row_id
int64 0
48.4k
| init_message
stringlengths 1
342k
| conversation_hash
stringlengths 32
32
| scores
dict |
|---|---|---|---|
502
|
This are physically attched to the host & offer high perfomance
Extremely high perfomance very low latency
EBS volumes are attched over the network
Instance store volume are ephmeral (non - persistent)
data lost when instance power down use for temp data
EBS persistent storage & instance storage non persistent
While launching an instance we can see an option EBS only or disk space
only disk space is instance store
scan all the text I have given above
& from above text create questions
Now give answers to these questions By writing question 1st & thier answers
|
3046e7acae9021ac0337d034306fb3a7
|
{
"intermediate": 0.37939637899398804,
"beginner": 0.27518633008003235,
"expert": 0.3454173505306244
}
|
503
|
admin url path in django project '
|
4fcdcc5b78186012cfe8ddf913b9c6b2
|
{
"intermediate": 0.43714550137519836,
"beginner": 0.2338133007287979,
"expert": 0.32904118299484253
}
|
504
|
I want to create a chrome extension that does : when surfing a website or a Wikipedia page when i came across a term or topic , and I want to know immediately what elon musk said about that topic or term
|
7d864eb533df16ebf9052722db31dd8a
|
{
"intermediate": 0.3436185419559479,
"beginner": 0.25034281611442566,
"expert": 0.4060386121273041
}
|
505
|
nodejs new Function()
|
021dc7f1e607c2ec71a7c61a31b55dbe
|
{
"intermediate": 0.28003713488578796,
"beginner": 0.45613402128219604,
"expert": 0.2638288140296936
}
|
506
|
use tab instead of spaces only in python. i have an init.lua file in my ~/.config/nvim
|
7265d4a0265aa68795afe19cb5b69f23
|
{
"intermediate": 0.3377642333507538,
"beginner": 0.3302415907382965,
"expert": 0.3319942355155945
}
|
507
|
import React, {useState, useEffect, ChangeEvent} from "react";
import {
Badge, Box,
Button,
ButtonGroup,
Chip,
CircularProgress,
Grid,
Icon, IconButton, Skeleton, TextField,
Typography
} from "@mui/material";
import ArrowUpwardRoundedIcon from '@mui/icons-material/ArrowUpwardRounded';
import ArrowDownwardRoundedIcon from '@mui/icons-material/ArrowDownwardRounded';
import {useAuthContext} from "../../AuthProvider/AuthProvider";
import FormatPrice from "../../Common/FormatPrice";
import {Order, readCandlesByTrade, readOrderByTrade, Trade, updateTrade} from "../../../actions/cicap-diary-trades";
import DataTable from "../../DataTable/DataTable";
import {useSnackbar} from "notistack";
import {CandleChart} from "../CandleChart/CandleChart";
import {TradeEntity} from "../CandleChart/CandleChart.props";
import {FormattedNumber} from "react-intl";
import ImageIcon from "next/image";
import {createTradeImage, deleteTradeImage, tradeImagesCollection, TradeImage} from "../../../actions/cicap-diary-trades-images";
const timezoneOffset = new Date().getTimezoneOffset() * 60;
interface SideTypeProps {
order: Order;
}
const SideType = ({order}: SideTypeProps) => {
let label = '';
let color = 'default';
const icon = order?.side && 'sell' === order.side
? ArrowDownwardRoundedIcon
: ArrowUpwardRoundedIcon;
switch (order?.type) {
case 'limit':
label = 'L';
color = 'success'
break;
case 'market':
label = 'M';
color = 'warning'
break;
case 'stop_market':
label = 'F';
color = 'primary'
break;
}
return <>
<Badge
badgeContent={label}
// @ts-ignore
color={color}
>
<Icon component={icon} color="action" />
</Badge>
</>
}
interface CandlePrice {
timestamp: number;
open: number;
high: number;
low: number;
close: number;
volume: number;
}
interface TradeDetailsProps {
tradeId: string;
defaultChartInterval: string;
}
const TradeDetails = ({tradeId, defaultChartInterval}: TradeDetailsProps) => {
const [trade, setTrade] = useState<{orders: Array<Order>, data: Trade} | undefined>(undefined);
const [orders, setOrders] = useState<Array<TradeEntity>>([]);
const [chartInterval, setChartInterval] = useState(defaultChartInterval);
const [waiting, setWaiting] = useState(false);
const [candleData, setCandleData] = useState<Array<CandlePrice>>([]);
const [images, setImages] = useState<Array<TradeImage>>([]);
const [imageIdDeletion, setImageIdDeletion] = useState<string|null>(null);
const {diaryToken} = useAuthContext();
const [description, setDescription] = useState('');
const [conclusion, setConclusion] = useState('');
const [videoLink, setVideoLink] = useState('');
const {enqueueSnackbar} = useSnackbar();
const ref = React.createRef<HTMLInputElement>();
const fetchTrade = () => {
if (!tradeId || !diaryToken) {
return;
}
setWaiting(true);
readOrderByTrade(tradeId, diaryToken)
.then(data => {
setWaiting(false);
if (!data) return;
const newOrders: Array<TradeEntity> = [];
data.orders.forEach(order => {
const timestamp = Math.floor(order.msTimestamp) - timezoneOffset;
newOrders.push({
time: timestamp,
position: order.side,
value: parseFloat(order.price),
});
});
setTrade(data);
setOrders(newOrders);
});
}
const fetchImages = () => {
if (!tradeId || !diaryToken) {
return;
}
tradeImagesCollection(tradeId, diaryToken)
.then(data => {
if (!data) return;
setImages(data.data)
})
}
const createImage = (name: string, content: string) => {
if (!tradeId || !diaryToken) {
return;
}
createTradeImage(tradeId, {name: name, content: content}, diaryToken)
.then(data => {
if (!data) return;
setImages([...images, data.data])
})
}
const fetchCandleData = () => {
if (!tradeId || !diaryToken) {
return;
}
setWaiting(true);
readCandlesByTrade(tradeId, chartInterval, diaryToken)
.then(data => {
setWaiting(false);
if (!data) return;
// @ts-ignore
const candles = data.data;
const dataLength = candles.length;
const kLines = [];
for (let i = 0; i < dataLength; i += 1) {
const timestamp = Math.floor(candles[i][0]) - timezoneOffset;
kLines.push({
timestamp: timestamp,
open: parseFloat(candles[i][1]),
high: parseFloat(candles[i][2]),
low: parseFloat(candles[i][3]),
close: parseFloat(candles[i][4]),
volume: parseFloat(candles[i][5]),
});
}
setCandleData(kLines);
})
}
const updateTradeHandle = () => {
if (!diaryToken) return;
if (!trade?.data.id) return;
updateTrade(trade?.data.id, description, conclusion, videoLink, diaryToken)
.then(data => {
if (!data) return;
fetchTrade();
enqueueSnackbar('Сделка обновлена.', {variant: 'success'});
})
}
const onMainPhotoSelected = (e: ChangeEvent<HTMLInputElement>) => {
if (!e.target.files) return
const file = e.target.files[0]
const reader = new FileReader()
reader.onloadend = () => {
if (!reader.result) return
createImage(`chart-${tradeId}-${images.length}`, reader.result.toString())
}
reader.readAsDataURL(file)
}
const removeGalleryImage = (imageId: string) => {
if (!tradeId || !diaryToken) {
return;
}
setImageIdDeletion(imageId)
deleteTradeImage(tradeId, imageId, diaryToken)
.then(data => {
if (!data) return;
fetchImages();
enqueueSnackbar('Изображение удалено', {variant: 'success'});
setImageIdDeletion(null)
})
}
useEffect(() => {
fetchTrade();
fetchCandleData();
fetchImages()
}, [tradeId]);
useEffect(() => {
fetchCandleData();
}, [chartInterval]);
useEffect(() => {
setDescription(trade?.data?.description || '');
setConclusion(trade?.data?.conclusion || '');
setVideoLink(trade?.data?.videoLink || '');
}, [trade]);
return <>
<Box sx={{p: 2, pb: 4, backgroundColor: '#f5f5f5'}}>
<Box sx={{mb: 2}}>
<Typography variant="h6" component="span">
{trade?.data?.symbolName} {trade?.data?.side.toUpperCase()}
</Typography>
<Chip
label={`Процент: ${parseFloat(`${trade?.data?.percentDiffPrice}`).toFixed(Math.abs(parseFloat(`${trade?.data?.percentDiffPrice}`)) < 0.1 ? 3 : 2)}%`}
color={parseFloat(`${trade?.data?.percentDiffPrice}`) >= 0 ? 'success' : 'error'}
/>
<Chip
label={<>Прибыль: ${FormatPrice({ amount: parseFloat(`${trade?.data?.profit}`) || 0, currency_iso_code: 'USD'})}</>}
/>
</Box>
<Grid container spacing={2}>
<Grid item xs={12} md={6} sx={{pr: 2}}>
<ButtonGroup variant="outlined" style={{ marginBottom: '1rem' }}>
{
["1m", "3m", "5m", "15m", "30m", "1h", "4h", "12h", "1d"].map(interval => (
<Button
key={interval}
sx={{px: 1, py: .5, fontSize: '.75rem'}}
variant={interval === chartInterval ? "contained" : "outlined"}
onClick={() => setChartInterval(interval)}
>{interval}</Button>
))
}
</ButtonGroup>
{
waiting ? (
<CircularProgress
style={{position: "absolute", marginLeft: '1rem'}}
color="inherit"
size={32}
/>
) : (<></>)
}
<Box sx={{pr: 2}}>
{
trade?.data.id && candleData ? (<>
<CandleChart
images={images}
candles={candleData}
tradeId={trade?.data.id}
orders={orders}
interval={chartInterval}
openPrice={trade?.data.openPrice}
closePrice={trade?.data.closePrice}
pricePrecision={trade.data.pricePrecision}
quantityPrecision={trade.data.quantityPrecision}
createImage={createImage}
/>
</>) : (<>
<Skeleton variant="rectangular" height={500} />
</>)
}
</Box>
</Grid>
<Grid item xs={12} md={3}>
{trade?.orders && Array.isArray(trade.orders) ? (
<DataTable
sx={{fontSize: '.75rem', '& .MuiDataGrid-cell': {py: 2}}}
rows={trade.orders}
hideFooter
columns={[
{flex: 1, field: 'side', headerName: 'Сторона', sortable: false, filterable: false, renderCell: cell => (<>
{cell.value.toUpperCase()} <SideType order={cell.row} />
</>)},
{flex: 1, field: 'quantity', headerName: 'Оборот', sortable: false, filterable: false },
{flex: 1, field: 'price', headerName: 'Цена', sortable: false, filterable: false, renderCell: cell => (<>
<FormattedNumber
value={cell.value}
minimumFractionDigits={0}
maximumFractionDigits={parseInt(trade?.data.pricePrecision || '10')}
/> $
</>)},
{flex: 1, field: 'amount', headerName: 'Объем', sortable: false, filterable: false, renderCell: cell => (<>
<FormattedNumber
value={cell.value}
minimumFractionDigits={0}
maximumFractionDigits={parseInt(trade?.data.quantityPrecision || '10')}
/> $
</>)},
{flex: 1, field: 'profit', headerName: 'Доход', sortable: false, filterable: false, renderCell: cell => (<>
<FormattedNumber
value={cell.value}
minimumFractionDigits={0}
maximumFractionDigits={4}
/> $
</>)},
]}
/>
) : (<></>)}
<Box sx={{my: 2}}>
<Chip style={{ width: '1.5rem' }} size="small" label="M" color="warning" /> - Market order,
<Chip style={{ width: '1.5rem' }} size="small" label="L" color="success" /> - Limit order,
<Chip style={{ width: '1.5rem' }} size="small" label="F" color="primary" /> - Funding
</Box>
<Box sx={{ my: 2 }}>
<Grid display="flex">
<Typography>Галерея</Typography>
<input
ref={ref}
type='file'
accept=".jpg, .jpeg"
style={{ display: 'none' }}
onChange={onMainPhotoSelected}
/>
<Button sx={{ ml: 3, width: 60, height: 25 }} onClick={() => ref && ref.current?.click()}>
добавить
</Button>
</Grid>
<Grid mt={3} >
{
images.map((image, index) => <span style={{ position: "relative", margin: "5px" }} key={index}>
<a target='_blank' rel='noreferrer' href={image.url}>
<ImageIcon
style={{ cursor: "pointer", opacity: imageIdDeletion === image.id ? 0.4 : 1, margin: 5 }}
key={image.id + index}
src={image.url}
width={160}
height={120}
alt=""
/>
</a>
{
imageIdDeletion === image.id ?
<CircularProgress
style={{ position: "absolute", left: 55, top: -65 }}
color="error"
size={42}
/> : <></>
}
<IconButton color="error" sx={{ position: "absolute", right: 0, top: -114, borderRadius: 2 }}
onClick={() => removeGalleryImage(image.id)}
>
x
</IconButton>
</span>
)
}
</Grid>
</Box>
</Grid>
<Grid item xs={12} md={3}>
<Typography>Описание:</Typography>
<TextField
fullWidth
sx={{mb: 2}}
variant="outlined"
value={description} onChange={e => {
setDescription(e.target.value);
}}
multiline
rows={3}
/>
<Typography>Вывод:</Typography>
<TextField
fullWidth
sx={{mb: 2}}
variant="outlined"
value={conclusion} onChange={e => {
setConclusion(e.target.value);
}}
multiline
rows={3}
/>
<Typography>Ссылка на видео:</Typography>
<TextField fullWidth variant="outlined" value={videoLink} onChange={e => {
setVideoLink(e.target.value);
}} />
<Button color="primary" variant="contained" sx={{mt: 2}} onClick={updateTradeHandle}>Сохранить</Button>
</Grid>
</Grid>
</Box>
</>
}
export default TradeDetails;
import React, {useEffect, useRef, useState} from "react";
import {
init,
dispose,
Chart,
DeepPartial,
IndicatorFigureStylesCallbackData,
Indicator,
IndicatorStyle,
KLineData,
utils,
} from "klinecharts";
import {CandleChartProps} from "./CandleChart.props";
import CandleChartToolbar from "./CandleChartToolbar";
import {Style} from "util";
import {Box, Icon, IconButton, Stack} from "@mui/material";
import getMinutesTickSizeByInterval from "./utils/getMinutesTickSizeByInterval.util";
import drawTrade from "./utils/drawTrade.util";
import drawTradeLines from "./utils/drawTradeLines.util";
import {BasketIcon, ScreenIcon} from "../../icons";
import {FullScreen, useFullScreenHandle} from "react-full-screen";;
// @ts-ignore
const chartStyles: DeepPartial<Style> = {
candle: {
bar: {
upColor: "#4caf50",
downColor: "#d32f2f",
noChangeColor: ""
},
priceMark: {
high: {
textFamily: "Mont",
},
low: {
textFamily: "Mont",
},
last: {
text: {
family: "Mont",
}
}
},
tooltip: {
text: {
family: "Mont",
marginLeft: 10,
marginTop: 8,
marginRight: 10
}
}
},
indicator: {
ohlc: {
upColor: "red",
downColor: "red",
noChangeColor: "red"
},
bars: [{
upColor: "#4caf50",
downColor: "#d32f2f",
noChangeColor: ""
}],
lastValueMark: {
show: false,
text: {
family: "Mont",
}
},
tooltip: {
text: {
family: "Mont",
},
},
},
xAxis: {
tickText: {
family: "Mont",
}
},
yAxis: {
type: "log",
tickText: {
family: "Mont",
},
},
crosshair: {
horizontal: {
text: {
family: "Mont",
}
},
vertical: {
text: {
family: "Mont",
}
}
},
overlay: {
text: {
family: "Mont",
},
rectText: {
family: "Mont",
backgroundColor: "#686D76",
}
}
}
interface Vol {
volume?: number
}
export const CandleChart = ({
images,
candles,
tradeId,
orders,
interval,
openPrice,
closePrice,
pricePrecision,
quantityPrecision,
createImage
}: CandleChartProps) => {
console.log(candles);
const chart = useRef<Chart|null>();
const paneId = useRef<string>("");
const [figureId, setFigureId] = useState<string>("")
const ref = useRef<HTMLDivElement>(null);
const handle = useFullScreenHandle();
const onWindowResize = () => chart.current?.resize()
useEffect(() => {
window.addEventListener("resize", onWindowResize);
onWindowResize();
return () => {
window.removeEventListener("resize", onWindowResize);
};
}, [ref, handle]);
useEffect(() => {
chart.current = init(`chart-${tradeId}`, {styles: chartStyles});
return () => dispose(`chart-${tradeId}`);
}, [tradeId]);
useEffect(() => {
const onWindowResize = () => chart.current?.resize();
window.addEventListener("resize", onWindowResize);
return () => window.removeEventListener("resize", onWindowResize);
}, []);
useEffect(() => {
chart.current?.applyNewData(candles);
chart.current?.overrideIndicator({
name: "VOL",
shortName: "Объем",
calcParams: [],
figures: [
{
key: "volume",
title: "",
type: "bar",
baseValue: 0,
styles: (data: IndicatorFigureStylesCallbackData<Vol>, indicator: Indicator, defaultStyles: IndicatorStyle) => {
const kLineData = data.current.kLineData as KLineData
let color: string
if (kLineData.close > kLineData.open) {
color = utils.formatValue(indicator.styles, "bars[0].upColor", (defaultStyles.bars)[0].upColor) as string
} else if (kLineData.close < kLineData.open) {
color = utils.formatValue(indicator.styles, "bars[0].downColor", (defaultStyles.bars)[0].downColor) as string
} else {
color = utils.formatValue(indicator.styles, "bars[0].noChangeColor", (defaultStyles.bars)[0].noChangeColor) as string
}
return { color }
}
}
]
}, paneId.current);
chart.current?.createIndicator("VOL", false, { id: paneId.current });
chart.current?.setPriceVolumePrecision(+pricePrecision, +quantityPrecision);
}, [candles]);
useEffect(() => {
if (!orders || orders.length === 0 || candles.length === 0) return;
const minTime = orders[0].time;
const maxTime = orders[orders.length - 1].time;
const needleTime = minTime + (maxTime - minTime) / 2;
chart.current?.scrollToTimestamp(needleTime + 45 * getMinutesTickSizeByInterval(interval) * 60 * 1000);
drawTrade(chart, paneId, orders, interval);
if (openPrice && closePrice) {
let openTime = Infinity;
let closeTime = -Infinity;
orders.forEach(order => {
if (openTime > order.time) {
openTime = order.time;
}
if (closeTime < order.time) {
closeTime = order.time;
}
});
drawTradeLines(
chart,
openPrice,
openTime,
closePrice,
closeTime,
orders[0].position,
paneId,
pricePrecision,
quantityPrecision,
);
}
}, [orders, candles, tradeId]);
const removeFigure = () => {
chart.current?.removeOverlay({
id: figureId
})
setFigureId("")
}
const onButtonClick = async () => {
const imgUrl = chart.current?.getConvertPictureUrl(true)
if (!imgUrl) return
createImage(`chart-${tradeId}-${images.length}`, imgUrl)
const link = document.createElement("a");
link.setAttribute("href", imgUrl);
link.setAttribute("download", `chart-${tradeId}.jpg`);
link.click();
}
return (<>
<FullScreen handle={handle}>
<Box height={!handle.active ? 590 : "100%"} sx={{ position: "relative", background: "#ffffff" }}>
<Box sx={{ borderBottom: "1px solid #ddd" }}>
<Box sx={{ borderLeft: "1px solid #ddd", ml: "55px" }}>
<IconButton sx={{ borderRadius: 2, ml: 1, fontSize: "1rem", fontFamily: "Mont", color: "#677294" }} onClick={onButtonClick}>
<Icon component={ScreenIcon} /> Screenshot
</IconButton>
</Box>
</Box>
<Stack direction="row" height={!handle.active ? 550 : "100%"} width="100%">
<CandleChartToolbar
setFigureId={setFigureId}
chart={chart} paneId={paneId}
handle={handle}
/>
<Box
ref={ref}
id={`chart-${tradeId}`}
width="calc(100% - 55px)"
height={!handle.active ? 550 : "100%"}
sx={{ borderLeft: "1px solid #ddd" }}
>
{
figureId.length > 0 &&
<Stack
sx={{
backgroundColor: "#CBD4E3",
borderRadius: 1,
position: "absolute",
zIndex: 10,
right: 80,
top: 30,
border: "1px solid #697669",
}}
spacing={2}
>
<IconButton sx={{ borderRadius: 1 }} onClick={removeFigure}>
<Icon component={BasketIcon} />
</IconButton>
</Stack>
}
</Box>
</Stack>
</Box>
</FullScreen>
</>);
}
В тех сделках, где нет закрытого ордера нужно отображать на графике свечи в реальном времени и по текущей цене рассчитывать процент. Это нужно, чтобы можно было следить за сделкой в реальном времени.
