("/reduce_functions", function(data, status) {
$("#reduce-functions").html(data);
$("#reduce-functions input[type=radio]").change(function() {
get_frames(
$("#chosen-one").text()
);
})
//Click on the first radio button - for 100% up to date with the model.
var first_radio = $("#reduce-functions input[type=radio]:first");
first_radio.attr("checked", true)
get_frames($("#chosen-one").text());
});
handle_resizing();
})
window.onresize = handle_resizing;
function view_get_rf() {
return $("#reduce-functions").find("input:checked").val();
}
function get_words(letter) {
$.get("/words/" + letter, function(data, status){
$("#words").html(data);
})
}
function get_frames(word, reduce_function=null, modify_view=true, callback=null) {
if (word == "") {
return
}
if (reduce_function == null) {
reduce_function = view_get_rf();
}
$("#chosen-one").text(word);
var opt_rf = "";
if (reduce_function != null) {
opt_rf = "&rf=" + reduce_function;
}
$.get("/frames?hw=" + word + opt_rf, function(data, status) {
$("#frames-area").html(data);
$("#n-frames").text("število stavčnih vzorcev: " + $(".frame-div").length);
// Add functor highlighting
$(".functor-link")
.mouseover(function() {
highlight_linked($(this))
})
.mouseout(unhighlight_linked)
.click(function() {
toggle_highlight_lock($(this))
});
// modify sense information div
if (modify_view) {
$("#word-info-right").html("");
$(".frame-sense-id").hide();
$(".frame-sense-id").find("input").prop("disabled", true);
$(".frame-sense-desc").hide();
//$(".frame-sense-desc").find("input").prop("disabled", true);
switch (reduce_function) {
case "reduce_0":
case "reduce_1":
break;
case "reduce_3":
//ssj
$(".frame-sense-id").show();
$(".frame-sense-desc").show();
break;
case "reduce_4":
//kmeans
$(".frame-sense-id").show();
break;
case "reduce_5":
//user
user_input_menu(false);
$(".frame-sense-id").show();
break;
}
}
if (callback != null) {
callback();
}
});
}
function handle_resizing() {
$("#words").height( ($(document).height() - $("#words").position().top) * 0.95 );
}
function highlight_linked(dom_element) {
if (highlight_lock) {
return;
}
var frame_div = dom_element.parents(".frame-div");
var frame_table = frame_div.find(".frame-table");
var frame_sentences = frame_div.find(".frame-sentences");
var classes = dom_element.attr("class").split(" ");
classes.forEach(function(cls) {
if (cls == "functor-link") {
return
}
cls = cls.replace(".", "\\."); //escaping dots!
var frame_table_matches = frame_table.find("." + cls);
var frame_sentences_matches = frame_sentences.find("." + cls);
if (frame_table_matches.length > 0 && frame_sentences_matches.length > 0) {
var matches = $.merge(frame_table_matches, frame_sentences_matches);
matches.addClass("functor-highlight");
hover_emph.push(matches);
}
})
}
function unhighlight_linked() {
if (highlight_lock) {
return;
}
hover_emph.forEach(function(el) {
el.removeClass("functor-highlight");
})
hover_emph = [];
}
function toggle_highlight_lock(dom_element) {
if (
hover_emph.len == 0 ||
!dom_element.hasClass("functor-highlight")
) {
return;
}
highlight_lock = !highlight_lock;
}
function helper_highlight_ssj_id(pdiv, ssj_ids) {
hover_emph = []
for (var i=0; i<ssj_ids.length; i++) {
ssj_id = ssj_ids[i];
ssj_id = ssj_id.replace(".", "\\.");
ssj_id = "." + ssj_id;
matches = pdiv.find(ssj_id).toArray();
if (matches.length > 1) {
hover_emph = matches;
break;
}
}
hover_emph.forEach(function(element) {
$(element).css("color", "red");
});
}
function helper_clear_highlight_ssj_id() {
hover_emph.forEach(function(element) {
$(element).css("color", "");
});
hover_emph = []
}
function toggle_frame_sentences(el, sign=null) {
pdiv = el.parents(".frame-div");
fs = pdiv.find(".frame-sentences");
sign_element = pdiv.find(".sign-element");
if ((sign == "+") || (sign_element.text() == "[+]")) {
sign_element.text("[-]");
fs.show();
} else {
sign_element.text("[+]");
fs.hide();
}
}
function user_input_menu(new_entries) {
if (new_entries) {
var tmp_sense_group = $("#word-info-right").find("option:selected").text();
if (tmp_sense_group != "-- izberi --") {
last_sense_group = tmp_sense_group;
}
$("#word-info-right").html(
"<input type=text name='sense_group' \
placeholder='ime skupine pomenov' value='" + last_sense_group + "'></input>"
);
$("#word-info-right").append(
"<button onclick='user_input_finish(false)'>prekliči</button>"
)
$("#word-info-right").append(
"<input name='sense_passwd' \
type=password placeholder='geslo' value='" + getCookie("sense_passwd") + "'></input>"
)
$("#word-info-right").append(
"<button onclick='user_input_finish(true)'>shrani</button>"
)
get_frames($("#chosen-one").text(), "reduce_0", false, function() {
$(".frame-sense-id").find("input")
.prop("disabled", false)
.val("");
$(".frame-sense-id").show();
//$(".frame-sense-desc").find("input").prop("disabled", true);
$(".frame-sense-desc").hide();
toggle_frame_sentences($(".frame-sense"), "+");
//fill input fields with known sense_ids
$.get("/get_sense_ids?collname=user_senses&hw=" +
$("#chosen-one").text() +
"&sg=" + last_sense_group, function(data, status) {
data = JSON.parse(data);
$(".frame-div").each(function(idx, el) {
var jqel = $(el);
var ssj_id = jqel.find(".frame-hw-id").text();
if (ssj_id in data) {
jqel.find("input[name='sense_id']").val(data[ssj_id]);
}
});
});
});
} else {
$.get("/user_sense_groups/" + $("#chosen-one").text(), function(data, status){
$("#word-info-right").html(data);
$("#word-info-right").append(
"<button onclick='user_input_menu(true)'>novi pomeni</button>"
)
});
}
}
function user_input_finish(save) {
if (save) {
var sense_group = $("input[name='sense_group']").val().applyXSSprotection();
var sense_passwd = $("input[name='sense_passwd']").val().applyXSSprotection();
setCookie("sense_passwd", sense_passwd, 1);
last_sense_group = sense_group;
if (sense_group == "") {
user_input_finish(false);
return;
}
sense_data = {
"headword": $("#chosen-one").text(),
"sense_group": sense_group,
"sense_passwd": sense_passwd,
"entries": {},
}
$(".frame-div").each(function(index){
var sense_id = $(this).find("input[name='sense_id']").val().applyXSSprotection();
if (sense_id === "None") {
return;
}
var frame_data = {};
ssj_id = $(this).find(".frame-hw-id").text();
sense_data["entries"][ssj_id] = sense_id;
});
if (Object.keys(sense_data["entries"]).length > 0) {
$.ajax({
method: "POST",
url: "/user_senses",
data: JSON.stringify(sense_data),
async: false,
complete: function() {
pick_sense_group(sense_group);
}
});
}
//pick_sense_group(sense_group);
}
user_input_menu(false);
get_frames($("#chosen-one").text());
}
function pick_sense_group(sense_group, gf=false) {
last_sense_group = sense_group;
$.get("/pick_sense_group/" + sense_group, function(){
if (gf) {
get_frames($("#chosen-one").text());
}
});
}
String.prototype.applyXSSprotection = function(){
return this.replace(/</g, "&lt;").replace(/>/g, "&gt;");
};
function setCookie(cname, cvalue, exdays) {
var d = new Date();
d.setTime(d.getTime() + (exdays*24*60*60*1000));
var expires = "expires="+ d.toUTCString();
document.cookie = cname + "=" + cvalue + ";" + expires + ";path=/";
}
function getCookie(cname) {
var name = cname + "=";
var ca = document.cookie.split(';');
for(var i = 0; i < ca.length; i++) {
var c = ca[i];
while (c.charAt(0) == ' ') {
c = c.substring(1);
}
if (c.indexOf(name) == 0) {
return c.substring(name.length, c.length);
}
}
return "";
}

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html {
height: 95%;
}
body {
height: 95%;
display: flex;
flex-direction: column;
/* font-family: "Arial", Helvetica, sans-serif; */
background-color: var(--color-1);
}
div {
border: 0.0px solid gray;
}
#letters a, #words a, .frame-sentences-wrapper a {
text-decoration: none;
color: inherit;
font-weight: bold;
}
#letters a:hover, #words a:hover {
color: var(--color-1);
}
.monospace {
font-family: "Lucida Console", Monaco, monospace
}
#header h2 {
text-align: center;
}
#letters {
display: flex;
flex-wrap: wrap;
justify-content: space-evenly;
padding: 5px;
margin: 5px;
background-color: var(--color-3);
border-radius: 5px;
}
#letters span {
margin: 5px;
}
#words {
width: 200px;
overflow-y: scroll;
background-color: var(--color-3);
border-radius: 5px;
margin: 5px;
padding-top: 5px;
}
#main-body {
display: flex;
flex-direction: row;
}
#main-content {
flex-grow: 1;
margin: 5px;
display: flex;
flex-direction: column;
}
#reduce-functions {
background-color: var(--color-3);
padding: 5px;
margin-bottom: 5px;
border-radius: 5px;
}
#reduce-functions * {
display: inline-block;
}
#word-info {
background-color: var(--color-4);
border-top-left-radius: 5px;
border-top-right-radius: 5px;
margin-top: 5px;
padding: 5px;
}
#word-info-left {
display: inline-block;
float: left;
margin-right: 50px;
}
#word-info-right {
display: inline-block;
float: left;
}
#frames-area {
flex-grow: 1;
background-color: var(--color-2);
padding: 5px;
}
#words {
width: 200px;
overflow-y: scroll;
}
.frame-sense {
display: inline;
float: left;
height: 100%;
}
.frame-table {
display: inline;
float: left;
border-collapse: collapse;
border: 1px solid;
margin-right: 20px;
}
.frame-table td, th {
border-left: 1px solid;
border-right: 1px solid;
padding: 2px;
min-width: 50px;
max-width: 100px;
max-height: 200px;
}
.frame-sentences-wrapper {
clear: both;
}
.frame-sentences td {
padding-bottom: 10px;
}
/* Hide some data*/
/*
.frame-table tr:nth-child(2) {
display: none;
}
.frame-table tr:nth-child(3) {
display: none;
}
*/
.token-div {
margin-top: 10px;
margin-bottom: 5px;
}
.token-div td:nth-child(1) {
min-width: 100px;
}
.hw-highlight {
color: blue;
}
.functor-highlight {
color: red;
cursor: pointer;
}
/* CSS - Cascading Style Sheet */
/* Palette color codes */
/* Palette URL: http://paletton.com/#uid=13D0u0k7UUa3cZA5wXlaiQ5cFL3 */
/* Feel free to copy&paste color codes to your application */
/* As hex codes */
/* As RGBa codes */
.rgba-primary-0 { color: rgba(183,206,236,1) } /* Main Primary color */
.rgba-primary-1 { color: rgba(228,238,251,1) }
.rgba-primary-2 { color: rgba(206,223,245,1) }
.rgba-primary-3 { color: rgba(159,188,225,1) }
.rgba-primary-4 { color: rgba(135,168,211,1) }
/* Generated by Paletton.com © 2002-2014 */
/* http://paletton.com */
:root {
--color-0: #B7CEEC;
--color-1: #E4EEFB;
--color-2: #CEDFF5;
--color-3: #9FBCE1;
--color-4: #87A8D3;
}

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{% for frame in frames %}
<div class="frame-div">
<div hidden class="frame-hw-id">{{ frame.tids[0] }}</div>
<div class="frame-table-wrapper">
<table class="frame-table">
<tr>
{% for slot in frame.slots %}
<td><span class="functor-link {{ slot.tids|join(' ') }}">{{ slot.functor }}</span></td>
{% endfor %}
</tr>
<tr>
{% for slot in frame.slots %}
<td title="št. pojavitev/št. povedi">{{ slot.tids|length }}/{{ frame.tids|length }}</td>
{% endfor %}
</tr>
</table>
<table class="frame-sense">
<tr class="frame-sense-id">
<td>ID pomena: </td>
<td>
<input type="text" name="sense_id" value="{{ frame.sense_info.get('sense_id') }}">
</td>
</tr>
<tr class="frame-sense-desc">
<td>Opis pomena: </td>
<td>
<!--input type="text" name="sense_desc" value="{{ frame.sense_info.get('sense_desc') }}"-->
<ul>
{% set desc_arr = frame.sense_info.get('sense_desc') %}
{% if desc_arr is not none %}
{% for desc in desc_arr %}
<li>{{ desc }}</li>
{% endfor %}
{% endif %}
</ul>
</td>
</tr>
</table>
</div>
<div class="frame-sentences-wrapper">
<p><a class="monospace sign-element" href="javascript:void(0)" onClick="toggle_frame_sentences($(this))">[+]</a> št. stavkov: {{ frame.tids|length }}</p>
<div hidden class="frame-sentences">
<table>
{% for sentence in frame.sentences %}
<tr><td>
{% for token in sentence %}
{% if token[1]["word"] != None %}
{% set hwclass = "" %}
{% if token[0] in frame.tids %}
{% set hwclass = " hw-highlight" %}
{% endif %}
<span class="functor-link {{ token[0] }}{{ hwclass }}">{{ token[1]["word"] }} </span>
{% endif %}
{% endfor %}
</td></tr>
{% endfor %}
</table>
</div>
<hr />
</div>
</div>
{% endfor %}

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{% for frame in frames %}
<div class="frame-div">
<p>[{% for tid in frame.tids %}
<a href="javascript:void(0)" onClick="get_token_info('{{ tid }}', this)">{{ tid }}</a>
{% if not loop.last %}
,
{% endif %}
{% endfor %}]</p>
<table class="frame-table">
<tr>
{% for slot in frame.slots %}
<td class="{{ slot.tids|join(" ") }}">{{ slot.functor }}</td>
{% endfor %}
</tr>
<tr>
{% for slot in frame.slots %}
<td>{% for sh in slot.shallows %}
{{ sh }}
{% if not loop.last %}
,
{% endif %}
{% endfor %}</td>
{% endfor %}
</tr>
<tr>
{% for slot in frame.slots %}
<td>{% for tid in slot.tids %}
<a href="javascript:void(0)" onClick="get_token_info('{{ tid }}', this)">{{ tid }}</a>
{% if not loop.last %}
,
{% endif %}
{% endfor %}</td>
{% endfor %}
</tr>
</table>
<div class="token-div"></div>
<hr />
</div>
{% endfor %}

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<!DOCTYPE html>
<html>
<meta charset="utf-8">
<link rel=stylesheet type=text/css href="{{ url_for('static', filename='./lib/bootstrap/css/bootstrap.min.css') }}">
<link rel=stylesheet type=text/css href="{{ url_for('static', filename='style.css') }}">
<head>
<title>Leksikon</title>
</head>
<body>
<div id=header>
<h2>Leksikon vezljivosti slovenskih glagolov</h2>
<div id=letters></div>
</div>
<div id=main-body>
<div id=left>
<div id=words></div>
</div>
<div id=main-content>
<div id=reduce-functions></div>
<div id=word-info>
<div id=word-info-left>
<h3 id="chosen-one"></h3>
<p><span id="n-frames"></span></p>
</div>
<div id="word-info-right">
<!--button onclick="user_input_menu('new')">debug_button</button-->
</div>
</div>
<div id=frames-area></div>
</div>
</div>
<script src="{{ url_for('static', filename='./lib/jquery.min.js') }}"></script>
<script src="{{ url_for('static', filename='./lib/bootstrap/js/bootstrap.min.js') }}"></script>
<script src="{{ url_for('static', filename='script.js') }}"></script>
</body>
</html>

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{% for l in letters %}
<span>
<a href="javascript:get_words('{{ l[0] }}')">{{ l[0]|upper + "(" + l[1]|string + ")" }}</a>
</span>
{% endfor %}

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<div class="row">
<div class="container">
<div class="col-sm-2">Način prikaza:</div>
<div class="col-sm-10">
{% for k, e in reduce_functions.items() | sort(attribute="0") %}
<label class=radio-inline title="{{ e['desc'] }}"><input type="radio" name="rf" value="{{ k }}">{{ e["simple_name"] }}</label>
{% endfor %}
</div>
</div>
</div>

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<select>
<option disabled selected value>-- izberi --</option>
{% for sg in sense_groups %}
<option {% if sg == state_sense_group %}selected {% endif %}onclick="pick_sense_group('{{ sg }}', true)">{{ sg }}</option>
{% endfor %}
</select>

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{% set alphabet = ["A", "B", "C", "Č", "D", "E", "F", "G", "H", "I", "J", "K", "L", "M", "N", "O", "P", "R", "S", "Š", "T", "U", "V", "Z", "Ž"] %}
{% for i in range(0, alphabet|length - 1) %}
<span><a href="javascript:get_words('{{ alphabet[i] }}')">{{ alphabet[i] }}</a>, </span>
{% endfor %}
<a href="javascript:get_words('{{ alphabet[-1] }}')">{{ alphabet[-1] }}</a>

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<table>
<tr>
<td>{{ tid }}: </td>
<td>{{ token }}</td>
</tr>
<tr>
<td>Stavek: </td>
<td class="token-sentence">{% for token in sentence %}
<span title="{{ token[1] }}" class="{{ token[0] }}">{{ token[1]["word"] }}</span>
{% endfor %}</td>
</tr>
<tr>
<td>sense_ids: </td>
<td>{{ sense_ids }}</td>
</tr>
</table>

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<ul>
{% for w in words %}
<li>
<a href="javascript:get_frames('{{ w[0] }}')">{{ w[0] + " (" + w[1]|string + ")" }}
{# Star indicates sense data has been preprocessed. #}
{% if w[2] %}
{{ "*" }}
{% endif %}
</a>
</li>
{% endfor %}
</ul>

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<!DOCTYPE html><html><head><meta charset=utf-8><meta name=viewport content="width=device-width,initial-scale=1"><title>vue_frontend</title><link href=/static/css/app.8cc8ad5cf4cf830949529795eff01e7f.css rel=stylesheet></head><body><div id=app></div><script type=text/javascript src=/static/js/manifest.2ae2e69a05c33dfc65f8.js></script><script type=text/javascript src=/static/js/vendor.3ae5086c460a20dc799c.js></script><script type=text/javascript src=/static/js/app.abe281d88cb13e210c8b.js></script></body></html>

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src_diploma/setup.py Normal file
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from setuptools import setup
setup(
name='Valency',
version='0.1',
description='Valency lexicon of slovenian verbs.',
url='https://bitbucket.org/voje/diploma',
author='Kristjan Voje',
author_email='kristjan.voje@gmail.com',
license='MIT',
packages=['valency'], # where to look for __init__.py
install_requires=[
'bs4',
'requests',
'matplotlib',
'flask',
'nltk',
'pymongo',
'xmltodict',
'scipy',
'scikit-learn',
'polyglot',
'pyicu',
'pycld2',
'morfessor',
'flask-cors',
]
)

