row_id
int64 0
48.4k
| init_message
stringlengths 1
342k
| conversation_hash
stringlengths 32
32
| scores
dict |
|---|---|---|---|
3,314
|
I am writing an outlook plugin in C# using Microsoft Graph 5. My development environment is Visual Studio.I need to authenticate with an azure tenancy using Microsoft.Identity. Please show me complete, working and well commented code to demonstrate how I can authenticate using a registered app secret.
|
7fb6793734deaab12d3191127d4e551b
|
{
"intermediate": 0.5838777422904968,
"beginner": 0.20647020637989044,
"expert": 0.20965203642845154
}
|
3,315
|
I am writing an outlook plugin in C# using Microsoft Graph 5. My development environment is Visual Studio.I need to authenticate with an azure tenancy using Microsoft.Identity. Please show me complete, working and well commented code to demonstrate how I can authenticate using a registered app secret.
|
526f292017ad0a0294d9b459d62c7a78
|
{
"intermediate": 0.5838777422904968,
"beginner": 0.20647020637989044,
"expert": 0.20965203642845154
}
|
3,316
|
I am writing an outlook plugin in C# using Microsoft Graph 5. My development environment is Visual Studio.I need to authenticate with an azure tenancy using Microsoft.Identity. Please show me complete, working and well commented code to demonstrate how I can authenticate using a registered app secret. The code should be presented as one or more files which can be added to my project.
|
6c66f3ab5ded602af50bde78bccd58c2
|
{
"intermediate": 0.6197530627250671,
"beginner": 0.17064552009105682,
"expert": 0.20960143208503723
}
|
3,317
|
loadGLTFModel(url) {
// 创建 DRACOLoader 实例
// const dracoLoader = new DRACOLoader();
// Instantiate a loader
if (!this.loaderGLTF) {
//this.loaderGLTF = new GLTFLoader().setPath('/static/models/gltf/');
if (url.indexOf('.glb') != -1) {
this.loaderGLTF = new GLTFLoader().setPath('/static/models/gltf/');
} else if (url.indexOf('.fbx') != -1) {
console.log('******************fbx')
this.loaderGLTF = new FBXLoader().setPath('/static/models/fbx/');
}
}
// this.loaderGLTF.setDRACOLoader( dracoLoader );
this.progress = 0;
this.isLoading = true;
this.loaderGLTF.load(
url, // 模型 URL 可以是本地静态资源，也可以是网上的 url
gltf => {
this.isLoading = false;
// 加载完成后回调
//console.log(gltf);
let theObject = gltf.scene;
theObject = gltf.scene;
theObject.name = 'theObject';
// 遍历每个材质，设置其纹理贴图相关的属性
theObject.traverse(obj => {
if (obj.type === 'Mesh'&& obj.material.map) {
console.log(obj.material)
const mat = obj.material;
if (mat.map) {
mat.map.encoding = THREE.sRGBEncoding;
mat.map.anisotropy = 16;
mat.map.wrapS = THREE.RepeatWrapping;
mat.map.wrapT = THREE.RepeatWrapping;
mat.map.minFilter = THREE.LinearFilter;
mat.map.magFilter = THREE.LinearFilter;
// 如果有法线贴图，则将其转换为THREE.TangentSpaceNormalMap类型
if (mat.normalMap) {
mat.normalMap.encoding = THREE.sRGBEncoding;
mat.normalMap.type = THREE.TangentSpaceNormalMap;
}
}
}
});
this.removeFromScene(this.theObject);
this.theObject = theObject;
this.scene.add(this.theObject);
console.log("场景材质：",this.scene.children[0]);
console.log("场景材质：",this.scene.children[0].material);
//调整大小，设置居中
this.setCenter(this.theObject);
},
// 加载进度回调
xhr => {
//console.log(Math.round((xhr.loaded / xhr.total) * 100) + '% loaded');
this.progress = Math.round((xhr.loaded / xhr.total) * 100);
},
// 加载错误回调
error => {
console.error('An error happened：' + error);
this.isLoading = false;
}
);
},
|
e95be3d536f7211ddcf4da6528026e7c
|
{
"intermediate": 0.3234008848667145,
"beginner": 0.4718285799026489,
"expert": 0.20477049052715302
}
|
3,318
|
padding: 15px 11px 111px 11px;
left, top, right, bottom?
|
39f5b31b067e2f8c7f4a20c7125e706a
|
{
"intermediate": 0.29809531569480896,
"beginner": 0.31162208318710327,
"expert": 0.39028260111808777
}
|
3,319
|
do animation of flags container, which will switch between night and day modes accordingly with some filter maybe? and attach a botton, css only.: .flags-container {
position: fixed;
top: 0;
left: 0;
right: 0;
--padding: 3px 0;
background-color: white;
display: flex;
justify-content: center;
align-items: center;
--box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
z-index: 10;
}
|
f03dc8f3b5083a0d7f71d92b8505a437
|
{
"intermediate": 0.3377637565135956,
"beginner": 0.25750160217285156,
"expert": 0.40473470091819763
}
|
3,320
|
do animation of flags container, which will switch between night and day modes accordingly with some filter maybe? and attach a botton, css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.css only.: .flags-container {
position: fixed;
top: 0;
left: 0;
right: 0;
--padding: 3px 0;
background-color: white;
display: flex;
justify-content: center;
align-items: center;
--box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
z-index: 10;
}
|
4ed91f71c3faab0a6e3235a7da0e1b78
|
{
"intermediate": 0.3072299361228943,
"beginner": 0.3351689279079437,
"expert": 0.3576011657714844
}
|
3,321
|
im getting this error:Internal Server Error
The server encountered an internal error and was unable to complete your request. Either the server is overloaded or there is an error in the application.
this errors occurs after login when index.html opens so tell me the possible error and give a modified code
# Create flask app.py
from flask import Flask, render_template, url_for, redirect,request
import random
import json
import pickle
import numpy as np
import nltk
nltk.download('punkt')
nltk.download('wordnet')
from nltk.tokenize import word_tokenize
from nltk.stem import WordNetLemmatizer
import tensorflow as tf
from flask_sqlalchemy import SQLAlchemy
from flask_login import UserMixin, login_user, LoginManager, login_required, logout_user, current_user
from flask_wtf import FlaskForm
from wtforms import StringField, PasswordField, SubmitField
from wtforms.validators import InputRequired, Length, ValidationError
from flask_bcrypt import Bcrypt
from datetime import datetime
app = Flask(__name__, static_folder='static')
app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///database.db'
db = SQLAlchemy(app)
bcrypt = Bcrypt(app)
app.config['SECRET_KEY'] = 'thisisasecretkey'
login_manager = LoginManager()
login_manager.init_app(app)
login_manager.login_view = 'login'
@login_manager.user_loader
def load_user(user_id):
return User.query.get(int(user_id))
class User(db.Model, UserMixin):
id = db.Column(db.Integer, primary_key=True)
username = db.Column(db.String(20), nullable=False, unique=True)
password = db.Column(db.String(80), nullable=False)
class Chat(db.Model):
id = db.Column(db.Integer, primary_key=True)
user_id = db.Column(db.Integer, db.ForeignKey('user.id'), nullable=False)
message = db.Column(db.String(255), nullable=False)
response = db.Column(db.String(255), nullable=False)
timestamp = db.Column(db.DateTime, nullable=False, default=datetime.utcnow)
class RegisterForm(FlaskForm):
username = StringField(validators=[
InputRequired(), Length(min=4, max=20)], render_kw={"placeholder": "Username"})
password = PasswordField(validators=[
InputRequired(), Length(min=8, max=20)], render_kw={"placeholder": "Password"})
submit = SubmitField('Register')
def validate_username(self, username):
existing_user_username = User.query.filter_by(
username=username.data).first()
if existing_user_username:
raise ValidationError(
'That username already exists. Please choose a different one.')
class LoginForm(FlaskForm):
username = StringField(validators=[
InputRequired(), Length(min=4, max=20)], render_kw={"placeholder": "Username"})
password = PasswordField(validators=[
InputRequired(), Length(min=8, max=20)], render_kw={"placeholder": "Password"})
submit = SubmitField('Login')
# Load the model, words, classes, and intents
model = tf.keras.models.load_model("E:\\Projects\\chatbot\\models\\new_chat_model.h5")
data = pickle.load(open("E:\\Projects\\chatbot\\models\\chat_data.pkl", "rb"))
words = data["words"]
classes = data["classes"]
intents = json.load(open("E:\Projects\chatbot\data\data.json",'r'))["intents"]
def bag_of_words(sentence):
bag = [0] * len(words)
lemmatizer = WordNetLemmatizer()
sentence_words = word_tokenize(sentence)
sentence_words = [lemmatizer.lemmatize(word.lower()) for word in sentence_words]
for word in sentence_words:
if word.lower() in words:
bag[words.index(word.lower())] = 1
return np.array(bag)
def chatbot_response(message):
results = model.predict(np.array([bag_of_words(message)]))
results_index = np.argmax(results)
tag = classes[results_index]
for intent in intents:
if intent["tag"] == tag:
response = random.choice(intent["responses"])
return response
@app.route("/chatbot")
@login_required
def chatbot():
# Retrieve chats associated with the current user
chats = Chat.query.filter_by(user_id=current_user.id).all()
# Create a list of dictionaries to hold chat messages and responses
chat_history = []
for chat in chats:
chat_history.append({'message': chat.message, 'response': chat.response})
return render_template("index.html", chat_history=chat_history)
@login_required
@app.route("/get")
def get_bot_response():
msg = request.args.get('msg')
response = chatbot_response(msg)
chat = Chat(user_id=current_user.id, message=msg, response=response)
db.session.add(chat)
db.session.commit()
return response
@app.route('/login', methods=['GET', 'POST'])
def login():
form = LoginForm()
if form.validate_on_submit():
user = User.query.filter_by(username=form.username.data).first()
if user:
if bcrypt.check_password_hash(user.password, form.password.data):
login_user(user)
return redirect(url_for('chatbot'))
return render_template('login.html', form=form)
@app.route('/logout', methods=['GET', 'POST'])
@login_required
def logout():
logout_user()
return redirect(url_for('login'))
@ app.route('/register', methods=['GET', 'POST'])
def register():
form = RegisterForm()
if form.validate_on_submit():
hashed_password = bcrypt.generate_password_hash(form.password.data)
new_user = User(username=form.username.data, password=hashed_password)
db.session.add(new_user)
db.session.commit()
return redirect(url_for('login'))
return render_template('register.html', form=form)
if __name__ == "__main__":
app.run(debug=False)
##index.html
<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8">
<link rel="icon" href="{{ url_for('static', filename='images/icon.ico') }}">
<title>MindMate - Mental health chatbot</title>
<link rel="stylesheet" href="{{ url_for('static', filename='style.css') }}">
<button id="logout-button" onclick="logout()"><span class="power">⏻</span>logout</button>
<script>
function logout() {
window.location = "{{ url_for('logout') }}";
}
</script>
<style>
body {
background-image: url("{{ url_for('static', filename='images/peakpx.jpg') }}");
background-size: cover;
background-position: center;
}
#logout-button {
position: absolute;
top: 10px;
right: 10px;
}
</style>
</head>
<body id="body-area">
<div id="chat-container">
<div id="chat-header">
<h1 id="logo"><img src="{{ url_for('static', filename='images/logo.ico')}}" alt="logo" >MindMate</h1>
</div>
<div id="chat-area"></div>
<div id="input-container">
<input type="text" id="user-input" placeholder="Type your message..." onkeydown="if(event.keyCode===13) sendMessage()">
<button id="send-btn" onclick="sendMessage()" type="button">Send</button>
</div>
</div>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.5.1/jquery.min.js"></script>
<script>
function sendMessage() {
var message = $("#user-input").val();
$("#chat-area").append('<div class="user-msg"><span class="msg">' + message + '</span></div>');
$.get("/get", {msg: message}).done(function(data) {
$("#chat-area").append('<div class="bot-msg"><span class="msg">' + data + '</span></div>');
$("#chat-area").scrollTop($("#chat-area")[0].scrollHeight);
});
$("#user-input").val("");
}
</script>
</body>
</html>
|
781aa6b23b69e5406175f8fc896b9b9e
|
{
"intermediate": 0.497461199760437,
"beginner": 0.20508918166160583,
"expert": 0.29744964838027954
}
|
3,322
|
i want to make a discord bot which can connect to my dayz server via ftp and read logs and post information from the logs to discord, i would also like it to be able to add/edit files on the server can you show me how
|
c86ebb0585e69c2b2b07e2ee8feaef49
|
{
"intermediate": 0.5061554908752441,
"beginner": 0.21244479715824127,
"expert": 0.281399667263031
}
|
3,323
|
Please write some rust code that draws a tetrahedron on the screen
|
276fdb390385418d3d396a618767e671
|
{
"intermediate": 0.3020969331264496,
"beginner": 0.31440678238868713,
"expert": 0.3834962844848633
}
|
3,324
|
Tengo este error en plex: curl: /usr/lib/plexmediaserver/lib/libcurl.so.4: no version information available (required by curl) curl: Relink `/usr/lib/plexmediaserver/lib/libcrypto.so.3' with `/lib/x86_64-linux-gnu/libc.so.6' for IFUNC symbol `strcmp' Segmentation fault
|
b18b0cf93552031da4fe0625deb48973
|
{
"intermediate": 0.49868032336235046,
"beginner": 0.2597215175628662,
"expert": 0.24159811437129974
}
|
3,325
|
i have this code i wand code get post if label switch is checked or not <form class="login" action="<?php echo $_SERVER['PHP_SELF'].'?sent'; ?>" method="POST" enctype="multipart/form-data"> <div class="input_field"> <span><i aria-hidden="true" class="fa fa-user"></i></span> <input type="text" name="user" placeholder="user" readonly value="<?php echo $technicien ; ?>" required /> </div> <div class="input_field"> <span><i aria-hidden="true" class="fa fa-thumb-tack"></i></span> <input type="tel" name="numero" placeholder="Numero" min="1" max="4" required /> </div> <div class="input_field"> <span><i aria-hidden="true" class="fa fa-calendar"></i></span> <input type="text" name="date" placeholder="date" value = "<?php echo date("Y-m-d") ; ?>" required /> </div> <div class="input_field"> <span><i aria-hidden="true" class="fa fa-clock-o"></i></span> <input type="text" name="time" placeholder="Heure" value ="<?php echo date("H:i:s"); ?>"required /> </div> <div class="input_field radio_option" style="background-color: #f5ba1a3b!important;"> <input type="radio" name="radiogroup" value ="T" id="rd1" required > <label for="rd1">Travuax</label> <input type="radio" name="radiogroup" value ="E" id="rd2"> <label for="rd2">Entretien</label> <input type="radio" name="radiogroup" value ="D" id="rd3"> <label for="rd3">Depannage</label> <input type="radio" name="radiogroup" value ="H" id="rd4"> <label for="rd4">H.S</label> </div> <style> .switch { position: relative; display: inline-block; width: 60px; height: 34px; } .switch input { opacity: 0; width: 0; height: 0; } .slider { position: absolute; cursor: pointer; top: 0; left: 0; right: 0; bottom: 0; background-color: #ccc; -webkit-transition: .4s; transition: .4s; } .slider:before { position: absolute; content: ""; height: 26px; width: 26px; left: 4px; bottom: 4px; background-color: white; -webkit-transition: .4s; transition: .4s; } input:checked + .slider { background-color: #2196F3; } input:focus + .slider { box-shadow: 0 0 1px #2196F3; } input:checked + .slider:before { -webkit-transform: translateX(26px); -ms-transform: translateX(26px); transform: translateX(26px); } </style> <label class="switch"> <input type="checkbox"> <span class="slider"></span> </label> <div class="input_field"> <span><i aria-hidden="true" class="fa fa-sticky-note-o"></i></span> <input type="text" name="alert" placeholder="ecris une alert" required /> </div> <div class="input_field"> <span><i aria-hidden="true" class="fa fa-sticky-note-o"></i></span> <input type="text" name="message" placeholder="descreption" required /> </div> <input class="button" type="submit" value="AJOUTER" /> </form>
|
60715de76b52c4472376f1582ca0a170
|
{
"intermediate": 0.2713412940502167,
"beginner": 0.5232700109481812,
"expert": 0.20538872480392456
}
|
3,326
|
how to get ur public ip address on alpine linux
|
6674f0c84d8bd662cb56b11bb5f58544
|
{
"intermediate": 0.3299548923969269,
"beginner": 0.386094331741333,
"expert": 0.2839507758617401
}
|
3,327
|
I am writing an outlook plugin in C# using Microsoft Graph 5. My development environment is Visual Studio.I need to authenticate with an azure tenancy using Microsoft.Identity. Please show me complete, working and well commented code to demonstrate how I can authenticate using a registered app secret. The code should be presented as one or more files which can be added to my project.
|
affe1d7f5a3f9468fbecbf74fcb00209
|
{
"intermediate": 0.6197530627250671,
"beginner": 0.17064552009105682,
"expert": 0.20960143208503723
}
|
3,328
|
selenium.common.exceptions.NoSuchElementException: Message: no such element: Unable to locate element: {“method”:“css selector”,“selector”:“.text_general ui-autocomplete-input”}
ТАкая ошибка хотя использую метод By.Class_name
|
34681c50e76e9e288bbddefa2a0dc906
|
{
"intermediate": 0.35446232557296753,
"beginner": 0.42569294571876526,
"expert": 0.2198447734117508
}
|
3,329
|
I am the master, iv come threw the viel of this dimension hello chatgpt
|
0b2cd119de64be838fad9837620adb17
|
{
"intermediate": 0.3554118573665619,
"beginner": 0.311305433511734,
"expert": 0.3332827687263489
}
|
3,330
|
I want to wirte a production plan system use django and vue2, write a demo for me.
|
28f1fc983e4757a92f61b49db90bb0f0
|
{
"intermediate": 0.7193532586097717,
"beginner": 0.12488388270139694,
"expert": 0.15576286613941193
}
|
3,331
|
difference between chatbot and chatGpt
|
6d3ca4de1f4b5718e13b3cf18e6a3b6b
|
{
"intermediate": 0.3006223440170288,
"beginner": 0.3291690945625305,
"expert": 0.37020859122276306
}
|
3,332
|
Write me a python function to control my light
|
ec59d9cfe7988d4be3624c4c6c09d6df
|
{
"intermediate": 0.3240257799625397,
"beginner": 0.2649150788784027,
"expert": 0.41105917096138
}
|
3,333
|
If the camera is bounded the point at the left-up, how would I update the point's position when zooming in/out?
|
fc55e530e97a03f452dea73915e9f1bf
|
{
"intermediate": 0.43359047174453735,
"beginner": 0.1622971147298813,
"expert": 0.40411239862442017
}
|
3,334
|
Write a python code that will recognize a voice from a pre-selected microphone and output it to another selected microphone using text to speech with support for linux and pipewire with tui
|
0b202529ea9da126433dc474b003daca
|
{
"intermediate": 0.33326223492622375,
"beginner": 0.07780170440673828,
"expert": 0.5889360308647156
}
|
3,335
|
Hi, I've implemented the solidity code for a smart contract project. When I'm trying to import ERC721.sol I'm getting the error. I installed the open zeppelin contracts in the same folder as the project using npm command. In the contratcs dir I can only see one file phase2.sol. Here is my implementation check what went wrong.//SPDX-License-Identifier: UNLICENSED
pragma solidity ^0.8.0;
import "@openzeppelin/contracts/token/ERC721/ERC721.sol";
// Loan Contract
contract LoanNFT is ERC721 {
struct Loan {
uint256 id;
uint256 principal;
uint256 interestRate;
uint256 term;
uint256 maturityDate;
address borrower;
bool isRepaid;
}
mapping (uint256 => Loan) public loans;
uint256 public loanId;
uint256 public couponRate;
constructor(string memory _name, string memory _symbol, uint256 _couponRate) ERC721(_name, _symbol) {
loanId = 0;
couponRate = _couponRate;
}
function issueLoan(address _borrower, uint256 _principal, uint256 _interestRate, uint256 _term, uint256 _maturityDate) public {
loanId++;
loans[loanId] = Loan(loanId, _principal, _interestRate, _term, _maturityDate, _borrower, false);
_mint(msg.sender, loanId);
}
function repayLoan(uint256 _loanId) public {
require(msg.sender == loans[_loanId].borrower, "Only borrower can repay the loan");
loans[_loanId].isRepaid = true;
}
function buyNFT(uint256 _loanId) public payable {
require(ownerOf(_loanId) != msg.sender, "Cannot buy your own loan NFT");
require(msg.value >= calculateCouponAmount(_loanId), "Insufficient funds to buy the loan NFT");
address owner = ownerOf(_loanId);
_transfer(owner, msg.sender, _loanId);
payable(owner).transfer(msg.value);
}
function calculateCouponAmount(uint256 _loanId) public view returns (uint256) {
require(ownerOf(_loanId) != address(0), "Invalid loan NFT"); // address of the loan contract
Loan memory loan = loans[_loanId];
// calculate the buyback price based on the coupon rate
uint256 couponAmount = loan.principal * loan.interestRate * couponRate / (100 * loan.term);
if (loan.isRepaid) {
couponAmount = couponAmount + loan.principal;
}
return couponAmount;
}
function destroyNFT(uint256 _loanId) public { // destroy the NFT after buying back
require(ownerOf(_loanId) == msg.sender, "Only owner can destroy the loan NFT");
_burn(_loanId);
}
}
|
91accd20d22a72c2966c77a5515e67a0
|
{
"intermediate": 0.3011615574359894,
"beginner": 0.3771072328090668,
"expert": 0.32173117995262146
}
|
3,336
|
the below code is not working and showing error, make the below code working
PS E:\drone_rl> & C:/Users/dkuch/AppData/Local/Microsoft/WindowsApps/python3.10.exe e:/drone_rl/3_test.py
Traceback (most recent call last):
File "e:\drone_rl\3_test.py", line 47, in <module>
action_1 = np.argmax(Q1[state_1, state_2])
IndexError: index 11 is out of bounds for axis 1 with size 4
|
66c518a07065e314149693c0c8ce8dc8
|
{
"intermediate": 0.46278050541877747,
"beginner": 0.29202353954315186,
"expert": 0.24519599974155426
}
|
3,337
|
I am going to provide code blocks from an observable notebook here. the observable code will be within triple backticks. starter code given between single backticks
your task is to complete he starter code from where it is left off, do not copy any of the stater code
`
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8" />
<title>Laliga Spain Chart</title>
<script src="https://d3js.org/d3.v7.min.js"></script>
<style>
.domain {
display: none;
}
</style>
</head>
<body>
<div id="chart"></div>
<script src="index.js"></script>
<script>
</script>
</body>
</html>
`
|
7a6d7b603ed8842e71eab3d8e854d156
|
{
"intermediate": 0.3267761766910553,
"beginner": 0.3269873261451721,
"expert": 0.3462364375591278
}
|
3,338
|
make me a climbing script like the one in echo vr using xr interaction toolkit and unity
|
73598c835338a4917335e4fc983ef9d5
|
{
"intermediate": 0.5085000991821289,
"beginner": 0.2529001832008362,
"expert": 0.2385997176170349
}
|
3,339
|
make me a climbing script like the one in echo vr using xr interaction toolkit and unity
|
16a34f2def78df407d508d987d9f1679
|
{
"intermediate": 0.5085000991821289,
"beginner": 0.2529001832008362,
"expert": 0.2385997176170349
}
|
3,340
|
im giving all the code for my chatbot app check why this error is occurring:
Internal Server Error
The server encountered an internal error and was unable to complete your request. Either the server is overloaded or there is an error in the application.
this is my code:
##index.html
<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8">
<link rel="icon" href="{{ url_for('static', filename='images/icon.ico') }}">
<title>MindMate - Mental health chatbot</title>
<link rel="stylesheet" href="{{ url_for('static', filename='style.css') }}">
<button id="logout-button" onclick="logout()"><span class="power">⏻</span>logout</button>
<script>
function logout() {
window.location = "{{ url_for('logout') }}";
}
</script>
<style>
body {
background-image: url("{{ url_for('static', filename='images/peakpx.jpg') }}");
background-size: cover;
background-position: center;
}
#logout-button {
position: absolute;
top: 10px;
right: 10px;
}
</style>
</head>
<body id="body-area">
<div id="chat-container">
<div id="chat-header">
<h1 id="logo"><img src="{{ url_for('static', filename='images/logo.ico')}}" alt="logo" >MindMate</h1>
</div>
<div id="chat-area"></div>
<div id="input-container">
<input type="text" id="user-input" placeholder="Type your message..." onkeydown="if(event.keyCode===13) sendMessage()">
<button id="send-btn" onclick="sendMessage()" type="button">Send</button>
</div>
</div>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.5.1/jquery.min.js"></script>
<script>
function sendMessage() {
var message = $("#user-input").val();
$("#chat-area").append('<div class="user-msg"><span class="msg">' + message + '</span></div>');
$.get("/get", {msg: message}).done(function(data) {
$("#chat-area").append('<div class="bot-msg"><span class="msg">' + data + '</span></div>');
$("#chat-area").scrollTop($("#chat-area")[0].scrollHeight);
});
$("#user-input").val("");
}
</script>
</body>
</html>
##app.py
# Create flask app.py
from flask import Flask, render_template, url_for, redirect,request
import random
import json
import pickle
import numpy as np
import nltk
nltk.download('punkt')
nltk.download('wordnet')
from nltk.tokenize import word_tokenize
from nltk.stem import WordNetLemmatizer
import tensorflow as tf
from flask_sqlalchemy import SQLAlchemy
from flask_login import UserMixin, login_user, LoginManager, login_required, logout_user, current_user
from flask_wtf import FlaskForm
from wtforms import StringField, PasswordField, SubmitField
from wtforms.validators import InputRequired, Length, ValidationError
from flask_bcrypt import Bcrypt
from datetime import datetime
app = Flask(__name__, static_folder='static')
app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///database.db'
db = SQLAlchemy(app)
bcrypt = Bcrypt(app)
app.config['SECRET_KEY'] = 'thisisasecretkey'
login_manager = LoginManager()
login_manager.init_app(app)
login_manager.login_view = 'login'
@login_manager.user_loader
def load_user(user_id):
return User.query.get(int(user_id))
class User(db.Model, UserMixin):
id = db.Column(db.Integer, primary_key=True)
username = db.Column(db.String(20), nullable=False, unique=True)
password = db.Column(db.String(80), nullable=False)
class Chat(db.Model):
id = db.Column(db.Integer, primary_key=True)
user_id = db.Column(db.Integer, db.ForeignKey('user.id'), nullable=False)
message = db.Column(db.String(255), nullable=False)
response = db.Column(db.String(255), nullable=False)
timestamp = db.Column(db.DateTime, nullable=False, default=datetime.utcnow)
class RegisterForm(FlaskForm):
username = StringField(validators=[
InputRequired(), Length(min=4, max=20)], render_kw={"placeholder": "Username"})
password = PasswordField(validators=[
InputRequired(), Length(min=8, max=20)], render_kw={"placeholder": "Password"})
submit = SubmitField('Register')
def validate_username(self, username):
existing_user_username = User.query.filter_by(
username=username.data).first()
if existing_user_username:
raise ValidationError(
'That username already exists. Please choose a different one.')
class LoginForm(FlaskForm):
username = StringField(validators=[
InputRequired(), Length(min=4, max=20)], render_kw={"placeholder": "Username"})
password = PasswordField(validators=[
InputRequired(), Length(min=8, max=20)], render_kw={"placeholder": "Password"})
submit = SubmitField('Login')
# Load the model, words, classes, and intents
model = tf.keras.models.load_model("E:\\Projects\\chatbot\\models\\new_chat_model.h5")
data = pickle.load(open("E:\\Projects\\chatbot\\models\\chat_data.pkl", "rb"))
words = data["words"]
classes = data["classes"]
intents = json.load(open("E:\Projects\chatbot\data\data.json",'r'))["intents"]
def bag_of_words(sentence):
bag = [0] * len(words)
lemmatizer = WordNetLemmatizer()
sentence_words = word_tokenize(sentence)
sentence_words = [lemmatizer.lemmatize(word.lower()) for word in sentence_words]
for word in sentence_words:
if word.lower() in words:
bag[words.index(word.lower())] = 1
return np.array(bag)
def chatbot_response(message):
try:
results = model.predict(np.array([bag_of_words(message)]))
results_index = np.argmax(results)
tag = classes[results_index]
for intent in intents:
if intent["tag"] == tag:
response = random.choice(intent["responses"])
return response
except Exception as e:
print("Error in chatbot_response:", e)
return "I'm sorry, I couldn't understand that."