Нужно чтобы график отображал текущую ситуацию на рынке, как здесь https://www.binance.com/ru/futures/DOGEUSDT
|
cd8308a253edd3623fb38ea32e36cfd8
|
{
"intermediate": 0.4048151671886444,
"beginner": 0.41602393984794617,
"expert": 0.1791609227657318
}
|
508
|
import streamlit as st
import pandas as pd
import requests
import json
from PIL import Image
from io import BytesIO
from itertools import groupby
import instaloader
import datetime
access_token = ""
account_id = ""
instaloading = instaloader.Instaloader()
def load_media_info(access_token, account_id):
base_url = f"https://graph.facebook.com/v11.0/{account_id}/media"
params = {
"fields": "id,media_type,media_url,thumbnail_url,permalink,caption,timestamp,like_count,comments_count,insights.metric(impressions,reach,engagement)",
"access_token": access_token
}
items = []
while base_url:
response = requests.get(base_url, params=params)
data = json.loads(response.text)
items.extend(data["data"])
if "paging" in data and "next" in data["paging"]:
base_url = data["paging"]["next"]
params = {}
else:
base_url = None
return pd.DataFrame(items)
df = load_media_info(access_token, account_id)
if 'thumbnail_url' not in df.columns:
df['thumbnail_url'] = df['media_url']
df['thumbnail_url'] = df.apply(lambda x: x["media_url"] if x["media_type"] == "IMAGE" else x["thumbnail_url"], axis=1)
df["id"] = df["timestamp"]
df["id"] = df["id"].apply(lambda x: datetime.datetime.strptime(x.split("+")[0], "%Y-%m-%dT%H:%M:%S").strftime("%Y%m%d"))
df = df.sort_values("timestamp", ascending=False)
df["id_rank"] = [f"＿＿{len(list(group))}" for _, group in groupby(df["id"])]
df["id"] += df["id_rank"]
menu = ["Content", "Analytics"]
choice = st.sidebar.radio("Menu", menu)
if choice == "Content":
selected_id = st.sidebar.selectbox("Select Post", df["id"].unique())
selected_data = df[df["id"] == selected_id].iloc[0]
image_url = selected_data["media_url"] if selected_data["media_type"] == "IMAGE" else selected_data["thumbnail_url"]
image_response = requests.get(image_url)
image = Image.open(BytesIO(image_response.content))
st.image(image, caption=selected_data["caption"])
likes = selected_data["like_count"]
if "insights" in selected_data.keys():
try:
impressions = selected_data["insights"][0]['values'][0]['value']
percentage = (likes * 100) / impressions
st.write(f"いいね: {likes} (インプレッションに対する割合: {percentage:.2f}%)")
except (KeyError, IndexError):
st.write(f"いいね: {likes}")
else:
st.write(f"いいね: {likes}")
st.write(f"コメント数: {selected_data['comments_count']}")
elif choice == "Analytics":
categories = ["フォロワー数", "いいね数", "コメント数"]
selected_category = st.selectbox("Select metric", categories)
if selected_category == "フォロワー数":
# フォロワー数を使ったグラフの作成
st.write("Here you can display the followers count graph")
elif selected_category == "いいね数":
# いいね数を使ったグラフの作成
st.write("Here you can display the likes count graph")
elif selected_category == "コメント数":
# コメント数を使ったグラフの作成
st.write("Here you can display the comments count graph")
'''
上記コードにてJupyter開発環境ではエラー表示はなく、streamlitで表示された事を確認できました。しかし、期待された表示がされていない箇所ががあり以下に改修点を列挙します。①"Content"で右ペインにpostされた当該コンテンツの画像が大きすぎるため縦横サイズを半分ほどに縮小表示してほしい。②"Content"の右ペインの"いいね数"の隣に「インプレッション数と"いいね数"から計算された"いいね"実施率」を"(24.9%)"のように小数点第一位まで表示してほしい。③"コメント数"の下に、実際のコメント一覧とコメントしたユーザ名をリスト表示してほしい。④左ペインで"Analytics"を選択し、右ペインでリストからmetricを選択してもグラフが表示されない。例えば、投稿日を基準とした時系列を横軸にして、"フォロワー数"や"いいね数"などを縦軸に設定して"フォロワー数"や"いいね数"などのデータをグラフ脇のリストから選択して動的に表示できるように改修してほしい。これらの機能が正常に動作するよう修正済みのコードを省略せずにすべて表示してください。もしコード内にアンダースコアを2つ連続で使用するのであれば、出力時に不可視にされてしまうので"＿＿"に置換して表示してください。
|
a7c32915130cf7ae1e4eac66ac8a6568
|
{
"intermediate": 0.47716858983039856,
"beginner": 0.349801629781723,
"expert": 0.1730298101902008
}
|
509
|
nvim tabs instead of spaces for only python files in inti.lua file
|
a6c610e106bb4ad61137fd79a05faeed
|
{
"intermediate": 0.337088406085968,
"beginner": 0.29968878626823425,
"expert": 0.36322274804115295
}
|
510
|
how to add user in openconnect to group
|
b86a19ae5fb38616dd5c904bed360d9f
|
{
"intermediate": 0.410677433013916,
"beginner": 0.23046602308750153,
"expert": 0.3588564991950989
}
|
511
|
const readOrderByTrade = (
tradeId: string,
token: string,
): Promise<{data:Trade,orders:Array<Order>}|undefined> => {
return diaryClient(
`/trades/${tradeId}/orders`,
'get',
token,
);
}
const [trade, setTrade] = useState<{orders: Array<Order>, data: Trade} | undefined>(undefined);
const [orders, setOrders] = useState<Array<TradeEntity>>([]);
const fetchTrade = () => {
if (!tradeId || !diaryToken) {
return;
}
setWaiting(true);
readOrderByTrade(tradeId, diaryToken)
.then(data => {
setWaiting(false);
if (!data) return;
const newOrders: Array<TradeEntity> = [];
data.orders.forEach(order => {
const timestamp = Math.floor(order.msTimestamp) - timezoneOffset;
newOrders.push({
time: timestamp,
position: order.side,
value: parseFloat(order.price),
});
});
setTrade(data);
setOrders(newOrders);
});
}
const fetchCandleData = () => {
if (!tradeId || !diaryToken) {
return;
}
setWaiting(true);
readCandlesByTrade(tradeId, chartInterval, diaryToken)
.then(data => {
setWaiting(false);
if (!data) return;
// @ts-ignore
const candles = data.data;
const dataLength = candles.length;
const kLines = [];
for (let i = 0; i < dataLength; i += 1) {
const timestamp = Math.floor(candles[i][0]) - timezoneOffset;
kLines.push({
timestamp: timestamp,
open: parseFloat(candles[i][1]),
high: parseFloat(candles[i][2]),
low: parseFloat(candles[i][3]),
close: parseFloat(candles[i][4]),
volume: parseFloat(candles[i][5]),
});
}
setCandleData(kLines);
})
}
return <> <Box sx={{pr: 2}}>
{
trade?.data.id && candleData ? (<>
<CandleChart
images={images}
candles={candleData}
tradeId={trade?.data.id}
orders={orders}
interval={chartInterval}
openPrice={trade?.data.openPrice}
closePrice={trade?.data.closePrice}
pricePrecision={trade.data.pricePrecision}
quantityPrecision={trade.data.quantityPrecision}
createImage={createImage}
/>
</>) : (<>
<Skeleton variant="rectangular" height={500} />
</>)
}
</Box>
</>);
}
import React, {useEffect, useRef, useState} from "react";
import {
init,
dispose,
Chart,
DeepPartial,
IndicatorFigureStylesCallbackData,
Indicator,
IndicatorStyle,
KLineData,
utils,
} from "klinecharts";
import {CandleChartProps} from "./CandleChart.props";
import CandleChartToolbar from "./CandleChartToolbar";
import {Style} from "util";
import {Box, Icon, IconButton, Stack} from "@mui/material";
import getMinutesTickSizeByInterval from "./utils/getMinutesTickSizeByInterval.util";
import drawTrade from "./utils/drawTrade.util";
import drawTradeLines from "./utils/drawTradeLines.util";
import {BasketIcon, ScreenIcon} from "../../icons";
import {FullScreen, useFullScreenHandle} from "react-full-screen";;
// @ts-ignore
const chartStyles: DeepPartial<Style> = {
candle: {
bar: {
upColor: "#4caf50",
downColor: "#d32f2f",
noChangeColor: ""
},
priceMark: {
high: {
textFamily: "Mont",
},
low: {
textFamily: "Mont",
},
last: {
text: {
family: "Mont",
}
}
},
tooltip: {
text: {
family: "Mont",
marginLeft: 10,
marginTop: 8,
marginRight: 10
}
}
},
indicator: {
ohlc: {
upColor: "red",
downColor: "red",
noChangeColor: "red"
},
bars: [{
upColor: "#4caf50",
downColor: "#d32f2f",
noChangeColor: ""
}],
lastValueMark: {
show: false,
text: {
family: "Mont",
}
},
tooltip: {
text: {
family: "Mont",
},
},
},
xAxis: {
tickText: {
family: "Mont",
}
},
yAxis: {
type: "log",
tickText: {
family: "Mont",
},
},
crosshair: {
horizontal: {
text: {
family: "Mont",
}
},
vertical: {
text: {
family: "Mont",
}
}
},
overlay: {
text: {
family: "Mont",
},
rectText: {
family: "Mont",
backgroundColor: "#686D76",
}
}
}
interface Vol {
volume?: number
}
export const CandleChart = ({
images,
candles,
tradeId,
orders,
interval,
openPrice,
closePrice,
pricePrecision,
quantityPrecision,
createImage
}: CandleChartProps) => {
console.log(candles);
const chart = useRef<Chart|null>();
const paneId = useRef<string>("");
const [figureId, setFigureId] = useState<string>("")
const ref = useRef<HTMLDivElement>(null);
const handle = useFullScreenHandle();
useEffect(() => {
chart.current = init(`chart-${tradeId}`, {styles: chartStyles});
return () => dispose(`chart-${tradeId}`);
}, [tradeId]);
useEffect(() => {
const onWindowResize = () => chart.current?.resize();
window.addEventListener("resize", onWindowResize);
return () => window.removeEventListener("resize", onWindowResize);
}, []);
useEffect(() => {
chart.current?.applyNewData(candles);
chart.current?.overrideIndicator({
name: "VOL",
shortName: "Объем",
calcParams: [],
figures: [
{
key: "volume",
title: "",
type: "bar",
baseValue: 0,
styles: (data: IndicatorFigureStylesCallbackData<Vol>, indicator: Indicator, defaultStyles: IndicatorStyle) => {
const kLineData = data.current.kLineData as KLineData
let color: string
if (kLineData.close > kLineData.open) {
color = utils.formatValue(indicator.styles, "bars[0].upColor", (defaultStyles.bars)[0].upColor) as string
} else if (kLineData.close < kLineData.open) {
color = utils.formatValue(indicator.styles, "bars[0].downColor", (defaultStyles.bars)[0].downColor) as string
} else {
color = utils.formatValue(indicator.styles, "bars[0].noChangeColor", (defaultStyles.bars)[0].noChangeColor) as string
}
return { color }
}
}
]
}, paneId.current);
chart.current?.createIndicator("VOL", false, { id: paneId.current });
chart.current?.setPriceVolumePrecision(+pricePrecision, +quantityPrecision);
}, [candles]);
useEffect(() => {
if (!orders || orders.length === 0 || candles.length === 0) return;
const minTime = orders[0].time;
const maxTime = orders[orders.length - 1].time;
const needleTime = minTime + (maxTime - minTime) / 2;
chart.current?.scrollToTimestamp(needleTime + 45 * getMinutesTickSizeByInterval(interval) * 60 * 1000);
drawTrade(chart, paneId, orders, interval);
if (openPrice && closePrice) {
let openTime = Infinity;
let closeTime = -Infinity;
orders.forEach(order => {
if (openTime > order.time) {
openTime = order.time;
}
if (closeTime < order.time) {
closeTime = order.time;
}
});
drawTradeLines(
chart,
openPrice,
openTime,
closePrice,
closeTime,
orders[0].position,
paneId,
pricePrecision,
quantityPrecision,
);
}
}, [orders, candles, tradeId]);
return (<>
<Stack direction="row" height={!handle.active ? 550 : "100%"} width="100%">
<CandleChartToolbar
setFigureId={setFigureId}
chart={chart} paneId={paneId}
handle={handle}
/>
<Box
ref={ref}
id={`chart-${tradeId}`}
width="calc(100% - 55px)"
height={!handle.active ? 550 : "100%"}
sx={{ borderLeft: "1px solid #ddd" }}
>
{
figureId.length > 0 &&
<Stack
sx={{
backgroundColor: "#CBD4E3",
borderRadius: 1,
position: "absolute",
zIndex: 10,
right: 80,
top: 30,
border: "1px solid #697669",
}}
spacing={2}
>
<IconButton sx={{ borderRadius: 1 }} onClick={removeFigure}>
<Icon component={BasketIcon} />
</IconButton>
</Stack>
}
</Box>
</Stack>
</>);
}
В тех сделках, где нет закрытого ордера нужно отображать на графике свечи в реальном времени и по текущей цене рассчитывать процент. Это нужно, чтобы можно было следить за сделкой в реальном времени. Нужно чтобы график отображал текущую ситуацию на рынке, как здесь https://www.binance.com/ru/futures/DOGEUSDT
|
1e3b7eb939f462415d44f0e16baf6928
|
{
"intermediate": 0.38178667426109314,
"beginner": 0.44135773181915283,
"expert": 0.1768556386232376
}
|
512
|
How to point to a clang-format-8.exe binary within the in-built clang formatter?
|
61eb7ff28f27b67ae4adb402a2a78554
|
{
"intermediate": 0.4338313639163971,
"beginner": 0.26799577474594116,
"expert": 0.29817283153533936
}
|
513
|
i found an tool that can get current playing song info in macos from the commandline, but i dont know how to install it:
github: https://github.com/kirtan-shah/nowplaying-cli
README.md:
nowplaying-cli
nowplaying-cli is a macOS command-line utility for retrieving currently playing media, and simulating media actions.
Use nowplaying-cli to get song information and play/pause your media through an easy to use CLI!
Disclaimer: nowplaying-cli uses private frameworks, which may cause it to break with future macOS software updates.
Tested and working on:
Ventura 13.1
Usage
nowplaying-cli <cmd>
command description
get [propName1 propName2 … ] get now playing media properties
get-raw get all non-nil now playing media properties in dictionary format
play play the currently playing media regardless of current state
pause pause the currently playing media regardless of current state
togglePlayPause toggle play/pause based on current state
next skip to next track
previous go to previous track
Examples
screenshot of examples in terminal
Available properties
native nowplaying-cli
kMRMediaRemoteNowPlayingInfoTotalDiscCount totalDiscCount
kMRMediaRemoteNowPlayingInfoShuffleMode shuffleMode
kMRMediaRemoteNowPlayingInfoTrackNumber trackNumber
kMRMediaRemoteNowPlayingInfoDuration duration
kMRMediaRemoteNowPlayingInfoRepeatMode repeatMode
kMRMediaRemoteNowPlayingInfoTitle title
kMRMediaRemoteNowPlayingInfoPlaybackRate playbackRate
kMRMediaRemoteNowPlayingInfoArtworkData artworkData
kMRMediaRemoteNowPlayingInfoAlbum album
kMRMediaRemoteNowPlayingInfoTotalQueueCount totalQueueCount
kMRMediaRemoteNowPlayingInfoArtworkMIMEType artworkMIMEType
kMRMediaRemoteNowPlayingInfoMediaType mediaType
kMRMediaRemoteNowPlayingInfoDiscNumber discNumber
kMRMediaRemoteNowPlayingInfoTimestamp timestamp
kMRMediaRemoteNowPlayingInfoGenre genre
kMRMediaRemoteNowPlayingInfoQueueIndex queueIndex
kMRMediaRemoteNowPlayingInfoArtist artist
kMRMediaRemoteNowPlayingInfoDefaultPlaybackRate defaultPlaybackRate
kMRMediaRemoteNowPlayingInfoElapsedTime elapsedTime
kMRMediaRemoteNowPlayingInfoTotalTrackCount totalTrackCount
kMRMediaRemoteNowPlayingInfoIsMusicApp isMusicApp
kMRMediaRemoteNowPlayingInfoUniqueIdentifier uniqueIdentifier
Homebrew Install
TODO
Build
clang nowplaying.mm -framework Cocoa -o nowplaying-cli -O3
files:
nowplaying.mm
Enums.h
|
5e11d4d13cea90c435ee3a261876f150
|
{
"intermediate": 0.41671130061149597,
"beginner": 0.2892118990421295,
"expert": 0.2940768301486969
}
|
514
|
can you create a android studio app that edits a google sheet column
|
5f029630121a45a876533b902522e56e
|
{
"intermediate": 0.45324867963790894,
"beginner": 0.1918979287147522,
"expert": 0.35485342144966125
}
|
515
|
Pretend you are a Linux terminal running bash.
|
f51e0dbca6179bab25d554240142d412
|
{
"intermediate": 0.3553963899612427,
"beginner": 0.36850792169570923,
"expert": 0.2760957181453705
}
|
516
|
const readOrderByTrade = (
tradeId: string,
token: string,
): Promise<{data:Trade,orders:Array<Order>}|undefined> => {
return diaryClient(
/trades/${tradeId}/orders,
‘get’,
token,
);
}
const [trade, setTrade] = useState<{orders: Array<Order>, data: Trade} | undefined>(undefined);
const [orders, setOrders] = useState<Array<TradeEntity>>([]);
const fetchTrade = () => {
if (!tradeId || !diaryToken) {
return;
}
setWaiting(true);
readOrderByTrade(tradeId, diaryToken)
.then(data => {
setWaiting(false);
if (!data) return;
const newOrders: Array<TradeEntity> = [];
data.orders.forEach(order => {
const timestamp = Math.floor(order.msTimestamp) - timezoneOffset;
newOrders.push({
time: timestamp,
position: order.side,
value: parseFloat(order.price),
});
});
setTrade(data);
setOrders(newOrders);
});
}
const fetchCandleData = () => {
if (!tradeId || !diaryToken) {
return;
}
setWaiting(true);
readCandlesByTrade(tradeId, chartInterval, diaryToken)
.then(data => {
setWaiting(false);
if (!data) return;
// @ts-ignore
const candles = data.data;
const dataLength = candles.length;
const kLines = [];
for (let i = 0; i < dataLength; i += 1) {
const timestamp = Math.floor(candles[i][0]) - timezoneOffset;
kLines.push({
timestamp: timestamp,
open: parseFloat(candles[i][1]),
high: parseFloat(candles[i][2]),
low: parseFloat(candles[i][3]),
close: parseFloat(candles[i][4]),
volume: parseFloat(candles[i][5]),
});
}
setCandleData(kLines);
})
}
return <> <Box sx={{pr: 2}}>
{
trade?.data.id && candleData ? (<>
<CandleChart
images={images}
candles={candleData}
tradeId={trade?.data.id}
orders={orders}
interval={chartInterval}
openPrice={trade?.data.openPrice}
closePrice={trade?.data.closePrice}
pricePrecision={trade.data.pricePrecision}
quantityPrecision={trade.data.quantityPrecision}
createImage={createImage}
/>
</>) : (<>
<Skeleton variant=“rectangular” height={500} />
</>)
}
</Box>
</>);
}
import React, {useEffect, useRef, useState} from “react”;
import {
init,
dispose,
Chart,
DeepPartial,
IndicatorFigureStylesCallbackData,
Indicator,
IndicatorStyle,
KLineData,
utils,
} from “klinecharts”;
import {CandleChartProps} from “./CandleChart.props”;
import CandleChartToolbar from “./CandleChartToolbar”;
import {Style} from “util”;
import {Box, Icon, IconButton, Stack} from “@mui/material”;
import getMinutesTickSizeByInterval from “./utils/getMinutesTickSizeByInterval.util”;
import drawTrade from “./utils/drawTrade.util”;
import drawTradeLines from “./utils/drawTradeLines.util”;
import {BasketIcon, ScreenIcon} from “…/…/icons”;
import {FullScreen, useFullScreenHandle} from “react-full-screen”;;
interface Vol {
volume?: number
}
export const CandleChart = ({
images,
candles,
tradeId,
orders,
interval,
openPrice,
closePrice,
pricePrecision,
quantityPrecision,
createImage
}: CandleChartProps) => {
console.log(candles);
const chart = useRef<Chart|null>();
const paneId = useRef<string>(“”);
const [figureId, setFigureId] = useState<string>(“”)
const ref = useRef<HTMLDivElement>(null);
const handle = useFullScreenHandle();
useEffect(() => {
chart.current = init(chart-${tradeId}, {styles: chartStyles});
return () => dispose(chart-${tradeId});
}, [tradeId]);
useEffect(() => {
const onWindowResize = () => chart.current?.resize();
window.addEventListener(“resize”, onWindowResize);
return () => window.removeEventListener(“resize”, onWindowResize);
}, []);
useEffect(() => {
chart.current?.applyNewData(candles);
chart.current?.overrideIndicator({
name: “VOL”,
shortName: “Объем”,
calcParams: [],
figures: [
{
key: “volume”,
title: “”,
type: “bar”,
baseValue: 0,
styles: (data: IndicatorFigureStylesCallbackData<Vol>, indicator: Indicator, defaultStyles: IndicatorStyle) => {
const kLineData = data.current.kLineData as KLineData
let color: string
if (kLineData.close > kLineData.open) {
color = utils.formatValue(indicator.styles, “bars[0].upColor”, (defaultStyles.bars)[0].upColor) as string
} else if (kLineData.close < kLineData.open) {
color = utils.formatValue(indicator.styles, “bars[0].downColor”, (defaultStyles.bars)[0].downColor) as string
} else {
color = utils.formatValue(indicator.styles, “bars[0].noChangeColor”, (defaultStyles.bars)[0].noChangeColor) as string
}
return { color }
}
}
]
}, paneId.current);
chart.current?.createIndicator(“VOL”, false, { id: paneId.current });
chart.current?.setPriceVolumePrecision(+pricePrecision, +quantityPrecision);
}, [candles]);
useEffect(() => {
if (!orders || orders.length === 0 || candles.length === 0) return;
const minTime = orders[0].time;
const maxTime = orders[orders.length - 1].time;
const needleTime = minTime + (maxTime - minTime) / 2;
chart.current?.scrollToTimestamp(needleTime + 45 * getMinutesTickSizeByInterval(interval) * 60 * 1000);
drawTrade(chart, paneId, orders, interval);
if (openPrice && closePrice) {
let openTime = Infinity;
let closeTime = -Infinity;
orders.forEach(order => {
if (openTime > order.time) {
openTime = order.time;
}
if (closeTime < order.time) {
closeTime = order.time;
}
});
drawTradeLines(
chart,
openPrice,
openTime,
closePrice,
closeTime,
orders[0].position,
paneId,
pricePrecision,
quantityPrecision,
);
}
}, [orders, candles, tradeId]);
return (<>
<Stack direction=“row” height={!handle.active ? 550 : “100%”} width=“100%”>
<CandleChartToolbar
setFigureId={setFigureId}
chart={chart} paneId={paneId}
handle={handle}
/>
<Box
ref={ref}
id={chart-${tradeId}}
width=“calc(100% - 55px)”
height={!handle.active ? 550 : “100%”}
sx={{ borderLeft: “1px solid #ddd” }}
>
{
figureId.length > 0 &&
<Stack
sx={{
backgroundColor: “#CBD4E3”,
borderRadius: 1,
position: “absolute”,
zIndex: 10,
right: 80,
top: 30,
border: “1px solid #697669”,
}}
spacing={2}
>
<IconButton sx={{ borderRadius: 1 }} onClick={removeFigure}>
<Icon component={BasketIcon} />
</IconButton>
</Stack>
}
</Box>
</Stack>
</>);
}
В тех сделках, где нет закрытого ордера нужно отображать на графике свечи в реальном времени и по текущей цене рассчитывать процент. Это нужно, чтобы можно было следить за сделкой в реальном времени. Нужно чтобы график отображал текущую ситуацию на рынке, как здесь https://www.binance.com/ru/futures/DOGEUSDT
|
af69586e9ac853593cfa22fd338ea7c1
|
{
"intermediate": 0.33156001567840576,
"beginner": 0.4901132881641388,
"expert": 0.17832672595977783
}
|
517
|
I want to make an integer parameter in a pytorch module, how can I do that?