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#!/bin/bash
function echo_help () {
echo "
sherpa.sh
--help
--pack (zip watched files)
--unpack (unzip watched files)
--list (list watched files)
--build_vue (requires npm, builds vue_frontend for production)
"
}
function frontend_config () {
orig_path="$(pwd)"
cd ./vue_frontend/config/
if [[ $1 == "dev" ]]; then
cp config_dev.json config.json
elif [[ $1 == "pro" ]]; then
cp config_pro.json config.json
fi
echo "Using config: "
cat config.json
cd "${orig_path}"
}
function build_vue () {
echo "
API settings, pick a number:
----------------------------
1) development (API on localhost)
2) production (see conf. files in vue folder for IP settings)
"
read choice
if [ $choice == 1 ]; then
frontend_config "dev"
elif [ $choice == 2]; then
frontend_config "pro"
else
exit
fi
orig_path="$(pwd)"
cd ./vue_frontend
npm run build
cd "${orig_path}"
if [ -d ./flask_app/vue/dist ]; then
rm -r ./flask_app/vue/dist
fi
cp -r ./vue_frontend/dist/ ./flask_app/vue/
}
function unpack () {
orig_path="$(pwd)"
cd ../data/
unzip ./no_del_pickles.zip
cd "$orig_path"
}
function pack () {
orig_path="$(pwd)"
cd ../data/
zip -r no_del_pickles.zip ./no_del_pickles/
rm -r ./no_del_pickles
cd "$orig_path"
}
if [[ "$#" -eq 0 ]]; then
echo_help
fi
while [[ "$#" -gt 0 ]]; do
key="$1"
case "$key" in
--help)
echo_help
exit 0
;;
--pack)
pack
exit 0
;;
--unpack)
unpack
exit 0
;;
--build_vue)
build_vue
exit 0
;;
--frontend_config)
shift
arg1="$1"
frontend_config "$arg1"
exit 0
;;
*)
echo_help
exit 0
shift
esac
done

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# Drevesna struktura direktorija:
* data -- vhodne datoteke (sskj, ssj500k, slownet) (prazno)
* script -- izvorna koda
* flask_app -- zaledni del, backend
* app.py -- vhodna točka (main)
* valency -- modul za obdelavo vhodnih korpusov (glavna logika)
* seqparser -- orodje za razčlenjevanje vhodnega korpusa v .xml obliki
* dictionary_interface.py -- vmesnik za delo s slovarji v MongDB bazi
* evaluation.py -- algoritmi za evalvacijo
* rand_index()
* clustering_purity()
* ars() -- adjusted_rand_index sem uvozil iz sklearn.metrics
* frame.py -- objekt za valenčni okvir
* k_means.py -- algoritem k-voditeljev
* k_means()
* bkm() -- bisekcijski k-means
* silhouette_wrapper -- izračun silhuetne ocene
* kmeans_wrapper() -- kliče izbran algoritem k-means z različnimi vrednostmi K,
s pomočjo funkcije silhouette_wrapper() izbere najbolj optimalen K
* k_utils.py -- podporna orodja
* slo_bucket_sort() -- sort za slovenske besede
* stem_slo() -- približek korenjenja slovenskih besed
* leskFour.py -- implementacija štirih verzij Leskovega algoritma
* lesk_nltk()
* lesk_sl()
* lesk_al()
* lesk_ram()
* reduce_functions.py -- funkcije za združevanje vezljivostnih vzorcev (uporaljene v aplikaciji)
* ssj_struct.py -- vmesni objekt za branje korpusa
* sskj_scraper.py -- orodje za zbiranje podatkov iz spletnega SSKJ
* val_struct.py() -- objekt, ki predstavlja prebrani korpus
* vue_frontend -- uporabniški vmesnik

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*.pickle

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src_diploma/valency/__init__.py Normal file
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from valency import k_utils
import logging
from time import time
from valency.k_utils import dict_safe_key as dsk
from copy import deepcopy as DC
log = logging.getLogger(__name__)
# Upper limit for how many senses a lemma can have.
GUL = 20
SLOWNET_CACHE = "slownet_glosses_cache"
class DictionaryInterface:
def __init__(self, vallex, dictionary):
self.vallex = vallex
self.dictionary = "interface"
def find(self, lemma):
return []
def contains(self, lemma, upper_limit=GUL):
# useless. need to check if sense_glosses returns non empty list
res = self.find(lemma)
if upper_limit is not None and len(res) > upper_limit:
return False
return (len(res) is not 0)
def cached_glosses(self, lemma):
# preprocessed self_glosses (not used)
res = list(self.vallex.db.cached_glosses.find(
{"lemma": lemma, "dictionary": self.dictionary}))
if len(res) == 0:
return []
return res[0]["glosses"]
def sense_glosses(self, lemma):
# array: gloss for each sense
# gloss: {"gloss": ["<sense>", ...], "def": ["<sense"], ...}
return "dictionary_interface.py: not_yet_implemented"
# Recursively pull strgins out of a dictionary,
# based on a list of keys.
# uses self.recursion_buffer
def pull_strings_wrapper(self, element, keys):
if element is None:
return []
self.recursion_buffer = []
self.pull_strings(element, keys)
return self.recursion_buffer[:]
def pull_strings(self, element, keys):
# Recursively pull values out of a dict.
# correct key + element as string or list of strings
for k, e in element.items():
if k not in keys:
continue
if isinstance(e, dict):
self.pull_strings(e, keys)
elif isinstance(e, str):
self.recursion_buffer.append(e)
elif isinstance(e, list):
for ee in e:
if isinstance(ee, dict):
self.pull_strings(ee, keys)
elif isinstance(ee, str):
self.recursion_buffer.append(ee)
class Sskj(DictionaryInterface):
def __init__(self, vallex):
super().__init__(vallex, "sskj")
def find(self, lemma):
res = list(self.vallex.db.sskj.find(
{"ns0:entry.ns0:form.ns0:orth": lemma}
))
return res
def sense_glosses(self, lemma, upper_limit=GUL):
entries = self.find(lemma)
if upper_limit is not None and len(entries) > upper_limit:
log.info("sense_glosses({}): too many sense entries".format(lemma))
return []
senses = []
if len(entries) == 0:
return []
for e in entries:
senses.extend(dsk(
e["ns0:entry"], "ns0:sense"))
keys = [
"ns0:def", "ns0:cit", "ns0:quote",
"ns0:gloss", "ns0:sense", "ns0:orth",
"ns0:form", "#text"
]
glosses = []
for s in senses:
gloss = self.pull_strings_wrapper(s, keys)
if len(gloss) == 0:
continue
glosses.append({
"gloss": gloss,
"def": self.pull_strings_wrapper(s, ["ns0:sense", "ns0:def"])
})
return glosses
class SloWnet(DictionaryInterface):
def __init__(self, vallex):
super().__init__(vallex, "slownet")
self.hypernym_buffer = []
def slo_to_eng(self, lemma):
def helper_get_eng_lemmas(r):
res = []
for literal in dsk(r, "SYNONYM"):
if literal["@xml:lang"] == "en":
for lt in dsk(literal, "LITERAL"):
res.append(lt["#text"])
return res
# takes a slo token, returns array of english counterparts
results = self.find(lemma)
eng_lemmas = []
for r in results:
eng_lemmas.extend(helper_get_eng_lemmas(r))
return eng_lemmas
def helper_get_hypernyms(self, entry):
res = []
dd = dsk(entry, "ILR")
for d in dd:
if d["@type"] == "hypernym":
res.append(d["#text"])
return res
def helper_get_en_literals(self, entry):
res = []
synonyms = dsk(entry, "SYNONYM")
for syn in synonyms:
if syn["@xml:lang"] == "en":
literals = dsk(syn, "LITERAL")
for lit in literals:
res.append(lit["#text"])
return res
def rek_root_chain(self, slownet_id):
entry = self.find_by_id(slownet_id)
if entry is None:
return []
res = self.helper_get_en_literals(entry)
for hypernym_id in self.helper_get_hypernyms(slownet_id):
res.extend(self.rek_root_chain(hypernym_id))
return res
def root_chain(self, lemma):
cached = list(self.vallex.db.cached_root_chains.find({
"lemma": lemma
}))
if cached:
return cached[0]["data"]
res = self.slo_to_eng(lemma)
entries = self.find(lemma)
start_hypernym_ids = []
for ent in entries:
start_hypernym_ids.extend(self.helper_get_hypernyms(ent))
for shi in start_hypernym_ids:
res.extend(self.rek_root_chain(shi))
self.vallex.db.cached_root_chains.insert({
"lemma": lemma,
"data": res
})
return res
def find_by_id(self, slownet_id):
res = list(self.vallex.db.slownet.find({"ID": slownet_id}))
if len(res) == 0:
log.error("ID: {} not in db.slownet.".format(slownet_id))
return None
return res[0]
def find(self, lemma):
return list(self.vallex.db.slownet.find({"slo_lemma": lemma}))
"""
# elemMatch for array query
res = list(self.vallex.db.slownet.find({
"SYNONYM": {'$elemMatch': {
"LITERAL": {'$elemMatch': {"#text": lemma}}
}}
}))
"""
def hypernyms(self, slownet_id, level):
if level == 3:
return
elements = list(self.vallex.db.slownet.find({"ID": slownet_id}))
if len(elements) == 0:
return
for e in elements:
ei = self.extract_element_info(e)
self.hypernym_buffer.append({
"def": ei["domain"] + ei["def"],
"gloss": ei["domain"] + ei["def"] + ei["usage"]
})
for ilr in ei["ilr"]:
self.hypernyms(ilr, level + 1)
def extract_element_info(self, e):
domain = []
dd = dsk(e, "DOMAIN")
for d in dd:
domain.append(d)
definition = []
dd = dsk(e, "DEF")
for d in dd:
if d["@xml:lang"] == "en":
definition.append(d["#text"])
ilr = []
dd = dsk(e, "ILR")
for d in dd:
if d["@type"] == "hypernym":
ilr.append(d["#text"])
usage = []
dd = dsk(e, "USAGE")
for d in dd:
if d["@xml:lang"] == "en":
usage.append(d["#text"])
return {
"domain": domain,
"def": definition,
"ilr": ilr,
"usage": usage,
}
def sense_glosses(self, lemma, upper_limit=GUL):
# stime = time()
# caching
db_key = {
"lemma": lemma,
"upper_limit": upper_limit
}
cache = list(self.vallex.db[SLOWNET_CACHE].find(db_key))
if len(cache) > 0:
return cache[0]["data"]
entries = self.find(lemma)
if upper_limit is not None and len(entries) > upper_limit:
# log.info("sense_glosses({}): too many senses".format(lemma))
return []
ret_glosses = []
for e in entries:
defs = []
glosses = []
self.hypernym_buffer = []
ei = self.extract_element_info(e)
self.hypernym_buffer.append({
"def": ei["domain"] + ei["def"],
"gloss": ei["domain"] + ei["def"] + ei["usage"]
})
for ilr in ei["ilr"]:
self.hypernyms(ilr, 1)
[defs.extend(x["def"]) for x in self.hypernym_buffer]
[glosses.extend(x["gloss"]) for x in self.hypernym_buffer]
ret_glosses.append({
"def": defs,
"gloss": glosses,
})
# log.debug("slownet.sense_glosses({}): {:.2f}s".format(
# lemma, time() - stime))
# caching
db_entry = {
"lemma": db_key["lemma"],
"upper_limit": db_key["upper_limit"],
"data": ret_glosses
}
self.vallex.db.slownet_sense_glosses.update(
db_key, db_entry, upsert=True
)
return ret_glosses
class Sskj2(DictionaryInterface):
def __init__(self, vallex):
super().__init__(vallex, "sskj")
def find(self, lemma):
pos = "glagol"
if lemma[-1] == "_":
pos = "pridevnik"
res = list(self.vallex.db.sskj.find({
"izt_clean": lemma,
"pos": pos
}))
return res
def count_senses(self, lemma):
entries = self.find(lemma)
if len(entries) == 0:
return 0
ol = dsk(entries[0], "ol")
if len(ol) == 0:
return 1
return len(ol[0]["li"])
def sense_glosses(self, lemma, upper_limit=GUL):
def helper_dict_safe_add(dic, key, el):
if key not in dic:
dic[key] = []
dic[key].append(el)
def helper_pull_rec(el_lst, res_dct):
for el in el_lst:
if isinstance(el, dict):
if ("@title" in el) and ("#text" in el):
helper_dict_safe_add(
res_dct, el["@title"], el["#text"])
if "span" in el:
helper_pull_rec(dsk(el, "span"), res_dct)
if ("ol" in el) and ("li" in el["ol"]):
helper_pull_rec(el["ol"]["li"], res_dct)
if "li" in el:
helper_pull_rec(el["li"], res_dct)
entries = self.find(lemma)
if len(entries) == 0:
return []
if len(entries) > 1:
log.warning("{} entries for {} in sskj2.".format(
len(entries), lemma))
glosses_per_entry = []
for idx, entry in enumerate(entries):
res_dict = {}
if "span" in entry:
helper_pull_rec(dsk(entry, "span"), res_dict)
# senses
res_dict["senses"] = []
if ("ol" in entry) and ("li" in entry["ol"]):
for el in dsk(entry["ol"], "li"):
tmp = {"sskj_sense_id": el["span"][0]}
helper_pull_rec(dsk(el, "span"), tmp)
helper_pull_rec(dsk(el, "ol"), tmp)
res_dict["senses"].append(DC(tmp))
def helper_create_gloss(dct):
keys = ["Razlaga", "Zgled", "Stranska razlaga", "Sopomenka"]
ret = []
for k in keys:
ret.extend(dsk(dct, k))
return ret
glosses = []
n_senses = len(res_dict["senses"])
if n_senses == 0:
glosses.append({
"sskj_sense_id": "1-1",
"gloss": helper_create_gloss(res_dict),
"def": dsk(res_dict, "Razlaga")
})
return glosses
for sense in res_dict["senses"]:
glosses.append({
"sskj_sense_id": "{}-{}".format(
sense["sskj_sense_id"], n_senses),
"gloss": helper_create_gloss(sense),
"def": dsk(sense, "Razlaga")
})
glosses_per_entry.append(glosses)
# add entry_id before the_sense id
# entry_id-sskj_sense_id-n_senses
all_glosses = []
for idx, glosses in enumerate(glosses_per_entry):
entry_id = idx + 1 # start with 1
for gloss in glosses:
gloss["sskj_sense_id"] = "{}-{}".format(
entry_id, gloss["sskj_sense_id"])
all_glosses.append(gloss)
return all_glosses

96
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import logging
log = logging.getLogger(__name__)
class Frame():
def __init__(self, tids, deep_links=None, slots=None, hw=None):
self.hw = hw
self.tids = tids # list of tokens with the same hw_lemma
# Each tid = "S123.t123";
# you can get sentence with vallex.get_sentence(S123)
self.slots = []
if slots is None:
self.slots = self.init_slots(deep_links)
else:
self.slots = slots
self.sense_info = {}
self.sentences = None # Used for passing to view in app.py, get_frames
self.aggr_sent = None # Dictionary { hw: self.sentences idx }
def to_json(self):
ret = {
"hw": self.hw,
"tids": self.tids,
"slots": [slot.to_json() for slot in self.slots],
"sentences": self.sentences,
"aggr_sent": self.aggr_sent,
"sense_info": self.sense_info
}
return ret
def init_slots(self, deep):
slots = []
for link in deep:
slots.append(Slot(
functor=link["functor"],
tids=[link["to"]]
))
return slots
def sort_slots(self):
# ACT, PAT, alphabetically
srt1 = [
x for x in self.slots
if (x.functor == "ACT" or
x.functor == "PAT")
]
srt1 = sorted(srt1, key=lambda x: x.functor)
srt2 = [
x for x in self.slots
if (x.functor != "ACT" and
x.functor != "PAT")
]
srt2 = sorted(srt2, key=lambda x: x.functor)
self.slots = (srt1 + srt2)
def to_string(self):
ret = "Frame:\n"
ret += "sense_info: {}\n".format(str(self.sense_info))
ret += "tids: ["
for t in self.tids:
ret += (str(t) + ", ")
ret += "]\n"
if self.slots is not None:
ret += "slots:\n"
for sl in self.slots:
ret += (sl.to_string() + "\n")
return ret
class Slot():
# Each slot is identified by its functor (ACT, PAT, ...)
# It consists of different tokens.
def __init__(self, functor, tids=None, count=None):
self.functor = functor
self.tids = tids or []
self.count = count or 1
def to_string(self):
ret = "---- Slot:\n"
ret += "functor: {}\n".format(self.functor)
ret += "tids: ["
for t in self.tids:
ret += (str(t) + ", ")
ret += "]\n"
ret += "]\n"
ret += "----\n"
return ret
def to_json(self):
ret = {
"functor": self.functor,
"tids": self.tids,
"count": self.count
}
return ret