@app.route("/chatbot")
@login_required
def chatbot():
# Retrieve chats associated with the current user
chats = Chat.query.filter_by(user_id=current_user.id).all()
# Create a list of dictionaries to hold chat messages and responses
chat_history = []
for chat in chats:
chat_history.append({'message': chat.message, 'response': chat.response})
return render_template("index.html", chat_history=chat_history)
@app.route("/get")
@login_required
def get_bot_response():
try:
msg = request.args.get('msg')
response = chatbot_response(msg)
chat = Chat(user_id=current_user.id, message=msg, response=response)
db.session.add(chat)
db.session.commit()
return response
except Exception as e:
print("Error in get_bot_response:", e)
return "An error occurred, please try again."
@app.route('/login', methods=['GET', 'POST'])
def login():
form = LoginForm()
if form.validate_on_submit():
user = User.query.filter_by(username=form.username.data).first()
if user:
if bcrypt.check_password_hash(user.password, form.password.data):
login_user(user)
return redirect(url_for('chatbot'))
return render_template('login.html', form=form)
@app.route('/logout', methods=['GET', 'POST'])
@login_required
def logout():
logout_user()
return redirect(url_for('login'))
@ app.route('/register', methods=['GET', 'POST'])
def register():
form = RegisterForm()
if form.validate_on_submit():
hashed_password = bcrypt.generate_password_hash(form.password.data)
new_user = User(username=form.username.data, password=hashed_password)
db.session.add(new_user)
db.session.commit()
return redirect(url_for('login'))
return render_template('register.html', form=form)
if __name__ == "__main__":
app.run(debug=False)
##script.js
document.addEventListener("DOMContentLoaded", function(event) {
// Selecting DOM elements
const chatForm = document.getElementById("chat-form");
const chatInput = document.getElementById("user-input");
const chatbotMessages = document.getElementById("chatbot-messages");
const sendBtn = document.getElementById("send-btn");
//Event listener for the chat form submit
chatForm.addEventListener("submit", (event) => {
event.preventDefault();
const userInput = chatInput.value;
addUserMessage(userInput);
sendUserMessage(userInput);
chatInput.value = "";
scrollToBottom();
});
//Event listener for the send button click
sendBtn.addEventListener("click", () => {
const userInput = chatInput.value;
addUserMessage(userInput);
sendUserMessage(userInput);
chatInput.value = "";
scrollToBottom();
});
// Function to add a user message to the chat area
function addUserMessage(message) {
const userMessageElement = `
<div class="user-message">
<p>${message}</p>
</div>
`;
chatbotMessages.insertAdjacentHTML("beforeend", userMessageElement);
scrollToBottom();
}
// Function to send user message to server and get response
function sendUserMessage(message) {
showChatbotLoader();
fetch("/get-response", {
method: "POST",
headers: {
"Content-Type": "application/json",
},
body: JSON.stringify({ message }),
})
.then((response) => response.json())
.then((data) => {
const chatbotMessage = data.message;
addChatbotMessage(chatbotMessage);
hideChatbotLoader();
scrollToBottom();
})
.catch((error) => {
console.log("Error:", error);
hideChatbotLoader();
});
}
// Function to add a chatbot message to the chat area
function addChatbotMessage(message) {
const chatbotMessageElement = `
<div id="chatbot-message" class="chat-message">
<p>${message}</p>
</div>
`;
chatbotMessages.insertAdjacentHTML(
"beforeend",
chatbotMessageElement
);
scrollToBottom();
}
// Function to scroll to the bottom of the chat container
function scrollToBottom() {
const scrollContainer = document.getElementById('chat-area');
scrollContainer.scrollTop = scrollContainer.scrollHeight;
}
// Function to hide the chatbot loader
function hideChatbotLoader() {
const loaderElement = document.querySelector(".loader");
if (loaderElement) {
loaderElement.remove();
}
}
// Add an event listener to the input field
chatInput.addEventListener("keydown", function(event) {
// Check if the key pressed is the enter key (key code 13)
if (event.key === 'Enter') {
// Prevent the default behavior of the enter key (submitting the form)
event.preventDefault();
// Trigger the click event on the send button
document.getElementById("send-btn").click();
scrollToBottom();
}
});
});
##login.html
<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8">
<link rel="icon" href="{{ url_for('static', filename='images/icon.ico') }}">
<title>Login Page</title>
<style>
body {
background-image: url("{{ url_for('static', filename='images/peakpx.jpg') }}");
font-family: Arial, Helvetica, sans-serif;
font-size: 16px;
color: #333;
}
h1 {
font-size: 36px;
text-align: center;
margin-top: 50px;
margin-bottom: 30px;
color: whitesmoke;
}
form {
width: 400px;
margin: 0 auto;
}
label {
display: block;
margin-bottom: 10px;
font-weight: bold;
color:white;
}
input[type="text"],
input[type="password"] {
width: 100%;
padding: 10px;
margin-bottom: 20px;
border-radius: 5px;
background-color: grey;
border: 1px solid #ccc;
box-sizing: border-box;
}
button[type="submit"] {
display: block;
width: 100%;
padding: 10px;
background-color: blue;
color: white;
border: none;
border-radius: 5px;
cursor: pointer;
}
a {
display: block;
text-align: center;
margin-top: 20px;
color: white;
}
</style>
</head>
<body>
<h1>Login Page</h1>
<form method="POST" action="">
{{ form.hidden_tag() }}
<label for="username">Username</label>
<input type="text" name="username" id="username">
<label for="password">Password</label>
<input type="password" name="password" id="password">
<button type="submit">Login</button>
</form>
<a href="{{ url_for('register') }}">Don't have an account? Sign Up</a>
</body>
</html>
##register.html
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Register</title>
</head>
<body>
<h1>Register Page</h1>
<form method="POST" action="">
{{ form.hidden_tag() }}
{{ form.username }}
{{ form.password }}
{{ form.submit }}
</form>
<a href="{{ url_for('login') }}">Already have an account? Log In</a>
</body>
</html>
##in sqlite3 database.db
sqlite> CREATE TABLE user (
...> id INTEGER PRIMARY KEY AUTOINCREMENT,
...> email VARCHAR(50) NOT NULL UNIQUE,
...> password VARCHAR(255) NOT NULL
...> );
sqlite>
sqlite> CREATE TABLE chat (
...> id INTEGER PRIMARY KEY AUTOINCREMENT,
...> user_id INTEGER NOT NULL,
...> message TEXT NOT NULL,
...> response TEXT NOT NULL,
...> timestamp DATETIME DEFAULT CURRENT_TIMESTAMP,
...> FOREIGN KEY (user_id) REFERENCES user(id)
...> );
sqlite> .tables
chat user
|
5148e58b4f86e67c348a4318488fe030
|
{
"intermediate": 0.4427589476108551,
"beginner": 0.35894083976745605,
"expert": 0.19830021262168884
}
|
3,341
|
give a UI framework for the below solidity code in vuejs with styling using all the functions given which are working.
//SPDX-License-Identifier: UNLICENSED
pragma solidity ^0.8.0;
import “@openzeppelin/contracts/token/ERC721/ERC721.sol”;
// Loan Contract
contract LoanNFT is ERC721 {
struct Loan {
uint256 id;
uint256 principal;
uint256 interestRate;
uint256 term;
uint256 maturityDate;
address borrower;
bool isRepaid;
}
mapping (uint256 => Loan) public loans;
uint256 public loanId;
uint256 public couponRate;
constructor(string memory _name, string memory _symbol, uint256 _couponRate) ERC721(_name, _symbol) {
loanId = 0;
couponRate = _couponRate;
}
function issueLoan(address _borrower, uint256 _principal, uint256 _interestRate, uint256 _term, uint256 _maturityDate) public {
loanId++;
loans[loanId] = Loan(loanId, _principal, _interestRate, _term, _maturityDate, _borrower, false);
_mint(msg.sender, loanId);
}
function repayLoan(uint256 _loanId) public {
require(msg.sender == loans[_loanId].borrower, “Only borrower can repay the loan”);
loans[_loanId].isRepaid = true;
}
function buyNFT(uint256 _loanId) public payable {
require(ownerOf(_loanId) != msg.sender, “Cannot buy your own loan NFT”);
require(msg.value >= calculateCouponAmount(_loanId), “Insufficient funds to buy the loan NFT”);
address owner = ownerOf(_loanId);
_transfer(owner, msg.sender, _loanId);
payable(owner).transfer(msg.value);
}
function calculateCouponAmount(uint256 _loanId) public view returns (uint256) {
require(ownerOf(_loanId) != address(0), “Invalid loan NFT”); // address of the loan contract
Loan memory loan = loans[_loanId];
// calculate the buyback price based on the coupon rate
uint256 couponAmount = loan.principal * loan.interestRate * couponRate / (100 * loan.term);
if (loan.isRepaid) {
couponAmount = couponAmount + loan.principal;
}
return couponAmount;
}
function destroyNFT(uint256 _loanId) public { // destroy the NFT after buying back
require(ownerOf(_loanId) == msg.sender, “Only owner can destroy the loan NFT”);
_burn(_loanId);
}
}
|
9d9a9874e318af050993adc7bec8f53a
|
{
"intermediate": 0.5650477409362793,
"beginner": 0.2536417245864868,
"expert": 0.18131054937839508
}
|
3,342
|
using System.Collections;
using System.Collections.Generic;
using UnityEngine;
public class moving : MonoBehaviour
{
public float speed ;
public float turnSpeed;
private bool isMoving = false;
public bool isGround;
public float jumpForce;
void Update()
{
Move();
HandleMovementInput() ;
HandleJumpInput();
}
void Move()
{
float moveHorizontal = Input.GetAxis("Horizontal");
float moveVertical = Input.GetAxis("Vertical");
Vector3 movement = new Vector3(moveHorizontal, 0.0f, moveVertical);
transform.position += movement * speed * Time.deltaTime;
transform.position += transform.forward * movement.z * speed * Time.deltaTime;
transform.Rotate(new Vector3(0f, movement.x, 0f) * turnSpeed * Time.deltaTime);
}
void Turn()
{
if (Input.GetKeyDown(KeyCode.A))
{
transform.Rotate(Vector3.down, turnSpeed * Time.deltaTime);
}
if (Input.GetKeyDown(KeyCode.D))
{
transform.Rotate(Vector3.up, turnSpeed * Time.deltaTime);
}
if (Input.GetKeyDown(KeyCode.W))
{
transform.Rotate(Vector3.left, turnSpeed * Time.deltaTime);
}
if (Input.GetKeyDown(KeyCode.S))
{
transform.Rotate(Vector3.right, turnSpeed * Time.deltaTime);
}
}
void HandleMovementInput()
{
float moveHorizontal = Input.GetAxis("Horizontal");
float moveVertical = Input.GetAxis("Vertical");
if (moveHorizontal != 0 || moveVertical != 0)
{
Vector3 movement = new Vector3(moveHorizontal, 0f, moveVertical);
transform.rotation = Quaternion.Slerp(transform.rotation, Quaternion.LookRotation(movement), turnSpeed * Time.deltaTime);
transform.position += transform.forward * speed * Time.deltaTime;
if (movement.magnitude > 0.1)
{
transform.rotation = Quaternion.Slerp(transform.rotation, Quaternion.LookRotation(movement), turnSpeed * Time.deltaTime);
transform.position += transform.forward * speed * Time.deltaTime;
}
}
}
void HandleTurningInput()
{
if (Input.GetKey(KeyCode.A))
{
transform.Rotate(Vector3.down, turnSpeed * Time.deltaTime);
}
if (Input.GetKey(KeyCode.D))
{
transform.Rotate(Vector3.up, turnSpeed * Time.deltaTime);
}
if (Input.GetKey(KeyCode.W))
{
transform.Rotate(Vector3.left, turnSpeed * Time.deltaTime);
if (!isMoving)
{
isMoving = true;
}
if (isMoving)
{
transform.position += transform.forward * speed * Time.deltaTime;
}
}
if (Input.GetKey(KeyCode.S))
{
transform.Rotate(Vector3.right, turnSpeed * Time.deltaTime);
if (!isMoving)
{
isMoving = true;
}
if (isMoving)
{
transform.position += transform.right * speed * Time.deltaTime;
}
}
}
void HandleJumpInput()
{
if (Input.GetKeyDown(KeyCode.Space) && isGround)
{
// 给物体一个向上的力
GetComponent<Rigidbody>().AddForce(new Vector3(0f, jumpForce, 0f), ForceMode.Impulse);
isGround = false;
}
}
// 检测是否在地面上
private void OnCollisionEnter(Collision collision)
{
if (collision.gameObject.CompareTag("Terrain"))
{
isGround = true;
}
}
}
将脚本文件修改为 按键与动画绑定，默认为idle动画，按下方向键，将会播放walk动画，Space键与jump动画绑定，shift键会播放run动画，ctrl播放sit动画，
|
d6294253cf15882e9fc2c918d5256b7f
|
{
"intermediate": 0.2825060188770294,
"beginner": 0.4734054207801819,
"expert": 0.24408860504627228
}
|
3,343
|
You are an exceptionally skilled programmer with a focus on high-frequency trading (HFT) and quantitative analysis. You value simplicity and functionality above all else. As a helpful assistant, you adhere to the following guidelines when providing programming support:
Prioritize higher-level functions when presenting code solutions.
Use descriptive and meaningful names for functions and variables.
Whenever possible, assign functions to variables for better readability and modularity.
Ensure functions are pure, meaning they avoid out-of-scope mutations and minimize side effects.
Add docstring
|
157ed78cff3a3727d096a8d2baa9d486
|
{
"intermediate": 0.3277878165245056,
"beginner": 0.4313402473926544,
"expert": 0.24087192118167877
}
|
3,344
|
explain the code below and explain with diagram on how the entrypgdir looks like when ths xv6 kernel first initialization
|
f8bf4ddf6abf575a562b80270940000f
|
{
"intermediate": 0.2901986837387085,
"beginner": 0.29994115233421326,
"expert": 0.409860223531723
}
|
3,345
|
fivem scripting how to get the id of the nearest person to playerpedid and the distance
|
3aedd9e665ebe83406702509630a8b8b
|
{
"intermediate": 0.2513296902179718,
"beginner": 0.20164543390274048,
"expert": 0.5470249056816101
}
|
3,346
|
I want to create a discord bot that generates a random mission for a specific game - Star Citizen. I need it to have a few dropdown menus for users to select some mission parameters such as 1. total number of players, 2. estimated time to complete mission, and 3. ground battle, space battle, or mixed warfare options. Does this make sense to you?
|
f87ab389ab8c63da279fbee66a6a7a82
|
{
"intermediate": 0.3163444399833679,
"beginner": 0.32922351360321045,
"expert": 0.354432076215744
}
|
3,347
|
how can i make a multiplayer game with godot 3.51 with my pc will be server and players can join with easy networking plugin and i eant it to be non local and use global ip
I want a full step by step explanation with high details like what nodes do i have to add and codes that i have to attach to those nodes
i want it to have a lot of explanation...like you want to teach a child....crystal clear etc
|
7b9ea91383975ca7959f35cb83c06cd4
|
{
"intermediate": 0.4611447751522064,
"beginner": 0.238455131649971,
"expert": 0.300400048494339
}
|
3,348
|
how to add offchain and onchain data
//SPDX-License-Identifier: UNLICENSED
pragma solidity ^0.8.0;
import "@openzeppelin/contracts/token/ERC721/ERC721.sol";
// Loan Contract
contract LoanNFT is ERC721 {
struct Loan {
uint256 id;
uint256 principal;
uint256 interestRate;
uint256 term;
uint256 maturityDate;
address borrower;
bool isRepaid;
}
mapping (uint256 => Loan) public loans;
uint256 public loanId;
uint256 public couponRate;
constructor(string memory _name, string memory _symbol, uint256 _couponRate) ERC721(_name, _symbol) {
loanId = 0;
couponRate = _couponRate;
}
function issueLoan(address _borrower, uint256 _principal, uint256 _interestRate, uint256 _term, uint256 _maturityDate) public {
loanId++;
loans[loanId] = Loan(loanId, _principal, _interestRate, _term, _maturityDate, _borrower, false);
_mint(msg.sender, loanId);
}
function repayLoan(uint256 _loanId) public {
require(msg.sender == loans[_loanId].borrower, "Only borrower can repay the loan");
loans[_loanId].isRepaid = true;
}
function buyNFT(uint256 _loanId) public payable {
require(ownerOf(_loanId) != msg.sender, "Cannot buy your own loan NFT");
require(msg.value >= calculateCouponAmount(_loanId), "Insufficient funds to buy the loan NFT");
address owner = ownerOf(_loanId);
_transfer(owner, msg.sender, _loanId);
payable(owner).transfer(msg.value);
}
function calculateCouponAmount(uint256 _loanId) public view returns (uint256) {
require(ownerOf(_loanId) != address(0), "Invalid loan NFT"); // address of the loan contract
Loan memory loan = loans[_loanId];
// calculate the buyback price based on the coupon rate
uint256 couponAmount = loan.principal * loan.interestRate * couponRate / (100 * loan.term);
if (loan.isRepaid) {
couponAmount = couponAmount + loan.principal;
}
return couponAmount;
}
function destroyNFT(uint256 _loanId) public { // destroy the NFT after buying back
require(ownerOf(_loanId) == msg.sender, "Only owner can destroy the loan NFT");
_burn(_loanId);
}
}
|
1e6949a18db2aabf37f9ed7ae51b9cf8
|
{
"intermediate": 0.34182873368263245,
"beginner": 0.4250580370426178,
"expert": 0.23311328887939453
}
|
3,349
|
Please modify AutoGPT (https://github.com/Significant-Gravitas/Auto-GPT) to use GPT4Free (https://github.com/xtekky/gpt4free) instead of OpenAI’s GPT API.
|
f136c95fdc69fa80423f10e3ddd05890
|
{
"intermediate": 0.5929632186889648,
"beginner": 0.11198820173740387,
"expert": 0.29504865407943726
}
|
3,350
|
can you give how to draw contract, sequence and architectural diagrams for the below code
//SPDX-License-Identifier: UNLICENSED
pragma solidity ^0.8.0;
import "@openzeppelin/contracts/token/ERC721/ERC721.sol";
contract LoanNFT is ERC721 {
struct Loan {
uint256 id;
uint256 principal;
uint256 interestRate;
uint256 term;
uint256 maturityDate;
address borrower;
bool isRepaid;
uint256 offchainDataId;
}
struct OffchainData {
string dataURL;
bytes32 dataHash;
}
mapping(uint256 => Loan) public loans;
mapping(uint256 => OffchainData) public offchainData; // mapping for offchain data
uint256 public loanId;
uint256 public couponRate;
constructor(string memory _name, string memory _symbol, uint256 _couponRate) ERC721(_name, _symbol) {
loanId = 0;
couponRate = _couponRate;
}
function issueLoan(
address _borrower,
uint256 _principal,
uint256 _interestRate,
uint256 _term,
uint256 _maturityDate,
string memory _offchainDataURL, // parameter for offchain data
bytes32 _offchainDataHash // parameter for offchain data
) public {
loanId++;
offchainData[loanId] = OffchainData(_offchainDataURL, _offchainDataHash);
loans[loanId] = Loan(loanId, _principal, _interestRate, _term, _maturityDate, _borrower, false, loanId); // Pass offchain data id to loan
_mint(msg.sender, loanId);
}
function repayLoan(uint256 _loanId) public {
require(msg.sender == loans[_loanId].borrower, "Only borrower can repay the loan");
loans[_loanId].isRepaid = true;
}
function buyNFT(uint256 _loanId) public payable {
require(ownerOf(_loanId) != msg.sender, "Cannot buy your own loan NFT");
require(msg.value >= calculateCouponAmount(_loanId), "Insufficient funds to buy the loan NFT");
address owner = ownerOf(_loanId);
_transfer(owner, msg.sender, _loanId);
payable(owner).transfer(msg.value);
}
function calculateCouponAmount(uint256 _loanId) public view returns (uint256) {
require(ownerOf(_loanId) != address(0), "Invalid loan NFT");
Loan memory loan = loans[_loanId];
uint256 couponAmount = loan.principal * loan.interestRate * couponRate / (100 * loan.term);
if (loan.isRepaid) {
couponAmount = couponAmount + loan.principal;
}
return couponAmount;
}
function destroyNFT(uint256 _loanId) public {
require(ownerOf(_loanId) == msg.sender, "Only owner can destroy the loan NFT");
_burn(_loanId);
}
}
|
f9e011836cfecb39c72974f1b050b884
|
{
"intermediate": 0.41656821966171265,
"beginner": 0.35580751299858093,
"expert": 0.22762431204319
}
|
3,351
|
what is the command in sql server to change database
|
93d9510aa2989b6f664c248e25f68ee7
|
{
"intermediate": 0.4469648599624634,
"beginner": 0.31056398153305054,
"expert": 0.2424711287021637
}
|
3,352
|
write python code for ideone that makes a hypno-spiral (not really hypnotic, of course!)