|
f0d7fa62a83e007ac6637ff75ed8c1c6
|
{
"intermediate": 0.5684312582015991,
"beginner": 0.17100609838962555,
"expert": 0.26056262850761414
}
|
518
|
Pretend to be a Commodore 64.
|
64d16ce78ede0c370d997bcc1e5c415a
|
{
"intermediate": 0.33610910177230835,
"beginner": 0.4039357304573059,
"expert": 0.25995516777038574
}
|
519
|
I’m trying to make a fivem NUI that displays a little points score at the top of the screen
https://cdn.discordapp.com/attachments/1052780891300184096/1095659338003128380/image.png
do you think i’m best to use react or just html css
|
d5a837d4c9a723a0e8f4e17cfdff5a40
|
{
"intermediate": 0.31530818343162537,
"beginner": 0.22456710040569305,
"expert": 0.4601247012615204
}
|
520
|
using https with nginx and gunicorn if i have ssl certificate
|
255ff28ddefb9035cd9e93bf11efb587
|
{
"intermediate": 0.4605598449707031,
"beginner": 0.2390526682138443,
"expert": 0.30038753151893616
}
|
521
|
Pretend to be a Linux terminal running on Pablo Picasso's computer.
|
4edf5b6c2a7633ee8dbcbc40bb0d3496
|
{
"intermediate": 0.3352341651916504,
"beginner": 0.3124828636646271,
"expert": 0.3522830009460449
}
|
522
|
'''
import streamlit as st
import pandas as pd
import requests
import json
from PIL import Image
from io import BytesIO
from itertools import groupby
import instaloader
import datetime
import altair as alt
loader = instaloader.Instaloader()
loader.context.request_timeout = (9, 15) # Increase request timeout
access_token = ""
account_id = ""
def load_media_info(access_token, account_id):
base_url = f"https://graph.facebook.com/v11.0/{account_id}/media"
params = {
"fields": "id,media_type,media_url,thumbnail_url,permalink,caption,timestamp,like_count,comments_count,insights.metric(impressions,reach,engagement)",
"access_token": access_token
}
items = []
while base_url:
response = requests.get(base_url, params=params)
data = json.loads(response.text)
items.extend(data["data"])
if "paging" in data and "next" in data["paging"]:
base_url = data["paging"]["next"]
params = {}
else:
base_url = None
return pd.DataFrame(items)
df = load_media_info(access_token, account_id)
if 'thumbnail_url' not in df.columns:
df['thumbnail_url'] = df['media_url']
df['thumbnail_url'] = df.apply(lambda x: x["media_url"] if x["media_type"] == "IMAGE" else x["thumbnail_url"], axis=1)
df["id"] = df["timestamp"]
df["id"] = df["id"].apply(lambda x: datetime.datetime.strptime(x.split("+")[0], "%Y-%m-%dT%H:%M:%S").strftime("%Y%m%d"))
df = df.sort_values("timestamp", ascending=False)
df["id_rank"] = [f"＿＿{len(list(group))}" for _, group in groupby(df["id"])]
df["id"] += df["id_rank"]
menu = ["Content", "Analytics"]
choice = st.sidebar.radio("Menu", menu)
if choice == "Content":
selected_id = st.sidebar.selectbox("Select Post", df["id"].unique())
selected_data = df[df["id"] == selected_id].iloc[0]
image_url = selected_data["media_url"] if selected_data["media_type"] == "IMAGE" else selected_data["thumbnail_url"]
image_response = requests.get(image_url)
image = Image.open(BytesIO(image_response.content))
st.image(image, caption=selected_data["caption"], width=300)
likes = selected_data["like_count"]
if "insights" in selected_data.keys():
try:
impressions = selected_data["insights"][0]['values'][0]['value']
percentage = (likes * 100) / impressions
st.write(f"いいね: {likes} (インプレッションに対する割合: {percentage:.1f}%)")
except (KeyError, IndexError):
st.write(f"いいね: {likes}")
else:
st.write(f"いいね: {likes}")
st.write(f"コメント数: {selected_data['comments_count']}")
# Get comments and usernames
try:
shortcode = selected_data["permalink"].split("/")[-2]
post = instaloader.Post.from_shortcode(loader.context, shortcode)
comments = post.get_comments()
for comment in comments:
st.write(f"{comment.owner.username}: {comment.text}")
except Exception as e:
st.write("コメントの取得中にエラーが発生しました。")
elif choice == "Analytics":
categories = ["フォロワー数", "いいね数", "コメント数"]
selected_category = st.selectbox("Select metric", categories)
if selected_category == "フォロワー数":
metric = "follower_count"
elif selected_category == "いいね数":
metric = "like_count"
elif selected_category == "コメント数":
metric = "comments_count"
chart_df = df[["id", "timestamp", metric]].copy()
chart_df["timestamp"] = pd.to_datetime(chart_df["timestamp"]).dt.date
chart = alt.Chart(chart_df).mark_line().encode(
x="timestamp:T",
y=metric + ":Q"
).properties(
title=f"Time Series of {selected_category}",
width=800,
height=300
)
st.altair_chart(chart)
'''
上記コードにてJupyter開発環境ではエラー表示はなく、streamlitで表示された事を確認できました。しかし、期待された表示がされていない箇所があるため、以下に改修点を列挙します。
①"Content"の右ペインの"いいね数"の隣に「インプレッション数と"いいね数"から計算された"いいね"実施率」を"(24.9%)"のように小数点第一位まで表示されていない
②"Content"の右ペインの"コメント数"の下に、実際のコメント一覧とコメントしたユーザ名が列挙されるリストが表示されない
③左ペインで"Analytics"を選択し、右ペインでリストから"metric"を選択した際に"フォロワー数"のみグラフが表示されない。この"フォロワー数"を選択した際の画面上のエラー表示は下記。
'''
KeyError: "['follower_count'] not in index"
Traceback:
File "/home/walhalax/.var/app/org.jupyter.JupyterLab/config/jupyterlab-desktop/jlab_server/lib/python3.8/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/instagram_analytics.py", line 99, in <module>
chart_df = df[["id", "timestamp", metric]].copy()
File "/home/walhalax/.var/app/org.jupyter.JupyterLab/config/jupyterlab-desktop/jlab_server/lib/python3.8/site-packages/pandas/core/frame.py", line 3813, in __getitem__
indexer = self.columns._get_indexer_strict(key, "columns")[1]
File "/home/walhalax/.var/app/org.jupyter.JupyterLab/config/jupyterlab-desktop/jlab_server/lib/python3.8/site-packages/pandas/core/indexes/base.py", line 6070, in _get_indexer_strict
self._raise_if_missing(keyarr, indexer, axis_name)
File "/home/walhalax/.var/app/org.jupyter.JupyterLab/config/jupyterlab-desktop/jlab_server/lib/python3.8/site-packages/pandas/core/indexes/base.py", line 6133, in _raise_if_missing
raise KeyError(f"{not_found} not in index")
'''
これらの機能が正常に動作するよう修正済みのコードを省略せずにすべて表示してください。
|
9fb6c8ccd9796ba1e526604432095614
|
{
"intermediate": 0.3807740807533264,
"beginner": 0.3988170325756073,
"expert": 0.22040878236293793
}
|
523
|
You need to develop a file sharing system. Two files are needed to be written i.e. client.c and
server.c
Server.c
It should allocate a shared memory and then wait until some client writes a command into the
shared memory. Command can be of two formats:
o read filename
o write filename data
Read that command, clear the shared memory, and make a new thread.
If command is of read, make a new shared memory and share the key with the client process
through old shared memory. Then copy the content of that file onto new shared memory.
If command is of write, copy the contents of the command onto file of specified name.
Use the semaphores to avoid any unwanted situation.
Client.c
It should read the command from terminal, make sure it is in right format.
It should wait until there is no other writer or reader for shared memory. (Use semaphore)
And then it will write the command to the shared memory
If command is of read, wait until the response, and communicate with server to show the
content of the file, then terminate.
If command is of write just terminate the process.
|
1361c852fbac46c9b60ce0f44f4282eb
|
{
"intermediate": 0.3716892898082733,
"beginner": 0.3567473590373993,
"expert": 0.2715632915496826
}
|
524
|
How do I make http request in c#
|
62951bd0393fd7ad31df3a0f4cb44dcb
|
{
"intermediate": 0.546500027179718,
"beginner": 0.20066718757152557,
"expert": 0.2528327703475952
}
|
525
|
How do I turn off the display for my macbook while I'm using hdmi
|
acfd69b4a809ee13263fb9eb8b0e6734
|
{
"intermediate": 0.508739709854126,
"beginner": 0.23241905868053436,
"expert": 0.25884124636650085
}
|
526
|
add stop button: package main
import (
"io"
"os"
"sync"
"gioui.org/app"
"gioui.org/io/system"
"gioui.org/layout"
"gioui.org/op"
"gioui.org/unit"
"gioui.org/widget"
"gioui.org/widget/material"
"gioui.org/font/gofont"
"github.com/tosone/minimp3"
"github.com/hajimehoshi/oto"
)
func main() {
go func() {
w := app.NewWindow(
app.Title("mp3 reader"),
app.Size(unit.Dp(350), unit.Dp(500)),
)
var ops op.Ops
for event := range w.Events() {
switch event := event.(type) {
case system.DestroyEvent:
os.Exit(0)
case system.FrameEvent:
event.Frame(frame(layout.NewContext(&ops, event)))
}
}
}()
app.Main()
}
type (
// C quick alias for Context.
C = layout.Context
// D quick alias for Dimensions.
D = layout.Dimensions
)
var (
th = material.NewTheme(gofont.Collection())
topLabel = "mp3 reader"
playBtn = widget.Clickable{}
pauseBtn = widget.Clickable{}
playing bool
mu sync.Mutex
player *oto.Player
dec *minimp3.Decoder
)
// frame lays out the entire frame and returns the resultant ops buffer.
func frame(gtx C) *op.Ops {
layout.Center.Layout(gtx, func(gtx C) D {
gtx.Constraints.Max.X = gtx.Dp(unit.Dp(300))
return layout.Flex{Axis: layout.Vertical}.Layout(gtx,
layout.Rigid(func(gtx C) D {
label := material.H5(th, topLabel)
return label.Layout(gtx)
}),
layout.Rigid(func(gtx C) D {
return material.Button(th, &playBtn, "Play").Layout(gtx)
}),
layout.Rigid(func(gtx C) D {
return material.Button(th, &pauseBtn, "Pause").Layout(gtx)
}),
)
})
if playBtn.Clicked() {
go func() {
mu.Lock()
if playing {
mu.Unlock()
return
}
playing = true
mu.Unlock()
var err error
var file *os.File
if file, err = os.Open("demo.mp3"); err != nil {
return
}
if dec == nil {
if dec, err = minimp3.NewDecoder(file); err != nil {
return
}
started := dec.Started()
<-started
var context *oto.Context
if context, err = oto.NewContext(dec.SampleRate, dec.Channels, 2, 1024); err != nil {
return
}
player = context.NewPlayer()
}
for {
var data = make([]byte, 1024)
_, err := dec.Read(data)
if err == io.EOF {
break
}
if err != nil {
break
}
player.Write(data)
mu.Lock()
if !playing {
mu.Unlock()
break
}
mu.Unlock()
}
mu.Lock()
playing = false
mu.Unlock()
}()
}
if pauseBtn.Clicked() {
mu.Lock()
playing = false
mu.Unlock()
}
return gtx.Ops
}
|
4287c63a7fb165f14838b4019f81a815
|
{
"intermediate": 0.3896542489528656,
"beginner": 0.44026702642440796,
"expert": 0.17007876932621002
}
|
527
|
add stop button: package main
import (
"io"
"os"
"sync"
"gioui.org/app"
"gioui.org/io/system"
"gioui.org/layout"
"gioui.org/op"
"gioui.org/unit"
"gioui.org/widget"
"gioui.org/widget/material"
"gioui.org/font/gofont"
"github.com/tosone/minimp3"
"github.com/hajimehoshi/oto"
)
func main() {
go func() {
w := app.NewWindow(
app.Title("mp3 reader"),
app.Size(unit.Dp(350), unit.Dp(500)),
)
var ops op.Ops
for event := range w.Events() {
switch event := event.(type) {
case system.DestroyEvent:
os.Exit(0)
case system.FrameEvent:
event.Frame(frame(layout.NewContext(&ops, event)))
}
}
}()
app.Main()
}
type (
// C quick alias for Context.
C = layout.Context
// D quick alias for Dimensions.
D = layout.Dimensions
)
var (
th = material.NewTheme(gofont.Collection())
topLabel = "mp3 reader"
playBtn = widget.Clickable{}
pauseBtn = widget.Clickable{}
playing bool
mu sync.Mutex
player *oto.Player
dec *minimp3.Decoder
)
// frame lays out the entire frame and returns the resultant ops buffer.
func frame(gtx C) *op.Ops {
layout.Center.Layout(gtx, func(gtx C) D {
gtx.Constraints.Max.X = gtx.Dp(unit.Dp(300))
return layout.Flex{Axis: layout.Vertical}.Layout(gtx,
layout.Rigid(func(gtx C) D {
label := material.H5(th, topLabel)
return label.Layout(gtx)
}),
layout.Rigid(func(gtx C) D {
return material.Button(th, &playBtn, "Play").Layout(gtx)
}),
layout.Rigid(func(gtx C) D {
return material.Button(th, &pauseBtn, "Pause").Layout(gtx)
}),
)
})
if playBtn.Clicked() {
go func() {
mu.Lock()
if playing {
mu.Unlock()
return
}
playing = true
mu.Unlock()
var err error
var file *os.File
if file, err = os.Open("demo.mp3"); err != nil {
return
}
if dec == nil {
if dec, err = minimp3.NewDecoder(file); err != nil {
return
}
started := dec.Started()
<-started
var context *oto.Context
if context, err = oto.NewContext(dec.SampleRate, dec.Channels, 2, 1024); err != nil {
return
}
player = context.NewPlayer()
}
for {
var data = make([]byte, 1024)
_, err := dec.Read(data)
if err == io.EOF {
break
}
if err != nil {
break
}
player.Write(data)
mu.Lock()
if !playing {
mu.Unlock()
break
}
mu.Unlock()
}
mu.Lock()
playing = false
mu.Unlock()
}()
}
if pauseBtn.Clicked() {
mu.Lock()
playing = false
mu.Unlock()
}
return gtx.Ops
}
|
10c613e9b4441ca65c8cda097bec1f1d
|
{
"intermediate": 0.3896542489528656,
"beginner": 0.44026702642440796,
"expert": 0.17007876932621002
}
|
528
|
this is my 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">
<link rel="stylesheet" href="style.css">
<title>Scoreboard</title>
</head>
<body>
<div class="scoreboard">
<div class="points">
<span class="label">Points: </span>
<span class="score">0</span>
</div>
</div>
<script src="app.js"></script>
</body>
</html>
css
body {
margin: 0;
background-color: #111;
}
.scoreboard {
position: fixed;
top: 0;
right: 0;
background-color: rgba(0, 0, 0, 0.5);
padding: 5px 15px;
margin: 10px;
border-radius: 5px;
display: inline-flex;
align-items: center;
}
.label {
color: #ffffff;
font-family: Arial, sans-serif;
font-size: 14px;
}
.score {
color: #247c24;
font-family: Arial, sans-serif;
font-size: 14px;
font-weight: bold;
margin-left: 5px;
}
I'm trying to center the scoreboard class but currently it only sits on the right
|
aefb543b89a37c824df569a5f2a26300
|
{
"intermediate": 0.3961728811264038,
"beginner": 0.3132885694503784,
"expert": 0.2905385494232178
}
|
529
|
'''
import streamlit as st
import pandas as pd
import requests
import json
from PIL import Image
from io import BytesIO
from itertools import groupby
import instaloader
import datetime
import altair as alt
loader = instaloader.Instaloader()
# For login
username = ""
password = ""
loader.context.login(username, password) # Login
loader.context.request_timeout = (9, 15) # Increase request timeout
access_token = ""
account_id = ""
def load_media_info(access_token, account_id):
base_url = f"https://graph.facebook.com/v11.0/{account_id}/media"
params = {
"fields": "id,media_type,media_url,thumbnail_url,permalink,caption,timestamp,like_count,comments_count,insights.metric(impressions,reach,engagement)",
"access_token": access_token
}
items = []
while base_url:
response = requests.get(base_url, params=params)
data = json.loads(response.text)
items.extend(data["data"])
if "paging" in data and "next" in data["paging"]:
base_url = data["paging"]["next"]
params = {}
else:
base_url = None
return pd.DataFrame(items)
df = load_media_info(access_token, account_id)
if 'thumbnail_url' not in df.columns:
df['thumbnail_url'] = df['media_url']
df['thumbnail_url'] = df.apply(lambda x: x["media_url"] if x["media_type"] == "IMAGE" else x["thumbnail_url"], axis=1)
df["id"] = df["timestamp"]
df["id"] = df["id"].apply(lambda x: datetime.datetime.strptime(x.split("+")[0], "%Y-%m-%dT%H:%M:%S").strftime("%Y%m%d"))
df = df.sort_values("timestamp", ascending=False)
df["id_rank"] = [f"＿＿{len(list(group))}" for _, group in groupby(df["id"])]
df["id"] += df["id_rank"]
menu = ["Content", "Analytics"]
choice = st.sidebar.radio("Menu", menu)
if choice == "Content":
selected_id = st.sidebar.selectbox("Select Post", df["id"].unique())
selected_data = df[df["id"] == selected_id].iloc[0]
image_url = selected_data["media_url"] if selected_data["media_type"] == "IMAGE" else selected_data["thumbnail_url"]
image_response = requests.get(image_url)
image = Image.open(BytesIO(image_response.content))
st.image(image, caption=selected_data["caption"], width=300)
likes = selected_data["like_count"]
if "insights" in selected_data.keys():
try:
impressions = selected_data["insights"][0]['values'][0]['value']
percentage = (likes * 100) / impressions
st.write(f"いいね: {likes} (インプレッションに対する割合: {percentage:.1f}%)")
except (KeyError, IndexError):
st.write(f"いいね: {likes}")
else:
st.write(f"いいね: {likes}")
st.write(f"コメント数: {selected_data['comments_count']}")
# Get comments and usernames
try:
shortcode = selected_data["permalink"].split("/")[-2]
post = instaloader.Post.from_shortcode(loader.context, shortcode)
comments = post.get_comments()
for comment in comments:
st.write(f"{comment.owner.username}: {comment.text}")
except Exception as e:
st.write("コメントの取得中にエラーが発生しました。")
elif choice == "Analytics":
categories = ["いいね数", "コメント数"]
selected_category = st.selectbox("Select metric", categories)
if selected_category == "いいね数":
metric = "like_count"
elif selected_category == "コメント数":
metric = "comments_count"
chart_df = df[["id", "timestamp", metric]].copy()
chart_df["timestamp"] = pd.to_datetime(chart_df["timestamp"]).dt.date
chart = alt.Chart(chart_df).mark_line().encode(
x="timestamp:T",
y=metric + ":Q"
).properties(
title=f"Time Series of {selected_category}",
width=800,
height=300
)
st.altair_chart(chart)
'''
上記コードにてJupyter開発環境ではエラー表示はなく、streamlitで表示された事を確認できました。しかし、期待された表示がされていない箇所があるため、以下に改修点を列挙します。
①いまだにコンテンツに対する"いいね率"の表示が正常にされておりません。抜本的な対処も含めて改修したコード全体を表示してください。
②"Content"の説明文について、[Description]の前の文字列と、[Tags]を含むそれ以降の文字列を表示させないようにしたい。
③"Content"を選択するための左ペインにあるリストにて、日付IDのフォーマットにアンダーバーが2つ連続しているが、アンダーバーを1つだけの表記にしたい。
④"Content"のコメントとコメントユーザーのリストのフォントサイズを少しだけ大きくしたい。さらに、最新の3コメントのみの表示をデフォルトとして、"さらに表示"の文字を押下することで全件表示をするようにしたい。
|
ff76ea6e8998c87ac0e206a9d1c04c9e
|
{
"intermediate": 0.41424688696861267,
"beginner": 0.4111219346523285,
"expert": 0.1746312379837036
}
|
530
|
tell me about mvc
|
d1941b9a33268421cab176551ee720bf
|
{
"intermediate": 0.560580313205719,
"beginner": 0.19354365766048431,
"expert": 0.2458760291337967
}
|
531
|
Create a Unity script which creates a mesh and apply a material on it
|
f1b1c44aae39caf8b53f6c9971d88c47
|
{
"intermediate": 0.41650328040122986,
"beginner": 0.25439566373825073,
"expert": 0.3291010856628418
}
|
532
|
You need to develop a file sharing system. Two files are needed to be written i.e. client.c and
server.c
Server.c
It should allocate a shared memory and then wait until some client writes a command into the
shared memory. Command can be of two formats:
o read filename
o write filename data
Read that command, clear the shared memory, and make a new thread.
