estudos | Repositório com projetos de teste e notas de estudo

by mstuttgart C Version: Current License: MIT

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kandi X-RAY | estudos Summary

estudos is a C library. estudos has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

:seedling: Repositório com projetos de teste e notas de estudo

Support

Quality

Security

License

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kandi-support Support

estudos has a low active ecosystem.
It has 16 star(s) with 6 fork(s). There are 1 watchers for this library.
It had no major release in the last 12 months.
There are 15 open issues and 150 have been closed. On average issues are closed in 517 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of estudos is current.

estudos Support

Best in #C

Average in #C

estudos Support

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quality kandi Quality

estudos has no bugs reported.

estudos Quality

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estudos Quality

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security Security

estudos has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

estudos Security

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estudos Security

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license License

estudos is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.

estudos License

Best in #C

Average in #C

estudos License

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build Reuse

estudos releases are not available. You will need to build from source code and install.

estudos Reuse

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estudos Reuse

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estudos Key Features

:seedling: Repositório com projetos de teste e notas de estudo

estudos Examples and Code Snippets

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Vuetify: My navigation drawer is positioned over another element (toolbar)

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Add clipped to v-navigation-drawer props like: 
<v-navigation-drawer
  clipped>
  <!-- ... -->
</v-navigation-drawer>

How to sort/order a list according to time in 00:00 format?

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void main() {
  json.sort((x, y) => '${x['time']}'.seconds.compareTo('${y['time']}'.seconds));
  for (final element in json) {
    print(element);
  }
}

final json = [
  {'id': 1, 'time': '10:00:01'},
  {'id': 3, 'time': '30:00'},
  {'id': 2, 'time': '20:00'},
  {'id': 4, 'time': '40:00'},
  {'id': 0, 'time': '10:00'},
];

extension _Time on String {
  int get seconds {
    var hours = 0;
    var minutes = 0;
    var seconds = 0;
    final parts = split(':');
    switch (parts.length) {
      case 2:
        minutes = _toInt(parts[0], 59);
        seconds = _toInt(parts[1], 59);
        break;
      case 3:
        hours = _toInt(parts[0], 23);
        minutes = _toInt(parts[1], 59);
        seconds = _toInt(parts[2], 59);
        break;
      default:
        _error();
    }

    return hours * 3600 + minutes * 60 + seconds;
  }

  void _error() {
    throw FormatException('Invalid time format: $this');
  }

  int _toInt(String part, int max) {
    final result = int.tryParse(part, radix: 10);
    if (result == null) {
      _error();
    }

    if (result < 0 || result > max) {
      _error();
    }

    return result;
  }
}

{id: 0, time: 10:00}
{id: 1, time: 10:00:01}
{id: 2, time: 20:00}
{id: 3, time: 30:00}
{id: 4, time: 40:00}

-----------------------

void main() {
  json.sort((x, y) => '${x['time']}'.seconds.compareTo('${y['time']}'.seconds));
  for (final element in json) {
    print(element);
  }
}

final json = [
  {'id': 1, 'time': '10:00:01'},
  {'id': 3, 'time': '30:00'},
  {'id': 2, 'time': '20:00'},
  {'id': 4, 'time': '40:00'},
  {'id': 0, 'time': '10:00'},
];

extension _Time on String {
  int get seconds {
    var hours = 0;
    var minutes = 0;
    var seconds = 0;
    final parts = split(':');
    switch (parts.length) {
      case 2:
        minutes = _toInt(parts[0], 59);
        seconds = _toInt(parts[1], 59);
        break;
      case 3:
        hours = _toInt(parts[0], 23);
        minutes = _toInt(parts[1], 59);
        seconds = _toInt(parts[2], 59);
        break;
      default:
        _error();
    }

    return hours * 3600 + minutes * 60 + seconds;
  }

  void _error() {
    throw FormatException('Invalid time format: $this');
  }

  int _toInt(String part, int max) {
    final result = int.tryParse(part, radix: 10);
    if (result == null) {
      _error();
    }

    if (result < 0 || result > max) {
      _error();
    }

    return result;
  }
}

{id: 0, time: 10:00}
{id: 1, time: 10:00:01}
{id: 2, time: 20:00}
{id: 3, time: 30:00}
{id: 4, time: 40:00}

C# - Entity Framework Code first, lazy loading not working

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[ForeignKey("idProgramas")]
public virtual Programas Programas { get; set; }

[ForeignKey("idProjetos")]
public virtual Projetos Projetos { get; set; }

db.Estudos
  .Include(x => x.Programas)
  .Include(x => x.Projetos)
  .ToList();

-----------------------

[ForeignKey("idProgramas")]
public virtual Programas Programas { get; set; }

[ForeignKey("idProjetos")]
public virtual Projetos Projetos { get; set; }

db.Estudos
  .Include(x => x.Programas)
  .Include(x => x.Projetos)
  .ToList();

Conditionally render JSX on specific routes

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import React from 'react';
import { Link, useLocation, useHistory, withRouter } from 'react-router-dom';

import logoImg from '../../assets/images/logo.svg';
import backIcon from '../../assets/images/icons/back.svg';

import './styles.css';

function SplitScreen(props: { children: React.ReactNode; }) {
  const { pathname } = useLoction();

  const showBack = !pathname.startsWith("/login");

  return (
    <section className="split-page-container">
      <div className="right-side">
        {showBack && (
          <Link
            className="back-arrow"
            to="/">
            <img src={backIcon} alt="Voltar" />
          </Link>
        )}
        <div className="proffy">
          <div className="proffy-fundo">
            <img src={logoImg} alt="Proffy Logo" />
            <h2>Sua plataforma de <br /> estudos online.</h2>
          </div>
        </div>
      </div>