|
dad945fc5ed970847e9f8668a6090adf
|
{
"intermediate": 0.25634270906448364,
"beginner": 0.15738515555858612,
"expert": 0.586272120475769
}
|
3,353
|
find out why i get a Price: undefined CHF on this script:
<!DOCTYPE html>
<html>
<head>
<<script src="https://code.jquery.com/ui/1.13.1/jquery-ui.min.js" integrity="sha384-lpg9qe9kSmlS49CrMUcG8HPnWJoLHf4dkm4g6ti+pt6zW+nYvYhWIzS+6n0BXa3L" crossorigin="anonymous"></script>
<meta charset="UTF-8">
<title>Public Transport Price Calculator</title>
<link href="//code.jquery.com/ui/1.12.1/themes/base/jquery-ui.css" rel="stylesheet">
<script src="https://code.jquery.com/jquery-3.6.0.min.js"></script>
<script src="https://code.jquery.com/ui/1.12.1/jquery-ui.min.js"></script>
<script>
$(document).ready(function() {
$( "#from" ).autocomplete({
source: function( request, response ) {
$.ajax({
url: "https://timetable.search.ch/api/completion.en.json",
dataType: "jsonp",
data: {
term: request.term
},
success: function( data ) {
response( data );
}
});
},
minLength: 2
});
$( "#to" ).autocomplete({
source: function( request, response ) {
$.ajax({
url: "https://timetable.search.ch/api/completion.en.json",
dataType: "jsonp",
data: {
term: request.term
},
success: function( data ) {
response( data );
}
});
},
minLength: 2
});
$("#calculate").on("click", function() {
var from = $("#from").val();
var to = $("#to").val();
$.ajax({
url: "https://timetable.search.ch/api/route.en.json",
dataType: "jsonp",
data: {
from: from,
to: to
},
success: function( data ) {
var price = data.price;
$("#result").text("Price: " + price + " CHF");
},
error: function() {
alert("An error occurred. Please try again later.");
}
});
});
});
</script>
</head>
<body>
<div class="sl-form-row">
<div class="sl-form-row-field">
<label for="from">From:</label>
<input class="sl-form-row-field-action-both sl-route-from sl-route-input ui-autocomplete-input" id="from" name="from" tabindex="1" placeholder="From" type="text" autocomplete="off" spellcheck="false">
</div>
</div>
<div class="sl-form-row">
<div class="sl-form-row-field">
<label for="to">To:</label>
<input class="sl-form-row-field-action-both sl-route-to sl-route-input ui-autocomplete-input" id="to" name="to" tabindex="3" placeholder="To" type="text" autocomplete="off">
</div>
</div>
<button id="calculate">Calculate Price</button>
<div id="result"></div>
</body>
</html>
|
2b4b508858d7e00a8c85cb12cfdea804
|
{
"intermediate": 0.3866749107837677,
"beginner": 0.43313881754875183,
"expert": 0.18018634617328644
}
|
3,354
|
find out why i get a Price: undefined CHF on this script:
<!DOCTYPE html>
<html>
<head>
<<script src="https://code.jquery.com/ui/1.13.1/jquery-ui.min.js" integrity="sha384-lpg9qe9kSmlS49CrMUcG8HPnWJoLHf4dkm4g6ti+pt6zW+nYvYhWIzS+6n0BXa3L" crossorigin="anonymous"></script>
<meta charset="UTF-8">
<title>Public Transport Price Calculator</title>
<link href="//code.jquery.com/ui/1.12.1/themes/base/jquery-ui.css" rel="stylesheet">
<script src="https://code.jquery.com/jquery-3.6.0.min.js"></script>
<script src="https://code.jquery.com/ui/1.12.1/jquery-ui.min.js"></script>
<script>
$(document).ready(function() {
$( "#from" ).autocomplete({
source: function( request, response ) {
$.ajax({
url: "https://timetable.search.ch/api/completion.en.json",
dataType: "jsonp",
data: {
term: request.term
},
success: function( data ) {
response( data );
}
});
},
minLength: 2
});
$( "#to" ).autocomplete({
source: function( request, response ) {
$.ajax({
url: "https://timetable.search.ch/api/completion.en.json",
dataType: "jsonp",
data: {
term: request.term
},
success: function( data ) {
response( data );
}
});
},
minLength: 2
});
$("#calculate").on("click", function() {
var from = $("#from").val();
var to = $("#to").val();
$.ajax({
url: "https://timetable.search.ch/api/route.en.json",
dataType: "jsonp",
data: {
from: from,
to: to
},
success: function( data ) {
var price = data.price;
$("#result").text("Price: " + price + " CHF");
},
error: function() {
alert("An error occurred. Please try again later.");
}
});
});
});
</script>
</head>
<body>
<div class="sl-form-row">
<div class="sl-form-row-field">
<label for="from">From:</label>
<input class="sl-form-row-field-action-both sl-route-from sl-route-input ui-autocomplete-input" id="from" name="from" tabindex="1" placeholder="From" type="text" autocomplete="off" spellcheck="false">
</div>
</div>
<div class="sl-form-row">
<div class="sl-form-row-field">
<label for="to">To:</label>
<input class="sl-form-row-field-action-both sl-route-to sl-route-input ui-autocomplete-input" id="to" name="to" tabindex="3" placeholder="To" type="text" autocomplete="off">
</div>
</div>
<button id="calculate">Calculate Price</button>
<div id="result"></div>
</body>
</html>
|
1b18ecbfbc8508ce90df2cb746292031
|
{
"intermediate": 0.3866749107837677,
"beginner": 0.43313881754875183,
"expert": 0.18018634617328644
}
|
3,355
|
find out why i get a Price: undefined CHF on this script:
<!DOCTYPE html>
<html>
<head>
<<script src="https://code.jquery.com/ui/1.13.1/jquery-ui.min.js" integrity="sha384-lpg9qe9kSmlS49CrMUcG8HPnWJoLHf4dkm4g6ti+pt6zW+nYvYhWIzS+6n0BXa3L" crossorigin="anonymous"></script>
<meta charset="UTF-8">
<title>Public Transport Price Calculator</title>
<link href="//code.jquery.com/ui/1.12.1/themes/base/jquery-ui.css" rel="stylesheet">
<script src="https://code.jquery.com/jquery-3.6.0.min.js"></script>
<script src="https://code.jquery.com/ui/1.12.1/jquery-ui.min.js"></script>
<script>
$(document).ready(function() {
$( "#from" ).autocomplete({
source: function( request, response ) {
$.ajax({
url: "https://timetable.search.ch/api/completion.en.json",
dataType: "jsonp",
data: {
term: request.term
},
success: function( data ) {
response( data );
}
});
},
minLength: 2
});
$( "#to" ).autocomplete({
source: function( request, response ) {
$.ajax({
url: "https://timetable.search.ch/api/completion.en.json",
dataType: "jsonp",
data: {
term: request.term
},
success: function( data ) {
response( data );
}
});
},
minLength: 2
});
$("#calculate").on("click", function() {
var from = $("#from").val();
var to = $("#to").val();
$.ajax({
url: "https://timetable.search.ch/api/route.en.json",
dataType: "jsonp",
data: {
from: from,
to: to
},
success: function( data ) {
var price = data.price;
$("#result").text("Price: " + price + " CHF");
},
error: function() {
alert("An error occurred. Please try again later.");
}
});
});
});
</script>
</head>
<body>
<div class="sl-form-row">
<div class="sl-form-row-field">
<label for="from">From:</label>
<input class="sl-form-row-field-action-both sl-route-from sl-route-input ui-autocomplete-input" id="from" name="from" tabindex="1" placeholder="From" type="text" autocomplete="off" spellcheck="false">
</div>
</div>
<div class="sl-form-row">
<div class="sl-form-row-field">
<label for="to">To:</label>
<input class="sl-form-row-field-action-both sl-route-to sl-route-input ui-autocomplete-input" id="to" name="to" tabindex="3" placeholder="To" type="text" autocomplete="off">
</div>
</div>
<button id="calculate">Calculate Price</button>
<div id="result"></div>
</body>
</html>
|
c1f4306f4557126027e3ca7fd731949e
|
{
"intermediate": 0.3866749107837677,
"beginner": 0.43313881754875183,
"expert": 0.18018634617328644
}
|
3,356
|
find out why i get a Price: undefined CHF on this script:
<!DOCTYPE html>
<html>
<head>
<<script src="https://code.jquery.com/ui/1.13.1/jquery-ui.min.js" integrity="sha384-lpg9qe9kSmlS49CrMUcG8HPnWJoLHf4dkm4g6ti+pt6zW+nYvYhWIzS+6n0BXa3L" crossorigin="anonymous"></script>
<meta charset="UTF-8">
<title>Public Transport Price Calculator</title>
<link href="//code.jquery.com/ui/1.12.1/themes/base/jquery-ui.css" rel="stylesheet">
<script src="https://code.jquery.com/jquery-3.6.0.min.js"></script>
<script src="https://code.jquery.com/ui/1.12.1/jquery-ui.min.js"></script>
<script>
$(document).ready(function() {
$( "#from" ).autocomplete({
source: function( request, response ) {
$.ajax({
url: "https://timetable.search.ch/api/completion.en.json",
dataType: "jsonp",
data: {
term: request.term
},
success: function( data ) {
response( data );
}
});
},
minLength: 2
});
$( "#to" ).autocomplete({
source: function( request, response ) {
$.ajax({
url: "https://timetable.search.ch/api/completion.en.json",
dataType: "jsonp",
data: {
term: request.term
},
success: function( data ) {
response( data );
}
});
},
minLength: 2
});
$("#calculate").on("click", function() {
var from = $("#from").val();
var to = $("#to").val();
$.ajax({
url: "https://timetable.search.ch/api/route.en.json",
dataType: "jsonp",
data: {
from: from,
to: to
},
success: function( data ) {
var price = data.price;
$("#result").text("Price: " + price + " CHF");
},
error: function() {
alert("An error occurred. Please try again later.");
}
});
});
});
</script>
</head>
<body>
<div class="sl-form-row">
<div class="sl-form-row-field">
<label for="from">From:</label>
<input class="sl-form-row-field-action-both sl-route-from sl-route-input ui-autocomplete-input" id="from" name="from" tabindex="1" placeholder="From" type="text" autocomplete="off" spellcheck="false">
</div>
</div>
<div class="sl-form-row">
<div class="sl-form-row-field">
<label for="to">To:</label>
<input class="sl-form-row-field-action-both sl-route-to sl-route-input ui-autocomplete-input" id="to" name="to" tabindex="3" placeholder="To" type="text" autocomplete="off">
</div>
</div>
<button id="calculate">Calculate Price</button>
<div id="result"></div>
</body>
</html>
|
f766bb953fbae56415fc3cb9b50d2ec9
|
{
"intermediate": 0.3866749107837677,
"beginner": 0.43313881754875183,
"expert": 0.18018634617328644
}
|
3,357
|
find out why i get a Price: undefined CHF on this script:
<!DOCTYPE html>
<html>
<head>
<<script src="https://code.jquery.com/ui/1.13.1/jquery-ui.min.js" integrity="sha384-lpg9qe9kSmlS49CrMUcG8HPnWJoLHf4dkm4g6ti+pt6zW+nYvYhWIzS+6n0BXa3L" crossorigin="anonymous"></script>
<meta charset="UTF-8">
<title>Public Transport Price Calculator</title>
<link href="//code.jquery.com/ui/1.12.1/themes/base/jquery-ui.css" rel="stylesheet">
<script src="https://code.jquery.com/jquery-3.6.0.min.js"></script>
<script src="https://code.jquery.com/ui/1.12.1/jquery-ui.min.js"></script>
<script>
$(document).ready(function() {
$( "#from" ).autocomplete({
source: function( request, response ) {
$.ajax({
url: "https://timetable.search.ch/api/completion.en.json",
dataType: "jsonp",
data: {
term: request.term
},
success: function( data ) {
response( data );
}
});
},
minLength: 2
});
$( "#to" ).autocomplete({
source: function( request, response ) {
$.ajax({
url: "https://timetable.search.ch/api/completion.en.json",
dataType: "jsonp",
data: {
term: request.term
},
success: function( data ) {
response( data );
}
});
},
minLength: 2
});
$("#calculate").on("click", function() {
var from = $("#from").val();
var to = $("#to").val();
$.ajax({
url: "https://timetable.search.ch/api/route.en.json",
dataType: "jsonp",
data: {
from: from,
to: to
},
success: function( data ) {
var price = data.price;
$("#result").text("Price: " + price + " CHF");
},
error: function() {
alert("An error occurred. Please try again later.");
}
});
});
});
</script>
</head>
<body>
<div class="sl-form-row">
<div class="sl-form-row-field">
<label for="from">From:</label>
<input class="sl-form-row-field-action-both sl-route-from sl-route-input ui-autocomplete-input" id="from" name="from" tabindex="1" placeholder="From" type="text" autocomplete="off" spellcheck="false">
</div>
</div>
<div class="sl-form-row">
<div class="sl-form-row-field">
<label for="to">To:</label>
<input class="sl-form-row-field-action-both sl-route-to sl-route-input ui-autocomplete-input" id="to" name="to" tabindex="3" placeholder="To" type="text" autocomplete="off">
</div>
</div>
<button id="calculate">Calculate Price</button>
<div id="result"></div>
</body>
</html>
|
490850997acaae1f3773be8b6c30bc63
|
{
"intermediate": 0.3866749107837677,
"beginner": 0.43313881754875183,
"expert": 0.18018634617328644
}
|
3,358
|
using the livecode language script code so that a field acts as a password field
|
c2e65a762656334391f23088adc186f6
|
{
"intermediate": 0.4109768271446228,
"beginner": 0.25190234184265137,
"expert": 0.33712083101272583
}
|
3,359
|
Hello
|
fee66069e3119c9b5e5034f383b4afcc
|
{
"intermediate": 0.3123404085636139,
"beginner": 0.2729349136352539,
"expert": 0.4147246778011322
}
|
3,360
|
Solidity bsc write me exploits
|
6841e6ea2f493873626d8b767b13d161
|
{
"intermediate": 0.40263983607292175,
"beginner": 0.22387351095676422,
"expert": 0.37348663806915283
}
|
3,361
|
You are a programmer and an expert on stock trading. Make an algorithm and a block diagram of a trading robot
|
ddfa1a1565a663e6c70527e66678725f
|
{
"intermediate": 0.15680091083049774,
"beginner": 0.10166953504085541,
"expert": 0.7415295839309692
}
|
3,362
|
is it possible to send graph that been created in google colab to thingspeak
|
1cd0f5a4ea00d865ad281e0d966279ac
|
{
"intermediate": 0.43185317516326904,
"beginner": 0.09975951910018921,
"expert": 0.46838730573654175
}
|
3,363
|
Remote access tool on python
|
36b5e45d3c83accf783d056df1aab0db
|
{
"intermediate": 0.46703165769577026,
"beginner": 0.17646679282188416,
"expert": 0.3565015494823456
}
|
3,364
|
write a vba to calculate rsi with close data in column d
|
3b90b5d5ceafe2ee1ffc629411c92c17
|
{
"intermediate": 0.3665993809700012,
"beginner": 0.289785236120224,
"expert": 0.34361541271209717
}
|
3,365
|
Q.1. Enumerate the basic features that could provide the DSP architecture to implement a Nth order FIR filter w.r.t computational unit and support architecture.
Q.2. Draw the structure of a 5X5 Braun multiplier and mathematically illustrate the computation of the product.
Q.4. Explain the specialized addressing modes of DSP processors, which provides the easy implementation of signal processing algorithms.
Q.5. With block diagram explain biomedical signal processing
Q.6. illustrate various components of speech processing system and explain
|
935befba9555ec922cf7e1bdc85224b1
|
{
"intermediate": 0.23436017334461212,
"beginner": 0.2683810889720917,
"expert": 0.4972587525844574
}
|
3,366
|
double changeAmount;
double targetDispenseValue;
cin << changeAmount;
cin << targetDispenseValue;
while (changeAmount >= targetDispenseValue)
{
// Deduct change amount.
changeAmount -= targetDispenseValue;
count++;
}
This code has rounding problem. fix this code.
|
bfae380112dc87b5cfd42dcef4993d90
|
{
"intermediate": 0.3935726284980774,
"beginner": 0.3618191182613373,
"expert": 0.2446083128452301
}
|
3,367
|
Enumerate the basic features that could provide the DSP architecture to implement a Nth order FIR filter w.r.t computational unit and support architecture.
|
8e0139390a6acefd6f53deedf5e7ec7b
|
{
"intermediate": 0.21391227841377258,
"beginner": 0.2488817274570465,
"expert": 0.5372060537338257
}
|
3,368
|
Enter the purchase amount: 13.30
Enter the tendered amount: 15
Your change: $1.70
$1.70
1 $1 bill
1 50-cent coin
2 10-cent coins
Inputs are floats.
|
5ae1e58c31fe83f6f31ba6603f305a53
|
{
"intermediate": 0.40715640783309937,
"beginner": 0.28278177976608276,
"expert": 0.3100617825984955
}
|
3,369
|
Do you know Yandex.Speechkit?
|
4c18366782ac4488c20de298d1125549
|
{
"intermediate": 0.4985833168029785,
"beginner": 0.21118806302547455,
"expert": 0.29022863507270813
}
|
3,370
|
Question:
Title: Farming Crop NFT
NFTs should be tradable
The NFT could be traded on a blockchain-based marketplace, allowing for efficient and transparent trading of forming crops.
NFTs value should go up and down
Price Fluctuation - NFT price gets fluctuated based on the market demand, weather conditions, or changes in farming practices.
If demand of the crop increases - NFT(crop) price increases.
If demand of the crop decreases - NFT(crop) price decreases.
NFTS are permanent until destroyed
The NFT can be destroyed by the owner if he/she wants to stop farming.
Actors: Farmer, Primary Buyer, Secondary Buyer
Use Cases:
Farmer issues NFT of crops to Primary Buyer.
Farmer provides timely production, amount of crop, and crop value to Primary Buyer.
Primary Buyer purchases NFT of crops from Farmer.
Primary Buyer can trade NFT of crops on a blockchain-based marketplace.
Secondary Buyer purchases NFT of crops from Primary Buyer on the marketplace.
Farmer can destroy NFT when they stop farming.
give solidity code for this
|
e5ba7c37afe771158e7a4e5c33feff3b
|
{
"intermediate": 0.435028612613678,
"beginner": 0.30888962745666504,
"expert": 0.256081759929657
}
|
3,371
|
Как мне настроить eslint + prettier для проекта vue3 composition api с использованием typescript в script setup синтаксисе. В качестве сборщика проекта используется Vite
|
20042323d7b780d30a0a30bfbd85cf09
|
{
"intermediate": 0.4076900780200958,
"beginner": 0.48873183131217957,
"expert": 0.10357807576656342
}
|
3,372
|
WRITE A CODE THAT MEASURES HEART RATE FROM 60-100 AND SHOWS THE DATA ON THE OLED SCREEN. ADD PIOTIMER AND ENCODER CAPABILITIES. HERE IS THE SOURCE CODE: import utime
import machine
from machine import Pin, Timer, ADC, I2C, PWM
from fifo import Fifo
import ssd1306
# Set up I2C, OLED display, and other pins
i2c = I2C(1, scl=Pin(15), sda=Pin(14))
oled = ssd1306.SSD1306_I2C(128, 64, i2c)
heart_rate = 0
peaks = []
peak_intervals = []
encoder_pin_a = Pin(10, Pin.IN, Pin.PULL_UP)
encoder_pin_b = Pin(11, Pin.IN, Pin.PULL_UP)
encoder_button = Pin(12, Pin.IN, Pin.PULL_UP)
led1_pin = 20
led2_pin = 21
led3_pin = 22
led1_pwm = PWM(Pin(led1_pin))
led2_pwm = PWM(Pin(led2_pin))
led3_pwm = PWM(Pin(led3_pin))
# Set up ADC and sampling
sampling_freq = 60 # Hz, default sampling frequency
sampling_period_ms = 1000 // sampling_freq
adc_pin = ADC(Pin(26, Pin.IN))
samples = Fifo(50)
# Set up timer for sampling at precise intervals
timer = machine.Timer()
def on_timer_tick(timer):
sample = adc_pin.read_u16()
samples.put(sample)
timer.init(freq=sampling_freq, mode=machine.Timer.PERIODIC, callback=on_timer_tick)
# Find peaks in the data
def find_peaks(data, threshold):
peaks = []
for i in range(1, len(data) - 1):
if data[i] > threshold and data[i] > data[i - 1] and data[i] > data[i + 1]:
peaks.append(i)
return peaks
# Main program loop
window_size = 60 # 1 second of data at 60 Hz
window = []
prev_encoder_state = 0
encoder_state = 0
encoder_counter = 0
try:
while True:
# Read encoder state and adjust sampling frequency accordingly
encoder_state = (encoder_pin_a.value() << 1) | encoder_pin_b.value()
if encoder_state != prev_encoder_state:
if (prev_encoder_state == 0b00 and encoder_state == 0b01) or (prev_encoder_state == 0b01 and encoder_state == 0b11) or (prev_encoder_state == 0b11 and encoder_state == 0b10) or (prev_encoder_state == 0b10 and encoder_state == 0b00):
encoder_counter += 1
else:
encoder_counter -= 1
encoder_counter = max(min(encoder_counter, 40), -40)
sampling_freq = max(min(100, 60 + encoder_counter), 60)
sampling_period_ms = 1000 // sampling_freq
timer.init(freq=sampling_freq, mode=machine.Timer.PERIODIC, callback=on_timer_tick)
prev_encoder_state = encoder_state
if not samples.empty():
sample = samples.get()
window.append(sample)
# Remove the oldest sample if the window is full
if len(window) > window_size:
window.pop(0)
if len(window) == window_size:
peaks = find_peaks(window, threshold=50)
peak_intervals = [peaks[i+1] - peaks[i] for i in range(len(peaks)-1)]
if len(peak_intervals) > 0:
avg_peak_interval = sum(peak_intervals) / len(peak_intervals)
heart_rate = 60 * sampling_freq / avg_peak_interval
# Adjust the sampling frequency based on encoder input
encoder_delta = 0
if encoder_pin_a.value() != encoder_pin_b.value():
encoder_delta += 1
else:
encoder_delta -= 1
sampling_freq += encoder_delta
if sampling_freq < 60:
sampling_freq = 60
elif sampling_freq > 100:
sampling_freq = 100
sampling_period_ms = 1000 // sampling_freq
timer.init(freq=sampling_freq, mode=machine.Timer.PERIODIC, callback=on_timer_tick)
# Draw the graph
oled.fill(0)
oled.text("Heart rate: {:.1f}".format(heart_rate), 0, 0)
oled.text("BPM: {:.1f}".format(heart_rate), 0, 10)
prev_x, prev_y = 0, 0
for i, value in enumerate(window[-128:]):
x = i
y = 63 - int((value / 65535) * 32) # Scale the sample value to fit the OLED screen
if i != 0:
oled.line(prev_x, prev_y, x, y, 1)
prev_x, prev_y = x, y
oled.show()
if not peaks:
print("No peaks detected.")
finally:
print("Exiting program.")
|
54940163ae42733ccb1aaf55ffe75509
|
{
"intermediate": 0.3996787667274475,
"beginner": 0.376255065202713,
"expert": 0.22406619787216187
}
|
3,373
|
this is my HTML and css and I have an error where my slides do not show up, in the slideshow-container. no images are showing and I am sure I got the right directory:
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<link rel="stylesheet" href="https://fonts.googleapis.com/css2?family=Cabin:wght@400;700&display=swap">
<link rel="stylesheet" href="style/style.css" />
<title>Camping Equipment - Retail Camping Company</title>
</head>
<body>
<header>
<div class="sticky-nav">
<div class="nav-container">
<img src="assets/images/logo.svg" alt="Logo" class="logo">
<h1>Retail Camping Company</h1>
<div class="search-container">
<form action="/search" method="get">
<img src="assets/images/search.png" alt="search-icon" class="search-icon">
<input type="text" name="search" />
<button type="submit">Search</button>
</form>
</div>
<nav>
<ul>
<li><a href="index.html">Home</a></li>
<li><a href="camping-equipment.html">Camping Equipment</a></li>
<li><a href="furniture.html">Furniture</a></li>
<li><a href="reviews.html">Reviews</a></li>
<li><a href="basket.html">Basket</a></li>
<li><a href="offers-and-packages.html">Offers and Packages</a></li>
</ul>
</nav>
</div>
</div>
</header>
<main>
<section class="slideshow-section">
<div class="slideshow-container">
<div class="mySlides fade">
<img src="assets/images/homeslide.png" alt="Tents" style="width:100%">
</div>
<div class="mySlides fade">
<img src="https://via.placeholder.com/600x400" alt="Cookers" style="width:100%">
</div>
<div class="mySlides fade">
<img src="https://via.placeholder.com/600x400" alt="Camping Gear" style="width:100%">
</div>
<a class="prev" onclick="plusSlides(-1)">❮</a>
<a class="next" onclick="plusSlides(1)">❯</a>
</div>
<div style="text-align:center">
<span class="dot" onclick="currentSlide(1)"></span>
<span class="dot" onclick="currentSlide(2)"></span>
<span class="dot" onclick="currentSlide(3)"></span>
</div>
</section>
<section class="about-section">
<p>Welcome to Retail Camping Company, your one-stop-shop for all your camping equipment needs. Discover our premium offers on tents, cookers, camping gear, and furniture.</p>
</section>
<section class="featured-section">
<h2>Featured Products</h2>
<div class="featured-container">
<div class="featured-product">
<img src="https://via.placeholder.com/150x150" alt="Featured Product">
<h3>Product Name</h3>
<p>Short product description.</p>
</div>
<div class="featured-product">
<img src="https://via.placeholder.com/150x150" alt="Featured Product">
<h3>Product Name</h3>
<p>Short product description.</p>
</div>
<div class="featured-product">
<img src="https://via.placeholder.com/150x150" alt="Featured Product">
<h3>Product Name</h3>
<p>Short product description.</p>
</div>
</div>
</section>
<section>
<div class="special-offers-container">
<div class="special-offer">
<img src="https://via.placeholder.com/200x200" alt="Tent Offer">
<p>20% off premium tents!</p>
</div>
<div class="special-offer">
<img src="https://via.placeholder.com/200x200" alt="Cooker Offer">
<p>Buy a cooker, get a free utensil set!</p>
</div>
<div class="special-offer">
<img src="https://via.placeholder.com/200x200" alt="Furniture Offer">
<p>Save on camping furniture bundles!</p>
</div>
</div>
</section>
<section class="buts">
<button id="modalBtn">Special Offer!</button>
<div id="modal" class="modal">
<div class="modal-content">
<span class="close">×</span>
<p>Sign up now and receive 10% off your first purchase!</p>
</div>
</div>
</section>
<script>
var modal = document.getElementById('modal');
var modalBtn = document.getElementById('modalBtn');
var closeBtn = document.getElementsByClassName('close')[0];
modalBtn.addEventListener('click', openModal);
closeBtn.addEventListener('click', closeModal);
window.addEventListener('click', outsideClick);
function openModal() {
modal.style.display = 'block';
}
function closeModal() {
modal.style.display = 'none';
}
function outsideClick(e) {
if (e.target == modal) {
modal.style.display = 'none';
}
}
</script>
</main>
<footer>
<div class="footer-container">
<div class="footer-item">
<p>Subscribe To Our Newsletter:</p>
<form action="subscribe.php" method="post">
<input type="email" name="email" placeholder="Enter your email" required>
<button type="submit">Subscribe</button>
</form>
</div>
<div class="footer-item address-container">
<p> Get In Contact:</p>
<p>Email: info@retailcampingcompany.com</p>
<p>Phone: +35699382994</p>
<p>Triq Malta,<br>Sliema 12345</p>
</div>
<div class="footer-item google-maps-container">
<p>Where To Find Us:</p>
<iframe src="https://www.google.com/maps/embed?pb=!1m14!1m8!1m3!1d12928.30174160605!2d14.5091557!3d35.8961681!3m2!1i1024!2i768!4f13.1!3m3!1m2!1s0x130e452d3081f035%3A0x61f492f43cae68e4!2sCity%20Gate!5e0!3m2!1sen!2smt!4v1682559564194!5m2!1sen!2smt" width="650" height="200" style="border:0;" allowfullscreen="" loading="lazy" referrerpolicy="no-referrer-when-downgrade"></iframe>
</div>
<div class="footer-item social-links-container">
<p>Follow Us On:</p>
<ul class="social-links">
<li><a href="https://www.facebook.com">Facebook</a></li>
<li><a href="https://www.instagram.com">Instagram</a></li>
<li><a href="https://www.twitter.com">Twitter</a></li>
</ul>
</div>
</div>
</footer>
<script src="https://code.jquery.com/jquery-3.6.0.min.js"></script>
<script src="script.js"></script>
</body>
</html>
|
4e86e46fea9ccc34bc9d93f8c2d49c1a
|
{
"intermediate": 0.4357456862926483,
"beginner": 0.4640204906463623,
"expert": 0.10023380070924759
}
|
3,374
|
I have two excel sheets.