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import os
import pickle
import nltk
import random
from time import time
import string
from polyglot.text import Word
import logging
log = logging.getLogger(__name__)
sno = nltk.stem.SnowballStemmer("english")
def dict_safe_key(dic, key):
# Returns a list, no matter what.
# Transform 1 element into a list.
# Return key not found as empty list.
if (
dic is None or
key not in dic
):
return []
subdic = dic[key]
if not isinstance(subdic, list):
return [subdic]
return subdic
def pickle_dump(data, path):
with open(path, "wb") as file:
pickle.dump(data, file)
log.info("Dumped data to {}.".format(path))
return True
def pickle_load(path):
ret = None
if os.path.isfile(path):
with open(path, "rb") as file:
ret = pickle.load(file)
log.info("Loaded data from {}.".format(path))
return ret # Returns None in case of failure.
# Implemented bucket sort for alphabetically sorting slovenian words.
# Bucket sort >>>>>>>>>>>>>>>>>>>>
def gen_sbs_alphabet():
alphabet = "abcčdefghijklmnoprsštuvzž"
return {letter: (idx + 1) for idx, letter in enumerate(alphabet)}
slo_bucket_sort_alphabet = gen_sbs_alphabet()
def slo_bucket_sort(words, key=None):
if key is None:
def key(x):
return x
def alph_score(word, idx):
kword = key(word)
if idx >= len(kword):
return 0
return slo_bucket_sort_alphabet.get(kword[idx]) or 0
def list_to_bins(words, idx):
bins = [[] for i in range(len(slo_bucket_sort_alphabet.keys()) + 1)]
for word in words:
bins[alph_score(word, idx)].append(word)
return bins
def bins_to_list(bins):
lst = []
for b in bins:
for el in b:
lst.append(el)
return lst
maxLen = 0
for w in words:
if len(key(w)) > maxLen:
maxLen = len(key(w))
maxIdx = maxLen - 1
for idx in range(maxIdx, -1, -1):
bins = list_to_bins(words, idx)
words = bins_to_list(bins)
"""
print(idx)
def get_letter(idx, word):
kword = key(word)
if idx < len(kword):
return(kword[idx])
return "#"
print([(word, get_letter(idx, word)) for word in words])
"""
return words
# Bucket sort <<<<<<<<<<<<<<<<<<<<
def stem_slo(x):
# Simplified;
# Remove the last syllable.
w = Word(x, language="sl").morphemes
ret = "".join(w[:-1])
return ret
def stem_eng(x):
return sno.stem(x)
def tokenize(sentence, min_token_len=3, stem=None):
# input: sentence string
# output: list of token strings
if stem is None:
def stem(x):
return x
all_tokens = []
sent_txt = nltk.sent_tokenize(sentence)
for sent in sent_txt:
tokens = nltk.word_tokenize(sent)
all_tokens.extend(tokens)
res = []
for x in all_tokens:
if x in string.punctuation:
continue
stemmed = stem(x.lower())
if len(stemmed) >= min_token_len:
res.append(stemmed)
return res
def tokenize_multiple(str_list, min_token_len=3, stem=None):
# tstart = time()
res = []
for sentence in str_list:
res.extend(tokenize(sentence, min_token_len, stem))
# log.debug("tokenize_multiple: {:.2f}s".format(time() - tstart))
return res
def t_tokenize():
teststring = "This is a test sentence. I hope it works. .. Asdf. asdf ,,,;"
print(teststring)
res = tokenize(teststring, min_token_len=None)
print(res)
def permute_paths(list2d, x=None, y=None, paths=None, current_path=None):
# python stuff
if x is None:
x = -1
if paths is None:
paths = []
if current_path is None:
current_path = []
if x >= len(list2d) - 1:
paths.append(current_path)
return paths
for i in range(len(list2d[x + 1])):
tmp_path = current_path + [(x + 1, i)]
# Computational complexity peoblem (prune long lists)
# len == 12 -> 30%, len == 5 -> 100%
# if random.randint(0, 100) <= (100 - 10 * (len(list2d) - 5)):
if True:
paths = permute_paths(
list2d,
x + 1,
i,
paths,
tmp_path
)
return paths
def t_permute_paths():
list2d = [
["Greta"],
["backflips"],
["through", "around"],
["North Korea", "kindergarten"],
["with", "without"],
["a"],
["bag of", "abundance of"],
["bolts", "janitors"]
]
print(list2d)
paths = permute_paths(list2d=list2d)
for path in paths:
print([list2d[p[0]][p[1]] for p in path])
def find_overlaps(list_a, list_b):
# Input: two lists.
# Output: lists of overlapping elements.
dict_a = {}
dict_b = {}
lists = [list_a, list_b]
dicts = [dict_a, dict_b]
for lidx in range(len(lists)):
for elidx in range(len(lists[lidx])):
el = lists[lidx][elidx]
if el not in dicts[lidx]:
dicts[lidx][el] = []
dicts[lidx][el].append(elidx)
substrings = []
sda = sorted(dict_a.keys())
sdb = sorted(dict_b.keys())
i_sda = 0
i_sdb = 0
while ((i_sda < len(sda) and i_sdb < len(sdb))):
if sda[i_sda] == sdb[i_sdb]:
lia = dict_a[sda[i_sda]]
lib = dict_b[sdb[i_sdb]]
for llia in lia:
for llib in lib:
tmp_substr = []
ii = 0
while (
(llia + ii < len(list_a)) and
(llib + ii < len(list_b)) and
(list_a[llia + ii] == list_b[llib + ii])
):
tmp_substr.append(list_a[llia + ii])
ii += 1
ii = 1
while (
(llia - ii >= 0) and
(llib - ii >= 0) and
(list_a[llia - ii] == list_b[llib - ii])
):
tmp_substr.insert(0, list_a[llia - ii])
ii += 1
substrings.append(tmp_substr)
if sda[i_sda] < sdb[i_sdb]:
i_sda += 1
else:
i_sdb += 1
uniques = set()
res = []
for ss in substrings:
if str(ss) not in uniques:
uniques.add(str(ss))
res.append(ss)
return res
def find_overlaps_str(tokens_a, tokens_b):
# Strings only.
overlaps = []
for N in range(1, 5):
ngrams_a = []
for i in range(len(tokens_a)):
if i + N <= len(tokens_a):
ngrams_a.append(tuple(tokens_a[i:i + N]))
ngrams_b = []
for i in range(len(tokens_b)):
if i + N <= len(tokens_b):
ngrams_b.append(tuple(tokens_b[i:i + N]))
overlaps.extend(list(set(ngrams_a).intersection(set(ngrams_b))))
res = []
for ovl in sorted(overlaps, key=lambda x: len(x), reverse=True):
oovl = " ".join(ovl)
for r in res:
if oovl in r:
break
else:
res.append(oovl)
res[:] = [x.split(" ") for x in res]
return res
def t_find_overlaps():
res = []
input_len = [10, 100, 1000, 10000]
for ll in input_len:
alen = ll + int(ll * random.uniform(0.8, 1))
blen = ll + int(ll * random.uniform(0.8, 1))
a = [random.randint(0, 100) for x in range(alen)]
b = [random.randint(0, 100) for x in range(blen)]
tstart = time()
find_overlaps(a, b)
res.append({
"time": time() - tstart,
"input_size": ll
})
"""
list_a = [6, 6, 4, 8, 3, 2, 2, 5, 6, 3, 4, 7, 5]
list_b = [5, 3, 6, 8, 6, 6, 5, 3, 2, 6, 7, 8, 3, 2, 3, 2, 2, 5]
res = find_overlaps(list_a, list_b)
"""
for r in res:
print(r)
def t1_find_overlaps():
t1 = "This is a test sentence. I hope it works. .. Asdf. asdf ,,,;"
t2 = "this is a seconde sentence. I hope my stuff works."
print(t1)
print(t2)
res = find_overlaps(tokenize(t1), tokenize(t2))
for r in res:
print(r)
print()
res = find_overlaps_str(tokenize(t1), tokenize(t2))
for r in res:
print(r)
def t_find_overlaps_str():
t1 = [
'vsa', 'moja', 'možganska', 'beda', 'se', 'združuje',
'v', 'dejstvu', 'da', 'sem', 'si', 'čeprav', 'sem', 'pozabil',
'ulico', 'zapomnil', 'hišno', 'številko'
]
t2 = [
'narediti', 'doseči', 'da', 'se', 'kaj', 'aktivno', 'ohrani',
'v', 'zavesti', 'zapomniti', 'si', 'imena', 'predstavljenih',
'gostov', 'dobro', 'natančno', 'slabo', 'si', 'kaj', 'zapomniti',
'takega', 'sem', 'si', 'zapomnil', 'zapomnite', 'te', 'prizore'
]
res = find_overlaps(t1, t2)
print(res)
def t_slo_bucket_sort():
a1 = []
a2 = []
with open("./tests/m_besede2.txt") as f:
for line in f:
a1.append(line.split("\n")[0])
a2.append((line.split("\n")[0], random.randint(0, 9)))
a1 = slo_bucket_sort(a1)
a2 = slo_bucket_sort(a2, key=lambda x: x[0])
check = True
for i in range(len(a1)):
check &= (a1[i] == a2[i][0])
print("{:<10}{:>10}".format(str(a1[i]), str(a2[i])))
print(check)
def t1_slo_bucket_sort():
words = "_xyz zebra. .bober raca bor borovnica antilopa".split(" ")
words.append("test space")
words.append("test srrrr")
words.append("test saaa")
for w in slo_bucket_sort(words):
print(w)
if __name__ == "__main__":
# t_find_overlaps()
# t1_find_overlaps()
# t_tokenize()
# t_find_overlaps_str()
t1_slo_bucket_sort()

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import pymongo
import xmltodict
import xml.etree.ElementTree as ET
from time import time
import json
from valency.sskj_scraper import SskjScraper
from bs4 import BeautifulSoup
# Get rid of accented characters.
intab = "ÁÉÍÓÚàáäçèéêìíîñòóôöùúüčŔŕ"
outtb = "AEIOUaaaceeeiiinoooouuučRr"
transtab = str.maketrans(intab, outtb)
def mongo_test():
client = pymongo.MongoClient(
"mongodb://{}:{}@127.0.0.1:26633/texts".format("kristjan", "simple567")
)
db = client.texts
coll = db.test
print(coll.find_one())
def basic_connection(ip_addr=None, port=None):
if ip_addr is None:
ip_addr = "127.0.0.1"
if port is None:
port = 26644
client = pymongo.MongoClient(
"mongodb://{}:{}@{}:{}/texts".format(
"kristjan", "simple567", ip_addr, str(port))
)
err_msg = "OK"
try:
client.server_info()
except pymongo.errors.ServerSelectionTimeoutError as err:
err_msg = err
return (None, err_msg)
db = client.texts
return (db, err_msg)
def check_collections(db, coll_names):
collections = db.collection_names()
for cn in coll_names:
if cn not in collections:
db.create_collection(cn)
def prepare_user_tokens(db):
CNAME = "v2_user_tokens"
db[CNAME].drop()
db.create_collection(CNAME)
EXPIRE = 151200 # 2 days
# EXPIRE = 10 # 10 sec
db[CNAME].ensure_index("date", expireAfterSeconds=EXPIRE)
# user this: utc_timestamp = datetime.datetime.utcnow()
# user_tokens.insert({
# '_id': 'utc_session', "date": utc_timestamp,
# "session": "test session"})
def sskj_to_mongo(sskj_path):
# Deprecated, use sskj2_to_mongo
ns = {"tei": "http://www.tei-c.org/ns/1.0"}
ts = time()
sskj = ET.parse(sskj_path).getroot()
db = basic_connection()
col_names = ["sskj"]
for cn in col_names:
if cn in db.collection_names():
db[cn].drop()
text = sskj.find("tei:text", ns)
body = text.find("tei:body", ns)
n_ent = 0
for entry in body.findall("tei:entry", ns):
n_ent += 1
tmpstr = ET.tostring(entry)
datachunk = xmltodict.parse(tmpstr)
dictchunk = json.loads(json.dumps(datachunk))
"""
pp = pprint.PrettyPrinter()
pp.pprint(dictchunk)
"""
db.sskj.insert(dictchunk)
# iskanje: db.sskj.find({'ns0:entry.ns0:form.ns0:orth':"kaplanček"})
print("sskj to mongo: {} entries in {:.2f}s".format(n_ent, time() - ts))
def slownet_to_mongo(slw_path):
# .slownet contains the database from .xml file
# added toplevel field ["slo_lemma"] for faster querying
ts = time()
slownet = ET.parse(slw_path).getroot()
db = basic_connection()
col_names = ["slownet_map", "slownet"]
for cn in col_names:
if cn in db.collection_names():
db[cn].drop()
slo_to_id = {}
for synset in slownet.findall("SYNSET"):
tmpstr = ET.tostring(synset)
datachunk = xmltodict.parse(tmpstr)
dictchunk = json.loads(json.dumps(datachunk))
dictchunk = dictchunk["SYNSET"]
# pp.pprint(dictchunk)
# insert into slo_ti_id
if "SYNONYM" in dictchunk:
synonyms = dictchunk["SYNONYM"]
if not isinstance(synonyms, list):
synonyms = [synonyms]
for syn in synonyms:
if syn["@xml:lang"] == "sl":
if "LITERAL" in syn:
literals = syn["LITERAL"]
if not isinstance(literals, list):
literals = [literals]
for lit in literals:
slo_keyword = lit["#text"]
if "." in slo_keyword:
continue
if "slo_lemma" not in dictchunk:
dictchunk["slo_lemma"] = []
dictchunk["slo_lemma"].append(slo_keyword)
db.slownet.insert(dictchunk)
# pp.pprint(slo_to_id)
db.slownet.ensure_index([("id", pymongo.ASCENDING)])
db.slo_to_id.insert(slo_to_id)
print("sloWNet to mongo in {:.2f}s".format(time() - ts))
def scrape_sskj():
# Deprecated!
# Walk through keys in slo_to_id and scrape sskj data.
client = pymongo.MongoClient(
"mongodb://{}:{}@127.0.0.1:26633/texts".format("kristjan", "simple567")
)
db = client.texts
words_list = sorted(db.slo_to_id.find_one())
print(len(words_list))
sscraper = SskjScraper()
last_word = "nogometaš"
db.scraped_sskj.remove({"word": last_word})
lock = True
for word in words_list:
if word == last_word:
lock = False
if not lock:
res = sscraper.scrape(word)
if len(res) > 0:
db.scraped_sskj.insert({"word": word, "bag": res})
def sskj2_to_mongo(sskj2_path):
tstart = time()
db = basic_connection()
col_names = ["sskj2"]
for cn in col_names:
if cn in db.collection_names():
db[cn].drop()
with open(sskj2_path) as f:
soup = BeautifulSoup(f.read(), "html.parser")
divs = soup.find_all("div")
for i, div in enumerate(divs):
if (i) % 100 == 0:
print("{}/{}".format(i, len(divs)))
datachunk = xmltodict.parse(str(div))
datachunk = datachunk["div"]
# pos (besedna vrsta)
pos_keywords = {
"samostalnik": 0,
"pridevnik": 0,
"glagol": 0,
"prislov": 0,
"predlog": 0,
"členek": 0,
"veznik": 0,
"medmet": 0,
"povedkovnik": 0
}
for span in div.find_all("span"):
attrs = [e for k, e in span.attrs.items()]
for attr in attrs:
for ak in attr.split(" "):
akl = ak.lower()
if akl in pos_keywords:
pos_keywords[akl] += 1
pos = "unknonw"
pos_max = 0
for k, e in pos_keywords.items():
if e > pos_max:
pos = k
pos_max = e
datachunk["pos"] = pos
# izt_clean
izts = div.find_all("span", {"title": "Iztočnica"})
if len(izts) == 0:
print("Entry {} has no Iztočnica.".format(i))
continue
izt = ((izts[0].text).translate(transtab)).lower()
ispl = izt.split(" ")
has_se = False
if len(ispl) and ispl[-1] == "se":
izt = " ".join(ispl[:-1])
has_se = True
datachunk["izt_clean"] = izt
datachunk["has_se"] = has_se
dictchunk = json.loads(json.dumps(datachunk))
db.sskj.insert(dictchunk)
db.sskj.create_index([("izt_clean", pymongo.TEXT)])
print("sskj2 to mongo: {} entries in {:.2f}s".format(
len(divs), time() - tstart))
return None
if __name__ == "__main__":
# slownet_path = "../../data/slownet/slownet-2015-05-07.xml"
# slownet_to_mongo(slownet_path)
# scrape_sskj()
# sskj_path = "../../data/sskj/sskj.p5.xml"
# sskj_to_mongo(sskj_path)
# first file for testing, the original file takes up most of RAM
# sskj2_path = "../../data/sskj/sskj2_200.html"
# sskj2_path = "../../data/sskj/sskj2_v1.html"
# sskj2_to_mongo(sskj2_path)
print("nothing here")

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# Reduction function for frames.
# Input: list of Frame objects, output: list of Frame objects.
# App uses reduce_0, 1 and 5
from valency.frame import Frame, Slot
from copy import deepcopy as DC
import logging
log = logging.getLogger(__name__)
SENSE_UNDEFINED = "nedefinirano"
def sorted_by_len_tids(frames):
return sorted(
frames,
key=lambda x: len(x.tids),
reverse=True
)
def reduce_0(frames, vallex=None):
# new request... frames should be sorded by
# functors list (basically reduce_1, just each
# sentence gets its own frame)
r1_frames = reduce_1(frames)
sorting_strings = []
separated_frames = []
for frame in r1_frames:
for tid in frame.tids:
tmp_frame = DC(frame)
tmp_frame.tids = [tid]
separated_frames.append(tmp_frame)
sorting_strings.append("".join(
[slot.functor for slot in tmp_frame.slots]
))
permutation = [x for _, x in sorted(
zip(sorting_strings, range(len(sorting_strings))))]
sorted_sep_frames = [separated_frames[i] for i in permutation]
return sorted_sep_frames
def reduce_1(frames, vallex=None):
# Combine frames with the same set of functors.
# The order of functors is not important.
frame_sets = [] # [set of functors, list of frames]
for frame in frames:
functors = [slot.functor for slot in frame.slots]
for fs in frame_sets:
if set(functors) == set(fs[0]):
fs[1].append(frame)
break
else:
# Python for else -> fires if loop has ended.
frame_sets.append([functors, [frame]])
ret_frames = []
for fs in frame_sets:
tids = []
slots = {}
# All possible slots in this frame.
for functor in fs[0]:
slots[functor] = Slot(functor=functor)
# Reduce slots from all frames. (Merge ACT from all frames, ...)
for frame in fs[1]:
tids += frame.tids
for sl in frame.slots:
slots[sl.functor].tids += sl.tids
slots_list = []
for k, e in slots.items():
slots_list.append(e)
rf = Frame(tids=tids, slots=slots_list)
rf.sort_slots()
ret_frames.append(rf)
return sorted_by_len_tids(ret_frames)
def reduce_3(raw_frames, vallex):
# sskj simple lesk ids
ssj_ids = [frame.tids[0] for frame in raw_frames]
db_results = list(vallex.db.sskj_simple_lesk.find(
{"ssj_id": {"$in": ssj_ids}}))
id_map = {}
for entry in db_results:
id_map.update({entry["ssj_id"]: {
"sense_id": entry.get("sense_id"),
"sense_desc": entry.get("sense_desc")
}})
return frames_from_sense_ids(raw_frames, id_map)
def reduce_4(raw_frames, vallex):
# kmeans ids
ssj_ids = [frame.tids[0] for frame in raw_frames]
db_results = list(vallex.db.kmeans.find(
{"ssj_id": {"$in": ssj_ids}}))
id_map = {}
for entry in db_results:
id_map.update({entry["ssj_id"]: {
"sense_id": entry["sense_id"]
}})
return frames_from_sense_ids(raw_frames, id_map)
def reduce_5(raw_frames, vallex):
USER_SENSE_COLL = "v2_sense_map"
headword = raw_frames[0].hw
ssj_ids_full = [frame.tids[0] for frame in raw_frames]
# v2_sense_map stores only sentence half of ssj_id
ssj_ids = [".".join(ssj_id.split(".")[:-1]) for ssj_id in ssj_ids_full]
db_results = list(vallex.db[USER_SENSE_COLL].find({
"ssj_id": {"$in": ssj_ids},
"hw": headword,
}))
id_map = {}
for entry in db_results:
id_map[entry["ssj_id"]] = entry["sense_id"]
ret_frames = frames_from_sense_ids(raw_frames, id_map)
# sort: frames with senses to top
senses_undefined = []
senses_defined = []
for frame in ret_frames:
if frame.sense_info["sense_id"] == SENSE_UNDEFINED:
senses_undefined.append(frame)
else:
senses_defined.append(frame)
ret_frames = senses_defined + senses_undefined
return ret_frames
def frames_from_sense_ids(raw_frames, id_map):
# id map = dict {
# ssj_id: sense_id
# }
# id_dict = dict {
# sense_id: [frame, ...]
# }
id_dict = {}
for frame in raw_frames:
# long version ssj_id (S123.t12)
frame_ssj_id = frame.tids[0]
frame_sense_id = id_map.get(frame_ssj_id)
if frame_sense_id is None:
# try short version ssj_id (S123)
frame_ssj_id = ".".join(frame_ssj_id.split(".")[:-1])
frame_sense_id = id_map.get(frame_ssj_id)
# set default if sense_id not found
if frame_sense_id is None:
frame_sense_id = SENSE_UNDEFINED
"""
sense_id = id_map.get(frame.tids[0])
if sense_id is not None:
sense_id = sense_id.get("sense_id")
else:
sense_id = "nedefinirano"
"""
if frame_sense_id not in id_dict:
id_dict[frame_sense_id] = []
id_dict[frame_sense_id].append(DC(frame))
ret_frames = []
for sense_id, frames in id_dict.items():
tids = []
reduced_slots = []
for frame in frames:
tids.extend(frame.tids)
for slot in frame.slots:
# if functor not in reduced slots,
# add new slot; else increase count
for rslot in reduced_slots:
if slot.functor == rslot.functor:
rslot.count += 1
rslot.tids.extend(slot.tids)
break
else:
# in case for loop didn't match a slot
reduced_slots.append(Slot(
functor=slot.functor,
tids=slot.tids,
count=1
))
reduced_frame = Frame(tids, slots=reduced_slots)
id_map_entry = (
id_map.get(tids[0]) or
id_map.get(".".join(tids[0].split(".")[:-1]))
)
if id_map_entry is None:
reduced_frame.sense_info = {
"sense_id": SENSE_UNDEFINED,
}
else:
reduced_frame.sense_info = {
"sense_id": id_map_entry
}
reduced_frame.sort_slots()
ret_frames.append(reduced_frame)
return ret_frames
reduce_functions = {
"reduce_0": {
"f": reduce_0,
"desc":
"Vsaka pojavitev glagola dobi svoj stavčni vzorec.",
"simple_name": "posamezni stavki"
},
"reduce_1": {
"f": reduce_1,
"desc":
"Združevanje stavčnih vzorcev z enako skupino udeleženskih vlog.",
"simple_name": "združeni stavki"
},
"reduce_3": {
"f": reduce_3,
"desc":
"Združevanje stavčnih vzorcev na osnovi pomenov povedi v SSKJ. "
"Pomeni so dodeljeni s pomočjo algoritma Simple Lesk.",
"simple_name": "SSKJ_pomeni"
},
"reduce_4": {
"f": reduce_4,
"desc":
"Združevanje stavčnih vzorcev na osnovi pomenov povedi "
"s pomočjo algoritma K-Means. Število predvidenih pomenov "
"podano na osnovi SSKJ.",
"simple_name": "KMeans_pomeni"
},
"reduce_5": {
"f": reduce_5,
"desc":
"Uporabniško dodeljeni pomeni povedi.",
"simple_name": "po meri"
}
}