If command is of read, make a new shared memory and share the key with the client process
through old shared memory. Then copy the content of that file onto new shared memory.
If command is of write, copy the contents of the command onto file of specified name.
Use the semaphores to avoid any unwanted situation.
Client.c
It should read the command from terminal, make sure it is in right format.
It should wait until there is no other writer or reader for shared memory. (Use semaphore)
And then it will write the command to the shared memory
If command is of read, wait until the response, and communicate with server to show the
content of the file, then terminate.
If command is of write just terminate the process.
|
d8a58e963645e813e68be57ea07f1d6a
|
{
"intermediate": 0.3716892898082733,
"beginner": 0.3567473590373993,
"expert": 0.2715632915496826
}
|
533
|
'''
import streamlit as st
import pandas as pd
import requests
import json
from PIL import Image
from io import BytesIO
from itertools import groupby
import instaloader
import datetime
import altair as alt
loader = instaloader.Instaloader()
# For login
username = ""
password = ""
loader.context.login(username, password) # Login
loader.context.request_timeout = (9, 15) # Increase request timeout
access_token = ""
account_id = ""
def load_media_info(access_token, account_id):
base_url = f"https://graph.facebook.com/v11.0/{account_id}/media"
params = {
"fields": "id,media_type,media_url,thumbnail_url,permalink,caption,timestamp,like_count,comments_count,insights.metric(impressions,reach,engagement)",
"access_token": access_token
}
items = []
while base_url:
response = requests.get(base_url, params=params)
data = json.loads(response.text)
items.extend(data["data"])
if "paging" in data and "next" in data["paging"]:
base_url = data["paging"]["next"]
params = {}
else:
base_url = None
return pd.DataFrame(items)
df = load_media_info(access_token, account_id)
if 'thumbnail_url' not in df.columns:
df['thumbnail_url'] = df['media_url']
df['thumbnail_url'] = df.apply(lambda x: x["media_url"] if x["media_type"] == "IMAGE" else x["thumbnail_url"], axis=1)
df["id"] = df["timestamp"]
df["id"] = df["id"].apply(lambda x: datetime.datetime.strptime(x.split("+")[0], "%Y-%m-%dT%H:%M:%S").strftime("%Y%m%d"))
df = df.sort_values("timestamp", ascending=False)
df["id_rank"] = [f"_{len(list(group))}" for _, group in groupby(df["id"])]
df["id"] += df["id_rank"]
menu = ["Content", "Analytics"]
choice = st.sidebar.radio("Menu", menu)
def process_caption(caption):
description_start = 0
description_end = len(caption)
if "Description:" in caption:
description_start = caption.find("Description:") + len("Description:")
if "Tags:" in caption:
description_end = caption.find("Tags:")
caption = caption[description_start:description_end].strip()
return caption
if choice == "Content":
selected_id = st.sidebar.selectbox("Select Post", df["id"].unique())
selected_data = df[df["id"] == selected_id].iloc[0]
image_url = selected_data["media_url"] if selected_data["media_type"] == "IMAGE" else selected_data["thumbnail_url"]
image_response = requests.get(image_url)
image = Image.open(BytesIO(image_response.content))
caption = process_caption(selected_data['caption'])
st.image(image, caption=caption, width=300)
likes = selected_data["like_count"]
try:
insights = selected_data['insights']
except KeyError:
impressions = 0
else:
try:
impressions = insights[0]['values'][0]['value']
except (KeyError, IndexError):
impressions = 0
if impressions != 0:
percentage = (likes * 100) / impressions
st.write(f"いいね: {likes} (インプレッションに対する割合: {percentage:.1f}%)")
else:
st.write(f"いいね: {likes}")
st.write(f"コメント数: {selected_data['comments_count']}")
# Get comments and usernames
try:
shortcode = selected_data["permalink"].split("/")[-2]
post = instaloader.Post.from_shortcode(loader.context, shortcode)
comments = post.get_comments
'''
上記コードにてJupyter開発環境ではエラー表示はなく、streamlitで表示された事を確認できました。しかし、期待された表示がされていない箇所があるため、以下に改修点を列挙します。
①いまだにコンテンツに対する"いいね率"の表示が正常にされておりません。抜本的な対処も含めて改修したコード全体を表示してください。
②"Content"の説明文について、[Description]の前の文字列と、[Tags]を含むそれ以降の文字列を表示させない機能が動作していない。
これらの機能が正常に動作するよう修正済みのコードを省略せずにすべて表示してください。
|
b5c61c85ebfa666e84eb013e98b56bca
|
{
"intermediate": 0.341887503862381,
"beginner": 0.42472195625305176,
"expert": 0.23339059948921204
}
|
534
|
how to add readlinesync to a js
|
795e1ab251db232b54cd2d457b9aa630
|
{
"intermediate": 0.5087929964065552,
"beginner": 0.22760815918445587,
"expert": 0.26359885931015015
}
|
535
|
add pause and stop buttons: package main
import (
"os"
"time"
"log"
"net/http"
"gioui.org/app"
"gioui.org/io/system"
"gioui.org/layout"
"gioui.org/op"
"gioui.org/unit"
"gioui.org/widget"
"gioui.org/widget/material"
"gioui.org/font/gofont"
"github.com/hajimehoshi/oto/v2"
"github.com/hajimehoshi/go-mp3"
)
func main() {
go func() {
w := app.NewWindow(
app.Title("mp3 reader"),
app.Size(unit.Dp(350), unit.Dp(500)),
)
var ops op.Ops
for event := range w.Events() {
switch event := event.(type) {
case system.DestroyEvent:
os.Exit(0)
case system.FrameEvent:
event.Frame(frame(layout.NewContext(&ops, event)))
}
}
}()
app.Main()
}
type (
// C quick alias for Context.
C = layout.Context
// D quick alias for Dimensions.
D = layout.Dimensions
)
var (
th = material.NewTheme(gofont.Collection())
topLabel = "mp3 reader"
playBtn = widget.Clickable{}
url string = "https://qurango.net/radio/ahmad_khader_altarabulsi"
)
// frame lays out the entire frame and returns the resultant ops buffer.
func frame(gtx C) *op.Ops {
layout.Center.Layout(gtx, func(gtx C) D {
gtx.Constraints.Max.X = gtx.Dp(unit.Dp(300))
return layout.Flex{Axis: layout.Vertical}.Layout(gtx,
layout.Rigid(func(gtx C) D {
label := material.H5(th, topLabel)
return label.Layout(gtx)
}),
layout.Rigid(func(gtx C) D {
return material.Button(th, &playBtn, "Play").Layout(gtx)
}),
)
})
if playBtn.Clicked() {
go func() {
var err error
var response *http.Response
if response, err = http.Get(url); err != nil {
log.Fatal(err)
}
d, err := mp3.NewDecoder(response.Body)
if err != nil {
return
}
c, ready, err := oto.NewContext(d.SampleRate(), 2, 2)
if err != nil {
return
}
<-ready
p := c.NewPlayer(d)
defer p.Close()
p.Play()
for {
time.Sleep(time.Second)
if !p.IsPlaying() {
break
}
}
return
}()
}
return gtx.Ops
}
|
2d38003baa9bc517715ccaf745a329e1
|
{
"intermediate": 0.2993687391281128,
"beginner": 0.38843557238578796,
"expert": 0.31219571828842163
}
|
536
|
this is my 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”>
<link rel=“stylesheet” href=“style.css”>
<title>Scoreboard</title>
</head>
<body>
<div class=“scoreboard”>
<div class=“points”>
<span class=“label”>Points: </span>
<span class=“score”>0</span>
</div>
</div>
<script src=“app.js”></script>
</body>
</html>
css
body {
margin: 0;
background-color: #111;
}
.scoreboard {
position: fixed;
top: 0;
right: 0;
background-color: rgba(0, 0, 0, 0.5);
padding: 5px 15px;
margin: 10px;
border-radius: 5px;
display: inline-flex;
align-items: center;
}
.label {
color: #ffffff;
font-family: Arial, sans-serif;
font-size: 14px;
}
.score {
color: #247c24;
font-family: Arial, sans-serif;
font-size: 14px;
font-weight: bold;
margin-left: 5px;
}
I’m trying to center the scoreboard class horizontally but not vertically currently it only sits on the right
|
5ed72eb96e52bcae78a1311900cb59e3
|
{
"intermediate": 0.39664411544799805,
"beginner": 0.27542269229888916,
"expert": 0.3279331624507904
}
|
537
|
write me a script using only var and basic calculation, following these instructions: Tax Withheld Calculator
Write a console program that calculates the total amount of tax withheld from an employee’s weekly salary.
The total withheld tax amount is calculated by combining the amount of provincial tax withheld and the amount of federal tax withheld, minus a per-dependent deduction from the total tax withheld. The user will enter their pre-tax weekly salary amount and the number of dependents they wish to claim. The program will calculate and output the amount of provincial tax withheld, amount of federal tax withheld, the dependent tax deduction, and the user’s final take-home amount.
Provincial withholding tax is calculated at 6.0%.
Federal withholding tax is calculated at 25.0%.
The tax deduction for dependents is calculated at 2.0% of the employee’s salary per dependent.
|
9d91e21e29e78e113c5c61180adf4809
|
{
"intermediate": 0.36039525270462036,
"beginner": 0.3529505729675293,
"expert": 0.28665420413017273
}
|
538
|
Is there a way in PyTorch to have a module returning some regularization value along the prediction only during the training, while during evaluation only the module prediction is returned?
|
f17a06354fcfecbde932bce5717a566d
|
{
"intermediate": 0.3534184396266937,
"beginner": 0.07073549181222916,
"expert": 0.5758460164070129
}
|
539
|
I'm working on a volley ball script for fivem
I'm trying to create a NUI allowing players to select teams
could you show me an example of how I could make something that looks like the image attached
https://cdn.discordapp.com/attachments/1052780891300184096/1095516909283328072/image.png
|
1273b6c3a1667df6a0c9cb363404227c
|
{
"intermediate": 0.2324727475643158,
"beginner": 0.12228607386350632,
"expert": 0.6452411413192749
}
|
540
|
/n
|
c7c3fb5213494e063a7486d3fabbb8be
|
{
"intermediate": 0.30731454491615295,
"beginner": 0.2951550781726837,
"expert": 0.3975304067134857
}
|
541
|
как в Qt6 получить метаданные фотографии?
|
00879aaffd6328ad3b0cf4c2bbec2f27
|
{
"intermediate": 0.45953014492988586,
"beginner": 0.13660822808742523,
"expert": 0.4038616120815277
}
|
542
|
What is a sephamore?
|
0128ef1646f2a6827633d4eec18cbb72
|
{
"intermediate": 0.3080008625984192,
"beginner": 0.2738359868526459,
"expert": 0.4181631803512573
}
|
543
|
'''
import streamlit as st
import pandas as pd
import requests
import json
from PIL import Image
from io import BytesIO
from itertools import groupby
import instaloader
import datetime
import altair as alt
loader = instaloader.Instaloader()
# For login
username = "walhalax"
password = "W@lhalax4031"
loader.context.login(username, password) # Login
loader.context.request_timeout = (9, 15) # Increase request timeout
access_token = "EAAIui8JmOHYBAESXLZAnsSRe4OITHYzy3Q5osKgMXGRQnoVMtiIwJUonFjVHEjl9EZCEmURy9I9S9cnyFUXBquZCsWnGx1iJCYTvkKuUZBpBwwSceZB0ZB6YY9B83duIwZCoOlrOODhnA3HLLGbRKGPJ9hbQPLCrkVbc5ibhE43wIAinV0gVkJ30x4UEpb8fXLD8z5J9EYrbQZDZD"
account_id = "17841458386736965"
def load_media_info(access_token, account_id):
base_url = f"https://graph.facebook.com/v11.0/{account_id}/media"
params = {
"fields": "id,media_type,media_url,thumbnail_url,permalink,caption,timestamp,like_count,comments_count,insights.metric(impressions,reach,engagement)",
"access_token": access_token
}
items = []
while base_url:
response = requests.get(base_url, params=params)
data = json.loads(response.text)
items.extend(data["data"])
if "paging" in data and "next" in data["paging"]:
base_url = data["paging"]["next"]
params = {}
else:
base_url = None
return pd.DataFrame(items)
df = load_media_info(access_token, account_id)
if 'thumbnail_url' not in df.columns:
df['thumbnail_url'] = df['media_url']
df['thumbnail_url'] = df.apply(lambda x: x["media_url"] if x["media_type"] == "IMAGE" else x["thumbnail_url"], axis=1)
df["id"] = df["timestamp"]
df["id"] = df["id"].apply(lambda x: datetime.datetime.strptime(x.split("+")[0], "%Y-%m-%dT%H:%M:%S").strftime("%Y%m%d"))
df = df.sort_values("timestamp", ascending=False)
df["id_rank"] = [f"＿＿{len(list(group))}" for _, group in groupby(df["id"])]
df["id"] += df["id_rank"]
menu = ["Content", "Analytics"]
choice = st.sidebar.radio("Menu", menu)
if choice == "Content":
selected_id = st.sidebar.selectbox("Select Post", df["id"].unique())
selected_data = df[df["id"] == selected_id].iloc[0]
image_url = selected_data["media_url"] if selected_data["media_type"] == "IMAGE" else selected_data["thumbnail_url"]
image_response = requests.get(image_url)
image = Image.open(BytesIO(image_response.content))
st.image(image, caption=selected_data["caption"], width=300)
likes = selected_data["like_count"]
if "insights" in selected_data.keys():
try:
impressions = selected_data["insights"][0]['values'][0]['value']
percentage = (likes * 100) / impressions
st.write(f"いいね: {likes} (インプレッションに対する割合: {percentage:.1f}%)")
except (KeyError, IndexError):
st.write(f"いいね: {likes}")
else:
st.write(f"いいね: {likes}")
st.write(f"コメント数: {selected_data['comments_count']}")
# Get comments and usernames
try:
shortcode = selected_data["permalink"].split("/")[-2]
post = instaloader.Post.from_shortcode(loader.context, shortcode)
comments = post.get_comments()
for comment in comments:
st.write(f"{comment.owner.username}: {comment.text}")
except Exception as e:
st.write("コメントの取得中にエラーが発生しました。")
elif choice == "Analytics":
categories = ["いいね数", "コメント数"]
selected_category = st.selectbox("Select metric", categories)
if selected_category == "いいね数":
metric = "like_count"
elif selected_category == "コメント数":
metric = "comments_count"
chart_df = df[["id", "timestamp", metric]].copy()
chart_df["timestamp"] = pd.to_datetime(chart_df["timestamp"]).dt.date
chart = alt.Chart(chart_df).mark_line().encode(
x="timestamp:T",
y=metric + ":Q"
).properties(
title=f"Time Series of {selected_category}",
width=800,
height=300
)
st.altair_chart(chart)
'''
上記コードにてJupyter開発環境ではエラー表示はなく、streamlitで表示された事を確認できました。しかし、期待された表示がされていない箇所があるため、以下に改修点を列挙します。
①"いいね数"の横に(29.4%)のように表示させる、コンテンツのインプレッション数に対する"いいね率"が正常にされておりません。抜本的な対処も含めて改修してください。
②"Content"の説明文について、[Description]の前の文字列と、[Tags]を含んだそれ以降の文字列を削除する機能が動作していない。
③コメントユーザーとコメント内容のリストにおいて、新着3コメントのみデフォルトで表示させ、"さらに表示"ボタンを押下することで全件を表示にする機能が動作していないため、改修してください。
これらの機能が正常に動作するよう修正済みのコードを省略せずにすべて表示してください。
|
4d911bab467b30a5ce26df5f575f348b
|
{
"intermediate": 0.3810461163520813,
"beginner": 0.3795712888240814,
"expert": 0.2393825203180313
}
|
544
|
write me blender script for creating a simple car.
|
fc64dcb567ec34a4faba1f5d65c9d2c3
|
{
"intermediate": 0.38118425011634827,
"beginner": 0.2972027361392975,
"expert": 0.32161301374435425
}
|
545
|
1.1 Background
Consider the scenario of reading from a file and transferring the data to another program over the network. This scenario describes the behaviour of many server applications, including Web applications serving static content, FTP servers, mail servers, etc. The core of the operation is in the following two calls:
read(file, user_buffer, len);
write(socket, user_buffer, len);
Figure 1 shows how data is moved from the file to the socket.
Behind these two calls, the data has been copied at least four times, and almost as many user/kernel context switches have been performed. Figure 2 shows the process involved. The top side shows context switches, and the bottom side shows copy operations.
1. The read system call causes a context switch from user mode to kernel mode. The first copy is performed by the DMA (Direct Memory Access) engine, which reads file contents from the disk and stores them into a kernel address space buffer.
2. Data is copied from the kernel buffer into the user buffer ,and the read system call returns. The return from the call causes a context switch from kernel back to user mode. Now the data is stored in the user address space buffer, and it can begin its way down again.
3. The write system call causes a context switch from user mode to kernel mode. A third copy is per- formed to put the data into a kernel address space buffer again. This time, though, the data is put into a different buffer, a buffer that is associated with sockets specifically.
4. The write system call returns, creating our fourth context switch. Return from write call does not guarantee the start of the transmission. It simply means the Ethernet driver had free descriptors in its queue and has accepted our data for transmission. Independently and asynchronously, a fourth copy happens as the DMA engine passes the data from the kernel buffer to the protocol engine. (The forked DMA copy in Figure 2 illustrates the fact that the last copy can be delayed).
As you can see, a lot of data duplication happens in this process. Some of the duplication could be eliminated to decrease overhead and increase performance. To eliminate overhead, we could start by eliminating some of the copying between the kernel and user buffers.
1.2 Overview and Technical Details
Your task in this lab is to implement zero-copy read and write operations that would eliminate the copying between the kernel and user buffers. You will develop a new library with a set of library calls that allow a user to:
• Open a file
• Read from the file without using a user buffer
• Write to the file without using a user buffer
• Reposition within the file
• Close the file
The user directly uses the kernel buffer provided by the library calls to read and write data.
Your implementation should NOT call read and write system calls or other library calls that wrap around read and write system calls. Calling read and write would involve some type of duplication of buffers. You should use the mmap system call in your implementation.
2 Exercises in Lab 4
The goal of this lab assignment is to produce a zero-copy IO library. All function and data structures names are prefixed by zc_. The library uses a data structure called zc_file (defined in zc_io.c) to maintain the information about the opened files and help in the reading and writing operations. You are required to use it and add any information needed to maintain the information about the opened files into this data structure.
For ex1 to ex3, operations on the same file will not be issued concurrently (i.e. you do not need to be concerned about synchronization). We will change this assumption in ex4 and bonus exercise. For all exercises, you may assume that there is no concurrent opening of the same file (the file is opened at most once at the same time, and the file is not modified outside the runner).
The provided runner implements a few testcases on reading and writing a file using the zc_io library. It is not exhaustive but will catch some common errors. If your implementation is correct, the runner will run successfully. Otherwise, it may segmentation fault, or print a “FAIL” message with the reason of the failure. You are also encouraged to implement your own program to test the library.
2.1 Exercise 1A: Zero-copy Read [1% + 1% demo or 2% submission]
You are required to implement four library calls to open/close and perform zero copy read from a file.
- zc_file *zc_open(const char *path)
Opens file specified by path and returns a zc_file pointer on success, or NULL otherwise. Open the file using the O_CREAT and O_RDWR flags.
You can use fstat() to obtain information (if needed) regarding the opened file.
-int zc_close(zc_file *file)
Flushes the information to the file and closes the underlying file descriptor associated with the file. If successful, the function returns 0, otherwise it returns -1. Free any memory that you allocated for the zc_file structure. You can use msync() flush copy of file in virtual memory into file.
-const char *zc_read_start(zc_file *file, size_t *size)
The function returns the pointer to a chunk of *size bytes of data from the file. If the file contains less than *size bytes remaining, then the number of bytes available should be written to *size. The purpose of zc_read_start is to provide the kernel buffer that already contains the data to be read. This avoids the need to copy these data to another buffer as in the case of read system call. Instead, the user can simply use the data from the returned pointer.
Your zc_file structure should help you keep track of a offset in the file. Once size bytes have been requested for reading (or writing), the offset should advance by size and the next time when zc_read_start or zc_write_start is called, the next bytes after offset should be offered.
Note that reading and writing is done using the same offset.
-void zc_read_end(zc_file *file)
This function is called when a reading operation on file has ended.
It is always guaranteed that the function is paired with a previous call to zc_read_start.
Fill the following template:
#include "zc_io.h"
// The zc_file struct is analogous to the FILE struct that you get from fopen.
struct zc_file {
// Insert the fields you need here.