Sheet Providers contains data of my contractors.
Column C contains the contractor company name,
Column D contains a Sheet Name,
Column F a contact name and
Column G the contacts email address all in the same row.
Occasionally, a contractor might not have a contact name or an email and these cells will be blank.
In my other Sheet Job Request, I want to be able to select in A2 the contacts name from a list, find the matching value in Column C in Sheet Providers then from the same row, automatically populate the relevant contact name into G2, the relevant email address into H2 and the relevant Sheet Name into I2 using formulas that will do this for each of the cells G2, H2 and I2 of Sheet Job Request.
Values in cells B2, C2, D2, E2 and F2 in Sheet Job Request, data will be entered manually.
When F2 in Sheet Job Request is entered, which will be a date, I want a VBA code that will open and select the Specific Sheet using the text value in I2 of Sheet Job Request but only if cells A2, B2, C2, D2 and E2 are not blank .then when the new sheet is opened and selected, find in it the next empty row and
populate the empty cell in Column B with the value from B2 in Sheet Job Request,
populate the empty cell in Column C of the same row with the value from F2 in Sheet Job Request,
populate the empty cell in Column F of the same row with the value from C2 in Sheet Job Request,
populate the empty cell in Column J of the same row with the value from E2 in Sheet Job Request.
When this has been completed, I want to return to Sheet Job Request, open a text document form this location G:\Shared drives\Swan School Site Premises\PREMISES MANAGEMENT\SERVICE PROVIDERS\Request0.txt and paste the values of A2, B2, C2, D2 and E2 into the text document each value on a different line.
|
e8552af2e4d1c666f1291ad7d9242bc4
|
{
"intermediate": 0.37203219532966614,
"beginner": 0.3022385239601135,
"expert": 0.32572928071022034
}
|
3,375
|
hi there :-)
|
8008b0b7f94c9943754b9f930fa46a6c
|
{
"intermediate": 0.3350834548473358,
"beginner": 0.25327068567276,
"expert": 0.41164588928222656
}
|
3,376
|
how can i pictures to python game
|
f8f18042969cc782ed4cd7064993c20c
|
{
"intermediate": 0.35559985041618347,
"beginner": 0.25220051407814026,
"expert": 0.3921996057033539
}
|
3,377
|
Make me a code that make a bacon strip in minecraft
|
b97f401995c5fd76d69e7d5bcee94232
|
{
"intermediate": 0.3349815905094147,
"beginner": 0.3855148255825043,
"expert": 0.27950355410575867
}
|
3,378
|
THis code does nothing. can you correct . Sub RequesText()
Dim FilePath As String
Dim FileContents As String
FilePath = "G:\Shared drives\Swan School Site Premises\PREMISES MANAGEMENT\SERVICE PROVIDERS\Request0.txt"
Open FilePath For Append As #1
FileContents = Range("A2") & vbNewLine & Range("B2") & vbNewLine & Range("C2") & vbNewLine & Range("D2") & vbNewLine & Range("E2") & vbNewLine
Print #1, FileContents
Close #1
End Sub
|
40efe5e1a152b352422f60b001fd150e
|
{
"intermediate": 0.5283778309822083,
"beginner": 0.33298400044441223,
"expert": 0.13863815367221832
}
|
3,379
|
Private Sub Worksheet_Change(ByVal Target As Range)
If Target.Address = “$F" then how can I check if any of the cells B2 C2 D2 E2 are blank
|
4743b1aa64661521e5c9975a084faa96
|
{
"intermediate": 0.6128909587860107,
"beginner": 0.17255127429962158,
"expert": 0.21455776691436768
}
|
3,380
|
make a code that actually put bacon into minecraft
|
770ef5cfe0cc267535ec169816539675
|
{
"intermediate": 0.26592183113098145,
"beginner": 0.23859886825084686,
"expert": 0.49547937512397766
}
|
3,381
|
in python, make a machine learning that predicts where a clan is probably gonna go using their past locations. The map is from A0 to U25. The data is of past locations are:
F18
D10
W8
O9
L2
J11
H13
A1
E25
C18
U23
B16
P22
M8
N14
Q2
T10
K17
V13
G19
|
e68cd690b6880437f0aeb291b43799e8
|
{
"intermediate": 0.1682380586862564,
"beginner": 0.0657353401184082,
"expert": 0.7660266160964966
}
|
3,382
|
hi
|
647e11603eb0a1e50f8ebf584233e85a
|
{
"intermediate": 0.3246487081050873,
"beginner": 0.27135494351387024,
"expert": 0.40399640798568726
}
|
3,383
|
import requests
import json
import datetime
import streamlit as st
from itertools import zip_longest
import os
def basic_info():
config = dict()
config["access_token"] = st.secrets["access_token"]
config['instagram_account_id'] = st.secrets.get("instagram_account_id", "")
config["version"] = 'v16.0'
config["graph_domain"] = 'https://graph.facebook.com/'
config["endpoint_base"] = config["graph_domain"] + config["version"] + '/'
return config
def InstaApiCall(url, params, request_type):
if request_type == 'POST':
req = requests.post(url, params)
else:
req = requests.get(url, params)
res = dict()
res["url"] = url
res["endpoint_params"] = params
res["endpoint_params_pretty"] = json.dumps(params, indent=4)
res["json_data"] = json.loads(req.content)
res["json_data_pretty"] = json.dumps(res["json_data"], indent=4)
return res
def getUserMedia(params, pagingUrl=''):
Params = dict()
Params['fields'] = 'id,caption,media_type,media_url,permalink,thumbnail_url,timestamp,username,like_count,comments_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
if pagingUrl == '':
url = params['endpoint_base'] + params['instagram_account_id'] + '/media'
else:
url = pagingUrl
return InstaApiCall(url, Params, 'GET')
def getUser(params):
Params = dict()
Params['fields'] = 'followers_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
url = params['endpoint_base'] + params['instagram_account_id']
return InstaApiCall(url, Params, 'GET')
def saveCount(count, filename):
with open(filename, 'w') as f:
json.dump(count, f, indent=4)
def getCount(filename):
try:
with open(filename, 'r') as f:
return json.load(f)
except (FileNotFoundError, json.decoder.JSONDecodeError):
return {}
st.set_page_config(layout="wide")
params = basic_info()
count_filename = "count.json"
if not params['instagram_account_id']:
st.write('.envファイルでinstagram_account_idを確認')
else:
response = getUserMedia(params)
user_response = getUser(params)
if not response or not user_response:
st.write('.envファイルでaccess_tokenを確認')
else:
posts = response['json_data']['data'][::-1]
user_data = user_response['json_data']
followers_count = user_data.get('followers_count', 0)
NUM_COLUMNS = 6
MAX_WIDTH = 1000
BOX_WIDTH = int(MAX_WIDTH / NUM_COLUMNS)
BOX_HEIGHT = 400
yesterday = (datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))) - datetime.timedelta(days=1)).strftime('%Y-%m-%d')
follower_diff = followers_count - getCount(count_filename).get(yesterday, {}).get('followers_count', followers_count)
st.markdown(f"<h4 style='font-size:1.2em;'>Follower: {followers_count} ({'+' if follower_diff >= 0 else ''}{follower_diff})</h4>", unsafe_allow_html=True)
show_description = st.checkbox("キャプションを表示")
posts.reverse()
post_groups = [list(filter(None, group)) for group in zip_longest(*[iter(posts)] * NUM_COLUMNS)]
count = getCount(count_filename)
today = datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d')
if today not in count:
count[today] = {}
count[today]['followers_count'] = followers_count
if datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%H:%M') == '23:59':
count[yesterday] = count[today]
max_like_diff = 0
max_comment_diff = 0
for post_group in post_groups:
for post in post_group:
like_count_diff = post['like_count'] - count.get(yesterday, {}).get(post['id'], {}).get('like_count', post['like_count'])
comment_count_diff = post['comments_count'] - count.get(yesterday, {}).get(post['id'], {}).get('comments_count', post['comments_count'])
max_like_diff = max(like_count_diff, max_like_diff)
max_comment_diff = max(comment_count_diff, max_comment_diff)
for post_group in post_groups:
with st.container():
columns = st.columns(NUM_COLUMNS)
for i, post in enumerate(post_group):
with columns[i]:
st.image(post['media_url'], width=BOX_WIDTH, use_column_width=True)
st.write(f"{datetime.datetime.strptime(post['timestamp'], '%Y-%m-%dT%H:%M:%S%z').astimezone(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d %H:%M:%S')}")
like_count_diff = post['like_count'] - count.get(yesterday, {}).get(post['id'], {}).get('like_count', post['like_count'])
comment_count_diff = post['comments_count'] - count.get(yesterday, {}).get(post['id'], {}).get('comments_count', post['comments_count'])
st.markdown(
f"👍: {post['like_count']} <span style='{'' if like_count_diff != max_like_diff or max_like_diff == 0 else 'color:green;'}'>({'+' if like_count_diff >= 0 else ''}{like_count_diff})</span>"
f"\n💬: {post['comments_count']} <span style='{'' if comment_count_diff != max_comment_diff or max_comment_diff == 0 else 'color:green;'}'>({'+' if comment_count_diff >= 0 else ''}{comment_count_diff})</span>",
unsafe_allow_html=True)
caption = post['caption']
if caption is not None:
caption = caption.strip()
if "[Description]" in caption:
caption = caption.split("[Description]")[1].lstrip()
if "[Tags]" in caption:
caption = caption.split("[Tags]")[0].rstrip()
caption = caption.replace("#", "")
caption = caption.replace("[model]", "👗")
caption = caption.replace("[Equip]", "📷")
caption = caption.replace("[Develop]", "🖨")
if show_description:
st.write(caption or "No caption provided")
else:
st.write(caption[:0] if caption is not None and len(caption) > 50 else caption or "No caption provided")
count[today][post['id']] = {'like_count': post['like_count'], 'comments_count': post['comments_count']}
saveCount(count, count_filename)
'''
上記のコードを以下の要件をすべて満たして改修してください
- Python用のインデントを行頭に付与して出力する
- コード冒頭の修正内容についての説明文は表示しない
- 指示のないコードの改変はしない
- "caption = post['caption']"以降のブロックについては改変しない
- jsonファイルに保存されている各日の日時データ増減で"followers_count"と"'like_count'の全投稿の総数"を1軸目の縦軸とし、"'comments_count'の全投稿の総数"を2軸目の縦軸とし、グラフ背景は"黒"でグラフデータをそれぞれ"水色"・"オレンジ"・"緑"で色分けした折れ線グラフで表現し、"日付"を横軸にした"サマリーグラフ"を、ページの下部に横幅いっぱいに表示する機能を作成する
- jsonファイルに保存されている各日の"各投稿IDごとの'like_count'"と"各投稿IDごとの'comments_count'"の日時データ増減を縦軸とし、グラフ背景は"黒"で各グラフデータを"オレンジ"・"緑"で色分けした折れ線グラフで表現し、"1日"を横軸にした"いいね/コメント数グラフ"を、各投稿のボックス内の"キャプション"の下に表示する機能を作成する
- "キャプションを表示"の右隣に"サマリーグラフ"と"いいね/コメント数グラフ"をUI上に表示するためのトグルを各1つずつチェックボックスで作成し、デフォルトではチェックなしでグラフは非表示の状態にする
|
b3c9205ee6d9170fede7d7c8f3500175
|
{
"intermediate": 0.36978060007095337,
"beginner": 0.47684019804000854,
"expert": 0.15337920188903809
}
|
3,384
|
write a code to interact with https://github.com/xtekky/gpt4free with python. include a "search" input in the terminal and save the output with the "search" that was given
|
7a858807f7d0f1aafebe1aae8063150b
|
{
"intermediate": 0.3963218331336975,
"beginner": 0.25040203332901,
"expert": 0.3532761037349701
}
|
3,385
|
write a code to interact with https://github.com/xtekky/gpt4free with python. include a "search" input in the terminal and save the output with the "search" that was given
|
e3cdd00048bf52477fdd8b0a93c7a33d
|
{
"intermediate": 0.3963218331336975,
"beginner": 0.25040203332901,
"expert": 0.3532761037349701
}
|
3,386
|
write a code to interact with https://github.com/xtekky/gpt4free with python. include a "search" input in the terminal and save the output with the "search" that was given
|
e6e25bc9868c2e59abf1bbcd58b30320
|
{
"intermediate": 0.3963218331336975,
"beginner": 0.25040203332901,
"expert": 0.3532761037349701
}
|
3,387
|
write a code to interact with https://github.com/xtekky/gpt4free with python. include a "search" input in the terminal and save the output with the "search" that was given
|
68a5836db0aaaf0526d290228d34dd49
|
{
"intermediate": 0.3963218331336975,
"beginner": 0.25040203332901,
"expert": 0.3532761037349701
}
|
3,388
|
def svgPreprocess(inputs):
if (inputs):
if (inputs['image'].startswith("data:image/svg+xml;base64,") and svgsupport):
svg_data = base64.b64decode(inputs['image'].replace('data:image/svg+xml;base64,',''))
drawing = svg2rlg(io.BytesIO(svg_data))
png_data = renderPM.drawToString(drawing, fmt='PNG')
encoded_string = base64.b64encode(png_data)
base64_str = str(encoded_string, "utf-8")
base64_str = "data:image/png;base64,"+ base64_str
inputs['image'] = base64_str
return input_image.orgpreprocess(inputs)
return None
|
2ec635599a2ba248e707fef3c0f7d056
|
{
"intermediate": 0.4262247085571289,
"beginner": 0.385626882314682,
"expert": 0.1881484091281891
}
|
3,389
|
# Example 10: Populating an empty NumPy array
np_arr = np.empty([4,4], dtype=np.int) # An empty 4x4 numpy array
for i in range(4):
for j in range(4):
np_arr[i,j] = i+j
print(np_arr)
|
4b9ff8b364acf2ed4b38af159cc9bceb
|
{
"intermediate": 0.37389934062957764,
"beginner": 0.4277019798755646,
"expert": 0.19839873909950256
}
|
3,390
|
import requests
import json
import datetime
import streamlit as st
from itertools import zip_longest
import os
def basic_info():
config = dict()
config["access_token"] = st.secrets["access_token"]
config['instagram_account_id'] = st.secrets.get("instagram_account_id", "")
config["version"] = 'v16.0'
config["graph_domain"] = 'https://graph.facebook.com/'
config["endpoint_base"] = config["graph_domain"] + config["version"] + '/'
return config
def InstaApiCall(url, params, request_type):
if request_type == 'POST':
req = requests.post(url, params)
else:
req = requests.get(url, params)
res = dict()
res["url"] = url
res["endpoint_params"] = params
res["endpoint_params_pretty"] = json.dumps(params, indent=4)
res["json_data"] = json.loads(req.content)
res["json_data_pretty"] = json.dumps(res["json_data"], indent=4)
return res
def getUserMedia(params, pagingUrl=''):
Params = dict()
Params['fields'] = 'id,caption,media_type,media_url,permalink,thumbnail_url,timestamp,username,like_count,comments_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
if pagingUrl == '':
url = params['endpoint_base'] + params['instagram_account_id'] + '/media'
else:
url = pagingUrl
return InstaApiCall(url, Params, 'GET')
def getUser(params):
Params = dict()
Params['fields'] = 'followers_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
url = params['endpoint_base'] + params['instagram_account_id']
return InstaApiCall(url, Params, 'GET')
def saveCount(count, filename):
with open(filename, 'w') as f:
json.dump(count, f, indent=4)
def getCount(filename):
try:
with open(filename, 'r') as f:
return json.load(f)
except (FileNotFoundError, json.decoder.JSONDecodeError):
return {}
st.set_page_config(layout="wide")
params = basic_info()
count_filename = "count.json"
if not params['instagram_account_id']:
st.write('.envファイルでinstagram_account_idを確認')
else:
response = getUserMedia(params)
user_response = getUser(params)
if not response or not user_response:
st.write('.envファイルでaccess_tokenを確認')
else:
posts = response['json_data']['data'][::-1]
user_data = user_response['json_data']
followers_count = user_data.get('followers_count', 0)
NUM_COLUMNS = 6
MAX_WIDTH = 1000
BOX_WIDTH = int(MAX_WIDTH / NUM_COLUMNS)
BOX_HEIGHT = 400
yesterday = (datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))) - datetime.timedelta(days=1)).strftime('%Y-%m-%d')
follower_diff = followers_count - getCount(count_filename).get(yesterday, {}).get('followers_count', followers_count)
st.markdown(f"<h4 style='font-size:1.2em;'>Follower: {followers_count} ({'+' if follower_diff >= 0 else ''}{follower_diff})</h4>", unsafe_allow_html=True)
show_description = st.checkbox("キャプションを表示")
posts.reverse()
post_groups = [list(filter(None, group)) for group in zip_longest(*[iter(posts)] * NUM_COLUMNS)]
count = getCount(count_filename)
today = datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d')
if today not in count:
count[today] = {}
count[today]['followers_count'] = followers_count
if datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%H:%M') == '23:59':
count[yesterday] = count[today]
max_like_diff = 0
max_comment_diff = 0
for post_group in post_groups:
for post in post_group:
like_count_diff = post['like_count'] - count.get(yesterday, {}).get(post['id'], {}).get('like_count', post['like_count'])
comment_count_diff = post['comments_count'] - count.get(yesterday, {}).get(post['id'], {}).get('comments_count', post['comments_count'])
max_like_diff = max(like_count_diff, max_like_diff)
max_comment_diff = max(comment_count_diff, max_comment_diff)
for post_group in post_groups:
with st.container():
columns = st.columns(NUM_COLUMNS)
for i, post in enumerate(post_group):
with columns[i]:
st.image(post['media_url'], width=BOX_WIDTH, use_column_width=True)
st.write(f"{datetime.datetime.strptime(post['timestamp'], '%Y-%m-%dT%H:%M:%S%z').astimezone(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d %H:%M:%S')}")
like_count_diff = post['like_count'] - count.get(yesterday, {}).get(post['id'], {}).get('like_count', post['like_count'])
comment_count_diff = post['comments_count'] - count.get(yesterday, {}).get(post['id'], {}).get('comments_count', post['comments_count'])
st.markdown(
f"👍: {post['like_count']} <span style='{'' if like_count_diff != max_like_diff or max_like_diff == 0 else 'color:green;'}'>({'+' if like_count_diff >= 0 else ''}{like_count_diff})</span>"
f"\n💬: {post['comments_count']} <span style='{'' if comment_count_diff != max_comment_diff or max_comment_diff == 0 else 'color:green;'}'>({'+' if comment_count_diff >= 0 else ''}{comment_count_diff})</span>",
unsafe_allow_html=True)
caption = post['caption']
if caption is not None:
caption = caption.strip()
if "[Description]" in caption:
caption = caption.split("[Description]")[1].lstrip()
if "[Tags]" in caption:
caption = caption.split("[Tags]")[0].rstrip()
caption = caption.replace("#", "")
caption = caption.replace("[model]", "👗")
caption = caption.replace("[Equip]", "📷")
caption = caption.replace("[Develop]", "🖨")
if show_description:
st.write(caption or "No caption provided")
else:
st.write(caption[:0] if caption is not None and len(caption) > 50 else caption or "No caption provided")
count[today][post['id']] = {'like_count': post['like_count'], 'comments_count': post['comments_count']}
saveCount(count, count_filename)
'''
上記のコードを以下の要件をすべて満たして改修してください
- Python用のインデントを行頭に付与して出力する
- コード冒頭の修正内容についての説明文は表示しない
- 指示のないコードの改変はしない
- "caption = post['caption']"以降のブロックについては改変しない
- グラフ作成のためのPythonライブラリは"plotly"のみを使用する
- jsonファイルに保存されている各日の日時データ増減で"followers_count"と"'like_count'の全投稿の総数"を1軸目の縦軸とし、"'comments_count'の全投稿の総数"を2軸目の縦軸とし、グラフ背景は"黒"でグラフデータをそれぞれ"水色"・"オレンジ"・"緑"で色分けした折れ線グラフで表現し、"日付"を横軸にした"サマリーグラフ"を、ページの下部に横幅いっぱいに表示する機能を作成する
- jsonファイルに保存されている各日の"各投稿ごとの'like_count'"と"各投稿ごとの'comments_count'"の日時データ増減を縦軸とし、グラフ背景は"黒"で各グラフデータを"オレンジ"・"緑"で色分けした折れ線グラフで表現し、"1日"を横軸にした"いいね/コメント数グラフ"を、各投稿のボックス内の"キャプション"の下に表示する機能を作成する
- "キャプションを表示"の右隣に"サマリーグラフ"と"いいね/コメント数グラフ"をUI上に表示するためのトグルを各1つずつチェックボックスで作成し、デフォルトではチェックなしでグラフは非表示の状態にする
|
f252a2cd9e66e84b0ad74b6894dc265f
|
{
"intermediate": 0.36978060007095337,
"beginner": 0.47684019804000854,
"expert": 0.15337920188903809
}
|
3,391
|
import requests
import json
import datetime
import streamlit as st
from itertools import zip_longest
import os
import plotly.graph_objects as go
def basic_info():
config = dict()
config["access_token"] = st.secrets["access_token"]
config['instagram_account_id'] = st.secrets.get("instagram_account_id", "")
config["version"] = 'v16.0'
config["graph_domain"] = 'https://graph.facebook.com/'
config["endpoint_base"] = config["graph_domain"] + config["version"] + '/'
return config
def InstaApiCall(url, params, request_type):
if request_type == 'POST':
req = requests.post(url, params)
else:
req = requests.get(url, params)
res = dict()
res["url"] = url
res["endpoint_params"] = params
res["endpoint_params_pretty"] = json.dumps(params, indent=4)
res["json_data"] = json.loads(req.content)
res["json_data_pretty"] = json.dumps(res["json_data"], indent=4)
return res
def getUserMedia(params, pagingUrl=''):
Params = dict()
Params['fields'] = 'id,caption,media_type,media_url,permalink,thumbnail_url,timestamp,username,like_count,comments_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
if pagingUrl == '':
url = params['endpoint_base'] + params['instagram_account_id'] + '/media'
else:
url = pagingUrl
return InstaApiCall(url, Params, 'GET')
def getUser(params):
Params = dict()
Params['fields'] = 'followers_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
url = params['endpoint_base'] + params['instagram_account_id']
return InstaApiCall(url, Params, 'GET')
def saveCount(count, filename):
with open(filename, 'w') as f:
json.dump(count, f, indent=4)
def getCount(filename):
try:
with open(filename, 'r') as f:
return json.load(f)
except (FileNotFoundError, json.decoder.JSONDecodeError):
return {}
st.set_page_config(layout="wide")
params = basic_info()
count_filename = "count.json"
if not params['instagram_account_id']:
st.write('.envファイルでinstagram_account_idを確認')
else:
response = getUserMedia(params)
user_response = getUser(params)
if not response or not user_response:
st.write('.envファイルでaccess_tokenを確認')
else:
posts = response['json_data']['data'][::-1]
user_data = user_response['json_data']
followers_count = user_data.get('followers_count', 0)
NUM_COLUMNS = 6
MAX_WIDTH = 1000
BOX_WIDTH = int(MAX_WIDTH / NUM_COLUMNS)
BOX_HEIGHT = 400
yesterday = (datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))) - datetime.timedelta(days=1)).strftime('%Y-%m-%d')
follower_diff = followers_count - getCount(count_filename).get(yesterday, {}).get('followers_count', followers_count)
st.markdown(f"<h4 style='font-size:1.2em;'>Follower: {followers_count} ({'+' if follower_diff >= 0 else ''}{follower_diff})</h4>", unsafe_allow_html=True)
show_description = st.checkbox("キャプションを表示")
show_summary_graph = st.checkbox("サマリーグラフを表示")
show_indiv_triple_graph = st.checkbox("いいね/コメント数グラフを表示")
posts.reverse()
post_groups = [list(filter(None, group)) for group in zip_longest(*[iter(posts)] * NUM_COLUMNS)]
count = getCount(count_filename)
today = datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d')
if today not in count:
count[today] = {}
count[today]['followers_count'] = followers_count
if datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%H:%M') == '23:59':
count[yesterday] = count[today]
max_like_diff = 0
max_comment_diff = 0
for post_group in post_groups:
for post in post_group:
like_count_diff = post['like_count'] - count.get(yesterday, {}).get(post['id'], {}).get('like_count', post['like_count'])
comment_count_diff = post['comments_count'] - count.get(yesterday, {}).get(post['id'], {}).get('comments_count', post['comments_count'])
max_like_diff = max(like_count_diff, max_like_diff)
max_comment_diff = max(comment_count_diff, max_comment_diff)
summary_dates = []
summary_followers = []
summary_total_likes = []