      <div className="left-side">
        <div className="content-box">
          {props.children}
        </div>
      </div>
    </section>
  );
}

function SplitScreen(props: { children: React.ReactNode; }) {
  const { pathname } = useLoction();

  const showBack = !pathname.startsWith("/login");

  return (
    <section className="split-page-container">
      <div className="left-side"> // <-- now the left side
        {showBack && (
          <Link
            className="back-arrow"
            to="/">
            <img src={backIcon} alt="Voltar" />
          </Link>
        )}
        <div className="proffy">
          <div className="proffy-fundo">
            <img src={logoImg} alt="Proffy Logo" />
            <h2>Sua plataforma de <br /> estudos online.</h2>
          </div>
        </div>
      </div>

      <div className="right-side"> // <-- now the right side
        <div className="content-box">
          {props.children}
        </div>
      </div>
    </section>
  );
}

-----------------------

import React from 'react';
import { Link, useLocation, useHistory, withRouter } from 'react-router-dom';

import logoImg from '../../assets/images/logo.svg';
import backIcon from '../../assets/images/icons/back.svg';

import './styles.css';

function SplitScreen(props: { children: React.ReactNode; }) {
  const { pathname } = useLoction();

  const showBack = !pathname.startsWith("/login");

  return (
    <section className="split-page-container">
      <div className="right-side">
        {showBack && (
          <Link
            className="back-arrow"
            to="/">
            <img src={backIcon} alt="Voltar" />
          </Link>
        )}
        <div className="proffy">
          <div className="proffy-fundo">
            <img src={logoImg} alt="Proffy Logo" />
            <h2>Sua plataforma de <br /> estudos online.</h2>
          </div>
        </div>
      </div>

      <div className="left-side">
        <div className="content-box">
          {props.children}
        </div>
      </div>
    </section>
  );
}

function SplitScreen(props: { children: React.ReactNode; }) {
  const { pathname } = useLoction();

  const showBack = !pathname.startsWith("/login");

  return (
    <section className="split-page-container">
      <div className="left-side"> // <-- now the left side
        {showBack && (
          <Link
            className="back-arrow"
            to="/">
            <img src={backIcon} alt="Voltar" />
          </Link>
        )}
        <div className="proffy">
          <div className="proffy-fundo">
            <img src={logoImg} alt="Proffy Logo" />
            <h2>Sua plataforma de <br /> estudos online.</h2>
          </div>
        </div>
      </div>

      <div className="right-side"> // <-- now the right side
        <div className="content-box">
          {props.children}
        </div>
      </div>
    </section>
  );
}

Converting a block of code into a function results in error

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 def substance_evaluation(substance)

 for ..., substance in ...:

 ... >= substance_mean(substance)

 median = df[substance].mean()

 if substance >= median:

for ..., value in ...:
    if value >= median:

def substance_evaluation(substance):

    median = df[substance].mean()

    for index, value in enumerate(df[substance]):
        if value >= median:
            df.loc[index, substance] = 'high'
        else:
            df.loc[index, substance] = 'low'

    print(df.groupby(substance).quality.mean())

def substance_evaluation(substance):

    median = df[substance].mean()

    mask = (df[substance] >= mediam)

    df[substance][  mask ] = 'high'
    df[substance][ ~mask ] = 'low'

    print(df.groupby(substance).quality.mean())

def substance_evaluation(substance):

    median = df[substance].mean()

    mask = (df[substance] >= mediam)

    df[substance] = np.where(mask, 'high', 'low')

    print(df.groupby(substance).quality.mean())

    df["new column"] = np.where(mask, 'high', 'low')

import pandas as pd
import random
import numpy as np
import time

def version1(df, substance):
    median = df[substance].mean()
    for index, value in enumerate(df[substance]):
        if value >= median:
            df.loc[index, substance] = 'high'
        else:
            df.loc[index, substance] = 'low'

def version2(df, substance):
    median = df[substance].mean()
    mask = (df[substance] >= median)
    df[substance][  mask ] = 'high'
    df[substance][ ~mask ] = 'low'

def version3(df, substance):
    median = df[substance].mean()
    mask = (df[substance] >= median)
    df[substance] = np.where(mask, 'high', 'low')

# ---

random.seed(0) # to generate always the same values

df = pd.DataFrame({'pH': [random.randint(0,7) for _ in range(5)]})

substance = 'pH'

print('--- before ---')
print(df)

# ---

df1 = df.copy()
start = time.time()

version1(df1, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

# ---

df2 = df.copy()
start = time.time()

version2(df2, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

# ---

df3 = df.copy()
start = time.time()

version3(df3, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

-----------------------

 def substance_evaluation(substance)

 for ..., substance in ...:

 ... >= substance_mean(substance)

 median = df[substance].mean()

 if substance >= median:

for ..., value in ...:
    if value >= median:

def substance_evaluation(substance):

    median = df[substance].mean()

    for index, value in enumerate(df[substance]):
        if value >= median:
            df.loc[index, substance] = 'high'
        else:
            df.loc[index, substance] = 'low'

    print(df.groupby(substance).quality.mean())

def substance_evaluation(substance):

    median = df[substance].mean()

    mask = (df[substance] >= mediam)

    df[substance][  mask ] = 'high'
    df[substance][ ~mask ] = 'low'

    print(df.groupby(substance).quality.mean())

def substance_evaluation(substance):

    median = df[substance].mean()

    mask = (df[substance] >= mediam)

    df[substance] = np.where(mask, 'high', 'low')

    print(df.groupby(substance).quality.mean())

    df["new column"] = np.where(mask, 'high', 'low')

import pandas as pd
import random
import numpy as np
import time

def version1(df, substance):
    median = df[substance].mean()
    for index, value in enumerate(df[substance]):
        if value >= median:
            df.loc[index, substance] = 'high'
        else:
            df.loc[index, substance] = 'low'

def version2(df, substance):
    median = df[substance].mean()
    mask = (df[substance] >= median)
    df[substance][  mask ] = 'high'
    df[substance][ ~mask ] = 'low'

def version3(df, substance):
    median = df[substance].mean()
    mask = (df[substance] >= median)
    df[substance] = np.where(mask, 'high', 'low')

# ---

random.seed(0) # to generate always the same values

df = pd.DataFrame({'pH': [random.randint(0,7) for _ in range(5)]})

substance = 'pH'

print('--- before ---')
print(df)

# ---

df1 = df.copy()
start = time.time()

version1(df1, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

# ---

df2 = df.copy()
start = time.time()

version2(df2, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

# ---

df3 = df.copy()
start = time.time()

version3(df3, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

-----------------------

 def substance_evaluation(substance)

 for ..., substance in ...:

 ... >= substance_mean(substance)

 median = df[substance].mean()

 if substance >= median:

for ..., value in ...:
    if value >= median:

def substance_evaluation(substance):

    median = df[substance].mean()

    for index, value in enumerate(df[substance]):
        if value >= median:
            df.loc[index, substance] = 'high'
        else:
            df.loc[index, substance] = 'low'

    print(df.groupby(substance).quality.mean())

def substance_evaluation(substance):

    median = df[substance].mean()

    mask = (df[substance] >= mediam)

    df[substance][  mask ] = 'high'
    df[substance][ ~mask ] = 'low'

    print(df.groupby(substance).quality.mean())

def substance_evaluation(substance):

    median = df[substance].mean()

    mask = (df[substance] >= mediam)

    df[substance] = np.where(mask, 'high', 'low')

    print(df.groupby(substance).quality.mean())

    df["new column"] = np.where(mask, 'high', 'low')

import pandas as pd
import random
import numpy as np
import time

def version1(df, substance):
    median = df[substance].mean()
    for index, value in enumerate(df[substance]):
        if value >= median:
            df.loc[index, substance] = 'high'
        else:
            df.loc[index, substance] = 'low'

def version2(df, substance):
    median = df[substance].mean()
    mask = (df[substance] >= median)
    df[substance][  mask ] = 'high'
    df[substance][ ~mask ] = 'low'

def version3(df, substance):
    median = df[substance].mean()
    mask = (df[substance] >= median)
    df[substance] = np.where(mask, 'high', 'low')

# ---

random.seed(0) # to generate always the same values

df = pd.DataFrame({'pH': [random.randint(0,7) for _ in range(5)]})

substance = 'pH'

print('--- before ---')
print(df)

# ---

df1 = df.copy()
start = time.time()

version1(df1, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

# ---

df2 = df.copy()
start = time.time()

version2(df2, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

# ---

df3 = df.copy()
start = time.time()

version3(df3, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

-----------------------

 def substance_evaluation(substance)

 for ..., substance in ...:

 ... >= substance_mean(substance)

 median = df[substance].mean()

 if substance >= median:

for ..., value in ...:
    if value >= median:

def substance_evaluation(substance):

    median = df[substance].mean()

    for index, value in enumerate(df[substance]):
        if value >= median:
            df.loc[index, substance] = 'high'
        else:
            df.loc[index, substance] = 'low'

    print(df.groupby(substance).quality.mean())

def substance_evaluation(substance):

    median = df[substance].mean()

    mask = (df[substance] >= mediam)

    df[substance][  mask ] = 'high'
    df[substance][ ~mask ] = 'low'

    print(df.groupby(substance).quality.mean())

def substance_evaluation(substance):

    median = df[substance].mean()

    mask = (df[substance] >= mediam)

    df[substance] = np.where(mask, 'high', 'low')

    print(df.groupby(substance).quality.mean())

    df["new column"] = np.where(mask, 'high', 'low')

import pandas as pd
import random
import numpy as np
import time

def version1(df, substance):
    median = df[substance].mean()
    for index, value in enumerate(df[substance]):
        if value >= median:
            df.loc[index, substance] = 'high'
        else:
            df.loc[index, substance] = 'low'

def version2(df, substance):
    median = df[substance].mean()
    mask = (df[substance] >= median)
    df[substance][  mask ] = 'high'
    df[substance][ ~mask ] = 'low'

def version3(df, substance):
    median = df[substance].mean()
    mask = (df[substance] >= median)
    df[substance] = np.where(mask, 'high', 'low')

# ---

random.seed(0) # to generate always the same values

df = pd.DataFrame({'pH': [random.randint(0,7) for _ in range(5)]})

substance = 'pH'

print('--- before ---')
print(df)