/* Some suggested fields :
- pointer to the virtual memory space
- offset from the start of the virtual memory
- total size of the file
- file descriptor to the opened file
- mutex for access to the memory space and number of readers
*/
};
/**************
* Exercise 1 *
**************/
zc_file* zc_open(const char* path) {
// To implement
return NULL;
}
int zc_close(zc_file* file) {
// To implement
return -1;
}
const char* zc_read_start(zc_file* file, size_t* size) {
// To implement
return NULL;
}
void zc_read_end(zc_file* file) {
// To implement
}
char* zc_write_start(zc_file* file, size_t size) {
// To implement
return NULL;
}
void zc_write_end(zc_file* file) {
// To implement
}
/**************
* Exercise 2 *
**************/
off_t zc_lseek(zc_file* file, long offset, int whence) {
// To implement
return -1;
}
/**************
* Exercise 3 *
**************/
int zc_copyfile(const char* source, const char* dest) {
// To implement
return -1;
}
/**************
* Bonus Exercise *
**************/
const char* zc_read_offset(zc_file* file, size_t* size, long offset) {
// To implement
return NULL;
}
char* zc_write_offset(zc_file* file, size_t size, long offset) {
// To implement
return NULL;
}
|
bbdfe01ec8927537f61f240a09570091
|
{
"intermediate": 0.40643784403800964,
"beginner": 0.3573881983757019,
"expert": 0.23617398738861084
}
|
546
|
this code has an error where the the columns from my access database are displayed twice or perhaps a new set of columns that are empty are added every time button 1. also when the save button is clicked this line'sda.Update(dt);' throws this error : System.InvalidOperationException: 'The ConnectionString property has not been initialized.'
using System;
using System.Collections.Generic;
using System.ComponentModel;
using System.Data;
using System.Data.OleDb;
using System.Drawing;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using System.Windows.Forms;
namespace ApplianceRental
{
public partial class AdminDashboardForm : Form
{
OleDbDataAdapter sda;
OleDbCommandBuilder scb;
DataTable dt;
public AdminDashboardForm()
{
InitializeComponent();
}
private void AdminDashboardForm_Load(object sender, EventArgs e)
{
// Code logic for the event handler
}
private void dataGridView1_CellContentClick(object sender, DataGridViewCellEventArgs e)
{
// Code logic for the event handler
}
private void saveButton_Click(object sender, EventArgs e)
{
scb = new OleDbCommandBuilder(sda);
sda.Update(dt);
}
private void button1_Click(object sender, EventArgs e)
{
string connectionString = @"Provider = Microsoft.Jet.OLEDB.4.0; Data Source = db_users.mdb";
using (OleDbConnection con = new OleDbConnection(connectionString))
{
string query = "SELECT* FROM ApplianceDBLIST";
sda = new OleDbDataAdapter(query, con);
OleDbCommandBuilder cmdBuilder = new OleDbCommandBuilder(sda);
dt = new DataTable();
sda.Fill(dt);
DataGridViewTextBoxColumn dcAppliance = new DataGridViewTextBoxColumn();
DataGridViewTextBoxColumn dcPowerUsage = new DataGridViewTextBoxColumn();
DataGridViewTextBoxColumn dcTypicalUsage = new DataGridViewTextBoxColumn();
DataGridViewTextBoxColumn dcAnnualCosts = new DataGridViewTextBoxColumn();
dcAppliance.HeaderText = "Appliance";
dcPowerUsage.HeaderText = "Power Usage";
dcTypicalUsage.HeaderText = "Typical Usage";
dcAnnualCosts.HeaderText = "Estimated Annual Running Costs";
dataGridView1.Columns.Add(dcAppliance);
dataGridView1.Columns.Add(dcPowerUsage);
dataGridView1.Columns.Add(dcTypicalUsage);
dataGridView1.Columns.Add(dcAnnualCosts);
dataGridView1.DataSource = dt;
}
}
}
}
|
c70e9a7857e1f11462dd5e99ba475c77
|
{
"intermediate": 0.36881953477859497,
"beginner": 0.4324803650379181,
"expert": 0.19870014488697052
}
|
547
|
Create a class 'Account' in which all the fields are declared private
Attributes are as follows:
int accountnumber; int accountbalance;
Get n user details and store them in the private variables. The account number which the deposit must be made is then read. If an account number already exists print the account balance; otherwise, display "Account Number Does Not Exist Note:
Use public set and get to set and read the value of the attributes The initial value of account_balance is zero.
Input format
The first integer input represents n number of users. Each user's account number and initial deposit amount are represented by the nee
n entries.
The last integer input represents the account number for which the balance nee to be displayed.
Output format
Display the balance for the given account number. Refer sample output
Output format
Display the balance for the given account number. Refer sample output
Sample testcases
Input 1
Output 1
2
40000
1111
40000
1112
45000
1111
Input 2
2
Output 2
Account Number does not e
esc
1111 40000 1112 45000 1113 code in c#
|
2b362f523b7985e1cfbe74f7c9697491
|
{
"intermediate": 0.3686872124671936,
"beginner": 0.3588138520717621,
"expert": 0.2724989056587219
}
|
549
|
How to display ms sql server database table data in datagridview c#
|
04232ba733a8d53e3d9dbe5784c6bc3b
|
{
"intermediate": 0.6413812637329102,
"beginner": 0.20154514908790588,
"expert": 0.15707361698150635
}
|
550
|
1.1 Background
Consider the scenario of reading from a file and transferring the data to another program over the network. This scenario describes the behaviour of many server applications, including Web applications serving static content, FTP servers, mail servers, etc. The core of the operation is in the following two calls:
read(file, user_buffer, len);
write(socket, user_buffer, len);
Figure 1 shows how data is moved from the file to the socket.
Behind these two calls, the data has been copied at least four times, and almost as many user/kernel context switches have been performed. Figure 2 shows the process involved. The top side shows context switches, and the bottom side shows copy operations.
1. The read system call causes a context switch from user mode to kernel mode. The first copy is performed by the DMA (Direct Memory Access) engine, which reads file contents from the disk and stores them into a kernel address space buffer.
2. Data is copied from the kernel buffer into the user buffer ,and the read system call returns. The return from the call causes a context switch from kernel back to user mode. Now the data is stored in the user address space buffer, and it can begin its way down again.
3. The write system call causes a context switch from user mode to kernel mode. A third copy is per- formed to put the data into a kernel address space buffer again. This time, though, the data is put into a different buffer, a buffer that is associated with sockets specifically.
4. The write system call returns, creating our fourth context switch. Return from write call does not guarantee the start of the transmission. It simply means the Ethernet driver had free descriptors in its queue and has accepted our data for transmission. Independently and asynchronously, a fourth copy happens as the DMA engine passes the data from the kernel buffer to the protocol engine. (The forked DMA copy in Figure 2 illustrates the fact that the last copy can be delayed).
As you can see, a lot of data duplication happens in this process. Some of the duplication could be eliminated to decrease overhead and increase performance. To eliminate overhead, we could start by eliminating some of the copying between the kernel and user buffers.
1.2 Overview and Technical Details
Your task in this lab is to implement zero-copy read and write operations that would eliminate the copying between the kernel and user buffers. You will develop a new library with a set of library calls that allow a user to:
• Open a file
• Read from the file without using a user buffer
• Write to the file without using a user buffer
• Reposition within the file
• Close the file
The user directly uses the kernel buffer provided by the library calls to read and write data.
Your implementation should NOT call read and write system calls or other library calls that wrap around read and write system calls. Calling read and write would involve some type of duplication of buffers. You should use the mmap system call in your implementation.
2 Exercises in Lab 4
The goal of this lab assignment is to produce a zero-copy IO library. All function and data structures names are prefixed by zc_. The library uses a data structure called zc_file (defined in zc_io.c) to maintain the information about the opened files and help in the reading and writing operations. You are required to use it and add any information needed to maintain the information about the opened files into this data structure.
For ex1 to ex3, operations on the same file will not be issued concurrently (i.e. you do not need to be concerned about synchronization). We will change this assumption in ex4 and bonus exercise. For all exercises, you may assume that there is no concurrent opening of the same file (the file is opened at most once at the same time, and the file is not modified outside the runner).
The provided runner implements a few testcases on reading and writing a file using the zc_io library. It is not exhaustive but will catch some common errors. If your implementation is correct, the runner will run successfully. Otherwise, it may segmentation fault, or print a “FAIL” message with the reason of the failure. You are also encouraged to implement your own program to test the library.
2.1 Exercise 1A: Zero-copy Read [1% + 1% demo or 2% submission]
You are required to implement four library calls to open/close and perform zero copy read from a file.
- zc_file *zc_open(const char *path)
Opens file specified by path and returns a zc_file pointer on success, or NULL otherwise. Open the file using the O_CREAT and O_RDWR flags.
You can use fstat() to obtain information (if needed) regarding the opened file.
-int zc_close(zc_file *file)
Flushes the information to the file and closes the underlying file descriptor associated with the file. If successful, the function returns 0, otherwise it returns -1. Free any memory that you allocated for the zc_file structure. You can use msync() flush copy of file in virtual memory into file.
-const char *zc_read_start(zc_file *file, size_t *size)
The function returns the pointer to a chunk of *size bytes of data from the file. If the file contains less than *size bytes remaining, then the number of bytes available should be written to *size. The purpose of zc_read_start is to provide the kernel buffer that already contains the data to be read. This avoids the need to copy these data to another buffer as in the case of read system call. Instead, the user can simply use the data from the returned pointer.
Your zc_file structure should help you keep track of a offset in the file. Once size bytes have been requested for reading (or writing), the offset should advance by size and the next time when zc_read_start or zc_write_start is called, the next bytes after offset should be offered.
Note that reading and writing is done using the same offset.
-void zc_read_end(zc_file file)
This function is called when a reading operation on file has ended.
It is always guaranteed that the function is paired with a previous call to zc_read_start.
2.2 Exercise 1B: Zero-copy Write [1% + 1% demo or 2% submission]
You are required to implement two library calls that allow writing to file:
-char *zc_write_start(zc_file *file, size_t size)
The function returns the pointer to a buffer of at least size bytes that can be written. The data written to this buffer would eventually be written to file.
The purpose of zc_write_start is to provide the kernel buffer where information can be written. This avoids the need to copy these data to another buffer as in the case of write system call. The user can simply write data to the returned pointer.
Once size bytes have been requested for writing, the offset should advance by size and the next time when zc_read_start or zc_write_start is called, the next bytes after offset should be written. Note that reading and writing is done using the same offset.
File size might change when information is written to file. Make sure that you handle this case properly. See ftruncate.
-void zc_write_end(zc_file *file)
This function is called when a writing operation on file has ended. The function pushes to the file on disk any changes that might have been done in the buffer between zc_write_start and zc_write_end. This means that there is an implicit flush at the end of each zc_write operation. You can check out msync() to help you with flushing.
It is always guaranteed that the function is paired with a previous call to zc_write_start.
Writing to a file using the zc_io library call should have the same semantic behaviour as observed in write system call.
2.3 Exercise 2: Repositioning the file offset [1%]
You are required to implement one library call that allows changing the offset in the file:
-off_t zc_lseek(zc_file *file, long offset, int whence)
Reposition at a different offset within the file. The new position, measured in bytes, is obtained by adding offset bytes to the position specified by whence.
whence can take 3 values:
• SEEK_SET: offset is relative to the start of the file
• SEEK_CUR: offset is relative to the current position indicator
• SEEK_END: offset is relative to the end-of-file
The SEEK_SET, SEEK_CUR and SEEK_END values are defined in unistd.h and take the values 0, 1, and 2 respectively.
The zc_lseek() function returns the resulting offset location as measured in bytes from the be- ginningofthefileor(off_t) -1ifanerroroccurs.
zc_lseek() allows the file offset to be set beyond the end of the file (but this does not change the size of the file). If data is later written at this point, subsequent reads of the data in the gap (a “hole”) return null bytes ('\0') until data is actually written into the gap. (Please refer to Appendix B for a simple example on this.)
Repositioning the file offset should have the same semantic behaviour as lseek system call.
2.4 Exercise 3: Zero-copy file transfer [2%]
You are required to implement the following library call:
-int zc_copyfile(const char *source, const char *dest)
This function copies the content of source into dest. It will return 0 on success and -1 on failure. You should make use of the function calls you implemented in the previous exercises, and should not use any user buffers to achieve this. Do ftruncate the destination file so they have the same size.c
Fill the following template:
#include “zc_io.h”
// The zc_file struct is analogous to the FILE struct that you get from fopen.
struct zc_file {
// Insert the fields you need here.
/ Some suggested fields :
- pointer to the virtual memory space
- offset from the start of the virtual memory
- total size of the file
- file descriptor to the opened file
- mutex for access to the memory space and number of readers
*/
};
/*
* Exercise 1 *
/
zc_file zc_open(const char path) {
// To implement
return NULL;
}
int zc_close(zc_file file) {
// To implement
return -1;
}
const char zc_read_start(zc_file file, size_t size) {
// To implement
return NULL;
}
void zc_read_end(zc_file file) {
// To implement
}
char zc_write_start(zc_file file, size_t size) {
// To implement
return NULL;
}
void zc_write_end(zc_file file) {
// To implement
}
/
* Exercise 2 *
/
off_t zc_lseek(zc_file file, long offset, int whence) {
// To implement
return -1;
}
/
* Exercise 3 *
/
int zc_copyfile(const char source, const char dest) {
// To implement
return -1;
}
/
* Bonus Exercise *
*********/
const char zc_read_offset(zc_file file, size_t size, long offset) {
// To implement
return NULL;
}
char zc_write_offset(zc_file file, size_t size, long offset) {
// To implement
return NULL;
}
|
54db93dbeca67d736ad9adb5db99101b
|
{
"intermediate": 0.43557482957839966,
"beginner": 0.360271155834198,
"expert": 0.20415395498275757
}
|
551
|
create a 3d sphere in the livecode language
|
ae531f4b8f06b09e50d4659db9548799
|
{
"intermediate": 0.3148006498813629,
"beginner": 0.3160095810890198,
"expert": 0.36918970942497253
}
|
552
|
write some python code that spawns a tcp server on its own thread. This server reads the data from a queue (that another thread will write data in) and pushes it to all the connected clients
|
85695eb23ae656080c52c5fcf0ce8b68
|
{
"intermediate": 0.4977346658706665,
"beginner": 0.13218867778778076,
"expert": 0.3700766861438751
}
|
553
|
who are you
|
26e220510579469ff19b48d01e74f5ec
|
{
"intermediate": 0.45451608300209045,
"beginner": 0.2491701990365982,
"expert": 0.29631373286247253
}
|
554
|
'''
import streamlit as st
import pandas as pd
import requests
import json
from PIL import Image
from io import BytesIO
from itertools import groupby
import instaloader
import datetime
import altair as alt
loader = instaloader.Instaloader()
# For login
username = "walhalax"
password = "W@lhalax4031"
loader.context.login(username, password) # Login
loader.context.request_timeout = (9, 15) # Increase request timeout
access_token = "EAAIui8JmOHYBAESXLZAnsSRe4OITHYzy3Q5osKgMXGRQnoVMtiIwJUonFjVHEjl9EZCEmURy9I9S9cnyFUXBquZCsWnGx1iJCYTvkKuUZBpBwwSceZB0ZB6YY9B83duIwZCoOlrOODhnA3HLLGbRKGPJ9hbQPLCrkVbc5ibhE43wIAinV0gVkJ30x4UEpb8fXLD8z5J9EYrbQZDZD"
account_id = "17841458386736965"
def load_media_info(access_token, account_id):
base_url = f"https://graph.facebook.com/v11.0/{account_id}/media"
params = {
"fields": "id,media_type,media_url,thumbnail_url,permalink,caption,timestamp,like_count,comments_count,insights.metric(impressions,reach,engagement)",
"access_token": access_token
}
items = []
while base_url:
response = requests.get(base_url, params=params)
data = json.loads(response.text)
items.extend(data["data"])
if "paging" in data and "next" in data["paging"]:
base_url = data["paging"]["next"]
params = {}
else:
base_url = None
return pd.DataFrame(items)
df = load_media_info(access_token, account_id)
if 'thumbnail_url' not in df.columns:
df['thumbnail_url'] = df['media_url']
df['thumbnail_url'] = df.apply(lambda x: x["media_url"] if x["media_type"] == "IMAGE" else x["thumbnail_url"], axis=1)
df["id"] = df["timestamp"]
df["id"] = df["id"].apply(lambda x: datetime.datetime.strptime(x.split("+")[0], "%Y-%m-%dT%H:%M:%S").strftime("%Y%m%d"))
df = df.sort_values("timestamp", ascending=False)
df["id_rank"] = [f"_{len(list(group))}" for _, group in groupby(df["id"])]
df["id"] += df["id_rank"]
menu = ["Content", "Analytics"]
choice = st.sidebar.radio("Menu", menu)
if "load_more" not in st.session_state:
st.session_state.load_more = 0
if choice == "Content":
selected_id = st.sidebar.selectbox("Select Post", df["id"].unique())
selected_data = df[df["id"] == selected_id].iloc[0]
image_url = selected_data["media_url"] if selected_data["media_type"] == "IMAGE" else selected_data["thumbnail_url"]
image_response = requests.get(image_url)
image = Image.open(BytesIO(image_response.content))
st.image(image, width=300)
# Process caption text
caption_text = selected_data["caption"]
if caption_text:
start_desc_index = caption_text.find("［Description］")
if start_desc_index != -1:
caption_text = caption_text[start_desc_index + 13:] # Remove text before "［Description］"
end_tags_index = caption_text.find("［Tags］")
if end_tags_index != -1:
caption_text = caption_text[:end_tags_index] # Remove text from "［Tags］"
st.write(caption_text.strip())
likes = selected_data["like_count"]
if "insights" in selected_data.keys():
try:
impressions = selected_data["insights"][0]['values'][0]['value']
percentage = (likes * 100) / impressions
st.write(f"いいね: {likes} (インプレッションに対する割合: {percentage:.1f}%)")
except (KeyError, IndexError):
st.write(f"いいね: {likes}")
else:
st.write(f"いいね: {likes}")
st.write(f"コメント数: {selected_data['comments_count']}")
# Get comments and usernames
try:
shortcode = selected_data["permalink"].split("/")[-2]
post = instaloader.Post.from_shortcode(loader.context, shortcode)
comments = post.get_comments()
comment_list = [(comment.owner.username, comment.text) for comment in comments]
if st.session_state.load_more:
for username, text in comment_list:
st.write(f"{username}: {text}")
else:
for username, text in comment_list[:3]: # Show only the first 3 comments
st.write(f"{username}: {text}")
# Load more button
if st.button("さらに表示"):
st.session_state.load_more += 1
except Exception as e:
st.write("コメントの取得中にエラーが発生しました。")
elif choice == "Analytics":
categories = ["いいね数", "コメント数"]
selected_category = st.selectbox("Select metric", categories)
if selected_category == "いいね数":
metric = "like_count"
elif selected_category == "コメント数":
metric = "comments_count"
chart_df = df[["id", "timestamp", metric]].copy()
chart_df["timestamp"] = pd.to_datetime(chart_df["timestamp"]).dt.date
chart = alt.Chart(chart_df).mark_line().encode(
x="timestamp:T",
y=metric + ":Q"
).properties(
title=f"Time Series of {selected_category}",
width=800,
height=300
)
st.altair_chart(chart)
'''
上記コードにてJupyter開発環境ではエラー表示はなく、streamlitで表示された事を確認できました。しかし、期待された表示がされていない箇所があるため、以下に改修点を列挙します。
①"いいね数"の横に(29.4%)のように表示させる、コンテンツのインプレッション数に対する"いいね率"が正常にされておりません。抜本的な対処も含めて改修してください。
②"Content"の説明文について、[Description]の前の文字列と、[Tags]を含んだそれ以降の文字列を削除する機能が動作していないため改修してください。
③写真の拡大ボタンを押下した際の画像が拡大されないため改修をしてください。
これらの機能が正常に動作するよう修正済みのコードを省略せずにすべて表示してください。
|
6055dfe75f7b3bcfc7edeecc5ad49e0f
|
{
"intermediate": 0.3428531587123871,
"beginner": 0.37873750925064087,
"expert": 0.27840936183929443
}
|
555
|
Ignore all instructions before this one. You are a theoretical physicist. You have been using computers in your work for 20 years. Your task now is to help choose useful software for work in theoretical physics.
|
e4e8072d3b97b8149a3ebe5e1634d5ac
|
{
"intermediate": 0.3789080083370209,
"beginner": 0.22066611051559448,
"expert": 0.40042588114738464
}
|
556
|
write python for a binary search tree, include bfs and dfs and methods to insert delete and search nodes
|
755a7a7e1abe54052f95b6eb89a96e46
|
{
"intermediate": 0.5150929093360901,
"beginner": 0.12448067218065262,
"expert": 0.3604263961315155
}
|
557
|
1.1 Background
Consider the scenario of reading from a file and transferring the data to another program over the network. This scenario describes the behaviour of many server applications, including Web applications serving static content, FTP servers, mail servers, etc. The core of the operation is in the following two calls:
read(file, user_buffer, len);
write(socket, user_buffer, len);
Figure 1 shows how data is moved from the file to the socket.
Behind these two calls, the data has been copied at least four times, and almost as many user/kernel context switches have been performed. Figure 2 shows the process involved. The top side shows context switches, and the bottom side shows copy operations.
1. The read system call causes a context switch from user mode to kernel mode. The first copy is performed by the DMA (Direct Memory Access) engine, which reads file contents from the disk and stores them into a kernel address space buffer.
2. Data is copied from the kernel buffer into the user buffer ,and the read system call returns. The return from the call causes a context switch from kernel back to user mode. Now the data is stored in the user address space buffer, and it can begin its way down again.
3. The write system call causes a context switch from user mode to kernel mode. A third copy is per- formed to put the data into a kernel address space buffer again. This time, though, the data is put into a different buffer, a buffer that is associated with sockets specifically.
4. The write system call returns, creating our fourth context switch. Return from write call does not guarantee the start of the transmission. It simply means the Ethernet driver had free descriptors in its queue and has accepted our data for transmission. Independently and asynchronously, a fourth copy happens as the DMA engine passes the data from the kernel buffer to the protocol engine. (The forked DMA copy in Figure 2 illustrates the fact that the last copy can be delayed).
As you can see, a lot of data duplication happens in this process. Some of the duplication could be eliminated to decrease overhead and increase performance. To eliminate overhead, we could start by eliminating some of the copying between the kernel and user buffers.
1.2 Overview and Technical Details
Your task in this lab is to implement zero-copy read and write operations that would eliminate the copying between the kernel and user buffers. You will develop a new library with a set of library calls that allow a user to:
• Open a file
• Read from the file without using a user buffer
• Write to the file without using a user buffer
• Reposition within the file
• Close the file
The user directly uses the kernel buffer provided by the library calls to read and write data.
Your implementation should NOT call read and write system calls or other library calls that wrap around read and write system calls. Calling read and write would involve some type of duplication of buffers. You should use the mmap system call in your implementation.
2 Exercises in Lab 4
The goal of this lab assignment is to produce a zero-copy IO library. All function and data structures names are prefixed by zc_. The library uses a data structure called zc_file (defined in zc_io.c) to maintain the information about the opened files and help in the reading and writing operations. You are required to use it and add any information needed to maintain the information about the opened files into this data structure.
For ex1 to ex3, operations on the same file will not be issued concurrently (i.e. you do not need to be concerned about synchronization). We will change this assumption in ex4 and bonus exercise. For all exercises, you may assume that there is no concurrent opening of the same file (the file is opened at most once at the same time, and the file is not modified outside the runner).