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src_diploma/valency/seqparser/__init__.py Normal file
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src_diploma/valency/seqparser/seqparser.py Normal file
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from bs4 import BeautifulSoup as BS
import re
from collections import defaultdict
from time import time
import pickle
import json
from copy import deepcopy as DC
# Match sese ordinals (1., 2., ...)
rord = re.compile(r"^ *[0-9]+\. *$")
# Get rid of accented characters.
intab = "ÁÉÍÓÚàáäçèéêìíîñòóôöùúüčŔŕ"
outtb = "AEIOUaaaceeeiiinoooouuučRr"
transtab = str.maketrans(intab, outtb)
class Seqparser:
def __init__(self):
pass
# main functions
def html_to_raw_pickle(self, sskj_html_filepath, raw_pickle_filepath):
entries = dict(self.parse_file(sskj_html_filepath, self.parse_line))
print("entries len: " + str(len(entries)))
with open(raw_pickle_filepath, "wb") as f:
tmpstr = json.dumps(dict(entries))
pickle.dump(tmpstr, f)
# debugging
def raw_pickle_to_parsed_pickle(
self, raw_pickle_filepath, parsed_pickle_filepath,
se_list_filepath
):
data = self.load_raw_pickle(raw_pickle_filepath)
print("raw_pickle data len: " + str(len(data)))
se_list = self.gen_se_list(data)
print("se_list len: " + str(len(se_list)))
with open(se_list_filepath, "wb") as f:
pickle.dump(se_list, f)
data1 = self.remove_se(data)
data2 = self.reorganize(data1, se_list)
print("data2 len: " + str(len(data2.keys())))
with open(parsed_pickle_filepath, "wb") as f:
pickle.dump(data2, f)
# helper html reading functions
def parse_file(self, path, f_parse_line):
tstart = time()
entries = defaultdict(list)
with open(path, "r") as f:
for line in f:
data = f_parse_line(line)
if data is not None:
entries[data["izt_clean"]].append(data)
print("parse_file({}) in {:.2f}s".format(path, time() - tstart))
return entries
def parse_line(self, line):
def helper_bv_set(g_or_p):
if g_or_p not in ["G", "P"]:
print("Err g_or_p.")
exit(1)
if data.get("bv") is not None:
if data["bv"] != g_or_p:
print(str(line))
# exit(1)
data["bv"] = g_or_p
data = {
"izt": "",
"izt_clean": "",
"senses": defaultdict(list)
}
soup = BS(line, "html.parser")
current_sense_id = "0"
for span in soup.find_all("span"):
# sense id
if span.string is not None:
rmatch = rord.match(span.string)
if rmatch is not None:
current_sense_id = rmatch.group().strip()
title = span.attrs.get("title")
if title is not None:
title = title.lower()
# only verbs and adjectives
if "glagol" in title:
helper_bv_set("G")
data["bv_full"] = title
elif "pridevn" in title:
helper_bv_set("P")
data["bv_full"] = title
# žšč
if title == "iztočnica":
data["izt"] = span.string
data["izt_clean"] = span.string.translate(transtab).lower()
# sense description
if title == "razlaga" and span.string is not None:
data["senses"][current_sense_id].append(
("razl", span.string))
if "pridevnik od" in span.string:
helper_bv_set("P")
if title == "sopomenka":
subspan = span.find_all("a")[0]
if subspan.string is not None:
data["senses"][current_sense_id].append(
("sopo", subspan.string))
# save verbs and adjectives
if (
("bv" not in data) or
(data["bv"] != "P" and data["bv"] != "G")
):
return None
# sanity check
if data["bv"] == "P" and " se" in data["izt_clean"]:
print(data)
exit(1)
# append _ to adjective keywords
if data["bv"] == "P":
data["izt_clean"] = data["izt_clean"] + "_"
# cleanup
if "bv" not in data:
print("Should not be here (no bv).")
exit(1)
del(data["bv"])
if "bv_full" in data:
del(data["bv_full"])
return data
# helper functions
def load_raw_pickle(self, raw_pickle_filepath):
with open(raw_pickle_filepath, "rb") as f:
tmpstr = pickle.load(f)
return json.loads(tmpstr)
def helper_loop(self, data, fnc):
for k, lst in data.items():
for el in lst:
fnc(el)
def gen_se_list(self, data):
def fnc1(el):
ic = el["izt_clean"]
if " se" in ic:
se_list.append(ic)
def fnc2(el):
ic = el["izt_clean"]
if ic in se_pruned:
se_pruned.remove(ic)
# hw entries that only exist with " se"
se_list = []
self.helper_loop(data, fnc1)
se_pruned = set([hw.split(" se")[0] for hw in se_list])
self.helper_loop(data, fnc2)
return sorted(list(se_pruned))
def remove_se(self, data):
def fnc1(el):
nel = DC(el)
ic = nel["izt_clean"]
if " se" in ic:
nic = ic.split(" se")[0]
nel["izt_clean"] = nic
data_new[nel["izt_clean"]].append(nel)
data_new = defaultdict(list)
self.helper_loop(data, fnc1)
return dict(data_new)
def reorganize(self, data, se_list):
# some hw entries have several headwords,
# some senses have subsenses
# index everything, make 1 object per hw
def helper_prune(sense_str):
# remove space padding
sense_str = sense_str.strip()
if len(sense_str) == 1:
return sense_str
# remove banned characters from string ending
banned = ": ; . , - ! ?".split(" ")
if sense_str[-1] in banned:
return sense_str[:-1]
return sense_str
data_new = {}
for k, lst in data.items():
new_el = {
"hw": k,
"has_se": k in se_list,
"senses": []
}
# if there is a single hw entry, hw_id is 0
if len(lst) == 1:
homonym_id = -1
else:
homonym_id = 0
# loop homonyms
for el in lst:
homonym_id += 1
# loop top lvl sense ids
for sense_id, sens_lst in el["senses"].items():
# loop subsenses
for i, sens in enumerate(sens_lst):
nsid = sense_id.split(".")[0]
if len(sens_lst) == 1:
nsid += "-0"
else:
nsid += ("-" + str(i + 1))
new_sense = {
"homonym_id": homonym_id,
# sense_id: sense_id-subsense_id
"sense_id": nsid,
"sense_type": sens[0],
"sense_desc": helper_prune(sens[1]),
}
new_el["senses"].append(new_sense)
hw = new_el["hw"]
if hw in data_new:
print("Shouldn't be here.")
print(new_el)
exit(1)
data_new[hw] = DC(new_el)
# return data_new
# check
for hw, el in data_new.items():
for sens in el["senses"]:
if sens["sense_desc"] is None:
print(sens)
return data_new
def plst(lst):
for el in lst:
print(el)
if __name__ == "__main__":
datapath = "../../../data"
html_filepath = datapath + "/sskj/sskj2_v1.html"
raw_pickle_filepath = datapath + "/tmp_pickles/raw_sskj.pickle"
parsed_pickle_filepath = datapath + "/no_del_pickles/sskj_senses.pickle"
se_list_filepath = datapath + "/no_del_pickles/se_list.pickle"
p = Seqparser()
if True:
print("html_to_raw_pickle({}, {})".format(
html_filepath, raw_pickle_filepath))
print("Big file, this might take a while (2 min).")
tstart = time()
p.html_to_raw_pickle(html_filepath, raw_pickle_filepath)
print("Finished in {:.2f}.".format(time() - tstart))
if True:
print("raw_pickle_to_parsed_pickle({}, {}, {})".format(
raw_pickle_filepath, parsed_pickle_filepath, se_list_filepath))
tstart = time()
p.raw_pickle_to_parsed_pickle(
raw_pickle_filepath, parsed_pickle_filepath, se_list_filepath)
print("Finished in {:.2f}.".format(time() - tstart))
print("Done.")

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src_diploma/valency/ssj_struct.py Normal file
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import xml.etree.ElementTree as ET
from copy import deepcopy as DC
from time import time
import re
import logging
import sys
import pickle
log = logging.getLogger(__name__)
ET.register_namespace("xml", "http://www.w3.org/XML/1998/namespace")
XML_ID = "{http://www.w3.org/XML/1998/namespace}id"
# |$ for a default empty match
re_int = re.compile(r"t\d+|$")
# For sorting a "s" section in ssj; returns key as integer.
# example: "S123.t34" --> 34
def re_lmbd(el):
s = re_int.findall(el)[0]
if len(s) == 0:
return 0
else:
return int(s[1:])
class SsjEntry:
def __init__(self, ssj_id, s, deep_links):
# See ssj xml structure.
self.id = ssj_id
self.s = DC(s)
self.deep_links = DC(deep_links)
class SsjDict:
def __init__(self):
self.entries = {}
"""
def read_xml(self, filepath):
# No data loss.
log.info("SsjDict.read_xml({})".format(filepath))
t_start = time()
tree = ET.parse(filepath)
root = tree.getroot()
stats = {
"skipped": [],
"duplicates": []
}
for s in root.iter("s"):
s_id = s.attrib[XML_ID]
tokens = {}
for token in s:
if token.tag == "linkGrp":
continue
if token.tag == "w":
tokens[token.attrib[XML_ID]] = {
"msd": token.attrib["msd"],
"lemma": token.attrib["lemma"],
"word": token.text
}
elif token.tag == "c":
tokens[token.attrib[XML_ID]] = {
"word": token.text
}
else:
# <S />
pass
linkGrps = s.findall("linkGrp")
if len(linkGrps) < 2:
# Take only entries with both deep and shallow
# syntactic annotation
stats["skipped"].append(s_id)
continue
linkG = {}
for el in linkGrps:
if el.attrib["type"] == "dep":
linkG["dep"] = el
elif el.attrib["type"] == "SRL":
linkG["SRL"] = el
else:
raise KeyError("Unknown linkGrp.")
if s_id in self.entries:
stats["duplicates"].append(s_id)
self.entries[s_id] = SsjEntry(
s_id,
s.attrib["n"],
tokens,
create_edge_dict(linkG["dep"]),
create_edge_dict(linkG["SRL"])
)
t_end = time()
log.info("Time: {}s.".format(t_end - t_start))
log.info(
"{} duplicates, skipped {} elements (missing linkGrp).".format(
len(stats["duplicates"]), len(stats["skipped"]))
)
"""
def read_xml_v2(self, filepath):
NS_DICT = {
"tei": "http://www.tei-c.org/ns/1.0",
"xml": "http://www.w3.org/XML/1998/namespace",
}
def ns_prefix(ns):
return "{" + NS_DICT[ns] + "}"
def helper_get_sentence(tree_s):
# all w and pc elements
ret = []
for el in tree_s.iter():
if (
el.tag == ns_prefix("tei") + "w" or
el.tag == ns_prefix("tei") + "pc"
):
ret.append(el)
return ret
def helper_get_functor_links(tree_s):
# links for SRL linkGrp
lg = None
for linkGrp in tree_s.findall("tei:linkGrp", NS_DICT):
if linkGrp.attrib["type"] == "SRL":
lg = linkGrp
break
else:
return []
ret = []
for link in lg:
ret.append(link)
return ret
def helper_gen_deep_links(link_list):
deep_links = []
for link in link_list:
deep_links.append({
"from": link.attrib["target"].split(" ")[0][1:],
"to": link.attrib["target"].split(" ")[1][1:],
"functor": link.attrib["ana"].split(":")[1]
})
return deep_links
log.info("SsjDict.read_xml({})".format(filepath))
t_start = time()
stats = {
"total_count": 0,
"deep_roles_count": 0,
"duplicated_sid": 0,
}
tree = ET.parse(filepath)
root = tree.getroot()
for s in root.findall(".//tei:s", NS_DICT):
stats["total_count"] += 1
s_id = s.attrib[ns_prefix("xml") + "id"]
# get_functors (deep semantic roles)
functor_links = helper_get_functor_links(s)
if len(functor_links) == 0:
continue
stats["deep_roles_count"] += 1
# get_sentence
tokens = {}
for token in helper_get_sentence(s):
tid = token.attrib[ns_prefix("xml") + "id"]
if token.tag == ns_prefix("tei") + "w":
tokens[tid] = {
"msd": token.attrib["ana"].split(":")[1],
"lemma": token.attrib["lemma"],
"word": token.text
}
elif token.tag == ns_prefix("tei") + "pc":
tokens[tid] = {
"word": token.text
}
else:
log.warning("Unrecognized sentence element: " + token.tag)
exit(1)
if s_id in self.entries:
log.warning("duplicated sentence: " + s_id)
stats["duplicated_sid"] += 1
continue
self.entries[s_id] = SsjEntry(
s_id,
tokens,
helper_gen_deep_links(functor_links)
)
t_end = time()
log.info("Time: {}s.".format(t_end - t_start))
log.info(str(stats))
if __name__ == "__main__":
# testing
log.setLevel(logging.DEBUG)
ch = logging.StreamHandler(sys.stdout)
log.addHandler(ch)
# Load
fpath = "../../data/ssj500k-sl.TEI/ssj500k-sl.body.xml"
ssj = SsjDict()
ssj.read_xml_v2(fpath)
with open("ssj_test.pickle", "wb") as file:
pickle.dump(ssj, file)

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src_diploma/valency/sskj_scraper.py Normal file
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# Deprecated!
import requests
from bs4 import BeautifulSoup
from time import time
from valency import k_utils
SSKJ_BASE = "http://bos.zrc-sazu.si/cgi/a03.exe?name=sskj_testa&expression="
class SskjScraper:
def __init__(self):
self.base_url = SSKJ_BASE
def scrape(self, word):
# returns unique set of words
soup = BeautifulSoup(
requests.get(self.base_url + word).content,
"html.parser"
)
# Check for failure.
h2 = soup.find_all("h2")
if len(h2) >= 2:
# <h2>Zadetkov ni bilo: ...</h2>
return []
li_elements = soup.find_all('li', class_="nounderline")
if len(li_elements) == 0:
return []
li = li_elements[0]
# It was horrible...
# <li> ... <li> ... <li> ...</li></li></li>
# Parse sequence until you find a sedond <li>
txts = []
for el in li.find_all():
if el.name == "li":
break
txts.append(el.get_text())
print("sskj scraped {}.".format(word))
return k_utils.tokenize(txts)
if __name__ == "__main__":
sskjScr = SskjScraper()
word = "tek"
tp = sskjScr.scrape("čaj")
print(tp)

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src_diploma/valency/testing_lesk.py Normal file
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from valency.val_struct import *
from valency.ssj_struct import *
from valency import k_utils
from valency.lesk import Lesk
vallex_path = "../../data/vallex.xml"
vallex = k_utils.pickle_load(vallex_path)
if vallex is None:
ssj_path = "../../data/anno_final.conll.xml"
# ssj_path = "../../data/ssj500kv1_1-SRL_500_stavkov_2017-04-11.xml"
ssj = k_utils.pickle_load(ssj_path)
if ssj is None:
ssj = SsjDict()
ssj.read_xml(ssj_path)
k_utils.pickle_dump(ssj, ssj_path)
vallex = Vallex()
vallex.read_ssj(ssj)
k_utils.pickle_dump(vallex, vallex_path)
vallex.process_after_read(False, False)
random_frame = None
lesk = Lesk()
successes = 0
for k, e in vallex.entries.items():
for rf in e.raw_frames:
random_frame = rf
break
print(rf.to_string())
print(vallex.get_token(random_frame.tids[0]))
print(vallex.get_sentence(random_frame.tids[0]))
tid = random_frame.tids[0]
token = vallex.get_token(tid)
context = vallex.get_context(tid)
sense = lesk.lesk(token, context)
if sense is not None:
successes += 1
if successes >= 10:
break