# ---

df1 = df.copy()
start = time.time()

version1(df1, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

# ---

df2 = df.copy()
start = time.time()

version2(df2, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

# ---

df3 = df.copy()
start = time.time()

version3(df3, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

-----------------------

 def substance_evaluation(substance)

 for ..., substance in ...:

 ... >= substance_mean(substance)

 median = df[substance].mean()

 if substance >= median:

for ..., value in ...:
    if value >= median:

def substance_evaluation(substance):

    median = df[substance].mean()

    for index, value in enumerate(df[substance]):
        if value >= median:
            df.loc[index, substance] = 'high'
        else:
            df.loc[index, substance] = 'low'

    print(df.groupby(substance).quality.mean())

def substance_evaluation(substance):

    median = df[substance].mean()

    mask = (df[substance] >= mediam)

    df[substance][  mask ] = 'high'
    df[substance][ ~mask ] = 'low'

    print(df.groupby(substance).quality.mean())

def substance_evaluation(substance):

    median = df[substance].mean()

    mask = (df[substance] >= mediam)

    df[substance] = np.where(mask, 'high', 'low')

    print(df.groupby(substance).quality.mean())

    df["new column"] = np.where(mask, 'high', 'low')

import pandas as pd
import random
import numpy as np
import time

def version1(df, substance):
    median = df[substance].mean()
    for index, value in enumerate(df[substance]):
        if value >= median:
            df.loc[index, substance] = 'high'
        else:
            df.loc[index, substance] = 'low'

def version2(df, substance):
    median = df[substance].mean()
    mask = (df[substance] >= median)
    df[substance][  mask ] = 'high'
    df[substance][ ~mask ] = 'low'

def version3(df, substance):
    median = df[substance].mean()
    mask = (df[substance] >= median)
    df[substance] = np.where(mask, 'high', 'low')

# ---

random.seed(0) # to generate always the same values

df = pd.DataFrame({'pH': [random.randint(0,7) for _ in range(5)]})

substance = 'pH'

print('--- before ---')
print(df)

# ---

df1 = df.copy()
start = time.time()

version1(df1, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

# ---

df2 = df.copy()
start = time.time()

version2(df2, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

# ---

df3 = df.copy()
start = time.time()

version3(df3, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

-----------------------

 def substance_evaluation(substance)

 for ..., substance in ...:

 ... >= substance_mean(substance)

 median = df[substance].mean()

 if substance >= median:

for ..., value in ...:
    if value >= median:

def substance_evaluation(substance):

    median = df[substance].mean()

    for index, value in enumerate(df[substance]):
        if value >= median:
            df.loc[index, substance] = 'high'
        else:
            df.loc[index, substance] = 'low'

    print(df.groupby(substance).quality.mean())

def substance_evaluation(substance):

    median = df[substance].mean()

    mask = (df[substance] >= mediam)

    df[substance][  mask ] = 'high'
    df[substance][ ~mask ] = 'low'

    print(df.groupby(substance).quality.mean())

def substance_evaluation(substance):

    median = df[substance].mean()

    mask = (df[substance] >= mediam)

    df[substance] = np.where(mask, 'high', 'low')

    print(df.groupby(substance).quality.mean())

    df["new column"] = np.where(mask, 'high', 'low')

import pandas as pd
import random
import numpy as np
import time

def version1(df, substance):
    median = df[substance].mean()
    for index, value in enumerate(df[substance]):
        if value >= median:
            df.loc[index, substance] = 'high'
        else:
            df.loc[index, substance] = 'low'

def version2(df, substance):
    median = df[substance].mean()
    mask = (df[substance] >= median)
    df[substance][  mask ] = 'high'
    df[substance][ ~mask ] = 'low'

def version3(df, substance):
    median = df[substance].mean()
    mask = (df[substance] >= median)
    df[substance] = np.where(mask, 'high', 'low')

# ---

random.seed(0) # to generate always the same values

df = pd.DataFrame({'pH': [random.randint(0,7) for _ in range(5)]})

substance = 'pH'

print('--- before ---')
print(df)

# ---

df1 = df.copy()
start = time.time()

version1(df1, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

# ---

df2 = df.copy()
start = time.time()

version2(df2, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

# ---

df3 = df.copy()
start = time.time()

version3(df3, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

-----------------------

 def substance_evaluation(substance)

 for ..., substance in ...:

 ... >= substance_mean(substance)

 median = df[substance].mean()

 if substance >= median:

for ..., value in ...:
    if value >= median:

def substance_evaluation(substance):

    median = df[substance].mean()

    for index, value in enumerate(df[substance]):
        if value >= median:
            df.loc[index, substance] = 'high'
        else:
            df.loc[index, substance] = 'low'

    print(df.groupby(substance).quality.mean())

def substance_evaluation(substance):

    median = df[substance].mean()

    mask = (df[substance] >= mediam)

    df[substance][  mask ] = 'high'
    df[substance][ ~mask ] = 'low'

    print(df.groupby(substance).quality.mean())

def substance_evaluation(substance):

    median = df[substance].mean()

    mask = (df[substance] >= mediam)

    df[substance] = np.where(mask, 'high', 'low')

    print(df.groupby(substance).quality.mean())

    df["new column"] = np.where(mask, 'high', 'low')

import pandas as pd
import random
import numpy as np
import time

def version1(df, substance):
    median = df[substance].mean()
    for index, value in enumerate(df[substance]):
        if value >= median:
            df.loc[index, substance] = 'high'
        else:
            df.loc[index, substance] = 'low'

def version2(df, substance):
    median = df[substance].mean()
    mask = (df[substance] >= median)
    df[substance][  mask ] = 'high'
    df[substance][ ~mask ] = 'low'

def version3(df, substance):
    median = df[substance].mean()
    mask = (df[substance] >= median)
    df[substance] = np.where(mask, 'high', 'low')