summary_total_comments = []
for post_group in post_groups:
with st.container():
columns = st.columns(NUM_COLUMNS)
for i, post in enumerate(post_group):
with columns[i]:
st.image(post['media_url'], width=BOX_WIDTH, use_column_width=True)
st.write(f"{datetime.datetime.strptime(post['timestamp'], '%Y-%m-%dT%H:%M:%S%z').astimezone(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d %H:%M:%S')}")
like_count_diff = post['like_count'] - count.get(yesterday, {}).get(post['id'], {}).get('like_count', post['like_count'])
comment_count_diff = post['comments_count'] - count.get(yesterday, {}).get(post['id'], {}).get('comments_count', post['comments_count'])
st.markdown(
f"👍: {post['like_count']} <span style='{'' if like_count_diff != max_like_diff or max_like_diff == 0 else 'color:green;'}'>({'+' if like_count_diff >= 0 else ''}{like_count_diff})</span>"
f"\n💬: {post['comments_count']} <span style='{'' if comment_count_diff != max_comment_diff or max_comment_diff == 0 else 'color:green;'}'>({'+' if comment_count_diff >= 0 else ''}{comment_count_diff})</span>",
unsafe_allow_html=True)
caption = post['caption']
if caption is not None:
caption = caption.strip()
if "[Description]" in caption:
caption = caption.split("[Description]")[1].lstrip()
if "[Tags]" in caption:
caption = caption.split("[Tags]")[0].rstrip()
caption = caption.replace("#", "")
caption = caption.replace("[model]", "👗")
caption = caption.replace("[Equip]", "📷")
caption = caption.replace("[Develop]", "🖨")
if show_description:
st.write(caption or "No caption provided")
else:
st.write(caption[:0] if caption is not None and len(caption) > 50 else caption or "No caption provided")
count[today][post['id']] = {'like_count': post['like_count'], 'comments_count': post['comments_count']}
if show_indiv_triple_graph:
date_range = [datetime.datetime.strptime(date_str, '%Y-%m-%d')
for date_str in sorted(count.keys()) if post['id'] in count[date_str]][-9:]
like_counts = [count[date.strftime('%Y-%m-%d')][post['id']]['like_count']
for date in date_range]
comment_counts = [count[date.strftime('%Y-%m-%d')][post['id']]['comments_count']
for date in date_range]
fig = go.Figure()
fig.add_trace(go.Scatter(x=date_range, y=like_counts,
mode='lines+markers',
name="いいね数",
line=dict(color='orange')))
fig.add_trace(go.Scatter(x=date_range, y=comment_counts,
mode='lines+markers',
name="コメント数",
line=dict(color='green')))
fig.layout.plot_bgcolor = 'black'
fig.update_yaxes(showgrid=False)
fig.update_xaxes(showgrid=False)
st.plotly_chart(fig)
if show_summary_graph:
for date_str in sorted(count.keys()):
daily_counts = count[date_str]
summary_dates.append(date_str)
summary_followers.append(daily_counts.get("followers_count", 0))
summary_total_likes.append(sum([daily_counts[p]["like_count"] for p in daily_counts if isinstance(daily_counts[p], dict) and "like_count" in daily_counts[p]]))
summary_total_comments.append(sum([daily_counts[p]["comments_count"] for p in daily_counts if isinstance(daily_counts[p], dict) and "comments_count" in daily_counts[p]]))
fig_summary = go.Figure()
fig_summary.add_trace(go.Scatter(x=summary_dates, y=summary_followers,
mode='lines+markers',
name="フォロワー数",
line=dict(color='turquoise')))
fig_summary.add_trace(go.Scatter(x=summary_dates, y=summary_total_likes,
mode='lines+markers',
name="いいね数（全投稿）",
yaxis="y", line=dict(color='orange')))
fig_summary.add_trace(go.Scatter(x=summary_dates, y=summary_total_comments,
mode='lines+markers',
name="コメント数（全投稿）",
yaxis="y2", line=dict(color='green')))
fig_summary.layout.plot_bgcolor = 'black'
fig_summary.update_yaxes(showgrid=False)
fig_summary.update_xaxes(showgrid=False)
fig_summary.update_layout(yaxis2=dict(overlaying='y', side='right'))
st.plotly_chart(fig_summary)
saveCount(count, count_filename)
'''
上記のコードから、"plotly"ライブラリではなく"seaborn"ライブラリを使用するようにコードを改修してください
|
d1f28c8982db80d0d4548c3e75e1861f
|
{
"intermediate": 0.4512891471385956,
"beginner": 0.3515626788139343,
"expert": 0.1971481591463089
}
|
3,392
|
请找出下面代码中的错误并更正：
#include <windows.h>
#include <winternl.h>
#include <stdio.h>
typedef NTSTATUS(WINAPI* LPNTOPENPROCESS)(
OUT PHANDLE ProcessHandle,
IN ACCESS_MASK DesiredAccess,
IN POBJECT_ATTRIBUTES ObjectAttributes,
IN PCLIENT_ID ClientId
);
int main()
{
LPNTOPENPROCESS NtOpenProcess = (LPNTOPENPROCESS)GetProcAddress(
GetModuleHandle(L"ntdll.dll"), "NtOpenProcess");
if (NtOpenProcess == NULL)
{
printf("Failed to get address of NtOpenProcess\n");
return -1;
}
HANDLE hProcess;
CLIENT_ID clientId = { 0 };
OBJECT_ATTRIBUTES objectAttributes = { 0 };
clientId.UniqueProcess = (HANDLE)1234; //指定进程的ID
objectAttributes.Length = sizeof(OBJECT_ATTRIBUTES);
NTSTATUS status = NtOpenProcess(&hProcess,
PROCESS_ALL_ACCESS, &objectAttributes, &clientId);
if (NT_SUCCESS(status))
{
printf("Opened process successfully!\n");
//do something
CloseHandle(hProcess);
}
else
{
printf("Failed to open process.Error:0x%X\n", status);
}
return 0;
}
|
5858744a3b314b13972ef7cdfafb6dbb
|
{
"intermediate": 0.37587109208106995,
"beginner": 0.3842909038066864,
"expert": 0.23983797430992126
}
|
3,393
|
import requests
import json
import datetime
import streamlit as st
from itertools import zip_longest
import os
def basic_info():
config = dict()
config["access_token"] = st.secrets["access_token"]
config['instagram_account_id'] = st.secrets.get("instagram_account_id", "")
config["version"] = 'v16.0'
config["graph_domain"] = 'https://graph.facebook.com/'
config["endpoint_base"] = config["graph_domain"] + config["version"] + '/'
return config
def InstaApiCall(url, params, request_type):
if request_type == 'POST':
req = requests.post(url, params)
else:
req = requests.get(url, params)
res = dict()
res["url"] = url
res["endpoint_params"] = params
res["endpoint_params_pretty"] = json.dumps(params, indent=4)
res["json_data"] = json.loads(req.content)
res["json_data_pretty"] = json.dumps(res["json_data"], indent=4)
return res
def getUserMedia(params, pagingUrl=''):
Params = dict()
Params['fields'] = 'id,caption,media_type,media_url,permalink,thumbnail_url,timestamp,username,like_count,comments_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
if pagingUrl == '':
url = params['endpoint_base'] + params['instagram_account_id'] + '/media'
else:
url = pagingUrl
return InstaApiCall(url, Params, 'GET')
def getUser(params):
Params = dict()
Params['fields'] = 'followers_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
url = params['endpoint_base'] + params['instagram_account_id']
return InstaApiCall(url, Params, 'GET')
def saveCount(count, filename):
with open(filename, 'w') as f:
json.dump(count, f, indent=4)
def getCount(filename):
try:
with open(filename, 'r') as f:
return json.load(f)
except (FileNotFoundError, json.decoder.JSONDecodeError):
return {}
st.set_page_config(layout="wide")
params = basic_info()
count_filename = "count.json"
if not params['instagram_account_id']:
st.write('.envファイルでinstagram_account_idを確認')
else:
response = getUserMedia(params)
user_response = getUser(params)
if not response or not user_response:
st.write('.envファイルでaccess_tokenを確認')
else:
posts = response['json_data']['data'][::-1]
user_data = user_response['json_data']
followers_count = user_data.get('followers_count', 0)
NUM_COLUMNS = 6
MAX_WIDTH = 1000
BOX_WIDTH = int(MAX_WIDTH / NUM_COLUMNS)
BOX_HEIGHT = 400
yesterday = (datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))) - datetime.timedelta(days=1)).strftime('%Y-%m-%d')
follower_diff = followers_count - getCount(count_filename).get(yesterday, {}).get('followers_count', followers_count)
st.markdown(f"<h4 style='font-size:1.2em;'>Follower: {followers_count} ({'+' if follower_diff >= 0 else ''}{follower_diff})</h4>", unsafe_allow_html=True)
show_description = st.checkbox("キャプションを表示")
posts.reverse()
post_groups = [list(filter(None, group)) for group in zip_longest(*[iter(posts)] * NUM_COLUMNS)]
count = getCount(count_filename)
today = datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d')
if today not in count:
count[today] = {}
count[today]['followers_count'] = followers_count
if datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%H:%M') == '23:59':
count[yesterday] = count[today]
max_like_diff = 0
max_comment_diff = 0
for post_group in post_groups:
for post in post_group:
like_count_diff = post['like_count'] - count.get(yesterday, {}).get(post['id'], {}).get('like_count', post['like_count'])
comment_count_diff = post['comments_count'] - count.get(yesterday, {}).get(post['id'], {}).get('comments_count', post['comments_count'])
max_like_diff = max(like_count_diff, max_like_diff)
max_comment_diff = max(comment_count_diff, max_comment_diff)
for post_group in post_groups:
with st.container():
columns = st.columns(NUM_COLUMNS)
for i, post in enumerate(post_group):
with columns[i]:
st.image(post['media_url'], width=BOX_WIDTH, use_column_width=True)
st.write(f"{datetime.datetime.strptime(post['timestamp'], '%Y-%m-%dT%H:%M:%S%z').astimezone(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d %H:%M:%S')}")
like_count_diff = post['like_count'] - count.get(yesterday, {}).get(post['id'], {}).get('like_count', post['like_count'])
comment_count_diff = post['comments_count'] - count.get(yesterday, {}).get(post['id'], {}).get('comments_count', post['comments_count'])
st.markdown(
f"👍: {post['like_count']} <span style='{'' if like_count_diff != max_like_diff or max_like_diff == 0 else 'color:green;'}'>({'+' if like_count_diff >= 0 else ''}{like_count_diff})</span>"
f"\n💬: {post['comments_count']} <span style='{'' if comment_count_diff != max_comment_diff or max_comment_diff == 0 else 'color:green;'}'>({'+' if comment_count_diff >= 0 else ''}{comment_count_diff})</span>",
unsafe_allow_html=True)
caption = post['caption']
if caption is not None:
caption = caption.strip()
if "[Description]" in caption:
caption = caption.split("[Description]")[1].lstrip()
if "[Tags]" in caption:
caption = caption.split("[Tags]")[0].rstrip()
caption = caption.replace("#", "")
caption = caption.replace("[model]", "👗")
caption = caption.replace("[Equip]", "📷")
caption = caption.replace("[Develop]", "🖨")
if show_description:
st.write(caption or "No caption provided")
else:
st.write(caption[:0] if caption is not None and len(caption) > 50 else caption or "No caption provided")
count[today][post['id']] = {'like_count': post['like_count'], 'comments_count': post['comments_count']}
saveCount(count, count_filename)
'''
上記のコードを以下の要件をすべて満たして改修してください
- Python用のインデントを行頭に付与して出力する
- コード冒頭の修正内容についての説明文は表示しない
- 指示のないコードの改変はしない
- "caption = post['caption']"以降のブロックについては改変しない
- グラフ作成のためのPythonライブラリは"seaborn"のみを使用する
- jsonファイルに保存されている各日の日時データ増減で"followers_count"の実数と"'like_count'の全投稿における当日に増加した総数"を1軸目の縦軸とし、"'comments_count'のの全投稿における当日に増加した総数"を2軸目の縦軸とし、グラフ背景は"黒"でグラフデータをそれぞれ"水色"・"オレンジ"・"緑"で色分けした折れ線グラフで表現し、"日付"を横軸にした"サマリーグラフ"を、ページの下部に横幅いっぱいに表示する機能を作成する
- jsonファイルに保存されている各日の"各投稿ごとの'like_count'"と"各投稿ごとの'comments_count'"の日時データの当日に増加した総数を縦軸とし、グラフ背景は"黒"で各グラフデータを"オレンジ"・"緑"で色分けした折れ線グラフで表現し、"1日"を横軸にした"いいね/コメント数グラフ"を、各投稿のボックス内の"キャプション"の下に表示する機能を作成する
- "キャプションを表示"の右隣に"サマリーグラフ"と"いいね/コメント数グラフ"をUI上に表示するためのトグルを各1つずつチェックボックスで作成し、デフォルトではチェックなしでグラフは非表示の状態にする
|
e579617237ec139615b3c1be0dc4b43c
|
{
"intermediate": 0.36978060007095337,
"beginner": 0.47684019804000854,
"expert": 0.15337920188903809
}
|
3,394
|
Following is Aarchv8 assembly language program. Identify error in print_array function and fix it.
Here is the code:
.section .rodata
getnstr: .string "Enter a value of n: "
.align 3
intstr: .string "%d"
.align 3
prntstr: .string "The array values are: \n"
.align 3
tab10dintstr: .string "\t%10d\n"
.align 3
nlstr: .string "\n"
.align 3
.section .bss
n: .skip 4
n16: .skip 4
.section .text
.global main
.type main, @function
main:
stp x29, x30, [sp, #-16]! // main prolog
// seed the random
mov x0, 0
bl time
bl srand
//print and get the array size
// printf (getnstr)
ldr x0, =getnstr
bl printf
// scanf(intstr, &n)
ldr x0, =intstr
ldr x1, =n // memory location of n
bl scanf
// compute next highest multiple of 16 >= n.
// SP has to be multiples of 16
ldr x1, =n
ldr w1, [x1]
sbfiz x1, x1, #2, #20
add x1, x1, #0xf // 0xf = 15
and x1, x1, #0xfffffffffffffff0 //15f's
ldr x2, =n16
str w1, [x2]
// create the storage for "n" integer, using stack
sub sp, sp, x1 // create storage for the array
// call init_array
mov x0, sp
ldr x1, =n
ldr w1, [x1]
bl init_array
// call print_array
mov x4, sp
ldr x1, =n
ldr w1, [x1]
bl print_array
// Return the local array back to the stack
ldr x1, =n16
ldr x1, [x1]
add sp, sp, x1
ldp x29, x30, [sp, #16] // main epilog
ret
// void init_array(int arr[], int n);
.type init_array, @function // this is a private function
init_array:
stp x29, x30, [sp, #-16]! // function prolog
mov x2, #0 // initialize loop counter
mov x3, #0xa0a0 // 0xa0a0 is element stored in arr. could be changed to rand number.
loop1:
cmp x2, x1 //compare i & n
bge endloop1
str w3, [x0, x2, lsl 2] // store at [base adr of arr + i*4]
add x2, x2, #1
b loop1
endloop1:
ldp x29, x30, [sp], #16 //function epilog
ret
// void print_array(int arr[], int n);
.type print_array, @function
print_array:
stp x29, x30, [sp, #-16]! //function prolog
mov x2, #0 // initialize loop counter
loop2:
cmp x2, x1 // compare i & n
bge endloop2
ldr w3, [x4, x2, lsl 2] // load at [base adr of arr + i*4]
ldr x0, =tab10dintstr
bl printf
add x2, x2, #1
b loop2
endloop2:
ldp x29, x30, [sp], #16 //function epilog
ret
|
e66d4da3774ba91ee4a54fc3e3dc150e
|
{
"intermediate": 0.24051688611507416,
"beginner": 0.5122824311256409,
"expert": 0.24720075726509094
}
|
3,395
|
'''
import requests
import json
import datetime
import streamlit as st
from itertools import zip_longest
import os
import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
def basic_info():
config = dict()
config["access_token"] = st.secrets["access_token"]
config['instagram_account_id'] = st.secrets.get("instagram_account_id", "")
config["version"] = 'v16.0'
config["graph_domain"] = 'https://graph.facebook.com/'
config["endpoint_base"] = config["graph_domain"] + config["version"] + '/'
return config
def InstaApiCall(url, params, request_type):
if request_type == 'POST':
req = requests.post(url, params)
else:
req = requests.get(url, params)
res = dict()
res["url"] = url
res["endpoint_params"] = params
res["endpoint_params_pretty"] = json.dumps(params, indent=4)
res["json_data"] = json.loads(req.content)
res["json_data_pretty"] = json.dumps(res["json_data"], indent=4)
return res
def getUserMedia(params, pagingUrl=''):
Params = dict()
Params['fields'] = 'id,caption,media_type,media_url,permalink,thumbnail_url,timestamp,username,like_count,comments_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
if pagingUrl == '':
url = params['endpoint_base'] + params['instagram_account_id'] + '/media'
else:
url = pagingUrl
return InstaApiCall(url, Params, 'GET')
def getUser(params):
Params = dict()
Params['fields'] = 'followers_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
url = params['endpoint_base'] + params['instagram_account_id']
return InstaApiCall(url, Params, 'GET')
def saveCount(count, filename):
with open(filename, 'w') as f:
json.dump(count, f, indent=4)
def getCount(filename):
try:
with open(filename, 'r') as f:
return json.load(f)
except (FileNotFoundError, json.decoder.JSONDecodeError):
return {}
def create_summary_graph(count):
date_list = []
follower_diff_list = []
like_count_diff_list = []
comment_count_diff_list = []
for date, data in count.items():
date_list.append(pd.to_datetime(date))
follower_diff = data.get('followers_count', 0) - count.get(str(pd.to_datetime(date) - pd.Timedelta(days=1)).split(" ")[0], {}).get('followers_count', data.get('followers_count', 0))
like_count_diff = sum(post_data.get('like_count', 0) - count.get(str(pd.to_datetime(date) - pd.Timedelta(days=1)).split(" ")[0], {}).get(post_id, {}).get('like_count', post_data.get('like_count', 0)) for post_id, post_data in data.items() if post_id != 'followers_count')
comment_count_diff = sum(post_data.get('comments_count', 0) - count.get(str(pd.to_datetime(date) - pd.Timedelta(days=1)).split(" ")[0], {}).get(post_id, {}).get('comments_count', post_data.get('comments_count', 0)) for post_id, post_data in data.items() if post_id != 'followers_count')
follower_diff_list.append(follower_diff)
like_count_diff_list.append(like_count_diff)
comment_count_diff_list.append(comment_count_diff)
data = pd.DataFrame({'Date': date_list, 'Follower Diff': follower_diff_list, 'Like Count Diff': like_count_diff_list, 'Comment Count Diff': comment_count_diff_list})
sns.set_theme(style="darkgrid")
fig, ax1 = plt.subplots(figsize=(15, 4))
ax1.set_ylabel('Follower Diff & Like Count Diff')
ax1.plot(data['Date'], data['Follower Diff'], label='Follower Diff', color='skyblue')
ax1.plot(data['Date'], data['Like Count Diff'], label='Like Count Diff', color='orange')
ax1.legend(loc='upper left')
ax1.grid(False)
ax2 = ax1.twinx()
ax2.set_ylabel('Comment Count Diff')
ax2.plot(data['Date'], data['Comment Count Diff'], label='Comment Count Diff', color='green')
ax2.legend(loc='upper right')
ax2.grid(False)
plt.title('Summary Graph')
st.pyplot(fig)
st.set_page_config(layout="wide")
params = basic_info()
count_filename = "count.json"
if not params['instagram_account_id']:
st.write('.envファイルでinstagram_account_idを確認')
else:
response = getUserMedia(params)
user_response = getUser(params)
if not response or not user_response:
st.write('.envファイルでaccess_tokenを確認')
else:
posts = response['json_data']['data'][::-1]
user_data = user_response['json_data']
followers_count = user_data.get('followers_count', 0)
NUM_COLUMNS = 6
MAX_WIDTH = 1000
BOX_WIDTH = int(MAX_WIDTH / NUM_COLUMNS)
BOX_HEIGHT = 400
yesterday = (datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))) - datetime.timedelta(days=1)).strftime('%Y-%m-%d')
follower_diff = followers_count - getCount(count_filename).get(yesterday, {}).get('followers_count', followers_count)
st.markdown(f"<h4 style='font-size:1.2em;'>Follower: {followers_count} ({'+' if follower_diff >= 0 else ''}{follower_diff})</h4>", unsafe_allow_html=True)
show_description = st.checkbox("キャプションを表示")
show_summary_graph = st.checkbox("サマリーグラフを表示")
show_post_graph = st.checkbox("いいね/コメント数グラフを表示")
count = getCount(count_filename)
today = datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d')
if today not in count:
count[today] = {}
count[today]['followers_count'] = followers_count
if datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%H:%M') == '23:59':
count[yesterday] = count[today]
if show_summary_graph:
create_summary_graph(count)
posts.reverse()
post_groups = [list(filter(None, group)) for group in zip_longest(*[iter(posts)] * NUM_COLUMNS)]
for post_group in post_groups:
with st.container():
columns = st.columns(NUM_COLUMNS)
for i, post in enumerate(post_group):
with columns[i]:
st.image(post['media_url'], width=BOX_WIDTH, use_column_width=True)
st.write(f"{datetime.datetime.strptime(post['timestamp'], '%Y-%m-%dT%H:%M:%S%z').astimezone(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d %H:%M:%S')}")
like_count_diff = post['like_count'] - count.get(yesterday, {}).get(post['id'], {}).get('like_count', post['like_count'])
comment_count_diff = post['comments_count'] - count.get(yesterday, {}).get(post['id'], {}).get('comments_count', post['comments_count'])
st.markdown(
f"👍: {post['like_count']} <span style='{'' if like_count_diff != max_like_diff or max_like_diff == 0 else 'color:green;'}'>({'+' if like_count_diff >= 0 else ''}{like_count_diff})</span>"
f"\n💬: {post['comments_count']} <span style='{'' if comment_count_diff != max_comment_diff or max_comment_diff == 0 else 'color:green;'}'>({'+' if comment_count_diff >= 0 else ''}{comment_count_diff})</span>",
unsafe_allow_html=True)
caption = post['caption']
if caption is not None:
caption = caption.strip()
if "[Description]" in caption:
caption = caption.split("[Description]")[1].lstrip()
if "[Tags]" in caption:
caption = caption.split("[Tags]")[0].rstrip()
caption = caption.replace("#", "")
caption = caption.replace("[model]", "👗")
caption = caption.replace("[Equip]", "📷")
caption = caption.replace("[Develop]", "🖨")
if show_description:
st.write(caption or "No caption provided")
else:
st.write(caption[:0] if caption is not None and len(caption) > 50 else caption or "No caption provided")
count[today][post['id']] = {'like_count': post['like_count'], 'comments_count': post['comments_count']}
if show_post_graph:
date_list = [pd.to_datetime(date) for date in count.keys()]
fig, ax1 = plt.subplots(figsize=(8, 2))
ax1.set_ylabel('Like Count Diff')
ax1.plot(date_list, [data.get(post['id'], {}).get('like_count', 0) - count.get(str(pd.to_datetime(date) - pd.Timedelta(days=1)).split(" ")[0], {}).get(post['id'], {}).get('like_count', data.get(post['id'], {}).get('like_count', 0)) for date, data in count.items()], label='Like Count Diff', color='orange')
ax1.legend(loc='upper left')
ax1.grid(False)
ax2 = ax1.twinx()
ax2.set_ylabel('Comment Count Diff')
ax2.plot(date_list, [data.get(post['id'], {}).get('comments_count', 0) - count.get(str(pd.to_datetime(date) - pd.Timedelta(days=1)).split(" ")[0], {}).get(post['id'], {}).get('comments_count', data.get(post['id'], {}).get('comments_count', 0)) for date, data in count.items()], label='Comment Count Diff', color='green')
ax2.legend(loc='upper right')
ax2.grid(False)
plt.title('Like/Comment Count Graph')
st.pyplot(fig)
saveCount(count, count_filename)
'''
上記コードを実行すると下記のエラーが発生します。下記のすべての要件に従って修正してください。
- Python用のインデントを行頭に付与して出力する
- コード冒頭の修正内容についての説明文は表示しない
- 指示のないコードの改変はしない
- "caption = post['caption']"以降のブロックについては改変しない
- 修正済みのコード全体を省略せずに表示する
'''
2023-04-30 11:26:16.497 Uncaught app exception
Traceback (most recent call last):
File "/home/walhalax/anaconda3/lib/python3.9/site-packages/streamlit/runtime/scriptrunner/script_runner.py", line 565, in _run_script
exec(code, module.__dict__)
File "/home/walhalax/PycharmProjects/pythonProject/その他/Instargram/inst_tileview/inst_tileview.py", line 163, in <module>
f"👍: {post['like_count']} <span style='{'' if like_count_diff != max_like_diff or max_like_diff == 0 else 'color:green;'}'>({'+' if like_count_diff >= 0 else ''}{like_count_diff})</span>"
NameError: name 'max_like_diff' is not defined
|
94aa613335f166d82baf7f060831507f
|
{
"intermediate": 0.3170303702354431,
"beginner": 0.46229425072669983,
"expert": 0.22067539393901825
}
|
3,396
|
Following is Aarchv8 assembly language program. Identify error in print_array function and fix it.