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from time import time
from copy import deepcopy as DC
from valency.frame import Frame
from valency.reduce_functions import *
from valency.lesk import *
from valency import mongo_tools
import random
import logging
from valency.evaluation import Evaluation
from valency.dictionary_interface import SloWnet, Sskj2
from valency.leskFour import LeskFour
from valency.k_kmeans import KmeansClass
from valency.ssj_struct import SsjDict, SsjEntry
from valency.seqparser.seqparser import Seqparser
import pickle
import sys
import hashlib
log = logging.getLogger(__name__)
def split_id(myid):
tmp = myid.split(".")
sid = ".".join(tmp[:-1])
tid = tmp[-1]
return (sid, tid)
class ValEntry():
def __init__(self, hw, frame):
self.hw = hw
self.raw_frames = [frame]
self.has_senses = False
class Vallex():
# Main class
def __init__(self):
# database
self.db, err_msg = mongo_tools.basic_connection("127.0.0.1", 26633)
if self.db is None:
log.error((
"Database not connected:"
"{}".format(err_msg)
))
exit(1)
mongo_tools.check_collections(self.db, [
"v2_users", "v2_senses", "v2_sense_map", "v2_user_tokens"
])
mongo_tools.prepare_user_tokens(self.db)
# these 3 might be obsolete for the web app (used for ML)
self.db_senses_map = self.db.senses_map3
self.slownet_interface = SloWnet(self)
self.sskj_interface = Sskj2(self)
# self.tokens["s0][t0"] = {word, lemma, msd, ...}
self.tokens = {}
# key = verb / adjective headword
self.entries = {}
# For alphabetical indexing in web app.
self.sorted_words = {}
# words = { first_letter: [hw1, hw2, ... sorted] }
self.functors_index = {}
self.has_se = [] # list of verbs with "se" ("bati se")
# Used for ML (deprecated).
self.leskFour = LeskFour(self)
self.kmeans = KmeansClass(self)
self.evaluation = Evaluation(self)
self.test_samples = []
# run self.process_after_read() after initiating Vallex
def read_ssj(self, ssj):
# ssj: object generated with ssj_strict.py.
BANNED_HW = ["biti"]
stats = {
"P_count": 0,
"skipped": 0,
}
log.info("Vallex.read_ssj({}).".format(
ssj
))
t_start = time()
for ssj_id, entry in ssj.entries.items():
# Read tokens
skip_entry = False
tmp_tokens = {}
for ssj_tid, token in entry.s.items():
sid, tid = split_id(ssj_tid)
# safety checks
if tid != "t" and not tid[1:].isdigit():
log.warning("dropping SID={} - corrupted keys".format(k))
skip_entry = True
break
if tid in tmp_tokens:
log.error(
"Vallex.read_ssj(): Duplicated ssj_tid:" + ssj_tid)
exit(1)
tmp_tokens[tid] = DC(token)
if skip_entry:
continue # skip corrupted keys
if sid in self.tokens:
log.error("sid duplicate: " + sid)
exit(1)
self.tokens[sid] = DC(tmp_tokens)
# Read frame data (each deep link gets its own raw frame).
link_map = {}
# hw_id: { hw_lemma: lemma, deep: [{functor: fnct, to: to}]}
for deep_link in entry.deep_links:
hw_id = deep_link["from"]
hw_token = self.get_token(hw_id)
hw_lemma = hw_token["lemma"]
hw_bv = hw_token["msd"][0]
if (hw_bv != "G" and hw_bv != "P"):
stats["skipped"] += 1
log.info("Skipping {}: not a verb or adjective.".format(
hw_lemma))
continue
if hw_bv == "P":
hw_lemma = hw_lemma + "_"
stats["P_count"] += 1
if hw_id in link_map:
link_map[hw_id]["deep"].append(deep_link)
else:
link_map[hw_id] = {
"hw_lemma": hw_lemma,
"deep": [deep_link]
}
for hw_id, data in link_map.items():
hw_lemma = data["hw_lemma"]
raw_frame = Frame(
hw=hw_lemma,
tids=[hw_id],
deep_links=data["deep"],
slots=None,
)
if hw_lemma not in self.entries:
self.entries[hw_lemma] = ValEntry(hw_lemma, raw_frame)
else:
self.entries[hw_lemma].raw_frames.append(raw_frame)
# cleanup banned
for hw in BANNED_HW:
if hw in self.entries:
del(self.entries[hw])
t_end = time()
log.info("Finished build_from_ssj() in {:.2}s.".format(
t_end - t_start
))
log.info("Vallex has a total of {} key entries.".format(
len(self.entries.keys())
))
log.info("Number of adjectives: {}".format(stats["P_count"]))
log.info("Number of skipped (not a verb or adjective): {}".format(
stats["skipped"]))
# Frames per hw
"""
for k, e in self.entries.items():
print(k + "," + str(len(e.raw_frames)))
"""
def get_token(self, myid):
# id = S123.t1
sid, tid = split_id(myid)
return self.tokens[sid][tid]
def get_sentence(self, myid):
sid, tid = split_id(myid)
tmp = []
sentence = ""
for k, token in self.tokens[sid].items():
if (k != "t") and (token["word"] is not None):
tmp.append((k, token))
for token in sorted(tmp, key=lambda x: int(x[0][1:])):
sentence += (token[1]["word"] + " ")
return sentence
def get_tokenized_sentence(self, myid):
sid, tid = split_id(myid)
tmp = []
sentence = []
for k, token in self.tokens[sid].items():
if k != "t":
tmp.append((k, token))
for token in sorted(tmp, key=lambda x: int(x[0][1:])):
sentence.append((".".join([sid, token[0]]), token[1]))
# return [(ssj_id, {word: _, lemma: _, msd: _}), ...]
return sentence
def process_after_read(
self, sskj_senses_pickle_path, se_list_pickle_path,
reload_sskj_senses
):
tstart = time()
# web app: index by hw
self.sorted_words = {}
self.gen_sorted_words()
# web app: index by functor
self.functors_index = {}
self.gen_functors_index()
# fill db.v2_senses
self.has_se = []
self.read_seqparser_pickles(
sskj_senses_pickle_path, se_list_pickle_path, reload_sskj_senses)
log.debug(
"vallex.process_after_read(): {:.2f}s".format(time() - tstart))
def gen_sorted_words(self):
res = {}
for hw, e in self.entries.items():
letter = hw[0].lower()
n_sent = len(e.raw_frames)
if letter not in res:
res[letter] = []
res[letter].append((hw, n_sent))
# sort and add to vallex object
self.sorted_words = {}
for letter, lst in res.items():
self.sorted_words[letter] = k_utils.slo_bucket_sort(
lst, key=lambda x: x[0])
def gen_functors_index(self):
for hw, e in self.entries.items():
for frame in e.raw_frames:
for slot in frame.slots:
if slot.functor not in self.functors_index:
self.functors_index[slot.functor] = []
self.functors_index[slot.functor].append(frame)
def read_seqparser_pickles(
self, sskj_senses_pickle_path, se_list_pickle_path,
reload_sskj_senses
):
log.info("read_seqparser_pickles()")
log.info((
"Reading list of has_se verbs from {}."
"Sskj senses into db.v2_senses from {}."
).format(se_list_pickle_path, sskj_senses_pickle_path))
AUTHOR_SSKJ = "SSKJ"
ERR_MSG = (
"Need to generate .pickle files first."
"Use: "
"$ python3 /script/valency/seqparser/seqparser.py"
"Input is /data/sskj_v2.html."
)
# has_se
with open(se_list_pickle_path, "rb") as f:
self.has_se = pickle.load(f)
if self.has_se is None:
log.error(ERR_MSG)
exit(1)
self.has_se = sorted(self.has_se)
log.info("Loaded self.has_se (len: {}) from {}.".format(
len(self.has_se), se_list_pickle_path))
# sskj senses
if reload_sskj_senses:
log.info("Reloading sskj_senses.")
reply = self.db.v2_senses.remove({"author": AUTHOR_SSKJ})
log.info(reply)
query = list(self.db.v2_senses.find({"author": AUTHOR_SSKJ}))
if len(query) > 0:
log.info("Sskj senses already in database.")
return
tstart = time()
data = None
with open(sskj_senses_pickle_path, "rb") as f:
data = pickle.load(f)
if data is None:
log.error(ERR_MSG)
exit(1)
for k, e in data.items():
for sense in e["senses"]:
db_entry = {
"hw": k,
"author": AUTHOR_SSKJ,
"desc": sense["sense_desc"],
# unique id for each sense
"sense_id": "{}-{}-{}-{}-{}".format(
AUTHOR_SSKJ,
sense["homonym_id"],
sense["sense_id"],
sense["sense_type"],
hashlib.sha256(
sense["sense_desc"].encode("utf-8")
).hexdigest()[:5]
)
}
self.db.v2_senses.insert(db_entry)
# print(db_entry)
log.info("db.v2_senses prepared in {:.2f}s".format(time() - tstart))
# Functions below can be used for interactively with flask_api.
def test_dev(self):
# self.prepare_sskj_senses()
hw = "dajati"
senses = self.sskj_interface.sense_glosses(hw)
return str(senses)
def calc_senses(self):
# self.calc_all_senses(self.leskFour.lesk_nltk)
# self.calc_all_senses(self.leskFour.lesk_sl)
# self.calc_all_senses(self.leskFour.lesk_al) # cca 8h!
# self.calc_all_senses(self.leskFour.lesk_ram)
self.calc_all_senses_kmeans(self.kmeans.bisection_kmeans)
self.calc_all_senses_kmeans(self.kmeans.normal_kmeans)
return "edit val_struct.py: calc_senses()"
# deprecated functions (used for machine learning experiments)
def prepare_sskj_senses(self):
# obsolete, using read_seqparser_pickles()
log.info("prepare_sskj_senses() (db.v2_senses)")
query = list(self.db.v2_senses.find({"author": "SSKJ2"}))
if len(query) > 0:
log.info("Sskj senses already in database.")
return
tstart = time()
log.info("Iterating over {} hw entries:".format(
len(self.entries.keys())))
for hw, e in self.entries.items():
senses = self.sskj_interface.sense_glosses(hw)
if len(senses) == 0:
continue
for sense in senses:
# create sense from each description
for i, de in enumerate(sense["def"]):
sense_def = sense["def"][i]
sense_def = sense_def[0].upper() + sense_def[1:]
if sense_def[-1] == ":" or sense_def[-1] == ";":
sense_def = sense_def[:-1] + "."
data = {
"hw": hw,
"author": "SSKJ2",
"desc": sense_def,
"sskj_id": sense["sskj_sense_id"],
"sskj_desc_id": i
}
self.db.v2_senses.insert(data)
log.info("sskj_senses prepared in {:.2f}s".format(time() - tstart))
def gen_sskj_sl(self):
# Takes about an hour.
tstart = time()
log.info("Generating new sskj_simple_lesk with Simple Lesk.")
for k, e in self.entries.items():
self.gen_sskj_sl_one(e.hw)
log.debug("gen_sskj_sl in {:.2f}s".format(time() - tstart))
def gen_sskj_sl_one(self, hw, update_db=True):
entry = None
ttstart = time()
e = self.entries.get(hw)
if e is None:
return
for frame in e.raw_frames:
tid = frame.tids[0]
sentence = self.get_sentence(tid)
res = self.lesk.simple_lesk_sskj(sentence, hw)
if res is None:
log.debug("headword {} not in sskj".format(hw))
continue
key = {"ssj_id": tid}
entry = {
"headword": hw,
"ssj_id": tid, # uniqe identifier
"sense_id": res[1],
# "sense_desc": k_utils.dict_safe_key(res[2], "ns0:def"),
"sense_desc": res[2]["def"]
}
# log.debug(str(res[2]))
# log.debug(entry["sense_id"])
# log.debug(entry["sense_desc"])
if update_db:
self.db.sskj_simple_lesk.update(key, entry, upsert=True)
log.debug("[*] sskj_ids for {} in {:.2f}s".format(
hw, time() - ttstart))
def get_context(self, myid, radius=None, min_lemma_size=None):
radius = radius or 5
min_lemma_size = min_lemma_size or 4
# gives you the token and 10 of its neighbors
sentence = self.get_sentence(myid)
sentlen = len(sentence.split(" "))
sid, tid = split_id(myid)
idx = int(tid[1:])
tokens_after = []
i = idx
while i < sentlen - 1 and len(tokens_after) < radius:
i += 1
token = self.get_token(sid + ".t" + str(i))
if (
token is not None and "lemma" in token and
len(token["lemma"]) >= min_lemma_size and
token["lemma"] != "biti"
):
tokens_after.append(token)
tokens_before = []
i = idx
while i > 1 and len(tokens_before) < radius:
i -= 1
token = self.get_token(sid + ".t" + str(i))
if (
token is not None and "lemma" in token and
len(token["lemma"]) >= min_lemma_size and
token["lemma"] != "biti"
):
tokens_before.append(token)
tokens = tokens_before + [self.get_token(myid)] + tokens_after
# find position of original token:
mid_idx = len(tokens_before)
return (mid_idx, tokens)
def get_sense_ids(self, collname, hw, sense_group=None):
query = {"headword": hw}
if sense_group is not None:
query["sense_group"] = sense_group
result = list(self.db[collname].find(query))
sense_ids = {}
for r in result:
sense_ids[r["ssj_id"]] = r["sense_id"]
return sense_ids
def t_get_context(self):
ii = 10
for k, e in self.entries.items():
for frame in e.raw_frames:
if random.randint(0, 100) > 20:
continue
ii -= 1
if ii <= 0:
return
mytid = frame.tids[0]
print()
print(mytid)
print(self.get_token(mytid))
sent = self.get_context(mytid, radius=3, min_lemma_size=4)
print("mid: {}".format(sent[0]))
for ii in range(len(sent[1])):
print("{} -> {}".format(
ii, sent[1][ii]))
def t_simple_lesk_sskj(self):
ii = 10
for k, e in self.entries.items():
if random.randint(0, 100) > 20:
continue
for frame in e.raw_frames:
if random.randint(0, 100) > 20:
continue
if ii == 0:
return
ii -= 1
print("\nTest frame: {}.".format(frame.tids))
hw_token = self.get_token(frame.tids[0])
print(hw_token)
context_sentence = self.get_sentence(frame.tids[0])
print(context_sentence)
self.lesk.simple_lesk_sskj(
context_sentence=context_sentence,
word_lemma=hw_token["lemma"]
)
def process_kmeans(self):
# Convert words to lemmas, cluseter using k-means.
# Number of clusters from sskj.
tstart = time()
log.info("Processing senses using kmeans.")
for k, e in self.entries.items():
# Frame start
ttstart = time()
lemma = e.hw
tokenized_sentences = []
for frame in e.raw_frames:
tid = frame.tids[0]
tokenized_sentences.append(self.get_tokenized_sentence(tid))
lemmatized_sentences = []
for sent in tokenized_sentences:
lemmatized = ""
for token in sent:
if "lemma" in token[1]:
lemmatized += (token[1]["lemma"] + " ")
lemmatized_sentences.append(lemmatized)
lls = len(lemmatized_sentences)
# We got the sentences
sskj_entry = self.db.sskj.find_one(
{"ns0:entry.ns0:form.ns0:orth": lemma})
if sskj_entry is None:
log.debug("headword {} has no <sense> in sskj".format(lemma))
continue
n_clusters = 1
if "ns0:sense" in sskj_entry["ns0:entry"]:
# Guess number of senses based on sskj senses.
n_clusters = len(sskj_entry["ns0:entry"]["ns0:sense"])
if lls >= n_clusters and n_clusters > 1:
labels = k_kmeans.k_means(
sentences=lemmatized_sentences,
n_clusters=n_clusters
)
kmeans_ids = [str(x) + "-" + str(lls) for x in labels]
elif n_clusters == 1:
kmeans_ids = ["1-1" for x in lemmatized_sentences]
elif lls < n_clusters:
# Each sentence gets its own sense.
kmeans_ids = []
for i in range(lls):
kmeans_ids.append(str(i + 1) + "lt" + str(n_clusters))
else:
log.error("Shouldn't be here (val_struct: process_kmeans()")
exit(1)
# Feed sense ides of whole frame to database.
for i in range(len(e.raw_frames)):
tid = e.raw_frames[i].tids[0]
key = {"ssj_id": tid}
entry = {
"headword": lemma,
"ssj_id": tid, # unique idenfitier
"sense_id": kmeans_ids[i],
}
self.db.kmeans.update(key, entry, upsert=True)
log.debug("[*] kemans_ids for {} in {:.2f}s".format(
lemma, time() - ttstart))
# Frame end
log.debug("process_kmeans in {:.2f}s".format(time() - tstart))
def get_context1(
self, mytid, collname, radius=None, min_token_len=3, get_glosses=None
):
# returns {
# "hw": headword lemma and its glosses
# "context": a list of lemmas and their glosses around the hw that
# have entries in collname dictionary (if get_glosses=True)
# }
# tstart = time()
if get_glosses is None:
get_glosses = False
if radius is None:
radius = 10000
if collname == "slownet":
dictionary_interface = self.slownet_interface
elif collname == "sskj":
dictionary_interface = self.sskj_interface
else:
log.error("argument error: get_context1(collname=<slownet/sskj>)")
return []
sentence = self.get_tokenized_sentence(mytid)
# return [(ssj_id, {word: _, lemma: _, msd: _}), ...]
hw_idx = -1
for i, e in enumerate(sentence):
if e[0] == mytid:
hw_idx = i
hw_lemma = e[1]["lemma"]
break
hw_glosses = dictionary_interface.sense_glosses(hw_lemma)
if len(hw_glosses) == 0:
log.info("hw: {} has 0 glosses".format(hw_lemma))
return {
"hw": None,
"err": "headword {} has no glosses in {}".format(
hw_lemma, collname)
}
tokens_before = []
ii = hw_idx - 1
while(ii >= 0 and len(tokens_before) < radius):
lemma = sentence[ii][1].get("lemma")
if (
lemma is not None and
len(lemma) >= min_token_len
):
if get_glosses:
glosses = dictionary_interface.sense_glosses(lemma)
else:
glosses = [{"def": "--none--", "gloss": "--none--"}]
if len(glosses) > 0:
tokens_before.insert(0, {
"lemma": lemma,
"glosses": glosses
})
ii -= 1
tokens_after = []
ii = hw_idx + 1
while(ii < len(sentence) and len(tokens_after) < radius):
lemma = sentence[ii][1].get("lemma")
if (
lemma is not None and
len(lemma) >= min_token_len
):
if get_glosses:
glosses = dictionary_interface.sense_glosses(lemma)
else:
glosses = [{"def": "--none--", "gloss": "--none--"}]
if len(glosses) > 0:
tokens_after.append({
"lemma": lemma,
"glosses": glosses
})
ii += 1
# log.debug("context1({}): {:.2f}".format(mytid, time() - tstart))
return {
"hw": {"lemma": hw_lemma, "glosses": hw_glosses},
"context": tokens_before + tokens_after
}
def test_context1(self, mytid, hw=""):
res = ""
context = self.get_context1(
mytid, collname="slownet", radius=2, get_glosses=True)
if context["hw"] is None:
return context["err"] + "<br><br>"
res = "hw: {}<br>sentence: {}<br>".format(
hw, self.get_sentence(mytid))
tfigf_input = []
glosses = [context["hw"]] + context["context"]
for e in glosses:
res += "--->lemma: {} ({} senses)<br>".format(
e["lemma"], len(e["glosses"]))
for g in e["glosses"]:
res += "{}<br>".format(str(g))
tfigf_input.append(" ".join(k_utils.tokenize_multiple(
g["gloss"],
min_token_len=3,
stem=k_utils.stem_eng
)))
res += "<br><br>"
return res
def calc_all_senses(self, lesk_algorithm):
allcount = 0
count = 0
for k, e in self.entries.items():
allcount += len(e.raw_frames)
for k, e in self.entries.items():
if k == "biti": # skip this huge bag of words
continue
for frame in e.raw_frames:
count += 1
if count % 10 == 0:
log.info("calc_all_senses: ({}/{})".format(
count, allcount))
lesk_algorithm(frame.tids[0])
return None
def calc_all_senses_kmeans(self, kmeans_algorithm):
tstart = time()
allcount = len(self.entries)
count = 0
avg_times = []
for key in self.entries:
count += 1
if key == "biti":
continue
# cluster frames of each entry
log.info("calc_all_senses_kmeans: ({}/{}) [{}]".format(
count, allcount, key))
kmeans_algorithm(key)
"""
try:
kmeans_algorithm(key)
except ValueError:
continue
"""
avg_times.append(1.0 * (time() - tstart) / count)
log.info("avg_time: {:.2f}s".format(avg_times[-1]))
log.info("calc_all_senses_kmeans in {:.2f}s.".format(time() - tstart))
return None
if __name__ == "__main__":
log.setLevel(logging.DEBUG)
ch = logging.StreamHandler(sys.stdout)
log.addHandler(ch)
# run ssj_struct to create a ssj_test.pickle file
with open("ssj_test.pickle", "rb") as file:
ssj = pickle.load(file)
vallex = Vallex()
vallex.read_ssj(ssj)
vallex.sorted_words = {}
vallex.gen_sorted_words()
vallex.functors_index = {}
vallex.gen_functors_index()