# ---

random.seed(0) # to generate always the same values

df = pd.DataFrame({'pH': [random.randint(0,7) for _ in range(5)]})

substance = 'pH'

print('--- before ---')
print(df)

# ---

df1 = df.copy()
start = time.time()

version1(df1, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

# ---

df2 = df.copy()
start = time.time()

version2(df2, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

# ---

df3 = df.copy()
start = time.time()

version3(df3, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

-----------------------

 def substance_evaluation(substance)

 for ..., substance in ...:

 ... >= substance_mean(substance)

 median = df[substance].mean()

 if substance >= median:

for ..., value in ...:
    if value >= median:

def substance_evaluation(substance):

    median = df[substance].mean()

    for index, value in enumerate(df[substance]):
        if value >= median:
            df.loc[index, substance] = 'high'
        else:
            df.loc[index, substance] = 'low'

    print(df.groupby(substance).quality.mean())

def substance_evaluation(substance):

    median = df[substance].mean()

    mask = (df[substance] >= mediam)

    df[substance][  mask ] = 'high'
    df[substance][ ~mask ] = 'low'

    print(df.groupby(substance).quality.mean())

def substance_evaluation(substance):

    median = df[substance].mean()

    mask = (df[substance] >= mediam)

    df[substance] = np.where(mask, 'high', 'low')

    print(df.groupby(substance).quality.mean())

    df["new column"] = np.where(mask, 'high', 'low')

import pandas as pd
import random
import numpy as np
import time

def version1(df, substance):
    median = df[substance].mean()
    for index, value in enumerate(df[substance]):
        if value >= median:
            df.loc[index, substance] = 'high'
        else:
            df.loc[index, substance] = 'low'

def version2(df, substance):
    median = df[substance].mean()
    mask = (df[substance] >= median)
    df[substance][  mask ] = 'high'
    df[substance][ ~mask ] = 'low'

def version3(df, substance):
    median = df[substance].mean()
    mask = (df[substance] >= median)
    df[substance] = np.where(mask, 'high', 'low')

# ---

random.seed(0) # to generate always the same values

df = pd.DataFrame({'pH': [random.randint(0,7) for _ in range(5)]})

substance = 'pH'

print('--- before ---')
print(df)

# ---

df1 = df.copy()
start = time.time()

version1(df1, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

# ---

df2 = df.copy()
start = time.time()

version2(df2, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

# ---

df3 = df.copy()
start = time.time()

version3(df3, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

-----------------------

 def substance_evaluation(substance)

 for ..., substance in ...:

 ... >= substance_mean(substance)

 median = df[substance].mean()

 if substance >= median:

for ..., value in ...:
    if value >= median:

def substance_evaluation(substance):

    median = df[substance].mean()

    for index, value in enumerate(df[substance]):
        if value >= median:
            df.loc[index, substance] = 'high'
        else:
            df.loc[index, substance] = 'low'

    print(df.groupby(substance).quality.mean())

def substance_evaluation(substance):

    median = df[substance].mean()

    mask = (df[substance] >= mediam)

    df[substance][  mask ] = 'high'
    df[substance][ ~mask ] = 'low'

    print(df.groupby(substance).quality.mean())

def substance_evaluation(substance):

    median = df[substance].mean()

    mask = (df[substance] >= mediam)

    df[substance] = np.where(mask, 'high', 'low')

    print(df.groupby(substance).quality.mean())

    df["new column"] = np.where(mask, 'high', 'low')

import pandas as pd
import random
import numpy as np
import time

def version1(df, substance):
    median = df[substance].mean()
    for index, value in enumerate(df[substance]):
        if value >= median:
            df.loc[index, substance] = 'high'
        else:
            df.loc[index, substance] = 'low'

def version2(df, substance):
    median = df[substance].mean()
    mask = (df[substance] >= median)
    df[substance][  mask ] = 'high'
    df[substance][ ~mask ] = 'low'

def version3(df, substance):
    median = df[substance].mean()
    mask = (df[substance] >= median)
    df[substance] = np.where(mask, 'high', 'low')

# ---

random.seed(0) # to generate always the same values

df = pd.DataFrame({'pH': [random.randint(0,7) for _ in range(5)]})

substance = 'pH'

print('--- before ---')
print(df)

# ---

df1 = df.copy()
start = time.time()

version1(df1, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

# ---

df2 = df.copy()
start = time.time()

version2(df2, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

# ---

df3 = df.copy()
start = time.time()

version3(df3, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

-----------------------

 def substance_evaluation(substance)

 for ..., substance in ...:

 ... >= substance_mean(substance)

 median = df[substance].mean()

 if substance >= median:

for ..., value in ...:
    if value >= median:

def substance_evaluation(substance):

    median = df[substance].mean()

    for index, value in enumerate(df[substance]):
        if value >= median:
            df.loc[index, substance] = 'high'
        else:
            df.loc[index, substance] = 'low'

    print(df.groupby(substance).quality.mean())

def substance_evaluation(substance):

    median = df[substance].mean()

    mask = (df[substance] >= mediam)

    df[substance][  mask ] = 'high'
    df[substance][ ~mask ] = 'low'

    print(df.groupby(substance).quality.mean())

def substance_evaluation(substance):

    median = df[substance].mean()

    mask = (df[substance] >= mediam)

    df[substance] = np.where(mask, 'high', 'low')

    print(df.groupby(substance).quality.mean())

    df["new column"] = np.where(mask, 'high', 'low')

import pandas as pd
import random
import numpy as np
import time

def version1(df, substance):
    median = df[substance].mean()
    for index, value in enumerate(df[substance]):
        if value >= median:
            df.loc[index, substance] = 'high'
        else:
            df.loc[index, substance] = 'low'

def version2(df, substance):
    median = df[substance].mean()
    mask = (df[substance] >= median)
    df[substance][  mask ] = 'high'
    df[substance][ ~mask ] = 'low'

def version3(df, substance):
    median = df[substance].mean()
    mask = (df[substance] >= median)
    df[substance] = np.where(mask, 'high', 'low')

# ---

random.seed(0) # to generate always the same values

df = pd.DataFrame({'pH': [random.randint(0,7) for _ in range(5)]})

substance = 'pH'

print('--- before ---')
print(df)

# ---

df1 = df.copy()
start = time.time()

version1(df1, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

# ---

df2 = df.copy()
start = time.time()

version2(df2, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

# ---

df3 = df.copy()
start = time.time()

version3(df3, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

-----------------------

 def substance_evaluation(substance)

 for ..., substance in ...:

 ... >= substance_mean(substance)

 median = df[substance].mean()

 if substance >= median:

for ..., value in ...:
    if value >= median:

def substance_evaluation(substance):

    median = df[substance].mean()

    for index, value in enumerate(df[substance]):
        if value >= median:
            df.loc[index, substance] = 'high'
        else:
            df.loc[index, substance] = 'low'

    print(df.groupby(substance).quality.mean())

def substance_evaluation(substance):

    median = df[substance].mean()

    mask = (df[substance] >= mediam)

    df[substance][  mask ] = 'high'
    df[substance][ ~mask ] = 'low'

    print(df.groupby(substance).quality.mean())

def substance_evaluation(substance):

    median = df[substance].mean()

    mask = (df[substance] >= mediam)

    df[substance] = np.where(mask, 'high', 'low')

    print(df.groupby(substance).quality.mean())

    df["new column"] = np.where(mask, 'high', 'low')

import pandas as pd
import random
import numpy as np
import time

def version1(df, substance):
    median = df[substance].mean()
    for index, value in enumerate(df[substance]):
        if value >= median:
            df.loc[index, substance] = 'high'
        else:
            df.loc[index, substance] = 'low'

def version2(df, substance):
    median = df[substance].mean()
    mask = (df[substance] >= median)
    df[substance][  mask ] = 'high'
    df[substance][ ~mask ] = 'low'

def version3(df, substance):
    median = df[substance].mean()
    mask = (df[substance] >= median)
    df[substance] = np.where(mask, 'high', 'low')

# ---

random.seed(0) # to generate always the same values

df = pd.DataFrame({'pH': [random.randint(0,7) for _ in range(5)]})

substance = 'pH'

print('--- before ---')
print(df)

# ---

df1 = df.copy()
start = time.time()

version1(df1, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

# ---

df2 = df.copy()
start = time.time()

version2(df2, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

# ---

df3 = df.copy()
start = time.time()

version3(df3, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

Python numpy error: only integer scalar arrays can be converted to a scalar index

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File "C:\Users\Lucas\Desktop\Estudos\Python\Simple Pendulum.py", line 27, in 
position x = np.cumsum(self.origin[0], L*np.sin(self.state[0]))

self.origin[0]
L*np.sin(self.state[0]

numpy.cumsum(a, axis=None, dtype=None, out=None)[source]

-----------------------

File "C:\Users\Lucas\Desktop\Estudos\Python\Simple Pendulum.py", line 27, in 
position x = np.cumsum(self.origin[0], L*np.sin(self.state[0]))

self.origin[0]
L*np.sin(self.state[0]

numpy.cumsum(a, axis=None, dtype=None, out=None)[source]

-----------------------

File "C:\Users\Lucas\Desktop\Estudos\Python\Simple Pendulum.py", line 27, in 
position x = np.cumsum(self.origin[0], L*np.sin(self.state[0]))

self.origin[0]
L*np.sin(self.state[0]

numpy.cumsum(a, axis=None, dtype=None, out=None)[source]

Nodejs with sequelize Returns Error Running Update

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const { id, name, provider } = await User.update(req.body);

const { id, name, provider } = await User.update(req.body, {
   where: {? : ?}
});

-----------------------

const { id, name, provider } = await User.update(req.body);

const { id, name, provider } = await User.update(req.body, {
   where: {? : ?}
});

How can I remove a large empty space from my page?