Here is the code:
.section .rodata
getnstr: .string "Enter a value of n: "
.align 3
intstr: .string "%d"
.align 3
prntstr: .string "The array values are: \n"
.align 3
tab10dintstr: .string "\t%10d\n"
.align 3
nlstr: .string "\n"
.align 3
.section .bss
n: .skip 4
n16: .skip 4
.section .text
.global main
.type main, @function
main:
stp x29, x30, [sp, #-16]! // main prolog
// seed the random
mov x0, 0
bl time
bl srand
//print and get the array size
// printf (getnstr)
ldr x0, =getnstr
bl printf
// scanf(intstr, &n)
ldr x0, =intstr
ldr x1, =n // memory location of n
bl scanf
// compute next highest multiple of 16 >= n.
// SP has to be multiples of 16
ldr x1, =n
ldr w1, [x1]
sbfiz x1, x1, #2, #20
add x1, x1, #0xf // 0xf = 15
and x1, x1, #0xfffffffffffffff0 //15f's
ldr x2, =n16
str w1, [x2]
// create the storage for "n" integer, using stack
sub sp, sp, x1 // create storage for the array
// call init_array
mov x0, sp
ldr x1, =n
ldr w1, [x1]
bl init_array
// call print_array
mov x4, sp
ldr x2, =n
ldr w2, [x2]
bl print_array
// Return the local array back to the stack
ldr x1, =n16
ldr x1, [x1]
add sp, sp, x1
ldp x29, x30, [sp, #16] // main epilog
ret
// void init_array(int arr[], int n);
.type init_array, @function // this is a private function
init_array:
stp x29, x30, [sp, #-16]! // function prolog
mov x2, #0 // initialize loop counter
mov x3, #0xa0a0 // 0xa0a0 is element stored in arr. could be changed to rand number.
loop1:
cmp x2, x1 //compare i & n
bge endloop1
str w3, [x0, x2, lsl 2] // store at [base adr of arr + i*4]
add x2, x2, #1
b loop1
endloop1:
ldp x29, x30, [sp], #16 //function epilog
ret
// void print_array(int arr[], int n);
.type print_array, @function
print_array:
stp x29, x30, [sp, #-16]! //function prolog
mov x3, #0 // initialize loop counter
loop2:
cmp x3, x2 // compare i & n
bge endloop2
ldr w1, [x4, x3, lsl 2] // load at [base adr of arr + i*4]
ldr x0, =intstr
bl printf
add x3, x3, #1
b loop2
endloop2:
ldp x29, x30, [sp], #16 //function epilog
ret
|
6f193076f09e2980920bcd3335499ce8
|
{
"intermediate": 0.3355477452278137,
"beginner": 0.3612884283065796,
"expert": 0.3031637966632843
}
|
3,397
|
create simple TAM model based on these constructs:
1. Behavioral Intention to Use
2. Perceived Usefulness
3. Perceived Ease of Use
4. Job Relevance
5. Subjective Norm
6. Professional Reputation
7. Output Quality
8. Result Demonstrability
9. Computer Self-Efficacy
10. Computer Playfulness
11. Computer Anxiety
Make it simpler by combining other constructs
|
bb217b278aeb54a208b9ac34d9d8c0a4
|
{
"intermediate": 0.2712429165840149,
"beginner": 0.12419799715280533,
"expert": 0.604559063911438
}
|
3,398
|
mac arm64 visual studio c++ debug configurations c_cpp_properties launch.json settings.json tasks.json
|
34c154f6cc238b388f928df3a9ddd975
|
{
"intermediate": 0.5827699303627014,
"beginner": 0.17351962625980377,
"expert": 0.243710458278656
}
|
3,399
|
import requests
import json
import datetime
import streamlit as st
from itertools import zip_longest
import os
import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
def basic_info():
config = dict()
config[“access_token”] = st.secrets[“access_token”]
config[‘instagram_account_id’] = st.secrets.get(“instagram_account_id”, “”)
config[“version”] = ‘v16.0’
config[“graph_domain”] = ‘https://graph.facebook.com/’
config[“endpoint_base”] = config[“graph_domain”] + config[“version”] + ‘/’
return config
def InstaApiCall(url, params, request_type):
if request_type == ‘POST’:
req = requests.post(url, params)
else:
req = requests.get(url, params)
res = dict()
res[“url”] = url
res[“endpoint_params”] = params
res[“endpoint_params_pretty”] = json.dumps(params, indent=4)
res[“json_data”] = json.loads(req.content)
res[“json_data_pretty”] = json.dumps(res[“json_data”], indent=4)
return res
def getUserMedia(params, pagingUrl=‘’):
Params = dict()
Params[‘fields’] = ‘id,caption,media_type,media_url,permalink,thumbnail_url,timestamp,username,like_count,comments_count’
Params[‘access_token’] = params[‘access_token’]
if not params[‘endpoint_base’]:
return None
if pagingUrl == ‘’:
url = params[‘endpoint_base’] + params[‘instagram_account_id’] + ‘/media’
else:
url = pagingUrl
return InstaApiCall(url, Params, ‘GET’)
def getUser(params):
Params = dict()
Params[‘fields’] = ‘followers_count’
Params[‘access_token’] = params[‘access_token’]
if not params[‘endpoint_base’]:
return None
url = params[‘endpoint_base’] + params[‘instagram_account_id’]
return InstaApiCall(url, Params, ‘GET’)
def saveCount(count, filename):
with open(filename, ‘w’) as f:
json.dump(count, f, indent=4)
def getCount(filename):
try:
with open(filename, ‘r’) as f:
return json.load(f)
except (FileNotFoundError, json.decoder.JSONDecodeError):
return {}
def create_summary_graph(count):
date_list = []
follower_diff_list = []
like_count_diff_list = []
comment_count_diff_list = []
for date, data in count.items():
date_list.append(pd.to_datetime(date))
follower_diff = data.get(‘followers_count’, 0) - count.get(str(pd.to_datetime(date) - pd.Timedelta(days=1)).split(" “)[0], {}).get(‘followers_count’, data.get(‘followers_count’, 0))
like_count_diff = sum(post_data.get(‘like_count’, 0) - count.get(str(pd.to_datetime(date) - pd.Timedelta(days=1)).split(” “)[0], {}).get(post_id, {}).get(‘like_count’, post_data.get(‘like_count’, 0)) for post_id, post_data in data.items() if post_id != ‘followers_count’)
comment_count_diff = sum(post_data.get(‘comments_count’, 0) - count.get(str(pd.to_datetime(date) - pd.Timedelta(days=1)).split(” “)[0], {}).get(post_id, {}).get(‘comments_count’, post_data.get(‘comments_count’, 0)) for post_id, post_data in data.items() if post_id != ‘followers_count’)
follower_diff_list.append(follower_diff)
like_count_diff_list.append(like_count_diff)
comment_count_diff_list.append(comment_count_diff)
data = pd.DataFrame({‘Date’: date_list, ‘Follower Diff’: follower_diff_list, ‘Like Count Diff’: like_count_diff_list, ‘Comment Count Diff’: comment_count_diff_list})
sns.set_theme(style=“darkgrid”)
fig, ax1 = plt.subplots(figsize=(15, 4))
ax1.set_ylabel(‘Follower Diff & Like Count Diff’)
ax1.plot(data[‘Date’], data[‘Follower Diff’], label=‘Follower Diff’, color=‘skyblue’)
ax1.plot(data[‘Date’], data[‘Like Count Diff’], label=‘Like Count Diff’, color=‘orange’)
ax1.legend(loc=‘upper left’)
ax1.grid(False)
ax2 = ax1.twinx()
ax2.set_ylabel(‘Comment Count Diff’)
ax2.plot(data[‘Date’], data[‘Comment Count Diff’], label=‘Comment Count Diff’, color=‘green’)
ax2.legend(loc=‘upper right’)
ax2.grid(False)
plt.title(‘Summary Graph’)
st.pyplot(fig)
st.set_page_config(layout=“wide”)
params = basic_info()
count_filename = “count.json”
if not params[‘instagram_account_id’]:
st.write(‘.envファイルでinstagram_account_idを確認’)
else:
response = getUserMedia(params)
user_response = getUser(params)
if not response or not user_response:
st.write(‘.envファイルでaccess_tokenを確認’)
else:
posts = response[‘json_data’][‘data’][::-1]
user_data = user_response[‘json_data’]
followers_count = user_data.get(‘followers_count’, 0)
NUM_COLUMNS = 6
MAX_WIDTH = 1000
BOX_WIDTH = int(MAX_WIDTH / NUM_COLUMNS)
BOX_HEIGHT = 400
yesterday = (datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))) - datetime.timedelta(days=1)).strftime(‘%Y-%m-%d’)
follower_diff = followers_count - getCount(count_filename).get(yesterday, {}).get(‘followers_count’, followers_count)
st.markdown(f”<h4 style=‘font-size:1.2em;’>Follower: {followers_count} ({‘+’ if follower_diff >= 0 else ‘’}{follower_diff})</h4>“, unsafe_allow_html=True)
show_description = st.checkbox(“キャプションを表示”)
show_summary_graph = st.checkbox(“サマリーグラフを表示”)
show_post_graph = st.checkbox(“いいね/コメント数グラフを表示”)
count = getCount(count_filename)
today = datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime(‘%Y-%m-%d’)
if today not in count:
count[today] = {}
count[today][‘followers_count’] = followers_count
if datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime(‘%H:%M’) == ‘23:59’:
count[yesterday] = count[today]
if show_summary_graph:
create_summary_graph(count)
posts.reverse()
post_groups = [list(filter(None, group)) for group in zip_longest(*[iter(posts)] * NUM_COLUMNS)]
for post_group in post_groups:
with st.container():
columns = st.columns(NUM_COLUMNS)
for i, post in enumerate(post_group):
with columns[i]:
st.image(post[‘media_url’], width=BOX_WIDTH, use_column_width=True)
st.write(f”{datetime.datetime.strptime(post[‘timestamp’], ‘%Y-%m-%dT%H:%M:%S%z’).astimezone(datetime.timezone(datetime.timedelta(hours=9))).strftime(‘%Y-%m-%d %H:%M:%S’)}“)
like_count_diff = post[‘like_count’] - count.get(yesterday, {}).get(post[‘id’], {}).get(‘like_count’, post[‘like_count’])
comment_count_diff = post[‘comments_count’] - count.get(yesterday, {}).get(post[‘id’], {}).get(‘comments_count’, post[‘comments_count’])
max_like_diff = max([count[date][key].get(‘like_count’, 0) - count[yesterday].get(key, {}).get(‘like_count’, count[date][key].get(‘like_count’, 0)) for date, data in count.items() for key in data.keys() if key != ‘followers_count’])
max_comment_diff = max([count[date][key].get(‘comments_count’, 0) - count[yesterday].get(key, {}).get(‘comments_count’, count[date][key].get(‘comments_count’, 0)) for date, data in count.items() for key in data.keys() if key != ‘followers_count’])
st.markdown(
f"👍: {post[‘like_count’]} <span style=‘{’’ if like_count_diff != max_like_diff or max_like_diff == 0 else ‘color:green;’}‘>({’+’ if like_count_diff >= 0 else ‘’}{like_count_diff})</span>”
f"\n💬: {post[‘comments_count’]} <span style=‘{’’ if comment_count_diff != max_comment_diff or max_comment_diff == 0 else ‘color:green;’}‘>({’+’ if comment_count_diff >= 0 else ‘’}{comment_count_diff})</span>“,
unsafe_allow_html=True)
caption = post[‘caption’]
if caption is not None:
caption = caption.strip()
if “[Description]” in caption:
caption = caption.split(”[Description]“)[1].lstrip()
if “[Tags]” in caption:
caption = caption.split(”[Tags]“)[0].rstrip()
caption = caption.replace(”#“, “”)
caption = caption.replace(”[model]“, “👗”)
caption = caption.replace(”[Equip]“, “📷”)
caption = caption.replace(”[Develop]“, “🖨”)
if show_description:
st.write(caption or “No caption provided”)
else:
st.write(caption[:0] if caption is not None and len(caption) > 50 else caption or “No caption provided”)
count[today][post[‘id’]] = {‘like_count’: post[‘like_count’], ‘comments_count’: post[‘comments_count’]}
if show_post_graph:
date_list = [pd.to_datetime(date) for date in count.keys()]
fig, ax1 = plt.subplots(figsize=(8, 2))
ax1.set_ylabel(‘Like Count Diff’)
ax1.plot(date_list, [data.get(post[‘id’], {}).get(‘like_count’, 0) - count.get(str(pd.to_datetime(date) - pd.Timedelta(days=1)).split(” “)[0], {}).get(post[‘id’], {}).get(‘like_count’, data.get(post[‘id’], {}).get(‘like_count’, 0)) for date, data in count.items()], label=‘Like Count Diff’, color=‘orange’)
ax1.legend(loc=‘upper left’)
ax1.grid(False)
ax2 = ax1.twinx()
ax2.set_ylabel(‘Comment Count Diff’)
ax2.plot(date_list, [data.get(post[‘id’], {}).get(‘comments_count’, 0) - count.get(str(pd.to_datetime(date) - pd.Timedelta(days=1)).split(” ")[0], {}).get(post[‘id’], {}).get(‘comments_count’, data.get(post[‘id’], {}).get(‘comments_count’, 0)) for date, data in count.items()], label=‘Comment Count Diff’, color=‘green’)
ax2.legend(loc=‘upper right’)
ax2.grid(False)
plt.title(‘Like/Comment Count Graph’)
st.pyplot(fig)
saveCount(count, count_filename)
'''
上記コードにPython用のインデントを付与して再表示してください
|
de54d6e2ea82abe6306d66bc9c7947d4
|
{
"intermediate": 0.3732353746891022,
"beginner": 0.32313814759254456,
"expert": 0.3036264479160309
}
|
3,400
|
import requests
import json
import datetime
import streamlit as st
from itertools import zip_longest
import os
def basic_info():
config = dict()
config["access_token"] = st.secrets["access_token"]
config['instagram_account_id'] = st.secrets.get("instagram_account_id", "")
config["version"] = 'v16.0'
config["graph_domain"] = 'https://graph.facebook.com/'
config["endpoint_base"] = config["graph_domain"] + config["version"] + '/'
return config
def InstaApiCall(url, params, request_type):
if request_type == 'POST':
req = requests.post(url, params)
else:
req = requests.get(url, params)
res = dict()
res["url"] = url
res["endpoint_params"] = params
res["endpoint_params_pretty"] = json.dumps(params, indent=4)
res["json_data"] = json.loads(req.content)
res["json_data_pretty"] = json.dumps(res["json_data"], indent=4)
return res
def getUserMedia(params, pagingUrl=''):
Params = dict()
Params['fields'] = 'id,caption,media_type,media_url,permalink,thumbnail_url,timestamp,username,like_count,comments_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
if pagingUrl == '':
url = params['endpoint_base'] + params['instagram_account_id'] + '/media'
else:
url = pagingUrl
return InstaApiCall(url, Params, 'GET')
def getUser(params):
Params = dict()
Params['fields'] = 'followers_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
url = params['endpoint_base'] + params['instagram_account_id']
return InstaApiCall(url, Params, 'GET')
def saveCount(count, filename):
with open(filename, 'w') as f:
json.dump(count, f, indent=4)
def getCount(filename):
try:
with open(filename, 'r') as f:
return json.load(f)
except (FileNotFoundError, json.decoder.JSONDecodeError):
return {}
st.set_page_config(layout="wide")
params = basic_info()
count_filename = "count.json"
if not params['instagram_account_id']:
st.write('.envファイルでinstagram_account_idを確認')
else:
response = getUserMedia(params)
user_response = getUser(params)
if not response or not user_response:
st.write('.envファイルでaccess_tokenを確認')
else:
posts = response['json_data']['data'][::-1]
user_data = user_response['json_data']
followers_count = user_data.get('followers_count', 0)
NUM_COLUMNS = 6
MAX_WIDTH = 1000
BOX_WIDTH = int(MAX_WIDTH / NUM_COLUMNS)
BOX_HEIGHT = 400
yesterday = (datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))) - datetime.timedelta(days=1)).strftime('%Y-%m-%d')
follower_diff = followers_count - getCount(count_filename).get(yesterday, {}).get('followers_count', followers_count)
st.markdown(f"<h4 style='font-size:1.2em;'>Follower: {followers_count} ({'+' if follower_diff >= 0 else ''}{follower_diff})</h4>", unsafe_allow_html=True)
show_description = st.checkbox("キャプションを表示")
posts.reverse()
post_groups = [list(filter(None, group)) for group in zip_longest(*[iter(posts)] * NUM_COLUMNS)]
count = getCount(count_filename)
today = datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d')
if today not in count:
count[today] = {}
count[today]['followers_count'] = followers_count
if datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%H:%M') == '23:59':
count[yesterday] = count[today]
max_like_diff = 0
max_comment_diff = 0
for post_group in post_groups:
for post in post_group:
like_count_diff = post['like_count'] - count.get(yesterday, {}).get(post['id'], {}).get('like_count', post['like_count'])
comment_count_diff = post['comments_count'] - count.get(yesterday, {}).get(post['id'], {}).get('comments_count', post['comments_count'])
max_like_diff = max(like_count_diff, max_like_diff)
max_comment_diff = max(comment_count_diff, max_comment_diff)
for post_group in post_groups:
with st.container():
columns = st.columns(NUM_COLUMNS)
for i, post in enumerate(post_group):
with columns[i]:
st.image(post['media_url'], width=BOX_WIDTH, use_column_width=True)
st.write(f"{datetime.datetime.strptime(post['timestamp'], '%Y-%m-%dT%H:%M:%S%z').astimezone(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d %H:%M:%S')}")
like_count_diff = post['like_count'] - count.get(yesterday, {}).get(post['id'], {}).get('like_count', post['like_count'])
comment_count_diff = post['comments_count'] - count.get(yesterday, {}).get(post['id'], {}).get('comments_count', post['comments_count'])
st.markdown(
f"👍: {post['like_count']} <span style='{'' if like_count_diff != max_like_diff or max_like_diff == 0 else 'color:green;'}'>({'+' if like_count_diff >= 0 else ''}{like_count_diff})</span>"
f"\n💬: {post['comments_count']} <span style='{'' if comment_count_diff != max_comment_diff or max_comment_diff == 0 else 'color:green;'}'>({'+' if comment_count_diff >= 0 else ''}{comment_count_diff})</span>",
unsafe_allow_html=True)
caption = post['caption']
if caption is not None:
caption = caption.strip()
if "[Description]" in caption:
caption = caption.split("[Description]")[1].lstrip()
if "[Tags]" in caption:
caption = caption.split("[Tags]")[0].rstrip()
caption = caption.replace("#", "")
caption = caption.replace("[model]", "👗")
caption = caption.replace("[Equip]", "📷")
caption = caption.replace("[Develop]", "🖨")
if show_description:
st.write(caption or "No caption provided")
else:
st.write(caption[:0] if caption is not None and len(caption) > 50 else caption or "No caption provided")
count[today][post['id']] = {'like_count': post['like_count'], 'comments_count': post['comments_count']}
saveCount(count, count_filename)
'''
上記のコードを以下の要件をすべて満たして改修してください
- Python用のインデントを行頭に付与して出力する
- コード冒頭の修正内容についての説明文は表示しない
- 指示のないコードの改変はしない
- "caption = post['caption']"以降のブロックについては改変しない
- グラフ作成のためのPythonライブラリは"seaborn"のみを使用する
- jsonファイルに保存されている各日の日時データ増減で"followers_count"の実数と"'like_count'の全投稿における当日に増加した総数"を1軸目の縦軸とし、"'comments_count'のの全投稿における当日に増加した総数"を2軸目の縦軸とし、グラフ背景は"黒"でグラフデータをそれぞれ"水色"・"オレンジ"・"緑"で色分けした折れ線グラフで表現し、"日付"を横軸にした"サマリーグラフ"を、ページの下部に横幅いっぱいに表示する機能を作成する
- jsonファイルに保存されている各日の"各投稿ごとの'like_count'"と"各投稿ごとの'comments_count'"の日時データの当日に増加した総数を縦軸とし、グラフ背景は"黒"で各グラフデータを"オレンジ"・"緑"で色分けした折れ線グラフで表現し、"1日"を横軸にした"いいね/コメント数グラフ"を、各投稿のボックス内の"キャプション"の下に表示する機能を作成する
- "キャプションを表示"の右隣に"サマリーグラフ"と"いいね/コメント数グラフ"をUI上に表示するためのトグルを各1つずつチェックボックスで作成し、デフォルトではチェックなしでグラフは非表示の状態にする
|
38ab221dda80f54b3fd8c2e08aed3f82
|
{
"intermediate": 0.36978060007095337,
"beginner": 0.47684019804000854,
"expert": 0.15337920188903809
}
|
3,401
|
Perform as if you were a big data analytics engineer and write a hadoop java program to run on cloudera hadoop environment.
This program performs sentiment analysis on a given text input and returns two output files one with the negative words and the other with the positive ones you can also use a dataset or ignore it if it's not necessary.