The provided runner implements a few testcases on reading and writing a file using the zc_io library. It is not exhaustive but will catch some common errors. If your implementation is correct, the runner will run successfully. Otherwise, it may segmentation fault, or print a “FAIL” message with the reason of the failure. You are also encouraged to implement your own program to test the library.
2.1 Exercise 1A: Zero-copy Read [1% + 1% demo or 2% submission]
You are required to implement four library calls to open/close and perform zero copy read from a file.
- zc_file *zc_open(const char *path)
Opens file specified by path and returns a zc_file pointer on success, or NULL otherwise. Open the file using the O_CREAT and O_RDWR flags.
You can use fstat() to obtain information (if needed) regarding the opened file.
-int zc_close(zc_file *file)
Flushes the information to the file and closes the underlying file descriptor associated with the file. If successful, the function returns 0, otherwise it returns -1. Free any memory that you allocated for the zc_file structure. You can use msync() flush copy of file in virtual memory into file.
-const char *zc_read_start(zc_file *file, size_t *size)
The function returns the pointer to a chunk of *size bytes of data from the file. If the file contains less than *size bytes remaining, then the number of bytes available should be written to *size. The purpose of zc_read_start is to provide the kernel buffer that already contains the data to be read. This avoids the need to copy these data to another buffer as in the case of read system call. Instead, the user can simply use the data from the returned pointer.
Your zc_file structure should help you keep track of a offset in the file. Once size bytes have been requested for reading (or writing), the offset should advance by size and the next time when zc_read_start or zc_write_start is called, the next bytes after offset should be offered.
Note that reading and writing is done using the same offset.
-void zc_read_end(zc_file file)
This function is called when a reading operation on file has ended.
It is always guaranteed that the function is paired with a previous call to zc_read_start.
2.2 Exercise 1B: Zero-copy Write [1% + 1% demo or 2% submission]
You are required to implement two library calls that allow writing to file:
-char *zc_write_start(zc_file *file, size_t size)
The function returns the pointer to a buffer of at least size bytes that can be written. The data written to this buffer would eventually be written to file.
The purpose of zc_write_start is to provide the kernel buffer where information can be written. This avoids the need to copy these data to another buffer as in the case of write system call. The user can simply write data to the returned pointer.
Once size bytes have been requested for writing, the offset should advance by size and the next time when zc_read_start or zc_write_start is called, the next bytes after offset should be written. Note that reading and writing is done using the same offset.
File size might change when information is written to file. Make sure that you handle this case properly. See ftruncate.
-void zc_write_end(zc_file *file)
This function is called when a writing operation on file has ended. The function pushes to the file on disk any changes that might have been done in the buffer between zc_write_start and zc_write_end. This means that there is an implicit flush at the end of each zc_write operation. You can check out msync() to help you with flushing.
It is always guaranteed that the function is paired with a previous call to zc_write_start.
Writing to a file using the zc_io library call should have the same semantic behaviour as observed in write system call.
2.3 Exercise 2: Repositioning the file offset [1%]
You are required to implement one library call that allows changing the offset in the file:
-off_t zc_lseek(zc_file *file, long offset, int whence)
Reposition at a different offset within the file. The new position, measured in bytes, is obtained by adding offset bytes to the position specified by whence.
whence can take 3 values:
• SEEK_SET: offset is relative to the start of the file
• SEEK_CUR: offset is relative to the current position indicator
• SEEK_END: offset is relative to the end-of-file
The SEEK_SET, SEEK_CUR and SEEK_END values are defined in unistd.h and take the values 0, 1, and 2 respectively.
The zc_lseek() function returns the resulting offset location as measured in bytes from the be- ginningofthefileor(off_t) -1ifanerroroccurs.
zc_lseek() allows the file offset to be set beyond the end of the file (but this does not change the size of the file). If data is later written at this point, subsequent reads of the data in the gap (a “hole”) return null bytes ('\0') until data is actually written into the gap. (Please refer to Appendix B for a simple example on this.)
Repositioning the file offset should have the same semantic behaviour as lseek system call.
2.4 Exercise 3: Zero-copy file transfer [2%]
You are required to implement the following library call:
-int zc_copyfile(const char *source, const char *dest)
This function copies the content of source into dest. It will return 0 on success and -1 on failure. You should make use of the function calls you implemented in the previous exercises, and should not use any user buffers to achieve this. Do ftruncate the destination file so they have the same size.c
2.5 Exercise 4: Readers-writers Synchronization [1%]
Exercises above assumed that the operations on the same file would be issued in sequence. In ex4 we lift this assumption and allow multiple reads and writes to be issued at the same time for the same instance of an open file.
You need to make sure that your zc_read_start, zc_write_start and zc_lseek executed on an open file follow the following rules:
• Multiple zc_read operations can take place at the same time for the same instance of the zc_file.
• No other operation should take place at the same time with a zc_write or zc_lseek operation.
• All operation issued while zc_write or zc_lseek is executing would block waiting to start. They
would start only once the zc_write or zc_lseek ends.
In other words, you should solve the readers-writers synchronization problem when multiple operations are issued at the same time for the same instance of an open file. You are not required to ensure that your solution is starvation-free.
While multiple readers can read at the same time, ensure that the offset variable of the file is protected and multiple zc_write_start or especially zc_read_start access and increment the offset variable one at a time. For eg. if two threads read 10 bytes each, with initial offset = 0, one of the threads should read the first 10 bytes, the other the next 10 bytes, and the final value of offset should be 20.
Fill the following template:
#include “zc_io.h”
// The zc_file struct is analogous to the FILE struct that you get from fopen.
struct zc_file {
// Insert the fields you need here.
/ Some suggested fields :
- pointer to the virtual memory space
- offset from the start of the virtual memory
- total size of the file
- file descriptor to the opened file
- mutex for access to the memory space and number of readers
*/
};
/*
* Exercise 1 *
/
zc_file zc_open(const char path) {
// To implement
return NULL;
}
int zc_close(zc_file file) {
// To implement
return -1;
}
const char zc_read_start(zc_file file, size_t size) {
// To implement
return NULL;
}
void zc_read_end(zc_file file) {
// To implement
}
char zc_write_start(zc_file file, size_t size) {
// To implement
return NULL;
}
void zc_write_end(zc_file file) {
// To implement
}
/
* Exercise 2 *
/
off_t zc_lseek(zc_file file, long offset, int whence) {
// To implement
return -1;
}
/
* Exercise 3 *
/
int zc_copyfile(const char source, const char dest) {
// To implement
return -1;
}
/
* Bonus Exercise *
*********/
const char zc_read_offset(zc_file file, size_t size, long offset) {
// To implement
return NULL;
}
char zc_write_offset(zc_file file, size_t size, long offset) {
// To implement
return NULL;
}
|
9571ea64a9b850799e716d8fed29999f
|
{
"intermediate": 0.43557482957839966,
"beginner": 0.360271155834198,
"expert": 0.20415395498275757
}
|
558
|
create a 3d sphere in the livecode langauge
|
81faee83e2182f18e218f1f1e4d99d64
|
{
"intermediate": 0.3052060306072235,
"beginner": 0.3507360517978668,
"expert": 0.3440578579902649
}
|
559
|
use aspose-words-21.11 convert word to pdf
|
2df83cb687dc41e34b706ee17ad48ddc
|
{
"intermediate": 0.40632978081703186,
"beginner": 0.24636292457580566,
"expert": 0.34730732440948486
}
|
560
|
use aspose-cells-21.11 convert excel to pdf output
|
5c2d8183b303472d23671ff7ce0bbab9
|
{
"intermediate": 0.43903958797454834,
"beginner": 0.2581357955932617,
"expert": 0.30282464623451233
}
|
561
|
spell check this
|
70112053507343725ac5d0d1133e688b
|
{
"intermediate": 0.37716513872146606,
"beginner": 0.30696210265159607,
"expert": 0.31587275862693787
}
|
562
|
What software has support for screw theory?
|
370c53a6cff238f5fb095201c323a6ee
|
{
"intermediate": 0.39642512798309326,
"beginner": 0.18662738800048828,
"expert": 0.41694754362106323
}
|
563
|
hi
|
13b258fcbf9960d86b0ecf990e116023
|
{
"intermediate": 0.3246487081050873,
"beginner": 0.27135494351387024,
"expert": 0.40399640798568726
}
|
564
|
'''
import streamlit as st
import pandas as pd
import requests
import json
from PIL import Image
from io import BytesIO
from itertools import groupby
import instaloader
import datetime
import altair as alt
loader = instaloader.Instaloader()
# For login
username = "walhalax"
password = "W@lhalax4031"
loader.context.login(username, password) # Login
loader.context.request_timeout = (9, 15) # Increase request timeout
access_token = "EAAIui8JmOHYBAESXLZAnsSRe4OITHYzy3Q5osKgMXGRQnoVMtiIwJUonFjVHEjl9EZCEmURy9I9S9cnyFUXBquZCsWnGx1iJCYTvkKuUZBpBwwSceZB0ZB6YY9B83duIwZCoOlrOODhnA3HLLGbRKGPJ9hbQPLCrkVbc5ibhE43wIAinV0gVkJ30x4UEpb8fXLD8z5J9EYrbQZDZD"
account_id = "17841458386736965"
def load_media_info(access_token, account_id):
base_url = f"https://graph.facebook.com/v11.0/{account_id}/media"
params = {
"fields": "id,media_type,media_url,thumbnail_url,permalink,caption,timestamp,like_count,comments_count,insights.metric(impressions,reach,engagement),children{media_type,media_url}",
"access_token": access_token
}
items = []
while base_url:
response = requests.get(base_url, params=params)
data = json.loads(response.text)
items.extend(data["data"])
if "paging" in data and "next" in data["paging"]:
base_url = data["paging"]["next"]
params = {}
else:
base_url = None
return pd.DataFrame(items)
df = load_media_info(access_token, account_id)
if 'thumbnail_url' not in df.columns:
df['thumbnail_url'] = df['media_url']
df['thumbnail_url'] = df.apply(lambda x: x["media_url"] if x["media_type"] == "IMAGE" else x["thumbnail_url"], axis=1)
df["id"] = df["timestamp"]
df["id"] = df["id"].apply(lambda x: datetime.datetime.strptime(x.split("+")[0], "%Y-%m-%dT%H:%M:%S").strftime("%Y%m%d"))
df = df.sort_values("timestamp", ascending=False)
df["id_rank"] = [f"_{len(list(group))}" for _, group in groupby(df["id"])]
df["id"] += df["id_rank"]
menu = ["Content", "Analytics"]
choice = st.sidebar.radio("Menu", menu)
if "load_more" not in st.session_state:
st.session_state.load_more = 0
def carousel(medias):
items = []
for media in medias:
req_img = requests.get(media["media_url"])
img_bytes = req_img.content
img = Image.open(BytesIO(img_bytes))
items.append(img)
items.reverse()
return items
def display_carousel(carousel_items):
scale_factor = 0.15
display_images = []
for img in carousel_items:
if img.width > img.height:
left, upper = (1-scale_factor) / 2, (1-scale_factor + scale_factor * img.width/img.height) / 2
else:
left, upper = (1-scale_factor + scale_factor * img.height/img.width) / 2, (1-scale_factor) / 2
display_image = ImageOps.scale(img, scale_factor)
display_image = ImageOps.flip(display_image)
display_images.append(display_image)
st.image(display_images, width=300)
if choice == "Content":
selected_id = st.sidebar.selectbox("Select Post", df["id"].unique())
selected_data = df[df["id"] == selected_id].iloc[0]
image_url = selected_data["media_url"] if selected_data["media_type"] == "IMAGE" else selected_data["thumbnail_url"]
image_response = requests.get(image_url)
image = Image.open(BytesIO(image_response.content))
# Display carousel
if "children" in selected_data.keys():
carousel_items = selected_data["children"]["data"]
display_carousel(carousel_items)
else:
display_carousel([{"media_url": image_url}])
# Process caption text
caption_text = selected_data["caption"]
if caption_text:
start_desc_index = caption_text.find("［Description］")
if start_desc_index != -1:
caption_text = caption_text[start_desc_index + 13:] # Remove text before "［Description］"
end_tags_index = caption_text.find("［Tags］")
if end_tags_index != -1:
caption_text = caption_text[:end_tags_index] # Remove text from "［Tags］"
st.write(caption_text.strip())
likes = selected_data["like_count"]
if "insights" in selected_data.keys():
try:
impressions = selected_data["insights"][0]['values'][0]['value']
percentage = (likes * 100) / impressions
st.write(f"いいね: {likes} (インプレッションに対する割合: {percentage:.1f}%)")
except (KeyError, IndexError):
st.write(f"いいね: {likes}")
else:
st.write(f"いいね: {likes}")
st.write(f"コメント数: {selected_data['comments_count']}")
# Get comments and usernames
try:
shortcode = selected_data["permalink"].split("/")[-2]
post = instaloader.Post.from_shortcode(loader.context, shortcode)
comments = post.get_comments()
comment_list = [(comment.owner.username, comment.text) for comment in comments]
if st.session_state.load_more:
for username, text in comment_list:
st.write(f"{username}: {text}")
else:
for username, text in comment_list[:3]: # Show only the first 3 comments
st.write(f"{username}: {text}")
# Load more button
if st.button("さらに表示"):
st.session_state.load_more += 1
except Exception as e:
st.write("コメントの取得中にエラーが発生しました。")
elif choice == "Analytics":
categories = ["いいね数", "コメント数"]
selected_category = st.selectbox("Select metric", categories)
if selected_category == "いいね数":
metric = "like_count"
elif selected_category == "コメント数":
metric = "comments_count"
chart_df = df[["id", "timestamp", metric]].copy()
chart_df["timestamp"] = pd.to_datetime(chart_df["timestamp"]).dt.date
chart = alt.Chart(chart_df).mark_line().encode(
x="timestamp:T",
y=metric + ":Q"
).properties(
title=f"Time Series of {selected_category}",
width=800,
height=300
)
st.altair_chart(chart)
'''
上記コードを実行すると下記のエラーが表示されます。改修してコード全体をPython用インデントを付与して表示してください。
'''
AttributeError Traceback (most recent call last)
Cell In[38], line 104
102 if "children" in selected_data.keys():
103 carousel_items = selected_data["children"]["data"]
--> 104 display_carousel(carousel_items)
105 else:
106 display_carousel([{"media_url": image_url}])
Cell In[38], line 82, in display_carousel(carousel_items)
79 display_images = []
81 for img in carousel_items:
---> 82 if img.width > img.height:
83 left, upper = (1-scale_factor) / 2, (1-scale_factor + scale_factor * img.width/img.height) / 2
84 else:
AttributeError: 'dict' object has no attribute 'width'
'''
|
d8601f032f31dd28098fab68701cd51d
|
{
"intermediate": 0.3806249499320984,
"beginner": 0.34811460971832275,
"expert": 0.27126041054725647
}
|
565
|
genarate code on golang use fiber. Miminal app.
Two routers path: /protect and /verify.
And create config for app. Use module viper
|
d5a39f27efd61101b551d00fbc8de4a3
|
{
"intermediate": 0.399598091840744,
"beginner": 0.2163473516702652,
"expert": 0.38405460119247437
}
|
566
|
Summarize the 10 deadly sins
|
89d92244336adc714f40d3389d4816d9
|
{
"intermediate": 0.34851759672164917,
"beginner": 0.4094378352165222,
"expert": 0.2420445680618286
}
|
567
|
I have this spring boot project https://github.com/Teller501/Miniprojekt_2semester that runs java maven
I want to deploy on it Azure using GitHub actions. Can you help me with that?
|
37f3598dd7421d5f74f738e23d6de874
|
{
"intermediate": 0.6077999472618103,
"beginner": 0.14595860242843628,
"expert": 0.24624143540859222
}
|
568
|
<Style x:Key="ClassAStyle" TargetType="{x:Type local:ClassA}">
<Setter Property="ColumnHeaderStyle" Value="{DynamicResource MyStyle}"/>
</Style>
<Style x:Key="ClassBStyle" TargetType="{x:Type local:ClassB}">
<Setter Property="ColumnHeaderStyle" Value="{DynamicResource MyStyle}"/>
</Style>
<Style x:Key="ClassCStyle" TargetType="{x:Type local:ClassC}">
<Setter Property="ColumnHeaderStyle" Value="{DynamicResource MyStyle}"/>
</Style>
Can I write this without having to repeat myself and without using inheritance on the classes?
|
26d10b1ab98307c18cd9471200636f8b
|
{
"intermediate": 0.2111508846282959,
"beginner": 0.7047874331474304,
"expert": 0.08406169712543488
}
|
569
|
in python, my game_window has these properties:
game_window.left: -8
game_window.top -8
game_window.width 1382
game_window.height 784
and the rectangle I need is in (game_window.width/2 + 150, game_window.bottom - 98, 145, 18)
import pyautogui
game_window = pyautogui.getWindowsWithTitle(window_title)[0]
left = game_window.left
top = game_window.top
width = game_window.width
height = game_window.height
Do_Something(game_window.width/2 + 150, game_window.bottom - 98, 145, 18)
give me a way to do this relative to the window size but having different window sizes
|
da5bfd2785c682d9b47f9befc3d15da4
|
{
"intermediate": 0.5047045350074768,
"beginner": 0.28659969568252563,
"expert": 0.20869576930999756
}
|
570
|
golang telegrambot example
|
e216ecddba093a04e5359bedb35e4575
|
{
"intermediate": 0.36196058988571167,
"beginner": 0.24606665968894958,
"expert": 0.3919728100299835
}
|
571
|
You shall thencefoeth Write a script in python for GFS model with the ability of rule base extraction and data base tuning for next day stock price prediction to extract useful patterns of information with a descriptive rule induction approach to cope with the fluctuation of stock price values and it also yields good prediction accuracy in short term stock price forecasting. constructing a stock price forecasting expert system. With display systems are almost always transparent. This can make it convenient for traders to understand how they work and why they make the decisions they do. This can help traders to make more informed decisions about when to buy and sell assets.
|
98ac38d1ad73c62921dce4fc40a52af6
|
{
"intermediate": 0.38241446018218994,
"beginner": 0.19534730911254883,
"expert": 0.42223820090293884
}
|
572
|
golang telegrab bot example
|
66774d380964405441168f5531afc3af
|
{
"intermediate": 0.29659491777420044,
"beginner": 0.4081093668937683,
"expert": 0.29529571533203125
}
|
573
|
Is it possible to migrate from a Pi 2B to a Pi 3 by just moving the SD card?
|
36a06f18828a0153482bcf61c5f7c4f1
|
{
"intermediate": 0.32733413577079773,
"beginner": 0.26388195157051086,
"expert": 0.4087839722633362
}
|
574
|
'''
import streamlit as st
import pandas as pd
import requests
import json
from PIL import Image, ImageOps
from io import BytesIO
from itertools import groupby
import instaloader
import datetime
import altair as alt
loader = instaloader.Instaloader()
# For login
username = "walhalax"
password = "W@lhalax4031"
loader.context.login(username, password) # Login
loader.context.request_timeout = (9, 15) # Increase request timeout
access_token = "EAAIui8JmOHYBAESXLZAnsSRe4OITHYzy3Q5osKgMXGRQnoVMtiIwJUonFjVHEjl9EZCEmURy9I9S9cnyFUXBquZCsWnGx1iJCYTvkKuUZBpBwwSceZB0ZB6YY9B83duIwZCoOlrOODhnA3HLLGbRKGPJ9hbQPLCrkVbc5ibhE43wIAinV0gVkJ30x4UEpb8fXLD8z5J9EYrbQZDZD"
account_id = "17841458386736965"
def load_media_info(access_token, account_id):
base_url = f"https://graph.facebook.com/v11.0/{account_id}/media"
params = {
"fields": "id,media_type,media_url,thumbnail_url,permalink,caption,timestamp,like_count,comments_count,insights.metric(impressions,reach,engagement),children{media_type,media_url}",
"access_token": access_token
}
items = []
while base_url:
response = requests.get(base_url, params=params)
data = json.loads(response.text)
items.extend(data["data"])
if "paging" in data and "next" in data["paging"]:
base_url = data["paging"]["next"]
params = {}
else:
base_url = None
return pd.DataFrame(items)
df = load_media_info(access_token, account_id)
if 'thumbnail_url' not in df.columns:
df['thumbnail_url'] = df['media_url']
df['thumbnail_url'] = df.apply(lambda x: x["media_url"] if x["media_type"] == "IMAGE" else x["thumbnail_url"], axis=1)
df["id"] = df["timestamp"]
df["id"] = df["id"].apply(lambda x: datetime.datetime.strptime(x.split("+")[0], "%Y-%m-%dT%H:%M:%S").strftime("%Y%m%d"))
df = df.sort_values("timestamp", ascending=False)
df["id_rank"] = [f"_{len(list(group))}" for _, group in groupby(df["id"])]
df["id"] += df["id_rank"]
menu = ["Content", "Analytics"]
choice = st.sidebar.radio("Menu", menu)
if "load_more" not in st.session_state:
st.session_state.load_more = 0
def display_carousel(carousel_items):
scale_factor = 0.15
display_images = []
for url in carousel_items:
req_img = requests.get(url)
img_bytes = req_img.content
img = Image.open(BytesIO(img_bytes))
display_image = ImageOps.scale(img, scale_factor)
display_images.append(display_image)
st.image(display_images, width=300)
if choice == "Content":
selected_id = st.sidebar.selectbox("Select Post", df["id"].unique())
selected_data = df[df["id"] == selected_id].iloc[0]
image_url = selected_data["media_url"] if selected_data["media_type"] == "IMAGE" else selected_data["thumbnail_url"]
image_response = requests.get(image_url)
image = Image.open(BytesIO(image_response.content))
# Display carousel
if "children" in selected_data.keys():
carousel_items = [child_data["media_url"] for child_data in selected_data["children"]["data"]]
display_carousel(carousel_items)
else:
display_carousel([image_url])
# Process caption text
caption_text = selected_data["caption"]
if caption_text:
start_desc_index = caption_text.find("［Description］")
if start_desc_index != -1:
caption_text = caption_text[start_desc_index + 13:] # Remove text before "［Description］"
end_tags_index = caption_text.find("［Tags］")
if end_tags_index != -1:
caption_text = caption_text[:end_tags_index] # Remove text from "［Tags］"
st.write(caption_text.strip())
likes = selected_data["like_count"]
if "insights" in selected_data.keys():
try:
impressions = selected_data["insights"][0]['values'][0]['value']
percentage = (likes * 100) / impressions
st.write(f"いいね: {likes} (インプレッションに対する割合: {percentage:.1f}%)")
except (KeyError, IndexError):
st.write(f"いいね: {likes}")
else:
st.write(f"いいね: {likes}")
st.write(f"コメント数: {selected_data['comments_count']}")
# Get comments and usernames
try:
shortcode = selected_data["permalink"].split("/")[-2]
post = instaloader.Post.from_shortcode(loader.context, shortcode)
comments = post.get_comments()
comment_list = [(comment.owner.username, comment.text) for comment in comments]
if st.session_state.load_more:
for username, text in comment_list:
st.write(f"{username}: {text}")
else:
for username, text in comment_list[:5]: # Show only the first 5 comments
st.write(f"{username}: {text}")
# Load more button
if st.button("さらに表示"):
st.session_state.load_more += 1
except Exception as e:
st.write("コメントの取得中にエラーが発生しました。")
elif choice == "Analytics":
categories = ["いいね数", "コメント数"]
selected_category = st.selectbox("Select metric", categories)
if selected_category == "いいね数":
metric = "like_count"
elif selected_category == "コメント数":
metric = "comments_count"
chart_df = df[["id", "timestamp", metric]].copy()
chart_df["timestamp"] = pd.to_datetime(chart_df["timestamp"]).dt.date
chart = alt.Chart(chart_df).mark_line().encode(
x="timestamp:T",
y=metric + ":Q"
).properties(
title=f"Time Series of {selected_category}",
width=800,
height=300
)
st.altair_chart(chart)
'''
上記コードにてJupyter開発環境ではエラー表示はなく、streamlitで表示された事を確認できました。しかし、期待された表示がされていない箇所があるため、以下に改修点を列挙します。
①"Content"の説明文について、"[Description]"の前の文字列と、"[Tags]"を含めたそれ以降の文字列を削除するための機能が動作していないため、抜本的な対処も含めて改修してください。
②"いいね数"の横に(29.4%)のように表示する、コンテンツのインプレッション数に対する"いいね率"が正常に表示されておりません。抜本的な対処も含めて改修してください。
③コンテンツの写真については、全画面表示に切り替えたとき以外は、1枚目の写真のみ表示するよう改修してください。
これらの機能が正常に動作するよう修正済みのコードを省略せずにすべて表示してください。
|
0d83f41f258c451489537fffe03b8377
|
{
"intermediate": 0.34760522842407227,
"beginner": 0.3995046615600586,
"expert": 0.25289005041122437
}
|
575
|
This is my game window size 1382 x 784
and these are the values of the correct rectangle
left: 841
top: 678
width: 145
height: 18
How can I get the relative values for different window sizes in python?