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* {
  border: 1px solid red;
}

article img {
  width: 700px;
  position: absolute;
  bottom: 250px;
  left: 900px; /* <-- Causing horizontal scroll */
}
.handwriting {
  font-family: Sepet;
  font-size: 30px;
  position: relative;
  left: 1000px; /* <-- Causing horizontal scroll */
  bottom: 150px;
}

-----------------------

* {
  border: 1px solid red;
}

article img {
  width: 700px;
  position: absolute;
  bottom: 250px;
  left: 900px; /* <-- Causing horizontal scroll */
}
.handwriting {
  font-family: Sepet;
  font-size: 30px;
  position: relative;
  left: 1000px; /* <-- Causing horizontal scroll */
  bottom: 150px;
}

-----------------------

.handwriting{
font-family: Sepet;
font-size: 30px;
position: relative;
left: 1000px;
bottom: 150px;
}

<p class="handwriting"><a href="#">Aulas</a></p>

-----------------------

.handwriting{
font-family: Sepet;
font-size: 30px;
position: relative;
left: 1000px;
bottom: 150px;
}

<p class="handwriting"><a href="#">Aulas</a></p>

Clean improperly positioned CR+LF in texts

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\R          # any kind of linebreak (ie. \r, \n, \r\n)
(?!         # negative lookahead, zero length assertion that makes sure we do not have after:
    \|      # a pipe character
)           # end lookahead

| 1020941333    |     569|SP    |500000343 | 9|18.05.2011|15:27:00|18.05.2011|18.05.2011|Y-0444871-ENCR    |           1,93 |BRL  |8000800000  |Juros, Comissões e T       |                  |           |                                        |    |          |     |                     |CLB082902  |     |     |                 |COEL  |COEL  |Y-0444871               |
| 1020941586    |      43|SP    |500000344 |43|18.05.2011|15:41:43|18.05.2011|18.05.2011|B-0447039-ENCR    |           9,02 |BRL  |8000800000  |Juros, Comissões e T       |                  |           |                                        |    |          |     |                     |CLB082902  |     |     |                 |COEL  |COEL  |B-0447039               |

-----------------------

\R          # any kind of linebreak (ie. \r, \n, \r\n)
(?!         # negative lookahead, zero length assertion that makes sure we do not have after:
    \|      # a pipe character
)           # end lookahead

| 1020941333    |     569|SP    |500000343 | 9|18.05.2011|15:27:00|18.05.2011|18.05.2011|Y-0444871-ENCR    |           1,93 |BRL  |8000800000  |Juros, Comissões e T       |                  |           |                                        |    |          |     |                     |CLB082902  |     |     |                 |COEL  |COEL  |Y-0444871               |
| 1020941586    |      43|SP    |500000344 |43|18.05.2011|15:41:43|18.05.2011|18.05.2011|B-0447039-ENCR    |           9,02 |BRL  |8000800000  |Juros, Comissões e T       |                  |           |                                        |    |          |     |                     |CLB082902  |     |     |                 |COEL  |COEL  |B-0447039               |

Serenity Cucumber: tests exit in first fail and report is empty

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<plugin>
            <groupId>net.serenity-bdd.maven.plugins</groupId>
            <artifactId>serenity-maven-plugin</artifactId>
            <version>${serenity.version}</version>
            <dependencies>
                <dependency>
                    <groupId>net.serenity-bdd</groupId>
                    <artifactId>serenity-core</artifactId>
                    <version>${serenity.version}</version>
                </dependency>
            </dependencies>

See all related Code Snippets

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Vuetify: My navigation drawer is positioned over another element (toolbar)
How to sort/order a list according to time in 00:00 format?
C# - Entity Framework Code first, lazy loading not working
Conditionally render JSX on specific routes
Converting a block of code into a function results in error
Python numpy error: only integer scalar arrays can be converted to a scalar index
Running C++ client/server for parallel processing using MPI
Nodejs with sequelize Returns Error Running Update
How can I remove a large empty space from my page?
Rendering a layout using an example as guide

Trending Discussions on estudos

QUESTION

Vuetify: My navigation drawer is positioned over another element (toolbar)

Asked 2021-Feb-11 at 16:35

I would like to put my navigation drawer under the toolbar.

I'm trying to achieve something like this :

I am trying to do something similar but all attempts are unsuccessful, at the moment I have the following:

My code:

<template>
 <nav>
   
    <v-snackbar v-model="snackbar" :timeout="4000" top color="success">
      <span>Awesome! You added a new project.</span>
      <v-btn text flat @click="snackbar = false">Close</v-btn>
    </v-snackbar>

        <v-toolbar app clipped-left >
            <v-toolbar-side-icon></v-toolbar-side-icon>
             <v-app-bar-nav-icon  @click.stop="drawer = !drawer"></v-app-bar-nav-icon>
            <v-toolbar-title class="text-uppercase gr ey--text">
                <span class="font-weight-light">estudos</span>
                <span>vue</span>
            </v-toolbar-title>
            <v-spacer></v-spacer>

            <v-menu offset-y>
      <template v-slot:activator="{ on, attrs }">
        <v-btn text
          color="primary"
          dark
          v-bind="attrs"
          v-on="on"
        >
          <v-icon left>expand_more</v-icon>
          <span>Menu</span>
        </v-btn>
      </template>
        <v-list>
          <v-list-item v-for="link in links" :key="link.text" router :to="link.route">
            <v-list-item-title>{{link.text}}</v-list-item-title>
          </v-list-item>
        </v-list>
    </v-menu>

            
            <v-btn text color="grey">
                <span>Sign Out</span>
                <v-icon right>exit_to_app</v-icon>
            </v-btn>
        </v-toolbar>


    