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{
"presets": [
["env", {
"modules": false,
"targets": {
"browsers": ["> 1%", "last 2 versions", "not ie <= 8"]
}
}],
"stage-2"
],
"plugins": ["transform-vue-jsx", "transform-runtime"]
}

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root = true
[*]
charset = utf-8
indent_style = space
indent_size = 2
end_of_line = lf
insert_final_newline = true
trim_trailing_whitespace = true

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.DS_Store
node_modules/
/dist/
npm-debug.log*
yarn-debug.log*
yarn-error.log*
# Editor directories and files
.idea
.vscode
*.suo
*.ntvs*
*.njsproj
*.sln

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// https://github.com/michael-ciniawsky/postcss-load-config
module.exports = {
"plugins": {
"postcss-import": {},
"postcss-url": {},
// to edit target browsers: use "browserslist" field in package.json
"autoprefixer": {}
}
}

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# vue_frontend
> Frontend for Valency App.
## Build Setup
``` bash
# install dependencies
npm install
# serve with hot reload at localhost:8080
npm run dev
# build for production with minification
npm run build
# build for production and view the bundle analyzer report
npm run build --report
```
For a detailed explanation on how things work, check out the [guide](http://vuejs-templates.github.io/webpack/) and [docs for vue-loader](http://vuejs.github.io/vue-loader).

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'use strict'
require('./check-versions')()
process.env.NODE_ENV = 'production'
const ora = require('ora')
const rm = require('rimraf')
const path = require('path')
const chalk = require('chalk')
const webpack = require('webpack')
const config = require('../config')
const webpackConfig = require('./webpack.prod.conf')
const spinner = ora('building for production...')
spinner.start()
rm(path.join(config.build.assetsRoot, config.build.assetsSubDirectory), err => {
if (err) throw err
webpack(webpackConfig, (err, stats) => {
spinner.stop()
if (err) throw err
process.stdout.write(stats.toString({
colors: true,
modules: false,
children: false, // If you are using ts-loader, setting this to true will make TypeScript errors show up during build.
chunks: false,
chunkModules: false
}) + '\n\n')
if (stats.hasErrors()) {
console.log(chalk.red(' Build failed with errors.\n'))
process.exit(1)
}
console.log(chalk.cyan(' Build complete.\n'))
console.log(chalk.yellow(
' Tip: built files are meant to be served over an HTTP server.\n' +
' Opening index.html over file:// won\'t work.\n'
))
})
})

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'use strict'
const chalk = require('chalk')
const semver = require('semver')
const packageConfig = require('../package.json')
const shell = require('shelljs')
function exec (cmd) {
return require('child_process').execSync(cmd).toString().trim()
}
const versionRequirements = [
{
name: 'node',
currentVersion: semver.clean(process.version),
versionRequirement: packageConfig.engines.node
}
]
if (shell.which('npm')) {
versionRequirements.push({
name: 'npm',
currentVersion: exec('npm --version'),
versionRequirement: packageConfig.engines.npm
})
}
module.exports = function () {
const warnings = []
for (let i = 0; i < versionRequirements.length; i++) {
const mod = versionRequirements[i]
if (!semver.satisfies(mod.currentVersion, mod.versionRequirement)) {
warnings.push(mod.name + ': ' +
chalk.red(mod.currentVersion) + ' should be ' +
chalk.green(mod.versionRequirement)
)
}
}
if (warnings.length) {
console.log('')
console.log(chalk.yellow('To use this template, you must update following to modules:'))
console.log()
for (let i = 0; i < warnings.length; i++) {
const warning = warnings[i]
console.log(' ' + warning)
}
console.log()
process.exit(1)
}
}

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'use strict'
const path = require('path')
const config = require('../config')
const ExtractTextPlugin = require('extract-text-webpack-plugin')
const packageConfig = require('../package.json')
exports.assetsPath = function (_path) {
const assetsSubDirectory = process.env.NODE_ENV === 'production'
? config.build.assetsSubDirectory
: config.dev.assetsSubDirectory
return path.posix.join(assetsSubDirectory, _path)
}
exports.cssLoaders = function (options) {
options = options || {}
const cssLoader = {
loader: 'css-loader',
options: {
sourceMap: options.sourceMap
}
}
const postcssLoader = {
loader: 'postcss-loader',
options: {
sourceMap: options.sourceMap
}
}
// generate loader string to be used with extract text plugin
function generateLoaders (loader, loaderOptions) {
const loaders = options.usePostCSS ? [cssLoader, postcssLoader] : [cssLoader]
if (loader) {
loaders.push({
loader: loader + '-loader',
options: Object.assign({}, loaderOptions, {
sourceMap: options.sourceMap
})
})
}
// Extract CSS when that option is specified
// (which is the case during production build)
if (options.extract) {
return ExtractTextPlugin.extract({
use: loaders,
fallback: 'vue-style-loader'
})
} else {
return ['vue-style-loader'].concat(loaders)
}
}
// https://vue-loader.vuejs.org/en/configurations/extract-css.html
return {
css: generateLoaders(),
postcss: generateLoaders(),
less: generateLoaders('less'),
sass: generateLoaders('sass', { indentedSyntax: true }),
scss: generateLoaders('sass'),
stylus: generateLoaders('stylus'),
styl: generateLoaders('stylus')
}
}
// Generate loaders for standalone style files (outside of .vue)
exports.styleLoaders = function (options) {
const output = []
const loaders = exports.cssLoaders(options)
for (const extension in loaders) {
const loader = loaders[extension]
output.push({
test: new RegExp('\\.' + extension + '$'),
use: loader
})
}
return output
}
exports.createNotifierCallback = () => {
const notifier = require('node-notifier')
return (severity, errors) => {
if (severity !== 'error') return
const error = errors[0]
const filename = error.file && error.file.split('!').pop()
notifier.notify({
title: packageConfig.name,
message: severity + ': ' + error.name,
subtitle: filename || '',
icon: path.join(__dirname, 'logo.png')
})
}
}

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'use strict'
const utils = require('./utils')
const config = require('../config')
const isProduction = process.env.NODE_ENV === 'production'
const sourceMapEnabled = isProduction
? config.build.productionSourceMap
: config.dev.cssSourceMap
module.exports = {
loaders: utils.cssLoaders({
sourceMap: sourceMapEnabled,
extract: isProduction
}),
cssSourceMap: sourceMapEnabled,
cacheBusting: config.dev.cacheBusting,
transformToRequire: {
video: ['src', 'poster'],
source: 'src',
img: 'src',
image: 'xlink:href'
}
}

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'use strict'
const path = require('path')
const utils = require('./utils')
const config = require('../config')
const vueLoaderConfig = require('./vue-loader.conf')
function resolve (dir) {
return path.join(__dirname, '..', dir)
}
module.exports = {
context: path.resolve(__dirname, '../'),
entry: {
app: './src/main.js'
},
output: {
path: config.build.assetsRoot,
filename: '[name].js',
publicPath: process.env.NODE_ENV === 'production'
? config.build.assetsPublicPath
: config.dev.assetsPublicPath
},
resolve: {
extensions: ['.js', '.vue', '.json'],
alias: {
'vue$': 'vue/dist/vue.esm.js',
'@': resolve('src'),
}
},
module: {
rules: [
{
test: /\.vue$/,
loader: 'vue-loader',
options: vueLoaderConfig
},
{
test: /\.js$/,
loader: 'babel-loader',
include: [resolve('src'), resolve('test'), resolve('node_modules/webpack-dev-server/client')]
},
{
test: /\.(png|jpe?g|gif|svg)(\?.*)?$/,
loader: 'url-loader',
options: {
limit: 10000,
name: utils.assetsPath('img/[name].[hash:7].[ext]')
}
},
{
test: /\.(mp4|webm|ogg|mp3|wav|flac|aac)(\?.*)?$/,
loader: 'url-loader',
options: {
limit: 10000,
name: utils.assetsPath('media/[name].[hash:7].[ext]')
}
},
{
test: /\.(woff2?|eot|ttf|otf)(\?.*)?$/,
loader: 'url-loader',
options: {
limit: 10000,
name: utils.assetsPath('fonts/[name].[hash:7].[ext]')
}
}
]
},
node: {
// prevent webpack from injecting useless setImmediate polyfill because Vue
// source contains it (although only uses it if it's native).
setImmediate: false,
// prevent webpack from injecting mocks to Node native modules
// that does not make sense for the client
dgram: 'empty',
fs: 'empty',
net: 'empty',
tls: 'empty',
child_process: 'empty'
}
}

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'use strict'
const utils = require('./utils')
const webpack = require('webpack')
const config = require('../config')
const merge = require('webpack-merge')
const path = require('path')
const baseWebpackConfig = require('./webpack.base.conf')
const CopyWebpackPlugin = require('copy-webpack-plugin')
const HtmlWebpackPlugin = require('html-webpack-plugin')
const FriendlyErrorsPlugin = require('friendly-errors-webpack-plugin')
const portfinder = require('portfinder')
const HOST = process.env.HOST
const PORT = process.env.PORT && Number(process.env.PORT)
const devWebpackConfig = merge(baseWebpackConfig, {
module: {
rules: utils.styleLoaders({ sourceMap: config.dev.cssSourceMap, usePostCSS: true })
},
// cheap-module-eval-source-map is faster for development
devtool: config.dev.devtool,
// these devServer options should be customized in /config/index.js
devServer: {
clientLogLevel: 'warning',
historyApiFallback: {
rewrites: [
{ from: /.*/, to: path.posix.join(config.dev.assetsPublicPath, 'index.html') },
],
},
hot: true,
contentBase: false, // since we use CopyWebpackPlugin.
compress: true,
host: HOST || config.dev.host,
port: PORT || config.dev.port,
open: config.dev.autoOpenBrowser,
overlay: config.dev.errorOverlay
? { warnings: false, errors: true }
: false,
publicPath: config.dev.assetsPublicPath,
proxy: config.dev.proxyTable,
quiet: true, // necessary for FriendlyErrorsPlugin
watchOptions: {
poll: config.dev.poll,
}
},
plugins: [
new webpack.DefinePlugin({
'process.env': require('../config/dev.env')
}),
new webpack.HotModuleReplacementPlugin(),
new webpack.NamedModulesPlugin(), // HMR shows correct file names in console on update.
new webpack.NoEmitOnErrorsPlugin(),
// https://github.com/ampedandwired/html-webpack-plugin
new HtmlWebpackPlugin({
filename: 'index.html',
template: 'index.html',
inject: true
}),
// copy custom static assets
new CopyWebpackPlugin([
{
from: path.resolve(__dirname, '../static'),
to: config.dev.assetsSubDirectory,
ignore: ['.*']
}
])
]
})
module.exports = new Promise((resolve, reject) => {
portfinder.basePort = process.env.PORT || config.dev.port
portfinder.getPort((err, port) => {
if (err) {
reject(err)
} else {
// publish the new Port, necessary for e2e tests
process.env.PORT = port
// add port to devServer config
devWebpackConfig.devServer.port = port
// Add FriendlyErrorsPlugin
devWebpackConfig.plugins.push(new FriendlyErrorsPlugin({
compilationSuccessInfo: {
messages: [`Your application is running here: http://${devWebpackConfig.devServer.host}:${port}`],
},
onErrors: config.dev.notifyOnErrors
? utils.createNotifierCallback()
: undefined
}))
resolve(devWebpackConfig)
}
})
})

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'use strict'
const path = require('path')
const utils = require('./utils')
const webpack = require('webpack')
const config = require('../config')
const merge = require('webpack-merge')
const baseWebpackConfig = require('./webpack.base.conf')
const CopyWebpackPlugin = require('copy-webpack-plugin')
const HtmlWebpackPlugin = require('html-webpack-plugin')
const ExtractTextPlugin = require('extract-text-webpack-plugin')
const OptimizeCSSPlugin = require('optimize-css-assets-webpack-plugin')
const UglifyJsPlugin = require('uglifyjs-webpack-plugin')
const env = require('../config/prod.env')
const webpackConfig = merge(baseWebpackConfig, {
module: {
rules: utils.styleLoaders({
sourceMap: config.build.productionSourceMap,
extract: true,
usePostCSS: true
})
},
devtool: config.build.productionSourceMap ? config.build.devtool : false,
output: {
path: config.build.assetsRoot,
filename: utils.assetsPath('js/[name].[chunkhash].js'),
chunkFilename: utils.assetsPath('js/[id].[chunkhash].js')
},
plugins: [
// http://vuejs.github.io/vue-loader/en/workflow/production.html
new webpack.DefinePlugin({
'process.env': env
}),
new UglifyJsPlugin({
uglifyOptions: {
compress: {
warnings: false
}
},
sourceMap: config.build.productionSourceMap,
parallel: true
}),
// extract css into its own file
new ExtractTextPlugin({
filename: utils.assetsPath('css/[name].[contenthash].css'),
// Setting the following option to `false` will not extract CSS from codesplit chunks.
// Their CSS will instead be inserted dynamically with style-loader when the codesplit chunk has been loaded by webpack.
// It's currently set to `true` because we are seeing that sourcemaps are included in the codesplit bundle as well when it's `false`,
// increasing file size: https://github.com/vuejs-templates/webpack/issues/1110
allChunks: true,
}),
// Compress extracted CSS. We are using this plugin so that possible
// duplicated CSS from different components can be deduped.
new OptimizeCSSPlugin({
cssProcessorOptions: config.build.productionSourceMap
? { safe: true, map: { inline: false } }
: { safe: true }
}),
// generate dist index.html with correct asset hash for caching.
// you can customize output by editing /index.html
// see https://github.com/ampedandwired/html-webpack-plugin
new HtmlWebpackPlugin({
filename: config.build.index,
template: 'index.html',
inject: true,
minify: {
removeComments: true,
collapseWhitespace: true,
removeAttributeQuotes: true
// more options:
// https://github.com/kangax/html-minifier#options-quick-reference
},
// necessary to consistently work with multiple chunks via CommonsChunkPlugin
chunksSortMode: 'dependency'
}),
// keep module.id stable when vendor modules does not change
new webpack.HashedModuleIdsPlugin(),
// enable scope hoisting
new webpack.optimize.ModuleConcatenationPlugin(),
// split vendor js into its own file
new webpack.optimize.CommonsChunkPlugin({
name: 'vendor',
minChunks (module) {
// any required modules inside node_modules are extracted to vendor
return (
module.resource &&
/\.js$/.test(module.resource) &&
module.resource.indexOf(
path.join(__dirname, '../node_modules')
) === 0
)
}
}),
// extract webpack runtime and module manifest to its own file in order to
// prevent vendor hash from being updated whenever app bundle is updated
new webpack.optimize.CommonsChunkPlugin({
name: 'manifest',
minChunks: Infinity
}),
// This instance extracts shared chunks from code splitted chunks and bundles them
// in a separate chunk, similar to the vendor chunk
// see: https://webpack.js.org/plugins/commons-chunk-plugin/#extra-async-commons-chunk
new webpack.optimize.CommonsChunkPlugin({
name: 'app',
async: 'vendor-async',
children: true,
minChunks: 3
}),
// copy custom static assets
new CopyWebpackPlugin([
{
from: path.resolve(__dirname, '../static'),
to: config.build.assetsSubDirectory,
ignore: ['.*']
}
])
]
})
if (config.build.productionGzip) {
const CompressionWebpackPlugin = require('compression-webpack-plugin')
webpackConfig.plugins.push(
new CompressionWebpackPlugin({
asset: '[path].gz[query]',
algorithm: 'gzip',
test: new RegExp(
'\\.(' +
config.build.productionGzipExtensions.join('|') +
')$'
),
threshold: 10240,
minRatio: 0.8
})
)
}
if (config.build.bundleAnalyzerReport) {
const BundleAnalyzerPlugin = require('webpack-bundle-analyzer').BundleAnalyzerPlugin
webpackConfig.plugins.push(new BundleAnalyzerPlugin())
}
module.exports = webpackConfig

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{
"api_addr": "http://localhost:5004"
}

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{
"api_addr": "http://localhost:5004"
}

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{
"api_addr": "http://193.2.76.103:5004"
}

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'use strict'
const merge = require('webpack-merge')
const prodEnv = require('./prod.env')
module.exports = merge(prodEnv, {
NODE_ENV: '"development"'
})