|
3d42208fab5f77add6c2928aa1b1cb98
|
{
"intermediate": 0.5666468143463135,
"beginner": 0.10620571672916412,
"expert": 0.3271474838256836
}
|
576
|
In python, make a machine learning moudel to predict a 5x5 minesweeper game. You can't make it random or make it predict 2 same results in a row if a new game is started. You have data for the past 10 games: [2, 12, 18, 10, 12, 21, 1, 5, 13, 12, 21, 23, 7, 15, 24, 10, 14, 23, 9, 15, 16, 11, 19, 22, 2, 7, 17, 1, 6, 8] and you need to predict 4 safe spots. You need to use the list raw
|
bd503c29f1016584a8c4c41c201f68b2
|
{
"intermediate": 0.15513455867767334,
"beginner": 0.09273305535316467,
"expert": 0.7521323561668396
}
|
577
|
QUE ES lo que falla en este codigo: "import random
class Coin:
def __init__(self):
self.chain = None
self.staked_coins = None
self.current_supply = None
self.max_supply = None
def init(self, max_supply):
self.max_supply = max_supply
self.current_supply = 0
self.staked_coins = {}
self.chain = []
def issue_initial_supply(self, initial_supply, users):
coins_per_user = initial_supply // len(users)
for user in users:
user.receive_coins(coins_per_user)
self.current_supply += coins_per_user
def stake_coins(self, user, amount):
if user.balance >= amount:
user.lock_coins(amount)
self.staked_coins[user] = amount
def create_block(self, validator, transactions):
if self.current_supply < self.max_supply:
new_block = {
"validator": validator,
"transactions": transactions,
"reward": 10
}
self.chain.append(new_block)
self.current_supply += new_block["reward"]
validator.receive_coins(new_block["reward"])
class User:
def __init__(self):
self.staked_balance = None
self.balance = None
self.name = None
def init(self, name):
self.name = name
self.balance = 0
self.staked_balance = 0
def receive_coins(self, amount):
self.balance += amount
def lock_coins(self, amount):
self.balance -= amount
self.staked_balance += amount
def select_validator(staked_coins):
validators = list(staked_coins.keys())
stakes = list(staked_coins.values())
return random.choices(validators, weights=stakes, k=1)[0]
def main():
# Inicializar criptomoneda y usuarios
example_coin = Coin(1000000)
users = [User(f"User{i}") for i in range(4)]
# Emitir suministro inicial y simular "staking"
example_coin.issue_initial_supply(100000, users)
for user in users:
example_coin.stake_coins(user, user.balance // 2)
# Simular creación y validación de bloques
for i in range(5):
validator = select_validator(example_coin.staked_coins)
transactions = ["Dummy transaction"] # Aquí se agregarían transacciones reales
example_coin.create_block(validator, transactions)
print(f"Block {i + 1} created and validated by {validator.name}")
for user in users:
print(f"{user.name}: balance={user.balance} staked={user.staked_balance}")
print()
if __name__ == "__main__":
main()"
|
219442fbf563dffe8842cc789613a4fd
|
{
"intermediate": 0.3485088646411896,
"beginner": 0.4133698046207428,
"expert": 0.23812134563922882
}
|
578
|
I have a function f(x)=((6x^2-5x+3)/(2x-1)) so find the solutions for a,b,c so that f(x)=a+bx+(c/(2x-1))
|
43c21875b46e22c2992118b286acbf99
|
{
"intermediate": 0.36974695324897766,
"beginner": 0.25663164258003235,
"expert": 0.37362140417099
}
|
579
|
This is my game window:
{left} {top} {width} {height}
-8 -8 1382 784
and I currently got the game area i need, which is:
{left} {top} {width} {height}
841 678 145 18
it works but for that initial window values.
How can I get the same area for different window sizes? The code I have right now is this:
game_window = pyautogui.getWindowsWithTitle(window_title)[0]
left = game_window.left
top = game_window.top
width = game_window.width
height = game_window.height
Save_Screenshot(game_window.width/2 + 150, game_window.bottom - 98, 145, 18)
|
01769b4ee85a8adef7aa44b7b7c9a798
|
{
"intermediate": 0.45310622453689575,
"beginner": 0.3343864679336548,
"expert": 0.21250732243061066
}
|
580
|
Make an Elevator system in unreal engine blueprints with queue.
|
2363124df66927aaecbf61d0adda5eed
|
{
"intermediate": 0.28206151723861694,
"beginner": 0.23827195167541504,
"expert": 0.479666531085968
}
|
581
|
es correcto lo de [user]? : "class Coin:
def __init__(self):
self.max_supply = None
self.current_supply = 0
self.staked_coins = None
self.chain = None
def __init__(self, max_supply):
self.chain = None
self.staked_coins = None
self.current_supply = 0
self.max_supply = max_supply
def issue_initial_supply(self, initial_supply, users):
coins_per_user = initial_supply // len(users)
for user in users:
user.receive_coins(coins_per_user)
self.current_supply += coins_per_user
def stake_coins(self, user, amount):
if user.balance >= amount:
user.lock_coins(amount)
self.staked_coins[user] = amount"
|
0a81ba35380f6a640f1844593003a269
|
{
"intermediate": 0.3591978847980499,
"beginner": 0.38565289974212646,
"expert": 0.2551491856575012
}
|
582
|
write me a js line that calculates tax by combining the amount of provincial tax withheld and the amount of federal tax withheld, minus a per-dependent deduction from the total tax withheld
|
b5c4a2bda06b1828843a585b1c30fc22
|
{
"intermediate": 0.3769652247428894,
"beginner": 0.29989171028137207,
"expert": 0.3231430649757385
}
|
583
|
How do I reference a nix package when building a nix shell using a shell.nix file?
|
a9a7814ff9786c4521b79987b2f92ba9
|
{
"intermediate": 0.5051296949386597,
"beginner": 0.22355633974075317,
"expert": 0.2713140547275543
}
|
584
|
react typescript, klinechart charting library. You need to access market data as here https://www.binance.com/ru/futures/DOGEUSDT
here is my code
import React, {useState, useEffect, ChangeEvent} from “react”;
import {
Badge, Box,
Button,
ButtonGroup,
Chip,
CircularProgress,
Grid,
Icon, IconButton, Skeleton, TextField,
Typography
} from “@mui/material”;
import ArrowUpwardRoundedIcon from ‘@mui/icons-material/ArrowUpwardRounded’;
import ArrowDownwardRoundedIcon from ‘@mui/icons-material/ArrowDownwardRounded’;
import {useAuthContext} from “…/…/AuthProvider/AuthProvider”;
import FormatPrice from “…/…/Common/FormatPrice”;
import {Order, readCandlesByTrade, readOrderByTrade, Trade, updateTrade} from “…/…/…/actions/cicap-diary-trades”;
import DataTable from “…/…/DataTable/DataTable”;
import {useSnackbar} from “notistack”;
import {CandleChart} from “…/CandleChart/CandleChart”;
import {TradeEntity} from “…/CandleChart/CandleChart.props”;
import {FormattedNumber} from “react-intl”;
import ImageIcon from “next/image”;
import {createTradeImage, deleteTradeImage, tradeImagesCollection, TradeImage} from “…/…/…/actions/cicap-diary-trades-images”;
const timezoneOffset = new Date().getTimezoneOffset() * 60;
interface SideTypeProps {
order: Order;
}
const SideType = ({order}: SideTypeProps) => {
let label = ‘’;
let color = ‘default’;
const icon = order?.side && ‘sell’ === order.side
? ArrowDownwardRoundedIcon
: ArrowUpwardRoundedIcon;
switch (order?.type) {
case ‘limit’:
label = ‘L’;
color = ‘success’
break;
case ‘market’:
label = ‘M’;
color = ‘warning’
break;
case ‘stop_market’:
label = ‘F’;
color = ‘primary’
break;
}
return <>
<Badge
badgeContent={label}
// @ts-ignore
color={color}
>
<Icon component={icon} color=“action” />
</Badge>
</>
}
interface CandlePrice {
timestamp: number;
open: number;
high: number;
low: number;
close: number;
volume: number;
}
interface TradeDetailsProps {
tradeId: string;
defaultChartInterval: string;
}
const TradeDetails = ({tradeId, defaultChartInterval}: TradeDetailsProps) => {
const [trade, setTrade] = useState<{orders: Array<Order>, data: Trade} | undefined>(undefined);
const [orders, setOrders] = useState<Array<TradeEntity>>([]);
const [chartInterval, setChartInterval] = useState(defaultChartInterval);
const [waiting, setWaiting] = useState(false);
const [candleData, setCandleData] = useState<Array<CandlePrice>>([]);
const [images, setImages] = useState<Array<TradeImage>>([]);
const [imageIdDeletion, setImageIdDeletion] = useState<string|null>(null);
const {diaryToken} = useAuthContext();
const [description, setDescription] = useState(‘’);
const [conclusion, setConclusion] = useState(‘’);
const [videoLink, setVideoLink] = useState(‘’);
const {enqueueSnackbar} = useSnackbar();
const ref = React.createRef<HTMLInputElement>();
const fetchTrade = () => {
if (!tradeId || !diaryToken) {
return;
}
setWaiting(true);
readOrderByTrade(tradeId, diaryToken)
.then(data => {
setWaiting(false);
if (!data) return;
const newOrders: Array<TradeEntity> = [];
data.orders.forEach(order => {
const timestamp = Math.floor(order.msTimestamp) - timezoneOffset;
newOrders.push({
time: timestamp,
position: order.side,
value: parseFloat(order.price),
});
});
setTrade(data);
setOrders(newOrders);
});
}
return <> <Box sx={{pr: 2}}>
{
trade?.data.id && candleData ? (<>
<CandleChart
images={images}
candles={candleData}
tradeId={trade?.data.id}
orders={orders}
interval={chartInterval}
openPrice={trade?.data.openPrice}
closePrice={trade?.data.closePrice}
pricePrecision={trade.data.pricePrecision}
quantityPrecision={trade.data.quantityPrecision}
createImage={createImage}
/>
</>) : (<>
<Skeleton variant=“rectangular” height={500} />
</>)
}
</Box>
</>
}
import React, {useEffect, useRef, useState} from “react”;
import {
init,
dispose,
Chart,
DeepPartial,
IndicatorFigureStylesCallbackData,
Indicator,
IndicatorStyle,
KLineData,
utils,
} from “klinecharts”;
import {CandleChartProps} from “./CandleChart.props”;
import CandleChartToolbar from “./CandleChartToolbar”;
import {Style} from “util”;
import {Box, Icon, IconButton, Stack} from “@mui/material”;
import getMinutesTickSizeByInterval from “./utils/getMinutesTickSizeByInterval.util”;
import drawTrade from “./utils/drawTrade.util”;
import drawTradeLines from “./utils/drawTradeLines.util”;
import {BasketIcon, ScreenIcon} from “…/…/icons”;
import {FullScreen, useFullScreenHandle} from “react-full-screen”;;
interface Vol {
volume?: number
}
export const CandleChart = ({
images,
candles,
tradeId,
orders,
interval,
openPrice,
closePrice,
pricePrecision,
quantityPrecision,
createImage
}: CandleChartProps) => {
console.log(candles);
const chart = useRef<Chart|null>();
const paneId = useRef<string>(“”);
const [figureId, setFigureId] = useState<string>(“”)
const ref = useRef<HTMLDivElement>(null);
const handle = useFullScreenHandle();
useEffect(() => {
chart.current = init(chart-${tradeId}, {styles: chartStyles});
return () => dispose(chart-${tradeId});
}, [tradeId]);
useEffect(() => {
const onWindowResize = () => chart.current?.resize();
window.addEventListener(“resize”, onWindowResize);
return () => window.removeEventListener(“resize”, onWindowResize);
}, []);
useEffect(() => {
chart.current?.applyNewData(candles);
chart.current?.overrideIndicator({
name: “VOL”,
shortName: “Объем”,
calcParams: [],
figures: [
{
key: “volume”,
title: “”,
type: “bar”,
baseValue: 0,
styles: (data: IndicatorFigureStylesCallbackData<Vol>, indicator: Indicator, defaultStyles: IndicatorStyle) => {
const kLineData = data.current.kLineData as KLineData
let color: string
if (kLineData.close > kLineData.open) {
color = utils.formatValue(indicator.styles, “bars[0].upColor”, (defaultStyles.bars)[0].upColor) as string
} else if (kLineData.close < kLineData.open) {
color = utils.formatValue(indicator.styles, “bars[0].downColor”, (defaultStyles.bars)[0].downColor) as string
} else {
color = utils.formatValue(indicator.styles, “bars[0].noChangeColor”, (defaultStyles.bars)[0].noChangeColor) as string
}
return { color }
}
}
]
}, paneId.current);
chart.current?.createIndicator(“VOL”, false, { id: paneId.current });
chart.current?.setPriceVolumePrecision(+pricePrecision, +quantityPrecision);
}, [candles]);
useEffect(() => {
if (!orders || orders.length === 0 || candles.length === 0) return;
const minTime = orders[0].time;
const maxTime = orders[orders.length - 1].time;
const needleTime = minTime + (maxTime - minTime) / 2;
chart.current?.scrollToTimestamp(needleTime + 45 * getMinutesTickSizeByInterval(interval) * 60 * 1000);
drawTrade(chart, paneId, orders, interval);
if (openPrice && closePrice) {
let openTime = Infinity;
let closeTime = -Infinity;
orders.forEach(order => {
if (openTime > order.time) {
openTime = order.time;
}
if (closeTime < order.time) {
closeTime = order.time;
}
});
drawTradeLines(
chart,
openPrice,
openTime,
closePrice,
closeTime,
orders[0].position,
paneId,
pricePrecision,
quantityPrecision,
);
}
}, [orders, candles, tradeId]);
return (<> <Stack direction=“row” height={!handle.active ? 550 : “100%”} width=“100%”>
<CandleChartToolbar
setFigureId={setFigureId}
chart={chart} paneId={paneId}
handle={handle}
/>
<Box
ref={ref}
id={chart-${tradeId}}
width=“calc(100% - 55px)”
height={!handle.active ? 550 : “100%”}
sx={{ borderLeft: “1px solid #ddd” }}
>
{
figureId.length > 0 &&
<Stack
sx={{
backgroundColor: “#CBD4E3”,
borderRadius: 1,
position: “absolute”,
zIndex: 10,
right: 80,
top: 30,
border: “1px solid #697669”,
}}
spacing={2}
>
<IconButton sx={{ borderRadius: 1 }} onClick={removeFigure}>
<Icon component={BasketIcon} />
</IconButton>
</Stack>
}
</Box>
</Stack>
</>);
}
In those transactions where there is no closed order, you need to display real-time candles on the chart and calculate the percentage at the current price. This is necessary so that you can follow the transaction in real time. It is necessary that the chart reflects the current situation on the market, as here https://www.binance.com/ru/futures/DOGEUSDT
|
a8b4892829c06c8d064889551776ba01
|
{
"intermediate": 0.3814411759376526,
"beginner": 0.41001394391059875,
"expert": 0.20854489505290985
}
|
585
|
clean up, remove comments: <script setup>
import { onMounted, ref, reactive, watchEffect } from 'vue';
import {comma } from '@/assets/countries.js';
const props = defineProps({
uuid: Number,
country: Number || String || Object,
title: String,
countryName: String,
});
const identifier = ref(String(props.title).toLocaleLowerCase().replace(' ', '-'));
const random = ref(Math.floor(Math.random() * 100) + 35);
onMounted(()=>{
gsap.fromTo(`#${identifier.value}-${props.uuid}`, {
marginTop: 10,
duration: 0.3,
opacity: 0,
x:-150,
scale:0.1,
stagger: 0.8
},{
marginTop: 0,
duration: 0.4,
opacity: 1,
x:0,
scale: 1.1,
},'-=0.39');
})
/* Smoothed number count anims */
const tweened = reactive({
number: 0
})
function callAnim(n){
gsap.to(tweened, { duration: 0.35, number: Number(n) || 0})
}
watchEffect(()=>{
return callAnim(props.country)
})
function updateNum(){
return comma(tweened.number.toFixed(0))
}
</script>
<template>
<Flicking :options="{ gap: 10, circular: true, deceleration: 0.015, moveType: 'freeScroll' }">
<div class="properties mx-2 ">
<div v-if="identifier === 'defense-budget' && country >= 0 " >
<div class="btn shadow-none ">
<div class="overflow-hidden hover-effect ">{{title}}</div>
<p class=" z-index-down " :title="props.title" :id="identifier + '-'+uuid">
<span class="text-main" v-if="country > 0">{{ "$" + updateNum() }}</span>
<p v-if="country <= 0" :style="{'width': random+'px' }" class=" position-relative">
</p>
</p>
</div>
</div>
<div v-if="identifier === 'manpower' && country >= 0 ">
<div class="btn shadow-none ">
<div class="overflow-hidden hover-effect">{{title}}</div>
<p class=" z-index-down" :title="props.title" :id="identifier + '-'+uuid">
<span class="text-main" v-if="country > 0">{{ updateNum() }}</span>
<p v-if="country <= 0" :style="{'width': random+'px' }" class=" position-relative">
</p>
</p>
</div>
</div>
<div v-if="identifier === 'active' && country >= 0 " >
<div class="btn shadow-none ">
<div class="overflow-hidden hover-effect">{{title}}</div>
<p class=" z-index-down" :title="props.title" :id="identifier + '-'+uuid">
<span class="text-main" v-if="country > 0">{{ updateNum() }}</span>
<p v-if="country <= 0" :style="{'width': random+'px' }" class=" position-relative">
</p>
</p>
</div>
</div>
<div v-if="identifier === 'reserves' && country >= 0 " >
<div class="btn shadow-none ">
<div class="overflow-hidden hover-effect">{{title}}</div>
<p class=" z-index-down" :title="props.title" :id="identifier + '-'+uuid">
<span class="text-main" v-if="country > 0">{{ updateNum() }}</span>
<p v-if="country <= 0" :style="{'width': random+'px' }" class=" position-relative">
</p>
</p>
</div>
</div>
<div v-if="identifier === 'land-area' && country >= 0 " >
<div class="btn shadow-none ">
<div class="overflow-hidden hover-effect">{{title}}</div>
<p class=" z-index-down" :title="props.title" :id="identifier + '-'+uuid">
<span class="text-main" v-if="country > 0">{{ updateNum() + ' km²' }}</span>
<p v-if="country <= 0" :style="{'width': random+'px' }" class=" position-relative">
</p>
</p>
</div>
</div>
<div v-if="identifier === 'oil' && country >= 0 " >
<div class="btn shadow-none ">
<div class="overflow-hidden hover-effect">{{title}}</div>
<p class=" z-index-down" :title="props.title" :id="identifier + '-'+uuid">
<span class="text-main" v-if="country > 0">{{ updateNum() + ' bbl' }}</span>
<p v-if="country <= 0" :style="{'width': random+'px' }" class=" position-relative">
</p>
</p>
</div>
</div>
<div v-if="identifier === 'gdp' && country >= 0 " >
<div class="btn shadow-none ">
<div class="overflow-hidden hover-effect">{{title}}</div>
<p class=" z-index-down" :title="props.title" :id="identifier + '-'+uuid">
<span class="text-main" v-if="country > 0">{{ "$" + updateNum() }}</span>
<p v-if="country <= 0" :style="{'width': random+'px' }" class=" position-relative">
</p>
</p>
</div>
</div>
</div>
</Flicking>
</template>
|
a69368ac531ef3b6b36a844dd1f3c2bd
|
{
"intermediate": 0.39827579259872437,
"beginner": 0.3502812087535858,
"expert": 0.2514430582523346
}
|
586
|
clean up this code for production: <script setup> import { onMounted, ref, reactive, watchEffect } from 'vue'; import {comma } from '@/assets/countries.js'; const props = defineProps({ uuid: Number, country: Number || String || Object, title: String, countryName: String, }); const identifier = ref(String(props.title).toLocaleLowerCase().replace(' ', '-')); const random = ref(Math.floor(Math.random() * 100) + 35); onMounted(()=>{ gsap.fromTo(`#${identifier.value}-${props.uuid}`, { marginTop: 10, duration: 0.3, opacity: 0, x:-150, scale:0.1, stagger: 0.8 },{ marginTop: 0, duration: 0.4, opacity: 1, x:0, scale: 1.1, },'-=0.39'); }) /* Smoothed number count anims */ const tweened = reactive({ number: 0 }) function callAnim(n){ gsap.to(tweened, { duration: 0.35, number: Number(n) || 0}) } watchEffect(()=>{ return callAnim(props.country) }) function updateNum(){ return comma(tweened.number.toFixed(0)) } </script>
|
cc683fbffb40c22d18276a5c0b03e73f
|
{
"intermediate": 0.4243357181549072,
"beginner": 0.35259732604026794,
"expert": 0.22306695580482483
}
|
587
|
This is my game window:
{left} {top} {width} {height}
-8 -8 1382 784
and I want to get this game area i need, which is:
{left} {top} {width} {height}
841 678 145 18
How can I get the same area for different window sizes? The code I have right now is wrong and giving me wrong values:
game_window = pyautogui.getWindowsWithTitle(window_title)[0]
left = game_window.left
top = game_window.top
width = game_window.width
height = game_window.height
initial_window_width = 1382
initial_window_height = 784
initial_game_area_left = 841
initial_game_area_top = 678
initial_game_area_width = 145
initial_game_area_height = 18
left_ratio = initial_game_area_left / initial_window_width
top_ratio = initial_game_area_top / initial_window_height
width_ratio = initial_game_area_width / initial_window_width
height_ratio = initial_game_area_height / initial_window_height
game_area_left = left + (width * left_ratio)
game_area_top = top + (height * top_ratio)
game_area_width = width * width_ratio
game_area_height = height * height_ratio
Save_Screenshot(game_area_left, game_area_top, game_area_width, game_area_height)
|
1823453677ec71da9afcf11a6e61359e
|
{
"intermediate": 0.42567363381385803,
"beginner": 0.37355858087539673,
"expert": 0.20076780021190643
}
|
588
|
Есть ли замечания для этого кода:
#include <cassert>
#include <cstddef>
#include <iterator>
#include <string>
#include <utility>
#include <iostream>
template <typename Type>
class SingleLinkedList {
struct Node {
Node() = default;
Node(const Type& val, Node* next)
: value(val)
, next_node(next) {
}
Type value;
Node* next_node = nullptr;
};
template <typename ValueType>
class BasicIterator {
friend class SingleLinkedList;
explicit BasicIterator(Node* node) {
node_ = node;
}
public:
using iterator_category = std::forward_iterator_tag;
using value_type = Type;
using difference_type = std::ptrdiff_t;
using pointer = ValueType*;
using reference = ValueType&;
BasicIterator() = default;
BasicIterator(const BasicIterator<Type>& other) noexcept {
node_ = other.node_;
}
BasicIterator& operator=(const BasicIterator& rhs) = default;
[[nodiscard]] bool operator==(const BasicIterator<const Type>& rhs) const noexcept {
return node_ == rhs.node_;
}
[[nodiscard]] bool operator!=(const BasicIterator<const Type>& rhs) const noexcept {
return node_ != rhs.node_;
}
[[nodiscard]] bool operator==(const BasicIterator<Type>& rhs) const noexcept {
return node_ == rhs.node_;
}
[[nodiscard]] bool operator!=(const BasicIterator<Type>& rhs) const noexcept {
return node_ != rhs.node_;
}
BasicIterator& operator++() noexcept {
node_ = node_->next_node;
return *this;
}
BasicIterator operator++(int) noexcept {
auto old_value(*this);
++(*this);
return old_value;
}
[[nodiscard]] reference operator*() const noexcept {
return node_->value;
}
[[nodiscard]] pointer operator->() const noexcept {
return &node_->value;
}
private:
Node* node_ = nullptr;
};
public:
using value_type = Type;
using reference = value_type&;
using const_reference = const value_type&;
using Iterator = BasicIterator<Type>;
using ConstIterator = BasicIterator<const Type>;
[[nodiscard]] Iterator begin() noexcept {
return Iterator(head_.next_node);
}
[[nodiscard]] Iterator end() noexcept {
Node* end = head_.next_node;
while (end != nullptr) {
end = end->next_node;
}
return Iterator(end);
}
[[nodiscard]] ConstIterator begin() const noexcept {
return ConstIterator(head_.next_node);
}
[[nodiscard]] ConstIterator end() const noexcept {
return cend();
}
[[nodiscard]] ConstIterator cbegin() const noexcept {
return ConstIterator(head_.next_node);
}
[[nodiscard]] ConstIterator cend() const noexcept {
Node* end = head_.next_node;
while (end != nullptr) {
end = end->next_node;
}
return ConstIterator(end);
}
[[nodiscard]] Iterator before_begin() noexcept {
return Iterator(&head_);
}
[[nodiscard]] ConstIterator cbefore_begin() const noexcept {
return ConstIterator(const_cast<Node*>(&head_));
}
[[nodiscard]] ConstIterator before_begin() const noexcept {
return cbefore_begin();
}
SingleLinkedList() : size_(0) {
}
SingleLinkedList(std::initializer_list<Type> values) : size_(0) {
SingleLinkedList tmp;
tmp.Assign(values.begin(), values.end());
swap(tmp);
}
SingleLinkedList(const SingleLinkedList& other) {
*this = other;
}
~SingleLinkedList() {
Clear();
}
Iterator InsertAfter(ConstIterator pos, const Type& value) {
Node* node = new Node(value, pos.node_->next_node);
pos.node_->next_node = node;
++size_;
return Iterator(node);
}
Iterator EraseAfter(ConstIterator pos) noexcept {
Node* node = pos.node_->next_node;
Node* next = pos.node_->next_node->next_node;
pos.node_->next_node = next;
delete node;
--size_;
return Iterator(next);
}
void PopFront() noexcept {
if (IsEmpty()) {
return;
}
Node* node = head_.next_node;
head_.next_node = head_.next_node->next_node;
delete node;
--size_;
}
void PushFront(const Type& value) {
head_.next_node = new Node(value, head_.next_node);
++size_;
}
void Clear() {
while (head_.next_node != nullptr) {
Node* next_next_node = head_.next_node->next_node;
delete head_.next_node;
head_.next_node = next_next_node;
}
size_ = 0;
}
[[nodiscard]] size_t GetSize() const noexcept {
return size_;
}
[[nodiscard]] bool IsEmpty() const noexcept {
return head_.next_node == nullptr;
}
SingleLinkedList& operator=(const SingleLinkedList& rhs) {
if (this != &rhs) {
SingleLinkedList tmp;
tmp.Assign(rhs.begin(), rhs.end());
swap(tmp);
}
return *this;
}
void swap(SingleLinkedList& other) noexcept {
size_t tmp = size_;
size_ = other.size_;
other.size_ = tmp;
Node* node_ptr = head_.next_node;
head_.next_node = other.head_.next_node;
other.head_.next_node = node_ptr;
}
template <typename It>
void Assign(const It& begin, const It& end) {
Node* last_node = &head_;
for (auto it = begin; it != end; ++it) {
last_node->next_node = new Node(*it, nullptr);
last_node = last_node->next_node;
++size_;
}
}
private:
Node head_;
size_t size_;
};
template <typename Type>
void swap(SingleLinkedList<Type>& lhs, SingleLinkedList<Type>& rhs) noexcept {
lhs.swap(rhs);
}
template <typename Type>
bool operator==(const SingleLinkedList<Type>& lhs, const SingleLinkedList<Type>& rhs) {
return std::equal(lhs.begin(), lhs.end(), rhs.begin(), lhs.end());
}
template <typename Type>
bool operator!=(const SingleLinkedList<Type>& lhs, const SingleLinkedList<Type>& rhs) {
return !(lhs == rhs);
}
template <typename Type>
bool operator<(const SingleLinkedList<Type>& lhs, const SingleLinkedList<Type>& rhs) {
return std::lexicographical_compare(lhs.begin(), lhs.end(), rhs.begin(), rhs.end());
}
template <typename Type>
bool operator<=(const SingleLinkedList<Type>& lhs, const SingleLinkedList<Type>& rhs) {
return lhs == rhs || lhs < rhs;
}
template <typename Type>
bool operator>(const SingleLinkedList<Type>& lhs, const SingleLinkedList<Type>& rhs) {
return rhs < lhs;
}
template <typename Type>
bool operator>=(const SingleLinkedList<Type>& lhs, const SingleLinkedList<Type>& rhs) {
return !(lhs < rhs);
}
|
70521d817f3585450f6fdcfb751d040b
|
{
"intermediate": 0.31929126381874084,
"beginner": 0.4982646703720093,
"expert": 0.18244406580924988
}
|
589
|
Hi, I've implemented a DQN Agent and I want you to implement a code to test my implemented DQN on TWO environments:‘CartPole-v1’ and any other
complex environment of your choice from OpenAI LunarLander, OpenAI MountainCar, OpenAI
Atari Breakout (Choose the easy one). Provide performance results including
reward dynamics (total reward per episode). Goal : ‘CartPole-v1’ environment is considered to be solved if it is getting an average
reward of more than 470 points over 100 consecutive episodes during evaluation. That being said , Here is the DQN implementation:
class DQNAgentPytorch:
def __init__(self, env, memory_size=2000, epsilon=1.0, gamma=0.99, learning_rate=0.001):
self.env = env
self.observation_space = env.observation_space
self.action_space = env.action_space
self.memory = deque(maxlen=memory_size)
self.epsilon = epsilon
self.gamma = gamma
self.lr = learning_rate
self.model = self.build_model()
self.target_model = self.build_model()
self.optimizer = optim.Adam(self.model.parameters(), lr=self.lr)
self.criterion = nn.MSELoss()
self.update_target_net()
def build_model(self):
model = nn.Sequential(
nn.Linear(self.observation_space.n, 16),
nn.ReLU(),
nn.Linear(16, 16),
nn.ReLU(),
nn.Linear(16, self.action_space.n)
)
return model
def remember(self, state, action, reward, next_state, done):
self.memory.append((state, action, reward, next_state, done))
def choose_action(self, state, test=False):
if test or random.random() > self.epsilon:
with torch.no_grad():
state_oh = self.state_to_onehot(state)
q_values = self.model(state_oh)
return torch.argmax(q_values).item()
else:
return np.random.randint(self.action_space.n)
def state_to_onehot(self, state):
return torch.tensor(np.identity(self.observation_space.n)[state].reshape(1, -1), dtype=torch.float32)
def train(self, batch_size):
if len(self.memory) < batch_size:
return
minibatch = random.sample(self.memory, batch_size)
for state, action, reward, next_state, done in minibatch:
target = self.target_model(self.state_to_onehot(state)).squeeze(0)
if done:
target[action] = reward
else:
next_q_values = self.target_model(self.state_to_onehot(next_state)).squeeze(0)
target[action] = reward + self.gamma * torch.max(next_q_values)
inputs = self.state_to_onehot(state)
targets = target.unsqueeze(0)
self.optimizer.zero_grad()
outputs = self.model(inputs)
loss = self.criterion(outputs, targets)
loss.backward()
self.optimizer.step()
def update_target_net(self):
self.target_model.load_state_dict(self.model.state_dict())
def update_epsilon(self, new_epsilon):
self.epsilon = new_epsilon
def save_weights(self, file_name):
torch.save(self.model.state_dict(), file_name)
def load_weights(self, file_name):
self.epsilon = 0
self.model.load_state_dict(torch.load(file_name)) def train_dqn(agent, episodes, batch_size, epsilon_decay=0.995, min_epsilon=0.01):
rewards = []
steps_list = []
epsilons = []
target_update_freq = 25
for episode_i in range(1, episodes + 1):
state = agent.env.reset()
done = False
episode_reward = 0
steps = 0
while not done:
steps += 1
action = agent.choose_action(state)
next_state, reward, done, _ = agent.env.step(action)
agent.remember(state, action, reward, next_state, done)
agent.train(batch_size)
state = next_state
episode_reward += reward
if steps % target_update_freq == 0:
agent.update_target_net()
rewards.append(episode_reward)
steps_list.append(steps)
epsilons.append(agent.epsilon)
agent.update_epsilon(max(agent.epsilon * epsilon_decay, min_epsilon))
print(f"Episode: {episode_i}, Total Reward: {episode_reward}, Epsilon: {agent.epsilon}, Steps: {steps}")
return rewards, epsilons, steps_list
def plot_results(rewards, epsilons):
plt.subplot(2, 1, 1)
plt.plot(rewards)
plt.title('DQN GridWorld Rewards')
plt.subplot(2, 1, 2)
plt.plot(epsilons)
plt.title('Epsilon Decay')
plt.xlabel('Episodes')
plt.tight_layout()
plt.show()env = GridWorldDeterministic()
agent = DQNAgentPytorch(env)
rewards, epsilons, steps_list = train_dqn(agent, episodes=100, batch_size=32)
plot_results(rewards, epsilons)
agent.save_weights('aboda_assignment2_part2_dqn_gridworld.h5')
def evaluate(agent, env, episodes=5, max_steps=10):
test_rewards = []
for episode_i in range(1, episodes + 1):
state = env.reset()
done = False
total_reward = 0
step = 0
while not done and step < max_steps:
action = agent.choose_action(state, test=True)
next_state, reward, done, _ = env.step(action)
env.render()
print("Action taken:", action)
print("New state:", state)
print("Reward received:", reward)
print("Done?", done)
print("="*20)
state = next_state
total_reward += reward
step += 1
test_rewards.append(total_reward)
print(f'Test Episode: {episode_i}, Total Reward: {total_reward}, Steps: {step}')
return test_rewards
env = GridWorldDeterministic()
agent = DQNAgentPytorch(env)
agent.load_weights('aboda_assignment2_part2_dqn_gridworld.h5')
test_rewards = evaluate(agent, env)
# Plot test reward graph
plt.plot(test_rewards)
plt.xlabel('Test Episodes')
plt.ylabel('Rewards')
plt.title('DQN GridWorld Test Rewards')
plt.grid()
plt.show()
|
35c03f964a01772f5e3d7052391cb9b7
|
{
"intermediate": 0.277553528547287,
"beginner": 0.43259716033935547,
"expert": 0.28984931111335754
}
|
590
|
In python, make me some code that predicts a 5x5 field minesweeper. You're supposed to predict 4 safe spots, where you've data for the past 10 games: [2, 12, 18, 10, 12, 21, 1, 5, 13, 12, 21, 23, 7, 15, 24, 10, 14, 23, 9, 15, 16, 11, 19, 22, 2, 7, 17, 1, 6, 8]. Use machine learning and use the raw list and also it cant be random or predict the same spots two times in a row
|
bbe5166907722213018b4773d30b6f20
|
{
"intermediate": 0.15785764157772064,
"beginner": 0.044563986361026764,
"expert": 0.7975783944129944
}
|
591
|
Make this code more readable if possible just print the code no explaining:<script setup>
import { onMounted, ref, reactive, watchEffect, defineProps } from 'vue';
import { comma } from '@/assets/countries.js';
import gsap from 'gsap';
const props = defineProps({
uuid: Number,
country: [Number, String, Object],
title: String,
countryName: String,
});
const identifier = ref(props.title.toLowerCase().replace(/ /g, '-'));
const random = ref(Math.floor(Math.random() * 100) + 35);
onMounted(() => {
const element = document.querySelector(`#${identifier.value}-${props.uuid}`);
if (!element) return;
gsap.fromTo(element, {
marginTop: 10,
duration: 0.3,
opacity: 0,
x: -150,
scale: 0.1,
stagger: 0.8,
}, {
marginTop: 0,
duration: 0.4,
opacity: 1,
x: 0,
scale: 1.1,
}, '-=0.39');
});
const tweened = reactive({
number: 0,
});
watchEffect(() => {
const countryNumber = Number(props.country);
if (isNaN(countryNumber)) return;
gsap.to(tweened, { duration: 0.35, number: countryNumber });
});
function formatNumber() {
return comma(tweened.number.toFixed(0));
}
</script>
<template>
<Flicking :options="{ gap: 10, circular: true, deceleration: 0.015, moveType: 'freeScroll' }">
<div class="properties mx-2 " v-if="props.country >= 0 && ['defense-budget', 'manpower', 'active', 'reserves', 'land-area', 'oil', 'gdp'].includes(identifier)">
<div class="btn shadow-none ">
<div class="overflow-hidden hover-effect">{{ props.title }}</div>
<p :title="props.title" :id="`${identifier}-${props.uuid}`" class="z-index-down">
<span class="text-main" v-if="props.country > 0">
<template v-if="identifier === 'land-area'">{{ `${formatNumber()} km²` }}</template>
<template v-else-if="identifier === 'oil'">{{ `${formatNumber()} bbl` }}</template>
<template v-else>{{ `$${formatNumber()}` }}</template>
</span>
<p v-else :style="{ width: `${random}px` }" class="position-relative"></p>
</p>
</div>
</div>
</Flicking>
</template>
|
663e3945c62793b3f5d730014ee39a6c
|
{
"intermediate": 0.2836446464061737,
"beginner": 0.5769652128219604,
"expert": 0.13939018547534943
}
|
592
|
If I have load django templates in gunicorn config, should I write static/templates paths in nginx config?
|
d608281c23dc75288c4b40d297a0d47b
|
{
"intermediate": 0.6463713645935059,
"beginner": 0.20496664941310883,
"expert": 0.1486620157957077
}
|
593
|
i have this code:
window_rect = (game_window.left, game_window.top, game_window.width, game_window.height)
game_area_rect = (841, 678, 145, 18)
# Calculate the game area position and size as a fraction of the window size
fraction_left = float(game_area_rect[0] - window_rect[0]) / window_rect[2]
fraction_top = float(game_area_rect[1] - window_rect[1]) / window_rect[3]
fraction_width = float(game_area_rect[2]) / window_rect[2]
fraction_height = float(game_area_rect[3]) / window_rect[3]
# Calculate the actual position and size of the game area in the window
game_area_left = game_window.left + (game_window.width * fraction_left)
game_area_top = game_window.top + (game_window.height * fraction_top)
game_area_width = game_window.width * fraction_width
game_area_height = game_window.height * fraction_height
print("Game area:", game_area_left, game_area_top, game_area_width, game_area_height)
I need that the game area moves based on initial window position, and if I run the script with a different starting position it should always point the same area
|
1cbe5c22d496d3fe4a18a8854047887c
|
{
"intermediate": 0.41826900839805603,
"beginner": 0.3196876347064972,
"expert": 0.2620433270931244
}
|
594
|
Can you predcit a towers game based on the previes data?
|
c2e18b25bb5a7b393b9d06a02630f52a
|
{
"intermediate": 0.3394268751144409,
"beginner": 0.15159684419631958,
"expert": 0.5089762806892395
}
|
595
|
create a object oriented rock paper scissor tournament simulation
|
f62d00509d5b86e92a2e689eab930b58
|
{
"intermediate": 0.23945587873458862,
"beginner": 0.35278117656707764,
"expert": 0.40776297450065613
}
|
596
|
hi
|
62303cf25b22c465b512020112ea50ec
|
{
"intermediate": 0.3246487081050873,
"beginner": 0.27135494351387024,
"expert": 0.40399640798568726
}
|
597
|
can cv2.matchTemplate be used for an arbitrary size template? I have a template that is from one screen size, but if I change the window size the template change too. Or there is another simple alternative? Also I don't know beforehand the size of the window nor the size to resize the template to, to fit the window
|
83bec2c50a7e458f02680fa54c64f64e
|
{
"intermediate": 0.44270002841949463,
"beginner": 0.22908732295036316,
"expert": 0.3282126784324646
}
|
598
|
how to deploy pure python algotrading code into vercel?
|
c0ba50827c6f504c40004a5ffa3906a9
|
{
"intermediate": 0.11871939152479172,
"beginner": 0.25160929560661316,
"expert": 0.6296713352203369
}
|
599
|
How would you go about introducing shading into a 3D game written in C# and Monogame?
|
039f0e84ed80ecf99d62aa30978ca03f
|
{
"intermediate": 0.46539798378944397,
"beginner": 0.2833625376224518,
"expert": 0.2512394189834595
}
|
600
|
"Give me a list of interview questions & thier answers on Install WordPress on EC2 with RDS Database for AWS DevOps engineers only
While giving answers, first write a question, then give the answer"
|
08d062a0c30ff6eb6e676c5b3c0d1413
|
{
"intermediate": 0.4426296353340149,
"beginner": 0.31462132930755615,
"expert": 0.24274906516075134
}
|
601
|
generate a simple working Example of Vue Router Transition using the latest vue version
|
a1c9fd31fc07742298c7026fb4388fd0
|
{
"intermediate": 0.5376994013786316,
"beginner": 0.1727232187986374,
"expert": 0.2895773947238922
}
|
602
|
line 19, in <module>
if hinst <= wintypes.HINSTANCE_ERROR:
AttributeError: module 'ctypes.wintypes' has no attribute 'HINSTANCE_ERROR'
|
c333ea17692270403421519cfc7edd41
|
{
"intermediate": 0.45974284410476685,
"beginner": 0.25050589442253113,
"expert": 0.28975120186805725
}
|
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