def addUserToChat(chat_id):
'''
Adds a user to a chat (just in case you want to add more users to a chat after it's creation)
input: the user's id (dic): e.g. {'userId': 0}
output: user_id, chat_id
'''
db, coll = connectCollection('chats', 'chats')
data = list(coll.find({'idChat': int(chat_id)}))
# Checking if chat exists:
if len(data) == 0:
error = "Sorry, this chat doesn't exist. You must create it first."
return {'Exception': error}
user = int(request.forms.get('userId'))
db2, coll2 = connectCollection('chats', 'users')
usersData = list(coll2.aggregate([{'$project': {'idUser': 1}}]))
# Checking if user exists:
if user not in [e['idUser'] for e in usersData]:
error = 'Sorry, the user you are trying to include does not exist in the database. You must create it first.'
return {'Exception': error}
users = [
int(e) for e in re.sub('\[|\]', '', data[0]['users']).split(', ')
]
# Checking if user is already part of the chat:
if user in users:
error = 'Sorry, this user is already part of the chat'
return {'Exception': error}
users.append(user)
# Adding the new user to the chat:
coll.update_one({'idChat': int(chat_id)},
{'$set': {
'users': str(users)
}})
return {'UserId': user, 'ChatId': int(chat_id)}
def createChat():
'''
Creates a conversation to load messages
input: A dictionary containing an array of user ids: e.g. {'users': '[8, 9, 10]'}
output: chat_id
'''
users = str(request.forms.get('users'))
print(users)
db, coll = connectCollection('chats', 'chats')
data = list(coll.aggregate([{'$project': {'idChat': 1}}]))
newChat = {
'idChat': max([e['idChat'] for e in data]) + 1,
'users': users
}
print(newChat)
# Checking if users exist in the database
db2, coll2 = connectCollection('chats', 'users')
usersData = list(coll2.aggregate([{'$project': {'idUser': 1}}]))
chatUsers = [
int(e) for e in re.sub('\[|\]', '', newChat['users']).split(', ')
]
for e in chatUsers:
if e not in [f['idUser'] for f in usersData]:
error = 'Sorry, one or more of the users you are trying to include do not exist in the database. You must create them first.'
return {'Exception': error}
# Inserting new chat to the database:
chat_id = coll.insert_one(newChat).inserted_id
return {'ObjectId': str(chat_id), 'ChatId': newChat['idChat']}
def addMessageToChat(chat_id):
'''
Adds a message to an existing chat
input: chat_id / user_id and message as dict: e.g. {'user':0, 'message':'Hi!'}
output: message_id
'''
db, coll = connectCollection('chats', 'messages_linked')
data = list(coll.find({'idChat': int(chat_id)}))
user = int(request.forms.get('user'))
message = str(request.forms.get('message'))
# Checking if the chat exists
db2, coll2 = connectCollection('chats', 'chats')
chat = list(coll2.find({'idChat': int(chat_id)}))
if len(chat) == 0:
error = "Sorry, this chat doesn't exist. You must create it first."
return {'Exception': error}
# Checking that the incoming user is part of this chat before adding the chat message to the database.
chatUsers = [
int(e) for e in re.sub('\[|\]', '', chat[0]['users']).split(', ')
]
if user not in chatUsers:
error = 'Sorry, this user is not part of the chat. You must add him/her first.'
return {'Exception': error}
# Adding the new message:
db3, coll3 = connectCollection('chats', 'users')
selectedUser = list(coll3.find({'idUser': user}))
if len(data) == 0:
newMessageId = 0
else:
newMessageId = max([e['idMessage'] for e in data]) + 1
newMessage = {
'datetime': datetime.datetime.utcnow(),
'idChat': int(chat_id),
'idMessage': newMessageId,
'idUser': user,
'text': message,
'userName': selectedUser[0]['userName'],
'user_id': selectedUser[0]['_id']
}
message_id = coll.insert_one(newMessage).inserted_id
return {
'ObjectId': str(message_id),
'MessageId': newMessage['idMessage']
}
def recommendUsers(user_id):
'''
Recommends a friend to a user based on chat contents
input: user_id
output: json array with top 3 similar users
'''
db, coll = connectCollection('chats', 'messages_linked')
data = list(coll.find({}))
# Checking if the user exists in the database:
if int(user_id) not in list(set([e['idUser'] for e in data])):
error = 'Sorry, this user does not exist in the database'
return {'Exception': error}
tokenizer = RegexpTokenizer(r'\w+')
stop_words = set(stopwords.words('english'))
TokensDict = {}
for userId in list(set([e['idUser'] for e in data])):
usersData = list(coll.find({'idUser': userId}))
usersTokens = [tokenizer.tokenize(e['text']) for e in usersData]
usersTokens_clean = [
word for message in usersTokens for word in message
if word not in stop_words
]
TokensDict[f'{userId}'] = ' '.join(usersTokens_clean)
sim_df = similarityDF(TokensDict)
recommendedIds = [
int(e) for e in list(sim_df[str(user_id)].sort_values(
ascending=False)[0:3].index)
]
db2, coll2 = connectCollection('chats', 'users')
recommendedNames = []
for e in recommendedIds:
userInfo = list(coll2.find({'idUser': e}))
recommendedNames.append(userInfo[0]['userName'])
return {
'recommended_users_ids': recommendedIds,
'recommended_users_names': recommendedNames
}
def createUser():
'''
Creates a user and saves it into the database
input: the user's name (dic): e.g. {'username': '******'}
output: user_id
'''
username = str(request.forms.get('username'))
db, coll = connectCollection('chats', 'users')
data = list(coll.aggregate([{'$project': {'idUser': 1}}]))
newUser = {