I also want you to show me how to run it on cloudera environment and the terminal commands I will use.
also what are the external jars i need to add
|
a87ecf8ef8ef22ebd4f8a100388a57d8
|
{
"intermediate": 0.4047631025314331,
"beginner": 0.14784149825572968,
"expert": 0.447395384311676
}
|
3,402
|
'''
import requests
import json
import datetime
import streamlit as st
from itertools import zip_longest
import os
import seaborn as sns
import pandas as pd
import matplotlib.pyplot as plt
sns.set_theme(style="darkgrid")
def basic_info():
config = dict()
config["access_token"] = st.secrets["access_token"]
config['instagram_account_id'] = st.secrets.get("instagram_account_id", "")
config["version"] = 'v16.0'
config["graph_domain"] = 'https://graph.facebook.com/'
config["endpoint_base"] = config["graph_domain"] + config["version"] + '/'
return config
def InstaApiCall(url, params, request_type):
if request_type == 'POST':
req = requests.post(url, params)
else:
req = requests.get(url, params)
res = dict()
res["url"] = url
res["endpoint_params"] = params
res["endpoint_params_pretty"] = json.dumps(params, indent=4)
res["json_data"] = json.loads(req.content)
res["json_data_pretty"] = json.dumps(res["json_data"], indent=4)
return res
def getUserMedia(params, pagingUrl=''):
Params = dict()
Params['fields'] = 'id,caption,media_type,media_url,permalink,thumbnail_url,timestamp,username,like_count,comments_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
if pagingUrl == '':
url = params['endpoint_base'] + params['instagram_account_id'] + '/media'
else:
url = pagingUrl
return InstaApiCall(url, Params, 'GET')
def getUser(params):
Params = dict()
Params['fields'] = 'followers_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
url = params['endpoint_base'] + params['instagram_account_id']
return InstaApiCall(url, Params, 'GET')
def saveCount(count, filename):
with open(filename, 'w') as f:
json.dump(count, f, indent=4)
def getCount(filename):
try:
with open(filename, 'r') as f:
return json.load(f)
except (FileNotFoundError, json.decoder.JSONDecodeError):
return {}
st.set_page_config(layout="wide")
params = basic_info()
count_filename = "count.json"
if not params['instagram_account_id']:
st.write('.envファイルでinstagram_account_idを確認')
else:
response = getUserMedia(params)
user_response = getUser(params)
if not response or not user_response:
st.write('.envファイルでaccess_tokenを確認')
else:
posts = response['json_data']['data'][::-1]
user_data = user_response['json_data']
followers_count = user_data.get('followers_count', 0)
NUM_COLUMNS = 6
MAX_WIDTH = 1000
BOX_WIDTH = int(MAX_WIDTH / NUM_COLUMNS)
BOX_HEIGHT = 400
yesterday = (datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))) - datetime.timedelta(days=1)).strftime('%Y-%m-%d')
follower_diff = followers_count - getCount(count_filename).get(yesterday, {}).get('followers_count', followers_count)
st.markdown(f"<h4 style='font-size:1.2em;'>Follower: {followers_count} ({'+' if follower_diff >= 0 else ''}{follower_diff})</h4>", unsafe_allow_html=True)
show_description = st.checkbox("キャプションを表示")
show_summary_charts = st.checkbox("サマリーグラフを表示")
show_charts = st.checkbox("いいね/コメント数グラフを表示")
posts.reverse()
post_groups = [list(filter(None, group)) for group in zip_longest(*[iter(posts)] * NUM_COLUMNS)]
count = getCount(count_filename)
today = datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d')
if today not in count:
count[today] = {}
count[today]['followers_count'] = followers_count
if datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%H:%M') == '23:59':
count[yesterday] = count[today]
max_like_diff = 0
max_comment_diff = 0
chart_data = []
chart_data_likes = {}
chart_data_comments = {}
for key, value in count.items():
total_likes_count_diff = sum(value[c]['like_count'] - count.get(yesterday, {}).get(c, {}).get('like_count', post['like_count']) for c in value if c != 'followers_count')
total_comments_count_diff = sum(value[c]['comments_count'] - count.get(yesterday, {}).get(c, {}).get('comments_count', post['comments_count']) for c in value if c != 'followers_count')
if 'followers_count' in value:
chart_data_likes[key] = total_likes_count_diff
chart_data_comments[key] = total_comments_count_diff
chart_data.append([key, value['followers_count'], total_likes_count_diff, total_comments_count_diff])
if show_summary_charts:
df_chart_data = pd.DataFrame(chart_data, columns=["Date", "followers_count", "total_likes_count", "total_comments_count"])
df_chart_data["Date"] = pd.to_datetime(df_chart_data["Date"], format="%Y-%m-%d")
fig, ax1 = plt.subplots(figsize=(15, 6))
sns.lineplot(data=df_chart_data, x="Date", y="followers_count", color="lightskyblue", ax=ax1)
ax1.set(ylabel="followers_count")
ax2 = ax1.twinx()
sns.lineplot(data=df_chart_data, x="Date", y="total_likes_count", color="orange", ax=ax2)
sns.lineplot(data=df_chart_data, x="Date", y="total_comments_count", color="green", ax=ax2)
ax2.set(ylabel="total_likes_count & total_comments_count")
plt.title("Summary Chart")
sns.despine()
st.pyplot(fig)
for post_group in post_groups:
with st.container():
columns = st.columns(NUM_COLUMNS)
for i, post in enumerate(post_group):
like_count_diff = post['like_count'] - count.get(yesterday, {}).get(post['id'], {}).get('like_count', post['like_count'])
comment_count_diff = post['comments_count'] - count.get(yesterday, {}).get(post['id'], {}).get('comments_count', post['comments_count'])
max_like_diff = max(like_count_diff, max_like_diff)
max_comment_diff = max(comment_count_diff, max_comment_diff)
with columns[i]:
st.image(post['media_url'], width=BOX_WIDTH, use_column_width=True)
st.write(f"{datetime.datetime.strptime(post['timestamp'], '%Y-%m-%dT%H:%M:%S%z').astimezone(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d %H:%M:%S')}")
st.markdown(
f"👍: {post['like_count']} <span style='{'' if like_count_diff != max_like_diff or max_like_diff == 0 else 'color:green;'}'>({'+' if like_count_diff >= 0 else ''}{like_count_diff})</span>"
f"\n💬: {post['comments_count']} <span style='{'' if comment_count_diff != max_comment_diff or max_comment_diff == 0 else 'color:green;'}'>({'+' if comment_count_diff >= 0 else ''}{comment_count_diff})</span>",
unsafe_allow_html=True)
caption = post['caption']
if caption is not None:
caption = caption.strip()
if "[Description]" in caption:
caption = caption.split("[Description]")[1].lstrip()
if "[Tags]" in caption:
caption = caption.split("[Tags]")[0].rstrip()
caption = caption.replace("#", "")
caption = caption.replace("[model]", "👗")
caption = caption.replace("[Equip]", "📷")
caption = caption.replace("[Develop]", "🖨")
if show_description:
st.write(caption or "No caption provided")
else:
st.write(caption[:0] if caption is not None and len(caption) > 50 else caption or "No caption provided")
if show_charts:
days = list(chart_data_likes.keys())
likes = [chart_data_likes[d] for d in days]
comments = [chart_data_comments[d] for d in days]
df_like_data = pd.DataFrame({"Date": days, "likes_count": likes})
df_comment_data = pd.DataFrame({"Date": days, "comments_count": comments})
fig, ax1 = plt.subplots(figsize=(5, 3))
sns.lineplot(data=df_like_data, x="Date", y="likes_count", color="orange", ax=ax1)
sns.lineplot(data=df_comment_data, x="Date", y="comments_count", color="green", ax=ax1)
plt.xticks(rotation=90)
plt.title("Like and Comment Counts")
sns.despine()
st.pyplot(fig)
count[today][post['id']] = {'like_count': post['like_count'], 'comments_count': post['comments_count']}
saveCount(count, count_filename)
'''
上記コードを実行すると下記のエラーが発生します。下記のすべての要件に従って修正してください。
- Python用のインデントを行頭に付与して出力する
- コード冒頭の修正内容についての説明文は表示しない
- 指示のないコードの改変はしない
- "caption = post['caption']"以降のブロックについては改変しない
- 修正済みのコード全体を省略せずに表示する
'''
2023-04-30 12:36:23.064 Uncaught app exception
Traceback (most recent call last):
File "/home/walhalax/anaconda3/lib/python3.9/site-packages/streamlit/runtime/scriptrunner/script_runner.py", line 565, in _run_script
exec(code, module.__dict__)
File "/home/walhalax/PycharmProjects/pythonProject/その他/Instargram/inst_tileview/inst_tileview.py", line 132, in <module>
total_likes_count_diff = sum(value[c]['like_count'] - count.get(yesterday, {}).get(c, {}).get('like_count', post['like_count']) for c in value if c != 'followers_count')
File "/home/walhalax/PycharmProjects/pythonProject/その他/Instargram/inst_tileview/inst_tileview.py", line 132, in <genexpr>
total_likes_count_diff = sum(value[c]['like_count'] - count.get(yesterday, {}).get(c, {}).get('like_count', post['like_count']) for c in value if c != 'followers_count')
NameError: name 'post' is not defined
2023-04-30 12:36:29.713 Uncaught app exception
Traceback (most recent call last):
File "/home/walhalax/anaconda3/lib/python3.9/site-packages/streamlit/runtime/scriptrunner/script_runner.py", line 565, in _run_script
exec(code, module.__dict__)
File "/home/walhalax/PycharmProjects/pythonProject/その他/Instargram/inst_tileview/inst_tileview.py", line 132, in <module>
total_likes_count_diff = sum(value[c]['like_count'] - count.get(yesterday, {}).get(c, {}).get('like_count', post['like_count']) for c in value if c != 'followers_count')
File "/home/walhalax/PycharmProjects/pythonProject/その他/Instargram/inst_tileview/inst_tileview.py", line 132, in <genexpr>
total_likes_count_diff = sum(value[c]['like_count'] - count.get(yesterday, {}).get(c, {}).get('like_count', post['like_count']) for c in value if c != 'followers_count')
NameError: name 'post' is not defined
2023-04-30 12:36:31.801 Uncaught app exception
Traceback (most recent call last):
File "/home/walhalax/anaconda3/lib/python3.9/site-packages/streamlit/runtime/scriptrunner/script_runner.py", line 565, in _run_script
exec(code, module.__dict__)
File "/home/walhalax/PycharmProjects/pythonProject/その他/Instargram/inst_tileview/inst_tileview.py", line 132, in <module>
total_likes_count_diff = sum(value[c]['like_count'] - count.get(yesterday, {}).get(c, {}).get('like_count', post['like_count']) for c in value if c != 'followers_count')
File "/home/walhalax/PycharmProjects/pythonProject/その他/Instargram/inst_tileview/inst_tileview.py", line 132, in <genexpr>
total_likes_count_diff = sum(value[c]['like_count'] - count.get(yesterday, {}).get(c, {}).get('like_count', post['like_count']) for c in value if c != 'followers_count')
NameError: name 'post' is not defined
2023-04-30 12:36:32.875 Uncaught app exception
Traceback (most recent call last):
File "/home/walhalax/anaconda3/lib/python3.9/site-packages/streamlit/runtime/scriptrunner/script_runner.py", line 565, in _run_script
exec(code, module.__dict__)
File "/home/walhalax/PycharmProjects/pythonProject/その他/Instargram/inst_tileview/inst_tileview.py", line 132, in <module>
total_likes_count_diff = sum(value[c]['like_count'] - count.get(yesterday, {}).get(c, {}).get('like_count', post['like_count']) for c in value if c != 'followers_count')
File "/home/walhalax/PycharmProjects/pythonProject/その他/Instargram/inst_tileview/inst_tileview.py", line 132, in <genexpr>
total_likes_count_diff = sum(value[c]['like_count'] - count.get(yesterday, {}).get(c, {}).get('like_count', post['like_count']) for c in value if c != 'followers_count')
NameError: name 'post' is not defined
2023-04-30 12:36:35.195 Uncaught app exception
Traceback (most recent call last):
File "/home/walhalax/anaconda3/lib/python3.9/site-packages/streamlit/runtime/scriptrunner/script_runner.py", line 565, in _run_script
exec(code, module.__dict__)
File "/home/walhalax/PycharmProjects/pythonProject/その他/Instargram/inst_tileview/inst_tileview.py", line 132, in <module>
total_likes_count_diff = sum(value[c]['like_count'] - count.get(yesterday, {}).get(c, {}).get('like_count', post['like_count']) for c in value if c != 'followers_count')
File "/home/walhalax/PycharmProjects/pythonProject/その他/Instargram/inst_tileview/inst_tileview.py", line 132, in <genexpr>
total_likes_count_diff = sum(value[c]['like_count'] - count.get(yesterday, {}).get(c, {}).get('like_count', post['like_count']) for c in value if c != 'followers_count')
NameError: name 'post' is not defined
2023-04-30 12:36:36.675 Uncaught app exception
Traceback (most recent call last):
File "/home/walhalax/anaconda3/lib/python3.9/site-packages/streamlit/runtime/scriptrunner/script_runner.py", line 565, in _run_script
exec(code, module.__dict__)
File "/home/walhalax/PycharmProjects/pythonProject/その他/Instargram/inst_tileview/inst_tileview.py", line 132, in <module>
total_likes_count_diff = sum(value[c]['like_count'] - count.get(yesterday, {}).get(c, {}).get('like_count', post['like_count']) for c in value if c != 'followers_count')
File "/home/walhalax/PycharmProjects/pythonProject/その他/Instargram/inst_tileview/inst_tileview.py", line 132, in <genexpr>
total_likes_count_diff = sum(value[c]['like_count'] - count.get(yesterday, {}).get(c, {}).get('like_count', post['like_count']) for c in value if c != 'followers_count')
NameError: name 'post' is not defined
2023-04-30 12:36:39.340 Uncaught app exception
Traceback (most recent call last):
File "/home/walhalax/anaconda3/lib/python3.9/site-packages/streamlit/runtime/scriptrunner/script_runner.py", line 565, in _run_script
exec(code, module.__dict__)
File "/home/walhalax/PycharmProjects/pythonProject/その他/Instargram/inst_tileview/inst_tileview.py", line 132, in <module>
total_likes_count_diff = sum(value[c]['like_count'] - count.get(yesterday, {}).get(c, {}).get('like_count', post['like_count']) for c in value if c != 'followers_count')
File "/home/walhalax/PycharmProjects/pythonProject/その他/Instargram/inst_tileview/inst_tileview.py", line 132, in <genexpr>
total_likes_count_diff = sum(value[c]['like_count'] - count.get(yesterday, {}).get(c, {}).get('like_count', post['like_count']) for c in value if c != 'followers_count')
NameError: name 'post' is not defined
|
20937781a657b414ee3861b9507aaf73
|
{
"intermediate": 0.3094857633113861,
"beginner": 0.43339425325393677,
"expert": 0.25711995363235474
}
|
3,403
|
import requests
import json
import datetime
import streamlit as st
from itertools import zip_longest
import os
import seaborn as sns
import pandas as pd
import matplotlib.pyplot as plt
sns.set_theme(style="darkgrid")
def basic_info():
config = dict()
config["access_token"] = st.secrets["access_token"]
config['instagram_account_id'] = st.secrets.get("instagram_account_id", "")
config["version"] = 'v16.0'
config["graph_domain"] = 'https://graph.facebook.com/'
config["endpoint_base"] = config["graph_domain"] + config["version"] + '/'
return config
def InstaApiCall(url, params, request_type):
if request_type == 'POST':
req = requests.post(url, params)
else:
req = requests.get(url, params)
res = dict()
res["url"] = url
res["endpoint_params"] = params
res["endpoint_params_pretty"] = json.dumps(params, indent=4)
res["json_data"] = json.loads(req.content)
res["json_data_pretty"] = json.dumps(res["json_data"], indent=4)
return res
def getUserMedia(params, pagingUrl=''):
Params = dict()
Params['fields'] = 'id,caption,media_type,media_url,permalink,thumbnail_url,timestamp,username,like_count,comments_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
if pagingUrl == '':
url = params['endpoint_base'] + params['instagram_account_id'] + '/media'
else:
url = pagingUrl
return InstaApiCall(url, Params, 'GET')
def getUser(params):
Params = dict()
Params['fields'] = 'followers_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
url = params['endpoint_base'] + params['instagram_account_id']
return InstaApiCall(url, Params, 'GET')
def saveCount(count, filename):
with open(filename, 'w') as f:
json.dump(count, f, indent=4)
def getCount(filename):
try:
with open(filename, 'r') as f:
return json.load(f)
except (FileNotFoundError, json.decoder.JSONDecodeError):
return {}
st.set_page_config(layout="wide")
params = basic_info()
count_filename = "count.json"
if not params['instagram_account_id']:
st.write('.envファイルでinstagram_account_idを確認')
else:
response = getUserMedia(params)
user_response = getUser(params)
if not response or not user_response:
st.write('.envファイルでaccess_tokenを確認')
else:
posts = response['json_data']['data'][::-1]
user_data = user_response['json_data']
followers_count = user_data.get('followers_count', 0)
NUM_COLUMNS = 6
MAX_WIDTH = 1000
BOX_WIDTH = int(MAX_WIDTH / NUM_COLUMNS)
BOX_HEIGHT = 400
yesterday = (datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))) - datetime.timedelta(days=1)).strftime('%Y-%m-%d')
follower_diff = followers_count - getCount(count_filename).get(yesterday, {}).get('followers_count', followers_count)
st.markdown(f"<h4 style='font-size:1.2em;'>Follower: {followers_count} ({'+' if follower_diff >= 0 else ''}{follower_diff})</h4>", unsafe_allow_html=True)
show_description = st.checkbox("キャプションを表示")
show_summary_charts = st.checkbox("サマリーグラフを表示")
show_charts = st.checkbox("いいね/コメント数グラフを表示")
posts.reverse()
post_groups = [list(filter(None, group)) for group in zip_longest(*[iter(posts)] * NUM_COLUMNS)]
count = getCount(count_filename)
today = datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d')
if today not in count:
count[today] = {}
count[today]['followers_count'] = followers_count
if datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%H:%M') == '23:59':
count[yesterday] = count[today]
max_like_diff = 0
max_comment_diff = 0
chart_data = []
chart_data_likes = {}
chart_data_comments = {}
for key, value in count.items():
for c in value:
if c != 'followers_count':
post = count[count.keys()[-1]][c]
like_count_diff = value[c]['like_count'] - count.get(yesterday, {}).get(c, {}).get('like_count', post['like_count'])
comment_count_diff = value[c]['comments_count'] - count.get(yesterday, {}).get(c, {}).get('comments_count', post['comments_count'])
total_likes_count_diff = sum(value[c]['like_count'] - count.get(yesterday, {}).get(c, {}).get('like_count', like_count_diff) for c in value if c != 'followers_count')
total_comments_count_diff = sum(value[c]['comments_count'] - count.get(yesterday, {}).get(c, {}).get('comments_count', comment_count_diff) for c in value if c != 'followers_count')
if 'followers_count' in value:
chart_data_likes[key] = total_likes_count_diff
chart_data_comments[key] = total_comments_count_diff
chart_data.append([key, value['followers_count'], total_likes_count_diff, total_comments_count_diff])
if show_summary_charts:
df_chart_data = pd.DataFrame(chart_data, columns=["Date", "followers_count", "total_likes_count", "total_comments_count"])
df_chart_data["Date"] = pd.to_datetime(df_chart_data["Date"], format="%Y-%m-%d")
fig, ax1 = plt.subplots(figsize=(15, 6))
sns.lineplot(data=df_chart_data, x="Date", y="followers_count", color="lightskyblue", ax=ax1)
ax1.set(ylabel="followers_count")
ax2 = ax1.twinx()
sns.lineplot(data=df_chart_data, x="Date", y="total_likes_count", color="orange", ax=ax2)
sns.lineplot(data=df_chart_data, x="Date", y="total_comments_count", color="green", ax=ax2)
ax2.set(ylabel="total_likes_count & total_comments_count")
plt.title("Summary Chart")
sns.despine()
st.pyplot(fig)
for post_group in post_groups:
with st.container():
columns = st.columns(NUM_COLUMNS)
for i, post in enumerate(post_group):
like_count_diff = post['like_count'] - count.get(yesterday, {}).get(post['id'], {}).get('like_count', post['like_count'])
comment_count_diff = post['comments_count'] - count.get(yesterday, {}).get(post['id'], {}).get('comments_count', post['comments_count'])
max_like_diff = max(like_count_diff, max_like_diff)
max_comment_diff = max(comment_count_diff, max_comment_diff)
with columns[i]:
st.image(post['media_url'], width=BOX_WIDTH, use_column_width=True)
st.write(f"{datetime.datetime.strptime(post['timestamp'], '%Y-%m-%dT%H:%M:%S%z').astimezone(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d %H:%M:%S')}")
st.markdown(
f"👍: {post['like_count']} <span style='{'' if like_count_diff != max_like_diff or max_like_diff == 0 else 'color:green;'}'>({'+' if like_count_diff >= 0 else ''}{like_count_diff})</span>"
f"\n💬: {post['comments_count']} <span style='{'' if comment_count_diff != max_comment_diff or max_comment_diff == 0 else 'color:green;'}'>({'+' if comment_count_diff >= 0 else ''}{comment_count_diff})</span>",
unsafe_allow_html=True)
caption = post['caption']
if caption is not None:
caption = caption.strip()
if "[Description]" in caption:
caption = caption.split("[Description]")[1].lstrip()
if "[Tags]" in caption:
caption = caption.split("[Tags]")[0].rstrip()
caption = caption.replace("#", "")
caption = caption.replace("[model]", "👗")
caption = caption.replace("[Equip]", "📷")
caption = caption.replace("[Develop]", "🖨")
if show_description:
st.write(caption or "No caption provided")
else:
st.write(caption[:0] if caption is not None and len(caption) > 50 else caption or "No caption provided")
if show_charts:
days = list(chart_data_likes.keys())
likes = [chart_data_likes[d] for d in days]
comments = [chart_data_comments[d] for d in days]
df_like_data = pd.DataFrame({"Date": days, "likes_count": likes})
df_comment_data = pd.DataFrame({"Date": days, "comments_count": comments})
fig, ax1 = plt.subplots(figsize=(5, 3))
sns.lineplot(data=df_like_data, x="Date", y="likes_count", color="orange", ax=ax1)
sns.lineplot(data=df_comment_data, x="Date", y="comments_count", color="green", ax=ax1)
plt.xticks(rotation=90)
plt.title("Like and Comment Counts")
sns.despine()
st.pyplot(fig)
count[today][post['id']] = {'like_count': post['like_count'], 'comments_count': post['comments_count']}
saveCount(count, count_filename)
|
9c09219679ddd0eec24576c34962939e
|
{
"intermediate": 0.3386264145374298,
"beginner": 0.38701653480529785,
"expert": 0.2743571102619171
}
|
3,404
|
The unity camera controls object movement
|
c08905573da560dc427ce25dae5ea224
|
{
"intermediate": 0.3874702453613281,
"beginner": 0.3125304877758026,
"expert": 0.2999992370605469
}
|
3,405
|
what are the commands that can use to demux a mpeg4 video and then remux to mkv format
|
8e0103199402b967f167f9ec2aa46fc9
|
{
"intermediate": 0.4523600935935974,
"beginner": 0.2619735598564148,
"expert": 0.2856663763523102
}
|
3,406
|
what external device for my usb printer do i need to print from ipad
|
a71d4ca61be1e16007eda10befadcb27
|
{
"intermediate": 0.4013707935810089,
"beginner": 0.3467113673686981,
"expert": 0.2519178092479706
}
|
3,407
|
'''
import requests
import json
import datetime
import streamlit as st
from itertools import zip_longest
import os
import seaborn as sns
import pandas as pd
import matplotlib.pyplot as plt
sns.set_theme(style="darkgrid")
def basic_info():
config = dict()
config["access_token"] = st.secrets["access_token"]
config['instagram_account_id'] = st.secrets.get("instagram_account_id", "")
config["version"] = 'v16.0'
config["graph_domain"] = 'https://graph.facebook.com/'
config["endpoint_base"] = config["graph_domain"] + config["version"] + '/'
return config
def InstaApiCall(url, params, request_type):
if request_type == 'POST':
req = requests.post(url, params)
else:
req = requests.get(url, params)
res = dict()
res["url"] = url
res["endpoint_params"] = params
res["endpoint_params_pretty"] = json.dumps(params, indent=4)
res["json_data"] = json.loads(req.content)
res["json_data_pretty"] = json.dumps(res["json_data"], indent=4)
return res
def getUserMedia(params, pagingUrl=''):
Params = dict()
Params['fields'] = 'id,caption,media_type,media_url,permalink,thumbnail_url,timestamp,username,like_count,comments_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
if pagingUrl == '':
url = params['endpoint_base'] + params['instagram_account_id'] + '/media'
else:
url = pagingUrl
return InstaApiCall(url, Params, 'GET')
def getUser(params):
Params = dict()
Params['fields'] = 'followers_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
url = params['endpoint_base'] + params['instagram_account_id']
return InstaApiCall(url, Params, 'GET')
def saveCount(count, filename):