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'use strict'
// Template version: 1.3.1
// see http://vuejs-templates.github.io/webpack for documentation.
const path = require('path')
module.exports = {
dev: {
// Paths
assetsSubDirectory: 'static',
assetsPublicPath: '/',
proxyTable: {},
// Various Dev Server settings
host: 'localhost', // can be overwritten by process.env.HOST
port: 8080, // can be overwritten by process.env.PORT, if port is in use, a free one will be determined
autoOpenBrowser: false,
errorOverlay: true,
notifyOnErrors: true,
poll: false, // https://webpack.js.org/configuration/dev-server/#devserver-watchoptions-
/**
* Source Maps
*/
// https://webpack.js.org/configuration/devtool/#development
devtool: 'cheap-module-eval-source-map',
// If you have problems debugging vue-files in devtools,
// set this to false - it *may* help
// https://vue-loader.vuejs.org/en/options.html#cachebusting
cacheBusting: true,
cssSourceMap: true
},
build: {
// Template for index.html
index: path.resolve(__dirname, '../dist/index.html'),
// Paths
assetsRoot: path.resolve(__dirname, '../dist'),
assetsSubDirectory: 'static',
assetsPublicPath: '/',
/**
* Source Maps
*/
productionSourceMap: true,
// https://webpack.js.org/configuration/devtool/#production
devtool: '#source-map',
// Gzip off by default as many popular static hosts such as
// Surge or Netlify already gzip all static assets for you.
// Before setting to `true`, make sure to:
// npm install --save-dev compression-webpack-plugin
productionGzip: false,
productionGzipExtensions: ['js', 'css'],
// Run the build command with an extra argument to
// View the bundle analyzer report after build finishes:
// `npm run build --report`
// Set to `true` or `false` to always turn it on or off
bundleAnalyzerReport: process.env.npm_config_report
}
}

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'use strict'
module.exports = {
NODE_ENV: '"production"'
}

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<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width,initial-scale=1.0">
<title>vue_frontend</title>
</head>
<body>
<div id="app"></div>
<!-- built files will be auto injected -->
</body>
</html>

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{
"name": "vue_frontend",
"version": "1.0.0",
"description": "Frontend for Valency App.",
"author": "voje <kristjan.voje@gmail.com>",
"private": true,
"scripts": {
"dev": "webpack-dev-server --inline --progress --config build/webpack.dev.conf.js",
"start": "npm run dev",
"build": "node build/build.js"
},
"dependencies": {
"axios": "^0.18.0",
"bootstrap-vue": "^2.0.0-rc.11",
"sha256": "^0.2.0",
"vue": "^2.5.2",
"vue-cookies": "^1.5.6",
"vue-router": "^3.0.1",
"vue-spinner": "^1.0.3"
},
"devDependencies": {
"autoprefixer": "^7.1.2",
"babel-core": "^6.22.1",
"babel-helper-vue-jsx-merge-props": "^2.0.3",
"babel-loader": "^7.1.1",
"babel-plugin-syntax-jsx": "^6.18.0",
"babel-plugin-transform-runtime": "^6.22.0",
"babel-plugin-transform-vue-jsx": "^3.5.0",
"babel-preset-env": "^1.3.2",
"babel-preset-stage-2": "^6.22.0",
"chalk": "^2.0.1",
"copy-webpack-plugin": "^4.0.1",
"css-loader": "^0.28.0",
"extract-text-webpack-plugin": "^3.0.0",
"file-loader": "^1.1.4",
"friendly-errors-webpack-plugin": "^1.6.1",
"html-webpack-plugin": "^2.30.1",
"node-notifier": "^5.1.2",
"optimize-css-assets-webpack-plugin": "^3.2.0",
"ora": "^1.2.0",
"portfinder": "^1.0.13",
"postcss-import": "^11.0.0",
"postcss-loader": "^2.0.8",
"postcss-url": "^7.2.1",
"rimraf": "^2.6.0",
"semver": "^5.3.0",
"shelljs": "^0.7.6",
"uglifyjs-webpack-plugin": "^1.1.1",
"url-loader": "^0.5.8",
"vue-loader": "^13.3.0",
"vue-style-loader": "^3.0.1",
"vue-template-compiler": "^2.5.2",
"webpack": "^3.6.0",
"webpack-bundle-analyzer": "^2.9.0",
"webpack-dev-server": "^2.9.1",
"webpack-merge": "^4.1.0"
},
"engines": {
"node": ">= 6.0.0",
"npm": ">= 3.0.0"
},
"browserslist": [
"> 1%",
"last 2 versions",
"not ie <= 8"
]
}

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<template>
<router-view/>
</template>
<script>
export default {
name: 'App',
}
</script>

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<template>
<div class="container-fluid">
<div class="row">
<div class="col-sm-12">
<p class="pb-0 mb-0">Urejanje pomenov za besedo: <b>{{ hw }}</b>.</p>
<p><small>
Z miško kliknite na poved, nato kliknite na pomen, ki ga želite dodeliti povedi. Par poved&#8210;pomen bo obarvan z modro. Pare lahko shranite s klikom na gumb "Shrani". Možno je dodajanje poljubnih pomenov.
</small></p>
<button v-on:click="cancel_all">Prekliči</button>
<button v-on:click="save_all">Shrani</button>
</div>
</div>
<div class="row">
<!-- left column: sentences -->
<div class="my-sent col-sm-6">
<div
v-for="(sentence, ssj_id) in sentences"
v-on:click="pick_ssj_id(ssj_id)"
class="border rounded my-sentences my-pointer"
v-bind:class="{
'border-primary': ssj_id === picked_ssj_id
}"
>
<div>
<span
v-for="(word, index) in sentence.words"
v-bind:class="{
'text-primary': index === parseInt(sentence.hw_idx)
}"
>
<span v-if="$root.mkspace(index, word)">&nbsp;</span>{{ word }}
</span>
</div>
<hr>
<div class="col-sm-12"><small>
<div v-if="ssj_id in local_sense_map">
<Sense v-bind:sense="local_sense_map[ssj_id].sense"></Sense>
</div>
<div v-else>
<Sense v-bind:sense="undefined"></Sense>
</div>
</small></div>
</div>
</div>
<!-- right column: senses -->
<div class="col-sm-6 border rounded my-div-scroll sticky-top">
<div
v-for="sense in local_senses"
class="my-pointer"
v-on:click="picked_sense_id = sense.sense_id"
v-bind:class="{
'text-primary': sense.sense_id === picked_sense_id
}"
>
<Sense v-bind:sense="sense"></Sense>
</div>
<div class="row">
<div class="col-sm-12">
<textarea class="my-textarea" v-model="new_sense_desc"></textarea>
</div>
<div class="col-sm-12">
<button v-on:click="new_sense">Dodaj pomen</button>
</div>
</div>
</div>
</div>
</div>
</template>
<script>
import Sense from "./Sense"
export default {
name: "EditSenses",
props: ["hw", "sentences", "sens"],
components: {
Sense: Sense
},
data () { return {
picked_ssj_id: null,
picked_sense_id: null,
local_senses: [], // make changes on a local copy
local_sense_map: {}, // make changes on a local copy
new_sense_desc: "",
new_senses: [], // only send changes to server
delta_sense_map: {}, // only send changes to server
}},
created: function() {
// not sure if needed, maybe move to data()
this.local_senses = this.sens.senses
var json = JSON.stringify(this.sens.sense_map)
this.local_sense_map = JSON.parse(json)
for (var ssj_id in this.local_sense_map) {
this.local_sense_map[ssj_id].sense = this.sense_id_to_sense(
this.local_sense_map[ssj_id].sense_id)
}
},
watch: {
picked_ssj_id: function() {
this.new_link()
},
picked_sense_id: function() {
this.new_link()
}
},
methods: {
pick_ssj_id: function(ssj_id) {
this.picked_ssj_id = ssj_id
if (ssj_id in this.local_sense_map) {
this.picked_sense_id = this.local_sense_map[ssj_id].sense_id
}
},
new_link: function() {
if (this.picked_ssj_id === null ||
this.picked_sense_id === null) { return }
this.local_sense_map[this.picked_ssj_id] = {
sense_id: this.picked_sense_id,
sense: this.sense_id_to_sense(this.picked_sense_id)
}
this.delta_sense_map[this.picked_ssj_id] = { sense_id: this.picked_sense_id }
},
new_sense: function(sense_id) {
if (this.new_sense_desc === "") {
return
}
var new_sense = {
hw: this.hw,
author: this.$root.store.username,
desc: this.new_sense_desc,
sense_id: "tmp_sense_id" + (new Date().getTime()),
}
this.local_senses.push(new_sense)
this.new_senses.push(new_sense)
this.new_sense_desc = ""
},
sense_id_to_sense: function(sense_id) {
for (var i=0; i<this.local_senses.length; i++) {
if (this.local_senses[i].sense_id === sense_id) {
return this.local_senses[i]
}
}
return undefined
},
cancel_all: function() {
this.$parent.state = "normal"
},
save_all: function() {
const data = {
token: this.$root.store.token,
hw: this.hw,
sense_map: this.delta_sense_map,
new_senses: this.new_senses,
}
var component = this
function exit_edit(component) {
component.$parent.state = "normal"
component.$parent.request_reload = true
}
// don't update if there are no changes
if (
Object.keys(data.sense_map).length === 0 &&
data.new_senses.length === 0
) { exit_edit(component); return }
// exit after update
this.$http.post(
this.$root.store.api_addr + "/api/senses/update",
data,
{ headers: {
'Content-type': 'application/json',
}}
).then(function () {
exit_edit(component)
})
},
}
}
</script>
<style scoped>
.my-div-scroll {
margin-top: 5px;
height: 90vh;
overflow-y: auto;
padding-top: 5px;
}
.my-pointer {
cursor: pointer;
}
.my-textarea {
width: 100%;
}
.my-sentences {
margin: 5px 0px 20px 0px;
padding: 5px;
}
.my-sent {
word-wrap: break-word;
}
.my-sent span {
display: inline-block;
}
</style>

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<template>
<!-- clicking on empty space clears highlights -->
<div v-on:click="clearOnClick" class="container-fluid">
<hr>
<div class="row">
<div class="col-sm-7">
<div class="row">
<div class="col-sm-12">
št. povedi: {{ frameData.sentences.length }}
</div>
</div>
<!--frame slots-->
<div class="row my-frames">
<div class="col-sm-12">
<span v-for="(slot, key) in frameData.slots">
<span
v-bind:class="{
'my-pointer text-danger': hasHoverTid(idx=key),
'my-underline text-danger': hasSelTid(idx=key)
}"
v-on:mouseover="setHid(idx=key)"
v-on:mouseleave="setHid()"
v-on:click="setSid(idx=key)"
>{{ slot.functor }}</span>&nbsp;&nbsp;
</span>
</div>
</div>
</div>
<!--sense information-->
<div v-if="$root.store.radio === 'three'" class="col-sm-5">
<Sense v-bind:sense="getSense()"></Sense>
</div>
</div>
<!--sentences-->
<div class="row">
<!-- fmode: prikaz->udelezenske vloge (drugacno razvrscanje povedi) -->
<div v-if="fmode" class="col-sm-12">
<div v-for="hw in getAggrHws()">
<blockquote v-for="sentence in getAggrSent(hw)">
<span class="text-secondary">&nbsp;{{ hw }}</span><br>
<span
v-for="(token, index) in sentence"
v-bind:class="{
'my-pointer text-danger': hasHoverTid(idx=null, tid=token[0]), 'my-underline text-danger': hasSelTid(idx=null, tid=token[0]),
'text-primary': isHw(token[0]),
}"
v-on:mouseover="setHid(idx=null, tid=token[0])"
v-on:mouseleave="setHid()"
v-on:click="setSid(idx=null, tid=token[0])"
v-bind:title="token[1].msd"
><span v-if="$root.mkspace(index, token[1].word)">&nbsp;</span>{{ token[1].word }}</span>
</blockquote>
</div>
</div>
<div v-else class="col-sm-12">
<blockquote v-for="sentence in frameData.sentences">
<span
v-for="(token, index) in sentence"
v-bind:class="{
'my-pointer text-danger': hasHoverTid(idx=null, tid=token[0]), 'my-underline text-danger': hasSelTid(idx=null, tid=token[0]),
'text-primary': isHw(token[0]),
}"
v-on:mouseover="setHid(idx=null, tid=token[0])"
v-on:mouseleave="setHid()"
v-on:click="setSid(idx=null, tid=token[0])"
v-bind:title="token[1].msd"
><span v-if="$root.mkspace(index, token[1].word)">&nbsp;</span>{{ token[1].word }}</span>
</blockquote>
</div>
</div>
<br>
</div>
</template>
<script>
import Sense from "./Sense"
export default {
name: "Frame",
props: {
frameData: {},
sensData: {},
fmode: {
default: false,
type: Boolean,
},
},
data() { return {
hid: null, // hover functor index
sid: null, // select functor index (click)
}},
components: {
Sense: Sense
},
watch: {
frameData: function () {
this.hid = null,
this.sid = null
}
},
methods: {
setHid: function (idx=null, tid=null) {
// calling this functoin without parameters
// resets hid
if (tid === null) {
this.hid = idx
return
}
for (var i=0; i<this.frameData.slots.length; i++) {
if (this.frameData.slots[i].tids.includes(tid)) {
this.hid = i
return
}
}
},
clearOnClick: function (event) {
if (event.target.tagName !== "SPAN") {
this.sid = null
}
},
setSid: function (idx=null, tid=null) {
this.sid = null
if (tid === null) {
this.sid = idx
return
}
for (var i=0; i<this.frameData.slots.length; i++) {
if (this.frameData.slots[i].tids.includes(tid)) {
this.sid = i
return
}
}
},
hasHoverTid: function(idx=null, tid=null) {
if (this.hid === null) {
return false
}
if (tid === null) {
if (idx == this.hid) {
return true
}
return false
}
return this.frameData.slots[this.hid].tids.includes(tid)
},
hasSelTid: function (idx=null, tid=null) {
if (this.sid === null) {
return false
}
if (tid === null) {
if (idx == this.sid) {
return true
}
return false
}
return this.frameData.slots[this.sid].tids.includes(tid)
},
isHw: function (tid) {
return this.frameData.tids.includes(tid)
},
getSense: function () {
for (var i in this.sensData.senses) {
if (this.sensData.senses[i].sense_id === this.frameData.sense_info.sense_id) {
return this.sensData.senses[i]
}
}
return undefined
},
getAggrHws: function() {
return (Object.keys(this.frameData.aggr_sent)).sort()
},
getAggrSent: function(hw) {
var sentences = []
for (var i=0; i<this.frameData.aggr_sent[hw].length; i++) {
sentences.push(
this.frameData.sentences[this.frameData.aggr_sent[hw][i]]
)
}
return sentences
},
}
}
</script>
<style scoped>
.my-pointer {
cursor: pointer;
}
.my-underline {
text-decoration: underline;
}
.my-frames {
margin-top: 10px;
margin-bottom: 2px;
}
blockquote {
background: #ffffff;
border-left: 4px solid #ccc;
margin: 10px 0px 10px 10px;
padding: 0px 0px 0px 5px;
word-wrap: break-word;
}
blockquote span {
display: inline-block;
}
</style>

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<template>
<div>
<p
v-if="this.$root.store.api_error !== null"
class="text-warning"
>
api_error: {{ this.$root.store.api_error }}
</p>
<Nav></Nav>
<div class="my-home container-fluid">
<div class="row">
<div id="serach" class="col-sm-2 border-right fill">
<LWords v-if="navSS()"></LWords>
<LFunctors v-else></LFunctors>
</div>
<div class="col-sm-10">
<router-view></router-view>
</div>
</div>
</div>
</div>
</template>
<script>
import Nav from "./Nav"
import LWords from "./LWords"
import LFunctors from "./LFunctors"
import MainDispl from "./MainDispl"
export default {
name: 'Home',
components: {
Nav: Nav,
LWords: LWords,
LFunctors: LFunctors,
MainDispl: MainDispl,
},
methods: {
navSS: function () {
return this.$root.storeGet("navSS") === "words"
}
}
}
</script>
<style scoped>
.my-home {
padding-top: 10px;
}
</style>

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<template>
<div>
<table>
<tr v-for="functor in functors">
<td><a href="#" v-on:click="selectFunctor(functor)">{{ functor[0] }}</a></td>
<td>({{ functor[1] }})</td>
</tr>
</table>
</div>
</template>
<script>
export default {
name: "LWords",
props: ["appState"],
data() {return {
functors: []
}},
methods: {
apiGetFunctors: function () {
var component = this
this.$http.get(this.$root.store.api_addr + "/api/functors")
.then(function(response) {
component.$root.store.api_error = null
component.functors = response.data
})
.catch(function(error) {
component.$root.store.api_error = error
})
},
selectFunctor: function (functor) {
this.$router.push({
name: "MainDispl",
params: {
hw: functor[0],
fmode: true
}
})
}
},
mounted: function() {
this.apiGetFunctors()
}
}
</script>
<style>
table {
width: 100%;
}
</style>

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<template>
<div>
<select v-model="selectedLetter">
<option v-for="letter in alphabet" :value="letter">
{{ letter.toUpperCase() }} ({{ getNumWords(letter) }})
</option>
</select>
<table>
<tr v-for="word in getWords()">
<td><a href="#" v-on:click="selectHw(word)">{{ word[0] }}
<span v-if="$root.store.has_se.includes(word[0])">se</span>
</a></td>
<td>({{ word[1] }})</td>
</tr>
</table>
</div>
</template>
<script>
export default {
name: "LWords",
data() {return {
alphabet: "abcčdefghijklmnoprsštuvzž",
letters: {},
selectedLetter: "a"
}},
methods: {
apiGetWords: function() {
var component = this
this.$http.get(this.$root.storeGet("api_addr") + "/api/words")
.then(function(response) {
component.$root.store.api_error = null
component.$root.store.has_se = response.data["has_se"]
component.letters = response.data["sorted_words"]
})
.catch(function(error) {
component.$root.store.api_error = error
})
},
getNumWords: function(letter) {
var entry = this.letters[letter]
if (entry) {
return entry.length
} else {
return 0
}
},
getWords: function() {
var entry = this.letters[this.selectedLetter]
if (entry) {
return entry
} else {
return []
}
},
selectHw: function(word) {
this.$router.push({
name: "MainDispl",
params: {
hw: word[0],
fmode: false
}
})
}
},
mounted: function() {
this.apiGetWords()
}
}
</script>
<style scoped>
table {
width: 100%;
}
select {
width: 100%;
}
</style>

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<template>
<div>
<div class="col-sm-2">
<a href="#" v-on:click="this.$root.routeBack">Nazaj</a>
</div>
<div class="ev-login col-sm-4 offset-sm-4">
<div class="alert alert-danger" v-if="error">
<p>{{ error }}</p>
</div>
<div class="form-group">
<input
type="text"
data-id="login.username"
class="form-control js-login__username"
placeholder="Uporabnik"
v-model="credentials.username"
>
</div>
<div class="form-group">
<input
type="password"
class="form-control js-login__password "
placeholder="Geslo"
v-model="credentials.password"
>
</div>
<button
data-id="login.submit"
class="btn btn-primary solid blank js-login__submit"
@click="submit()"
>
Prijava<i class="fa fa-arrow-circle-o-right"></i>
</button>
<br>
<br>
<br>
<router-link to="/new_pass">Ste pozabili geslo?</router-link>
<br>
<br>
Nov uporabnik?
<br>
<router-link to="/register">Ustvarite nov račun.</router-link>
</div>
</div>
</template>
<script>
export default {
name: 'Login',
data () {
return {
credentials: {
username: '',
password: ''
},
loggingIn: false,
error: ''
}
},
methods: {
submit () {
this.error = ""
//this.loggingIn = true
// Auth.login() returns a promise. A redirect will happen on success.
// For errors, use .then() to capture the response to output
// error_description (if exists) as shown below:
/*
this.$auth.login(credentials, 'dashboard').then((response) => {
this.loggingIn = false
this.error = utils.getError(response)
})
*/
if ( this.credentials.username === "" ||
this.credentials.password === ""
) {
this.error = "Izpolnite vsa polja."
return
}
var data = {
username: this.credentials.username,
password: this.credentials.password
}
var component = this
this.$http.post(this.$root.storeGet("api_addr") + "/api/login",
data, // the data to post
{ headers: {
'Content-type': 'application/x-www-form-urlencoded',
}
})
.then(function (response) {
component.$root.store.api_error = null
var token = response.data.token
if (token === null) {
component.error = "Napačno uporabniško ime ali geslo."
} else {
// set cookies (if the page reloads)
component.$root.store.username = component.credentials.username
component.$root.store.token = token
component.$router.go(-1)
component.$cookies.set("valency_token", token, 60*60*48)
}
})
.catch(function (err) {
component.$root.store.api_error = err
})
},
},
}
</script>
<style scoped>
.ev-login {
margin-top: 100px;
}
</style>