'idUser': max([e['idUser'] for e in data]) + 1,
'userName': username
}
# Checking that the given username does not already exist in the database:
takenNames = list(coll.aggregate([{'$project': {'userName': 1}}]))
if newUser['userName'] in [e['userName'] for e in takenNames]:
error = 'Sorry, there is already a user with that exact name in the database'
return {'Exception': error}
else:
# Inserting new user to the database:
user_id = coll.insert_one(newUser).inserted_id
return {'ObjectId': str(user_id), 'UserId': newUser['idUser']}
def getMessages(chat_id):
'''
Get all messages from 'chat_id'
input: chat_id
output: json array with all messages from this chat_id
'''
db, coll = connectCollection('chats', 'messages_linked')
data = list(coll.find({'idChat': int(chat_id)}))
messages = {}
for index, dictionary in enumerate(data):
index += 1
messages[f'message_{index}'] = {
'user': dictionary['userName'],
'date': str(dictionary['datetime'])[0:10],
'time': str(dictionary['datetime'])[11:19],
'text': dictionary['text']
}
if len(messages) == 0:
error = 'Sorry, this chat does not exist in the database'
return {'Exception': error}
else:
return messages
#!/usr/bin/python3
from pymongo import MongoClient, ASCENDING
from bottle import request, response, post, get, run, route
from bson.json_util import dumps
import requests
import os
import json
import datetime
from src.mongo import connectCollection, stop_existence, stop_not_existence, get_name
from src.nltk import analyzer, get_text
from src.recommender import get_users_mod, get_messages_user, similarities_matrix, recommendations
# collections
db, chats = connectCollection('API', 'chats')
db, users = connectCollection('API', 'users')
db, messages = connectCollection('API', 'messages')
@route('/')
def main():
return 'Welcome to my first API! Check this project in: https://github.com/jgph91/API_project'
# users endpoints
@post('/users/create')
def user_creator():
'''Create a user and save into DB'''
#text entered via params
dict(request.forms)
def main():
# Importing original messages data to MongoDB:
db, coll = connectCollection('chats','messages')
with open('./input/original.json', encoding="utf8") as f:
chats_json = json.load(f)
coll.insert_many(chats_json)
# Users collection:
df = pd.read_json('./input/original.json')
userDF = df[['idUser','userName']]
userDF.drop_duplicates(inplace=True)
coll2 = db['users']
coll2.insert_many(userDF.to_dict('records'))
# userDF.to_json('./input/users.json', orient="records")
# Adding users_id to messages collection:
db, coll = connectCollection('chats','users')
data = list(coll.find({}))
user_id_list = []
for i in range(len(df)):
for e in data:
if df.at[i,'idUser'] == e['idUser']:
user_id_list.append(e['_id'])
df['user_id'] = user_id_list
coll3 = db['messages_linked']
coll3.insert_many(df.to_dict('records'))
# Chats collection:
chatsDF = df[['idChat', 'idUser']]
chatsDF.drop_duplicates(inplace=True)
chatsDF.reset_index(drop=True, inplace=True)
uniqueChats = list(set(chatsDF['idChat']))
users_total = []
for e in uniqueChats:
users = []
for i in range(len(chatsDF)):
if chatsDF.at[i,'idChat'] == e:
users.append(chatsDF.at[i,'idUser'])
users_total.append(str(users))
chatsDF = pd.DataFrame(uniqueChats, columns=['idChat'])
chatsDF['users'] = users_total
coll4 = db['chats']
coll4.insert_many(chatsDF.to_dict('records'))
# chatsDF.to_json('./input/chatsID.json', orient="records")
# Backup of collections:
db, coll = connectCollection('chats','messages_linked')
data = list(coll.find({}))
with open('./input/messages.json', 'w') as file:
json.dump(data, file, default=json_util.default)
db, coll = connectCollection('chats','users')
data = list(coll.find({}))
with open('./input/users.json', 'w') as file:
json.dump(data, file, default=json_util.default)
db, coll = connectCollection('chats','chats')
data = list(coll.find({}))
with open('./input/chats.json', 'w') as file:
json.dump(data, file, default=json_util.default)
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.metrics.pairwise import cosine_similarity as distance
from bottle import route, run, get, post, request, template
from nltk.tokenize import RegexpTokenizer
from nltk.corpus import stopwords
from bson.json_util import dumps
from dotenv import load_dotenv
nltk.download('stopwords')
nltk.download('punkt')
nltk.download('vader_lexicon')
load_dotenv()
db, coll = connectCollection('api-project', 'chats')
db, users = connectCollection('api-project', 'users')
db, chatsCR = connectCollection('api-project', 'chatsCR')
def main():
@get("/")
def home():
return template('info', title="WELCOME TO CHAT ANALYSIS API")
@get('/user/create')
def insert_name():
return template('users')
@post("/user/create")
def createUser():
from nltk import download
from nltk.sentiment.vader import SentimentIntensityAnalyzer
from pymongo import MongoClient, ASCENDING
from src.mongo import connectCollection
# collections
db, messages = connectCollection('API', 'messages')
def get_text(id, field):
'''Returns a string with the text of all the message
from the specified chat'''
id = int(id)
text_messages = messages.find({field: id})
text = ''
for e in text_messages:
text += e['text']
return text
def analyzer(text):
'''Rates the specified text'''
download('vader_lexicon')
mood = SentimentIntensityAnalyzer().polarity_scores(text)
return mood