with open(filename, 'w') as f:
json.dump(count, f, indent=4)
def getCount(filename):
try:
with open(filename, 'r') as f:
return json.load(f)
except (FileNotFoundError, json.decoder.JSONDecodeError):
return {}
st.set_page_config(layout="wide")
params = basic_info()
count_filename = "count.json"
if not params['instagram_account_id']:
st.write('.envファイルでinstagram_account_idを確認')
else:
response = getUserMedia(params)
user_response = getUser(params)
if not response or not user_response:
st.write('.envファイルでaccess_tokenを確認')
else:
posts = response['json_data']['data'][::-1]
user_data = user_response['json_data']
followers_count = user_data.get('followers_count', 0)
NUM_COLUMNS = 6
MAX_WIDTH = 1000
BOX_WIDTH = int(MAX_WIDTH / NUM_COLUMNS)
BOX_HEIGHT = 400
yesterday = (datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))) - datetime.timedelta(days=1)).strftime('%Y-%m-%d')
follower_diff = followers_count - getCount(count_filename).get(yesterday, {}).get('followers_count', followers_count)
st.markdown(f"<h4 style='font-size:1.2em;'>Follower: {followers_count} ({'+' if follower_diff >= 0 else ''}{follower_diff})</h4>", unsafe_allow_html=True)
show_description = st.checkbox("キャプションを表示")
show_summary_charts = st.checkbox("サマリーグラフを表示")
show_charts = st.checkbox("いいね/コメント数グラフを表示")
posts.reverse()
post_groups = [list(filter(None, group)) for group in zip_longest(*[iter(posts)] * NUM_COLUMNS)]
count = getCount(count_filename)
today = datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d')
if today not in count:
count[today] = {}
count[today]['followers_count'] = followers_count
if datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%H:%M') == '23:59':
count[yesterday] = count[today]
max_like_diff = 0
max_comment_diff = 0
chart_data = []
chart_data_likes = {}
chart_data_comments = {}
for key, value in count.items():
for c in value:
if c != 'followers_count':
post = count[count.keys()[-1]][c]
like_count_diff = value[c]['like_count'] - count.get(yesterday, {}).get(c, {}).get('like_count', post['like_count'])
comment_count_diff = value[c]['comments_count'] - count.get(yesterday, {}).get(c, {}).get('comments_count', post['comments_count'])
total_likes_count_diff = sum(value[c]['like_count'] - count.get(yesterday, {}).get(c, {}).get('like_count', like_count_diff) for c in value if c != 'followers_count')
total_comments_count_diff = sum(value[c]['comments_count'] - count.get(yesterday, {}).get(c, {}).get('comments_count', comment_count_diff) for c in value if c != 'followers_count')
if 'followers_count' in value:
chart_data_likes[key] = total_likes_count_diff
chart_data_comments[key] = total_comments_count_diff
chart_data.append([key, value['followers_count'], total_likes_count_diff, total_comments_count_diff])
if show_summary_charts:
df_chart_data = pd.DataFrame(chart_data, columns=["Date", "followers_count", "total_likes_count", "total_comments_count"])
df_chart_data["Date"] = pd.to_datetime(df_chart_data["Date"], format="%Y-%m-%d")
fig, ax1 = plt.subplots(figsize=(15, 6))
sns.lineplot(data=df_chart_data, x="Date", y="followers_count", color="lightskyblue", ax=ax1)
ax1.set(ylabel="followers_count")
ax2 = ax1.twinx()
sns.lineplot(data=df_chart_data, x="Date", y="total_likes_count", color="orange", ax=ax2)
sns.lineplot(data=df_chart_data, x="Date", y="total_comments_count", color="green", ax=ax2)
ax2.set(ylabel="total_likes_count & total_comments_count")
plt.title("Summary Chart")
sns.despine()
st.pyplot(fig)
for post_group in post_groups:
with st.container():
columns = st.columns(NUM_COLUMNS)
for i, post in enumerate(post_group):
like_count_diff = post['like_count'] - count.get(yesterday, {}).get(post['id'], {}).get('like_count', post['like_count'])
comment_count_diff = post['comments_count'] - count.get(yesterday, {}).get(post['id'], {}).get('comments_count', post['comments_count'])
max_like_diff = max(like_count_diff, max_like_diff)
max_comment_diff = max(comment_count_diff, max_comment_diff)
with columns[i]:
st.image(post['media_url'], width=BOX_WIDTH, use_column_width=True)
st.write(f"{datetime.datetime.strptime(post['timestamp'], '%Y-%m-%dT%H:%M:%S%z').astimezone(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d %H:%M:%S')}")
st.markdown(
f"👍: {post['like_count']} <span style='{'' if like_count_diff != max_like_diff or max_like_diff == 0 else 'color:green;'}'>({'+' if like_count_diff >= 0 else ''}{like_count_diff})</span>"
f"\n💬: {post['comments_count']} <span style='{'' if comment_count_diff != max_comment_diff or max_comment_diff == 0 else 'color:green;'}'>({'+' if comment_count_diff >= 0 else ''}{comment_count_diff})</span>",
unsafe_allow_html=True)
caption = post['caption']
if caption is not None:
caption = caption.strip()
if "[Description]" in caption:
caption = caption.split("[Description]")[1].lstrip()
if "[Tags]" in caption:
caption = caption.split("[Tags]")[0].rstrip()
caption = caption.replace("#", "")
caption = caption.replace("[model]", "👗")
caption = caption.replace("[Equip]", "📷")
caption = caption.replace("[Develop]", "🖨")
if show_description:
st.write(caption or "No caption provided")
else:
st.write(caption[:0] if caption is not None and len(caption) > 50 else caption or "No caption provided")
if show_charts:
days = list(chart_data_likes.keys())
likes = [chart_data_likes[d] for d in days]
comments = [chart_data_comments[d] for d in days]
df_like_data = pd.DataFrame({"Date": days, "likes_count": likes})
df_comment_data = pd.DataFrame({"Date": days, "comments_count": comments})
fig, ax1 = plt.subplots(figsize=(5, 3))
sns.lineplot(data=df_like_data, x="Date", y="likes_count", color="orange", ax=ax1)
sns.lineplot(data=df_comment_data, x="Date", y="comments_count", color="green", ax=ax1)
plt.xticks(rotation=90)
plt.title("Like and Comment Counts")
sns.despine()
st.pyplot(fig)
count[today][post['id']] = {'like_count': post['like_count'], 'comments_count': post['comments_count']}
saveCount(count, count_filename)
'''
上記コードを実行すると下記のエラーが発生します。下記のすべての要件に従って修正してください。
- Python用のインデントを行頭に付与して出力する
- コード冒頭の修正内容についての説明文は表示しない
- 指示のないコードの改変はしない
- "caption = post['caption']"以降のブロックについては改変しない
- 修正済みのコード全体を省略せずに表示する
'''
TypeError Traceback (most recent call last)
Cell In [16], line 134
132 for c in value:
133 if c != 'followers_count':
--> 134 post = count[count.keys()[-1]][c]
135 like_count_diff = value[c]['like_count'] - count.get(yesterday, {}).get(c, {}).get('like_count', post['like_count'])
136 comment_count_diff = value[c]['comments_count'] - count.get(yesterday, {}).get(c, {}).get('comments_count', post['comments_count'])
TypeError: 'dict_keys' object is not subscriptable
|
199825f3edbc9f286e91eb92e3c093c2
|
{
"intermediate": 0.3094857633113861,
"beginner": 0.43339425325393677,
"expert": 0.25711995363235474
}
|
3,408
|
'return': cannot convert from 'URagnaOffensiveAbility *' to 'UObject *
|
47a4c7b595a731e31395ed42c70c721a
|
{
"intermediate": 0.27684032917022705,
"beginner": 0.48022449016571045,
"expert": 0.24293513596057892
}
|
3,409
|
'''
import requests
import json
import datetime
import streamlit as st
from itertools import zip_longest
import os
import seaborn as sns
import pandas as pd
import matplotlib.pyplot as plt
sns.set_theme(style="darkgrid")
def basic_info():
config = dict()
config["access_token"] = st.secrets["access_token"]
config['instagram_account_id'] = st.secrets.get("instagram_account_id", "")
config["version"] = 'v16.0'
config["graph_domain"] = 'https://graph.facebook.com/'
config["endpoint_base"] = config["graph_domain"] + config["version"] + '/'
return config
def InstaApiCall(url, params, request_type):
if request_type == 'POST':
req = requests.post(url, params)
else:
req = requests.get(url, params)
res = dict()
res["url"] = url
res["endpoint_params"] = params
res["endpoint_params_pretty"] = json.dumps(params, indent=4)
res["json_data"] = json.loads(req.content)
res["json_data_pretty"] = json.dumps(res["json_data"], indent=4)
return res
def getUserMedia(params, pagingUrl=''):
Params = dict()
Params['fields'] = 'id,caption,media_type,media_url,permalink,thumbnail_url,timestamp,username,like_count,comments_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
if pagingUrl == '':
url = params['endpoint_base'] + params['instagram_account_id'] + '/media'
else:
url = pagingUrl
return InstaApiCall(url, Params, 'GET')
def getUser(params):
Params = dict()
Params['fields'] = 'followers_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
url = params['endpoint_base'] + params['instagram_account_id']
return InstaApiCall(url, Params, 'GET')
def saveCount(count, filename):
with open(filename, 'w') as f:
json.dump(count, f, indent=4)
def getCount(filename):
try:
with open(filename, 'r') as f:
return json.load(f)
except (FileNotFoundError, json.decoder.JSONDecodeError):
return {}
st.set_page_config(layout="wide")
params = basic_info()
count_filename = "count.json"
if not params['instagram_account_id']:
st.write('.envファイルでinstagram_account_idを確認')
else:
response = getUserMedia(params)
user_response = getUser(params)
if not response or not user_response:
st.write('.envファイルでaccess_tokenを確認')
else:
posts = response['json_data']['data'][::-1]
user_data = user_response['json_data']
followers_count = user_data.get('followers_count', 0)
NUM_COLUMNS = 6
MAX_WIDTH = 1000
BOX_WIDTH = int(MAX_WIDTH / NUM_COLUMNS)
BOX_HEIGHT = 400
yesterday = (datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))) - datetime.timedelta(days=1)).strftime('%Y-%m-%d')
follower_diff = followers_count - getCount(count_filename).get(yesterday, {}).get('followers_count', followers_count)
st.markdown(f"<h4 style='font-size:1.2em;'>Follower: {followers_count} ({'+' if follower_diff >= 0 else ''}{follower_diff})</h4>", unsafe_allow_html=True)
show_description = st.checkbox("キャプションを表示")
show_summary_charts = st.checkbox("サマリーグラフを表示")
show_charts = st.checkbox("いいね/コメント数グラフを表示")
posts.reverse()
post_groups = [list(filter(None, group)) for group in zip_longest(*[iter(posts)] * NUM_COLUMNS)]
count = getCount(count_filename)
today = datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d')
if today not in count:
count[today] = {}
count[today]['followers_count'] = followers_count
if datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%H:%M') == '23:59':
count[yesterday] = count[today]
max_like_diff = 0
max_comment_diff = 0
chart_data = []
chart_data_likes = {}
chart_data_comments = {}
for key, value in count.items():
for c in value:
if c != 'followers_count':
post = count[list(count.keys())[-1]][c]
like_count_diff = value[c]['like_count'] - count.get(yesterday, {}).get(c, {}).get('like_count', post['like_count'])
comment_count_diff = value[c]['comments_count'] - count.get(yesterday, {}).get(c, {}).get('comments_count', post['comments_count'])
total_likes_count_diff = sum(value[c]['like_count'] - count.get(yesterday, {}).get(c, {}).get('like_count', like_count_diff) for c in value if c != 'followers_count')
total_comments_count_diff = sum(value[c]['comments_count'] - count.get(yesterday, {}).get(c, {}).get('comments_count', comment_count_diff) for c in value if c != 'followers_count')
if 'followers_count' in value:
chart_data_likes[key] = total_likes_count_diff
chart_data_comments[key] = total_comments_count_diff
chart_data.append([key, value['followers_count'], total_likes_count_diff, total_comments_count_diff])
if show_summary_charts:
df_chart_data = pd.DataFrame(chart_data, columns=["Date", "followers_count", "total_likes_count", "total_comments_count"])
df_chart_data["Date"] = pd.to_datetime(df_chart_data["Date"], format="%Y-%m-%d")
fig, ax1 = plt.subplots(figsize=(15, 6))
sns.lineplot(data=df_chart_data, x="Date", y="followers_count", color="lightskyblue", ax=ax1)
ax1.set(ylabel="followers_count")
ax2 = ax1.twinx()
sns.lineplot(data=df_chart_data, x="Date", y="total_likes_count", color="orange", ax=ax2)
sns.lineplot(data=df_chart_data, x="Date", y="total_comments_count", color="green", ax=ax2)
ax2.set(ylabel="total_likes_count & total_comments_count")
plt.title("Summary Chart")
sns.despine()
st.pyplot(fig)
for post_group in post_groups:
with st.container():
columns = st.columns(NUM_COLUMNS)
for i, post in enumerate(post_group):
like_count_diff = post['like_count'] - count.get(yesterday, {}).get(post['id'], {}).get('like_count', post['like_count'])
comment_count_diff = post['comments_count'] - count.get(yesterday, {}).get(post['id'], {}).get('comments_count', post['comments_count'])
max_like_diff = max(like_count_diff, max_like_diff)
max_comment_diff = max(comment_count_diff, max_comment_diff)
with columns[i]:
st.image(post['media_url'], width=BOX_WIDTH, use_column_width=True)
st.write(f"{datetime.datetime.strptime(post['timestamp'], '%Y-%m-%dT%H:%M:%S%z').astimezone(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d %H:%M:%S')}")
st.markdown(
f"👍: {post['like_count']} <span style='{'' if like_count_diff != max_like_diff or max_like_diff == 0 else 'color:green;'}'>({'+' if like_count_diff >= 0 else ''}{like_count_diff})</span>"
f"\n💬: {post['comments_count']} <span style='{'' if comment_count_diff != max_comment_diff or max_comment_diff == 0 else 'color:green;'}'>({'+' if comment_count_diff >= 0 else ''}{comment_count_diff})</span>",
unsafe_allow_html=True)
caption = post['caption']
if caption is not None:
caption = caption.strip()
if "[Description]" in caption:
caption = caption.split("[Description]")[1].lstrip()
if "[Tags]" in caption:
caption = caption.split("[Tags]")[0].rstrip()
caption = caption.replace("#", "")
caption = caption.replace("[model]", "👗")
caption = caption.replace("[Equip]", "📷")
caption = caption.replace("[Develop]", "🖨")
if show_description:
st.write(caption or "No caption provided")
else:
st.write(caption[:0] if caption is not None and len(caption) > 50 else caption or "No caption provided")
if show_charts:
days = list(chart_data_likes.keys())
likes = [chart_data_likes[d] for d in days]
comments = [chart_data_comments[d] for d in days]
df_like_data = pd.DataFrame({"Date": days, "likes_count": likes})
df_comment_data = pd.DataFrame({"Date": days, "comments_count": comments})
fig, ax1 = plt.subplots(figsize=(5, 3))
sns.lineplot(data=df_like_data, x="Date", y="likes_count", color="orange", ax=ax1)
sns.lineplot(data=df_comment_data, x="Date", y="comments_count", color="green", ax=ax1)
plt.xticks(rotation=90)
plt.title("Like and Comment Counts")
sns.despine()
st.pyplot(fig)
count[today][post['id']] = {'like_count': post['like_count'], 'comments_count': post['comments_count']}
saveCount(count, count_filename)
'''
上記のコードを以下の要件をすべて満たして改修してください
- Python用のインデントを行頭に付与して出力する
- コード冒頭の修正内容についての説明文は表示しない
- 指示のないコードの改変はしない
- "caption = post['caption']"以降のブロックについては改変しない
- グラフ作成のためのPythonライブラリは"seaborn"のみを使用する
- "サマリーグラフ"の'like_count'と'comments_count'については、"各日の実数の合算"ではなく、"前日と比較して'増加した分'の数の合算"と変更する
- "いいね/コメント数グラフ"については、各投稿IDごとの'like_count'と'comments_count'の個別データを、"前日と比較して増加した総数"とし、その各投稿IDごとに別々のグラフを表示するようにする
|
f6da04055865e6f12863544bfc5a9e8c
|
{
"intermediate": 0.3094857633113861,
"beginner": 0.43339425325393677,
"expert": 0.25711995363235474
}
|
3,410
|
write a vba to calculate rsi with data in column d
|
d5b1c9912910a3f9f6b6da1caa31ed40
|
{
"intermediate": 0.3619370758533478,
"beginner": 0.30743157863616943,
"expert": 0.3306313753128052
}
|
3,411
|
'''
import requests
import json
import datetime
import streamlit as st
from itertools import zip_longest
import os
import seaborn as sns
import pandas as pd
import matplotlib.pyplot as plt
sns.set_theme(style="darkgrid")
def basic_info():
config = dict()
config["access_token"] = st.secrets["access_token"]
config['instagram_account_id'] = st.secrets.get("instagram_account_id", "")
config["version"] = 'v16.0'
config["graph_domain"] = 'https://graph.facebook.com/'
config["endpoint_base"] = config["graph_domain"] + config["version"] + '/'
return config
def InstaApiCall(url, params, request_type):
if request_type == 'POST':
req = requests.post(url, params)
else:
req = requests.get(url, params)
res = dict()
res["url"] = url
res["endpoint_params"] = params
res["endpoint_params_pretty"] = json.dumps(params, indent=4)
res["json_data"] = json.loads(req.content)
res["json_data_pretty"] = json.dumps(res["json_data"], indent=4)
return res
def getUserMedia(params, pagingUrl=''):
Params = dict()
Params['fields'] = 'id,caption,media_type,media_url,permalink,thumbnail_url,timestamp,username,like_count,comments_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
if pagingUrl == '':
url = params['endpoint_base'] + params['instagram_account_id'] + '/media'
else:
url = pagingUrl
return InstaApiCall(url, Params, 'GET')
def getUser(params):
Params = dict()
Params['fields'] = 'followers_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
url = params['endpoint_base'] + params['instagram_account_id']
return InstaApiCall(url, Params, 'GET')
def saveCount(count, filename):
with open(filename, 'w') as f:
json.dump(count, f, indent=4)
def getCount(filename):
try:
with open(filename, 'r') as f:
return json.load(f)
except (FileNotFoundError, json.decoder.JSONDecodeError):
return {}
st.set_page_config(layout="wide")
params = basic_info()
count_filename = "count.json"
if not params['instagram_account_id']:
st.write('.envファイルでinstagram_account_idを確認')
else:
response = getUserMedia(params)
user_response = getUser(params)
if not response or not user_response:
st.write('.envファイルでaccess_tokenを確認')
else:
posts = response['json_data']['data'][::-1]
user_data = user_response['json_data']
followers_count = user_data.get('followers_count', 0)
NUM_COLUMNS = 6
MAX_WIDTH = 1000
BOX_WIDTH = int(MAX_WIDTH / NUM_COLUMNS)
BOX_HEIGHT = 400
yesterday = (datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))) - datetime.timedelta(days=1)).strftime('%Y-%m-%d')
follower_diff = followers_count - getCount(count_filename).get(yesterday, {}).get('followers_count', followers_count)
st.markdown(f"<h4 style='font-size:1.2em;'>Follower: {followers_count} ({'+' if follower_diff >= 0 else ''}{follower_diff})</h4>", unsafe_allow_html=True)
show_description = st.checkbox("キャプションを表示")
show_summary_charts = st.checkbox("サマリーグラフを表示")
show_charts = st.checkbox("いいね/コメント数グラフを表示")
posts.reverse()
post_groups = [list(filter(None, group)) for group in zip_longest(*[iter(posts)] * NUM_COLUMNS)]
count = getCount(count_filename)
today = datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d')
if today not in count:
count[today] = {}
count[today]['followers_count'] = followers_count
if datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%H:%M') == '23:59':
count[yesterday] = count[today]
max_like_diff = 0
max_comment_diff = 0
chart_data = []
chart_data_likes = {}
chart_data_comments = {}
for key, value in count.items():
for c in value:
if c != 'followers_count':
post = count[list(count.keys())[-1]][c]
like_count_diff = value[c]['like_count'] - count.get(yesterday, {}).get(c, {}).get('like_count', post['like_count'])
comment_count_diff = value[c]['comments_count'] - count.get(yesterday, {}).get(c, {}).get('comments_count', post['comments_count'])
total_likes_count_diff = sum(value[c]['like_count'] - count.get(yesterday, {}).get(c, {}).get('like_count', like_count_diff) for c in value if c != 'followers_count')
total_comments_count_diff = sum(value[c]['comments_count'] - count.get(yesterday, {}).get(c, {}).get('comments_count', comment_count_diff) for c in value if c != 'followers_count')
if 'followers_count' in value:
chart_data_likes[key] = total_likes_count_diff
chart_data_comments[key] = total_comments_count_diff
chart_data.append([key, value['followers_count'], total_likes_count_diff, total_comments_count_diff])
if show_summary_charts:
df_chart_data = pd.DataFrame(chart_data, columns=["Date", "followers_count", "total_likes_count", "total_comments_count"])
df_chart_data["Date"] = pd.to_datetime(df_chart_data["Date"], format="%Y-%m-%d")
fig, ax1 = plt.subplots(figsize=(15, 6))
sns.lineplot(data=df_chart_data, x="Date", y="followers_count", color="lightskyblue", ax=ax1)
ax1.set(ylabel="followers_count")
ax2 = ax1.twinx()
sns.lineplot(data=df_chart_data, x="Date", y="total_likes_count", color="orange", ax=ax2)
sns.lineplot(data=df_chart_data, x="Date", y="total_comments_count", color="green", ax=ax2)
ax2.set(ylabel="total_likes_count & total_comments_count")
plt.title("Summary Chart")
sns.despine()
st.pyplot(fig)
for post_group in post_groups:
with st.container():
columns = st.columns(NUM_COLUMNS)
for i, post in enumerate(post_group):
like_count_diff = post['like_count'] - count.get(yesterday, {}).get(post['id'], {}).get('like_count', post['like_count'])
comment_count_diff = post['comments_count'] - count.get(yesterday, {}).get(post['id'], {}).get('comments_count', post['comments_count'])
max_like_diff = max(like_count_diff, max_like_diff)
max_comment_diff = max(comment_count_diff, max_comment_diff)
with columns[i]:
st.image(post['media_url'], width=BOX_WIDTH, use_column_width=True)
st.write(f"{datetime.datetime.strptime(post['timestamp'], '%Y-%m-%dT%H:%M:%S%z').astimezone(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d %H:%M:%S')}")
st.markdown(
f"👍: {post['like_count']} <span style='{'' if like_count_diff != max_like_diff or max_like_diff == 0 else 'color:green;'}'>({'+' if like_count_diff >= 0 else ''}{like_count_diff})</span>"
f"\n💬: {post['comments_count']} <span style='{'' if comment_count_diff != max_comment_diff or max_comment_diff == 0 else 'color:green;'}'>({'+' if comment_count_diff >= 0 else ''}{comment_count_diff})</span>",
unsafe_allow_html=True)
caption = post['caption']
if caption is not None:
caption = caption.strip()
if "[Description]" in caption:
caption = caption.split("[Description]")[1].lstrip()
if "[Tags]" in caption:
caption = caption.split("[Tags]")[0].rstrip()
caption = caption.replace("#", "")
caption = caption.replace("[model]", "👗")
caption = caption.replace("[Equip]", "📷")
caption = caption.replace("[Develop]", "🖨")
if show_description:
st.write(caption or "No caption provided")
else:
st.write(caption[:0] if caption is not None and len(caption) > 50 else caption or "No caption provided")
if show_charts:
days = list(chart_data_likes.keys())
likes = [chart_data_likes[d] for d in days]
comments = [chart_data_comments[d] for d in days]
df_like_data = pd.DataFrame({"Date": days, "likes_count": likes})
df_comment_data = pd.DataFrame({"Date": days, "comments_count": comments})
fig, ax1 = plt.subplots(figsize=(5, 3))
sns.lineplot(data=df_like_data, x="Date", y="likes_count", color="orange", ax=ax1)
sns.lineplot(data=df_comment_data, x="Date", y="comments_count", color="green", ax=ax1)
plt.xticks(rotation=90)
plt.title("Like and Comment Counts")
sns.despine()
st.pyplot(fig)
count[today][post['id']] = {'like_count': post['like_count'], 'comments_count': post['comments_count']}
saveCount(count, count_filename)
'''
上記のコードを以下の要件をすべて満たして改修してください
- Python用のインデントを行頭に付与して出力する
- コード冒頭の修正内容についての説明文は表示しない
- 指示のないコードの改変はしない
- "caption = post['caption']"以降のブロックについては改変しない
- グラフ作成のためのPythonライブラリは"seaborn"のみを使用する
- "サマリーグラフ"の'like_count'と'comments_count'の数は、"各日の実数の合算"ではなく、"前日と比較して増加した数"を算出し表示する
- "いいね/コメント数グラフ"については、各投稿IDごとに'like_count'と'comments_count'の"前日と比較して増加した数"を算出し、その各投稿IDごとに別々のグラフを表示するようにする
|
65422670547ca20f32ffec9123813047
|
{
"intermediate": 0.3094857633113861,
"beginner": 0.43339425325393677,
"expert": 0.25711995363235474
}
|
3,412
|
write a vba to calculate rsi with data in column d
|
a2620b01a31114c60dfd5ee696509923
|
{
"intermediate": 0.3619370758533478,
"beginner": 0.30743157863616943,
"expert": 0.3306313753128052
}
|
3,413
|
write a vba to calculate rsi with data in column d.write sub not function
|
03156e748304ff091513e4bcf3499285
|
{
"intermediate": 0.30664488673210144,
"beginner": 0.37796157598495483,
"expert": 0.3153935670852661
}
|
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