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<template>
<!--load mode-->
<div v-if="show_loader">
<pulse-loader :color="loader_color"></pulse-loader>
</div>
<!--edit mode (button: razvrsti po pomenih)-->
<div v-else-if="state === 'editing'" class="container-fluid">
<EditSenses
v-bind:hw="hw"
v-bind:sentences="sentences"
v-bind:sens="sens"
></EditSenses>
</div>
<!--normal mode-->
<div v-else class="container-fluid" id="head">
<!--header (verb/adjective, radio buttons)-->
<div class="row">
<div class="col-sm-4">
<table>
<tr><h4 id="main-displ-hw">{{ hw }}
<span v-if="$root.store.has_se.includes(hw)">se</span>
</h4></tr>
<tr>{{ calcPos() }}</tr>
</table>
</div>
<div class="col-sm-8">
<table>
<tr>Združevanje vezljivostnih vzorcev:</tr>
<tr>
<label class="radio-inline"><input value="one" v-model="$root.store.radio" v-on:change="reload()" checked="" type="radio" name="optradio">posamezne povedi</label>&nbsp;&nbsp;
<label class="radio-inline"><input value="two" v-model="$root.store.radio" v-on:change="reload()" type="radio" name="optradio">skupne udeleženske vloge</label>&nbsp;&nbsp;
<label v-if="this.$root.store.navSS === 'words'" class="radio-inline"><input value="three" v-model="$root.store.radio" v-on:change="reload()" type="radio" name="optradio">po meri</label>
</tr>
</table>
</div>
</div>
<!--frames-->
<div v-if="$root.store.radio === 'three'" class="row">
<div class="col-sm-4">
<button v-on:click="userEdit">razvrsti po pomenih</button>
</div>
</div>
<div class="row" v-for="frame in frames">
<Frame
v-bind:frameData="frame"
v-bind:sensData="sens"
v-bind:fmode="fmode">
</Frame>
</div>
</div>
</template>
<script>
import Frame from "./Frame"
import EditSenses from "./EditSenses"
import PulseLoader from 'vue-spinner/src/PulseLoader.vue'
export default {
name: "MainDispl",
components: {
Frame: Frame,
EditSenses: EditSenses,
PulseLoader: PulseLoader,
},
props: ["hw", "fmode"],
data () { return {
frames: [],
sentences: {},
sens: {
senses: [],
sense_map: {},
},
state: "loading", // editing, normal
request_reload: false,
loader_color: "#007bff",
}},
created: function () {
this.reload()
},
computed: {
show_loader: function () {
return this.state === "loading" && this.$root.store.api_error !== null
}
},
watch: {
hw: function () {
this.reload()
},
frames: function () {
this.buildSentences()
},
request_reload: function () {
if (this.request_reload) {
this.request_reload = false
this.reload()
}
},
},
methods: {
getFFrames: function(functor, reduce_fun=null) {
// get frames in functor mode
if (functor === null || functor === undefined) return
if (reduce_fun === null) {
switch (this.$root.store.radio) {
case "one":
reduce_fun = "reduce_0"
break
case "two":
reduce_fun = "reduce_1"
break
default:
reduce_fun = "reduce_0"
break
}
}
var component = this
this.$http.get(
this.$root.storeGet("api_addr") + "/api/functor-frames" +
"?functor=" + functor + "&rf=" + reduce_fun)
.then(function (response) {
component.$root.store.api_error = null
component.frames = response.data.frames
component.state = "normal"
})
.catch(function(error) {
component.$root.store.api_error = error
})
},
getFrames: function (hw, reduce_fun=null) {
if (hw === null || hw === undefined) return
if (reduce_fun === null) {
switch (this.$root.store.radio) {
case "one":
reduce_fun = "reduce_0"
break
case "two":
reduce_fun = "reduce_1"
break
case "three":
reduce_fun = "reduce_5"
break
}
}
var component = this
this.$http.get(
this.$root.storeGet("api_addr") + "/api/frames" +
"?hw=" + hw + "&rf=" + reduce_fun)
.then(function (response) {
component.$root.store.api_error = null
component.frames = response.data.frames
component.state = "normal"
})
.catch(function(error) {
component.$root.store.api_error = error
})
},
buildSentences: function () {
if (this.frames.length == 0) {
return
}
this.sentences = {}
for (var fi in this.frames) {
for (var si in this.frames[fi].sentences) {
var sentence = this.frames[fi].sentences[si]
// get ssj_id without .t123
var ssj_id = sentence[0][0].split(".")
ssj_id.splice(-1, 1) // removes last element
ssj_id = ssj_id.join(".")
var words = []
var hw_idx = -1
var tmp_hw = this.hw
if (tmp_hw[tmp_hw.length - 1] === "_") {
tmp_hw = tmp_hw.substr(0, tmp_hw.length - 1)
}
for (var i in sentence) {
words.push(sentence[i][1].word)
if (sentence[i][1].lemma === tmp_hw && hw_idx == -1) {
hw_idx = i
}
}
this.sentences[ssj_id] = {
hw_idx: hw_idx,
words: words
}
}
}
},
getSenses: function (hw, callback) {
if (hw === null || hw === undefined) {
return
}
var component = this
this.$http.get(
this.$root.store.api_addr + "/api/senses/get" + "?hw=" + hw)
.then(function(response) {
// console.log(response.data)
component.sens.senses = response.data.senses
component.sens.sense_map = response.data.sense_map
callback()
})
},
reload: function () {
this.state = "loading"
this.sentences = {}
if (this.$root.store.navSS === "functors") this.getFFrames(this.hw)
else {
this.getFrames(this.hw)
if (this.$root.store.radio === "three") {
this.getSenses(this.hw, this.sortBySense)
}
}
this.calcPos()
},
userEdit: function () {
// authenticate the user for this
var tthis = this
this.$root.checkToken()
.then(function (response) {tthis.state = "editing"})
.catch(function (err) {alert("Za urejanje je potrebna prijava.")}
)
},
calcPos: function() {
var bfmode = this.fmode
if (typeof(bfmode) === "string") {
bfmode = (bfmode === "true")
}
if (bfmode) return "udeleženska vloga"
else if (this.hw.substr(this.hw.length-1) === "_") return "pridevnik"
return "glagol"
},
sortBySense: function() {
// frames with defined senses on top
var undefFrames = []
var defFrames = []
//console.log(Object.keys(this.sens.sense_map))
for (var i=0; i<this.frames.length; i++) {
var sense_id = this.frames[i].sense_info.sense_id
if (sense_id === "nedefinirano") undefFrames.push(this.frames[i])
else defFrames.push(this.frames[i])
}
this.frames = defFrames.concat(undefFrames)
}
}
}
</script>
<style scoped>
#main-displ-hw {
margin: 0px;
}
</style>

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<template>
<nav>
<b-navbar toggleable="md" type="light" variant="light">
<b-navbar-toggle target="nav_collapse"></b-navbar-toggle>
<b-navbar-brand>Vezljivostni vzorci slovenskih glagolov</b-navbar-brand>
<b-collapse is-nav id="nav_collapse">
<b-navbar-nav>
<b-nav-item-dropdown text="Prikaz" right>
<b-dropdown-item v-for="option in search_options"
:value="option.val"
:key="option.val"
v-on:click="setNavSS(option.val)">
{{ option.key }}
</b-dropdown-item>
</b-nav-item-dropdown>
</b-navbar-nav>
<!-- Right aligned nav items -->
<b-navbar-nav class="ml-auto" right v-if="this.loggedIn()">
<b-nav-item>
Uporabnik: {{ this.$root.store.username }}
<a href="#" v-on:click="logOut()">(odjava)</a>
</b-nav-item>
</b-navbar-nav>
<b-navbar-nav class="ml-auto" right v-else>
<b-nav-item>
<router-link to="/register">
Registracija
</router-link>
</b-nav-item>
<b-nav-item>
<router-link to="/login">
Prijava
</router-link>
</b-nav-item>
</b-navbar-nav>
</b-collapse>
</b-navbar>
</nav>
</template>
<script>
export default {
name: "Nav",
props: ["appState"],
data() {return {
search_options: [
{key: "besede", val: "words"},
{key: "udeleženske vloge", val: "functors"},
],
}},
methods: {
setNavSS(val) {
this.$root.store.radio = "one"
this.$root.store.navSS = val
this.$router.push({
name: "Home"
})
},
loggedIn() {
return (this.$root.store.token !== null)
},
logOut() {
this.$root.store.token = null
this.$root.store.username = null
this.$router.push({
name: "Home"
})
}
}
}
</script>

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<template>
<div>
<div class="col-sm-2">
<a href="#" v-on:click="this.$root.routeBack">Nazaj</a>
</div>
<div class="ev-login col-sm-4 offset-sm-4">
<div class="alert alert-danger" v-if="error">
<p>{{ error }}</p>
</div>
<div class="form-group">
<input
type="text"
data-id="login.username"
class="form-control js-login__username"
placeholder="Uporabnik"
v-model="credentials.username"
>
</div>
<div class="form-group">
<input
type="email"
class="form-control"
placeholder="e-pošta"
v-model="credentials.email"
>
</div>
<div>
<p>Novo geslo bo poslano na vaš e-poštni naslov.</p>
</div>
<button
data-id="new_pass.submit"
class="btn btn-primary solid blank js-login__submit"
@click="submit()"
>
Novo geslo<i class="fa fa-arrow-circle-o-right"></i>
</button>
</div>
</div>
</template>
<script>
export default {
name: 'NewPass',
data () {
return {
credentials: {
username: '',
email: ''
},
error: ''
}
},
methods: {
submit () {
this.error = ""
//this.loggingIn = true
// Auth.login() returns a promise. A redirect will happen on success.
// For errors, use .then() to capture the response to output
// error_description (if exists) as shown below:
/*
this.$auth.login(credentials, 'dashboard').then((response) => {
this.loggingIn = false
this.error = utils.getError(response)
})
*/
if ( this.credentials.username === "" ||
this.credentials.email === ""
) {
this.error = "Izpolnite vsa polja."
return
}
var data = {
username: this.credentials.username,
email: this.credentials.email
}
var component = this
this.$http.post(this.$root.storeGet("api_addr") + "/api/new_pass",
data, // the data to post
{ headers: {
'Content-type': 'application/x-www-form-urlencoded',
}
})
.then(function (response) {
component.$root.store.api_error = null
var confirmation = response.data.confirmation
component.$router.push({
name: "Home"
})
})
.catch(function (err) {
component.$root.store.api_error = err
})
},
},
}
</script>
<style scoped>
.ev-login {
margin-top: 100px;
}
</style>

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<template>
<div>
<div class="col-sm-2">
<a href="#" v-on:click="this.$root.routeBack">Nazaj</a>
</div>
<div class="ev-login col-sm-4 offset-sm-4">
<div class="alert alert-danger" v-if="error">
<p>{{ error }}</p>
</div>
<div class="form-group">
<input
type="text"
class="form-control js-login__username"
placeholder="Uporabnik"
v-model="credentials.username"
autocomplete="off"
>
</div>
<div class="form-group">
<input
type="email"
class="form-control"
placeholder="e-pošta"
v-model="credentials.email"
autocomplete="off"
>
</div>
<div class="form-group">
<input
type="password"
class="form-control js-login__password "
placeholder="Geslo"
v-model="credentials.password"
autocomplete="off"
>
</div>
<div class="form-group">
<input
type="password"
class="form-control js-login__password "
placeholder="Ponovite geslo."
v-model="credentials.snd_password"
autocomplete="off"
>
</div>
<button
class="btn btn-primary solid blank js-login__submit"
@click="submit()"
>
Registracija<i class="fa fa-arrow-circle-o-right"></i>
</button>
</div>
</div>
</template>
<script>
export default {
name: 'Register',
data () { return {
credentials: {
username: "",
password: "",
snd_password: "",
email: ""
},
error: ""
}},
methods: {
clearFields () {
for (var key in this.credentials) {
this.credentials[key] = ""
}
},
checkEmail () {
// check? ... todo
return true
},
submit () {
//console.log(this.credentials.password)
//console.log(this.credentials.snd_password)
const credentials = {
username: this.credentials.username,
password: this.credentials.password
}
// check if fields are full
for (var key in this.credentials) {
if (credentials[key] === "") {
this.error = "Izpolnite vsa polja."
return
}
}
// check e-mail
if (!this.checkEmail(this.credentials.email)) {
this.error = "Preverite e-poštni naslov."
return
}
// check passwords
if (this.credentials.password !== this.credentials.snd_password) {
this.error = "Gesli se ne ujemata."
this.credentials.password = ""
this.credentials.snd_password = ""
return
}
var component = this
const post_data = {
username: this.credentials.username,
password: this.credentials.password,
email: this.credentials.email,
}
this.$http.post(this.$root.storeGet("api_addr") + "/api/register",
post_data, // the data to post
{ headers: {
'Content-type': 'application/json',
}
})
.then(function (response) {
component.$router.push({
name: "Home"
})
})
.catch(function (err) {
component.$root.store.api_error = err
component.error = "Registracija ni uspela."
})
}
}
}
</script>
<style scoped>
.ev-login {
margin-top: 100px;
}
</style>

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<template>
<div class="pb-3">
<div v-if="sense === undefined">
pomen ni definiran
</div>
<div v-else>
<span>{{ sense.desc }}</span>
<br>
&nbsp;&nbsp;
<small class="text-secondary">
- {{ sense.author }}
{{ gen_id() }}
</small>
</div>
</div>
</template>
<script>
export default {
name: "Sense",
props: ["sense"],
methods: {
gen_id: function() {
var id_arr = this.sense.sense_id.split("-")
var ret = ""
if (this.sense.author === "SSKJ") {
if (id_arr[1] !== "0") {
ret += ("[" + id_arr[1] + ["] "])
}
if (id_arr[2] !== "0") {
ret += ("pomen " + id_arr[2])
if (id_arr[3] !== "0") {
ret += ("." + id_arr[3])
}
}
if (id_arr[4] === "sopo") {
ret += " (sopomenka)"
}
}
// ret = this.sense.sense_id //debugging
if (ret.length > 0) {
ret = ": " + ret
}
return ret
}
}
}
</script>

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// The Vue build version to load with the `import` command
// (runtime-only or standalone) has been set in webpack.base.conf with an alias.
import Vue from 'vue'
import App from './App'
import router from './router'
import VueCookies from "vue-cookies"
// bootstrap
import BootstrapVue from "bootstrap-vue"
import 'bootstrap/dist/css/bootstrap.css'
import 'bootstrap-vue/dist/bootstrap-vue.css'
// ajax
import axios from "axios"
// config
import config_data from "../config/config.json"
// console.log(config_data)
Vue.config.productionTip = false
// cokies
Vue.use(VueCookies)
// bootstrap
Vue.use(BootstrapVue)
// CORS
// Vue.$http.headers.common['Access-Control-Allow-Origin'] = true
Vue.prototype.$http = axios
// hand-made global storage
const store = {
api_error: null,
api_addr: config_data.api_addr,
// api_addr: "http://localhost:5004", // development (webpack)
// api_addr: "http://193.2.76.103:5004", // production
token: null,
username: null,
navSS: "words",
radio: "one",
has_se: [], // used for appending (se) to certain verbs
}
const store_methods = {
storeSet: function(key, val) {
store[key] = val
},
storeGet: function(key) {
// returns undefined if not in dict.
// check if (variable)
return store[key]
}
}
const login_methods = {
checkToken: function () {
var tthis = this
return new Promise(function (resolve, reject) {
if (tthis.store.token === null) {
tthis.store.username = null
reject(false)
}
var data = {
token: tthis.store.token,
user: tthis.store.username
}
tthis.$http.post(tthis.store.api_addr + "/api/token", data,
{ headers: {
'Content-type': 'application/x-www-form-urlencoded',
}}
)
.then(function (response) {
tthis.store.api_error = null
if (response.data.confirmation) {
resolve(true)
} else {
tthis.store.username = null
tthis.store.token = null
reject(false)
}
})
.catch(function (err) {
tthis.store.api_error = err
reject(err)
})
})
}
}
const other_methods = {
routeBack: function() {
this.$router.go(-1)
},
mkspace: function (idx, word) {
var stopwords = [".", ",", ":", ";"]
if (stopwords.includes(word)) return false
return true
}
}
/* eslint-disable no-new */
new Vue({
el: '#app',
router,
components: { App },
template: '<App/>',
data() { return {
store: store,
}},
methods: Object.assign(store_methods, login_methods, other_methods),
beforeCreate: function() {
document.title = "Vezljivostni vzorci"
if (this.$cookies.isKey("valency_token")) {
var cookie_token = this.$cookies.get("valency_token")
var data = {
token: cookie_token,
}
var component = this
this.$http.post(store.api_addr + "/api/token",
data, // the data to post
{ headers: {
'Content-type': 'application/x-www-form-urlencoded',
}
})
.then(function (response) {
if (response.data.confirmation) {
store.username = response.data.username
store.token = cookie_token
} else {
this.$cookies.remove("valency_token")
}
})
.catch(function (err) {
store.api_error = err
})
}
}
})

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import Vue from 'vue'
import Router from 'vue-router'
import Home from "@/components/Home"
import Login from "@/components/Login"
import Register from "@/components/Register"
import NewPass from "@/components/NewPass"
import MainDispl from "@/components/MainDispl"
import EditSenses from "@/components/EditSenses"
Vue.use(Router)
export default new Router({
mode: "history",
routes: [
{
path: '/',
redirect: "/home"
},
{
path: "/home",
name: "Home",
component: Home,
children: [
{
path: "words/:hw",
name: "MainDispl",
component: MainDispl,
props: true,
},
]
},
{
path: '/login',
name: 'Login',
component: Login
},
{
path: '/register',
name: 'Register',
component: Register
},
{
path: '/new_pass',
name: 'NewPass',
component: NewPass
}
]
})

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proxy: {
'*': 'http://localhost:5004'
}