    <v-navigation-drawer  v-model="drawer" app  class="indigo white--text"> 
             <v-app-bar-nav-icon  @click.stop="drawer = !drawer"></v-app-bar-nav-icon>
             <v-layout column align-center>
              <v-flex class="mt-5">
                <v-avatar size="90">
                  <img src="/avatar-64.png">
                </v-avatar>
                <p class="white-text dubheading mt-1">
                  Estudos Vue
                </p>
              </v-flex>
              <v-flex class="mt-4 mb-3">
                <popup @projectAdded="snackbar=true" />
              </v-flex>
             </v-layout>
       <v-list >
        <v-divider></v-divider>

        <v-list-item 
          v-for="link in links"
          :key="link.text"
          router :to="link.route"
        >
          <v-list-item-action >
            <v-icon class="white--text">{{ link.icon }}</v-icon>
          </v-list-item-action>

          <v-list-item-content class="white--text">
            <v-list-item-title>{{ link.text }}</v-list-item-title>
          </v-list-item-content>
        </v-list-item>
      </v-list>
    </v-navigation-drawer>
    
     <v-row>
    <v-col
     
  
    >
      <v-img
      
      max-height="76%"
      max-width="100%"
        src="/imgtest.jpg"
        gradient="to top right, rgba(14,12,11,.51), rgba(14,12,11,.71)"
      >
      <v-img-title class="heading white--text">
        Bien saude</v-img-title></v-img>
    </v-col>

  </v-row>
    </nav>
    
</template>

<script>
import Popup from './Popup'
export default {
    components: { Popup },
    data() {
        return {
            drawer:false,
            links:[
                 {icon: 'dashboard', text:'Dashboard', route:'/'},
                 {icon: 'folder', text:'My Projects', route:'/projects'},
                 {icon: 'person', text:'Team', route:'/team'},

            ],
            items: [
        { title: 'Click Me' },
        { title: 'Click Me' },
        { title: 'Click Me' },
        { title: 'Click Me 2' },
      ],
            snackbar: true
        }
    },
  }
</script>

I tried adding Block and removing the app, but it didn't solve the problem... How do I put my drawer under the toolbar?

ANSWER

Answered 2021-Feb-10 at 16:07

Add clipped to v-navigation-drawer props like: 
<v-navigation-drawer
  clipped>
  <!-- ... -->
</v-navigation-drawer>

Source https://stackoverflow.com/questions/66138975

QUESTION

C# - Entity Framework Code first, lazy loading not working

Asked 2020-Aug-22 at 05:31

I have some issues with Entity Framework 6 code-first with a SQL Server database. I have an existing database, and I want to use them with Entity Framework. With Visual Studio 2017, I add a new item of type ADO.NET Entity Data Model to generate the code-first classes for the first time.

Once the classes are generated, I start to use the objects to interact with the database. Here I have some issues with lazy loading. Some navigation properties are null. The navigation properties are marked with virtual and lazy loading and ProxyCreationEnabled are true.

These screenshots illustrate the problem:

I can share the classes generated by Visual Studio:

public partial class ETRFContext : DbContext
{
    static string conn = "My connection string";

    public ETRFContext() : base(conn)
    {
    }

    public virtual DbSet<Acessos> Acessos { get; set; }
    public virtual DbSet<Caracteristicas> Caracteristicas { get; set; }
    public virtual DbSet<CircuitoAprovacoes> CircuitoAprovacoes { get; set; }
    public virtual DbSet<EstadosEstudo> EstadosEstudo { get; set; }
    public virtual DbSet<Estudos> Estudos { get; set; }
    public virtual DbSet<GruposAcesso> GruposAcesso { get; set; }
    public virtual DbSet<HistoricoDetalhadoEstudo> HistoricoDetalhadoEstudo { get; set; }
    public virtual DbSet<MembrosGruposAcesso> MembrosGruposAcesso { get; set; }
    public virtual DbSet<Normas> Normas { get; set; }
    public virtual DbSet<Paises> Paises { get; set; }
    public virtual DbSet<PrecedenciasEstudos> PrecedenciasEstudos { get; set; }
    public virtual DbSet<PrecedenciasProgramas> PrecedenciasProgramas { get; set; }
    public virtual DbSet<Programas> Programas { get; set; }
    public virtual DbSet<Projetos> Projetos { get; set; }
    public virtual DbSet<RegistosCAD> RegistosCAD { get; set; }
    public virtual DbSet<TiposEstadoEstudo> TiposEstadoEstudo { get; set; }
    public virtual DbSet<TiposMensagem> TiposMensagem { get; set; }
    public virtual DbSet<TiposProjeto> TiposProjeto { get; set; }

    protected override void OnModelCreating(DbModelBuilder modelBuilder)
    {
        modelBuilder.Entity<Caracteristicas>()
            .Property(e => e.Chave)
            .IsFixedLength();

        modelBuilder.Entity<Caracteristicas>()
            .Property(e => e.Valor)
            .IsFixedLength();

        modelBuilder.Entity<Estudos>()
            .HasMany(e => e.EstadosEstudo)
            .WithRequired(e => e.Estudos)
            .HasForeignKey(e => e.idEstudo);

        modelBuilder.Entity<Estudos>()
            .HasMany(e => e.HistoricoDetalhadoEstudo)
            .WithRequired(e => e.Estudos)
            .HasForeignKey(e => e.idEstudo);

        modelBuilder.Entity<Estudos>()
            .HasMany(e => e.PrecedenciasEstudos)
            .WithRequired(e => e.Estudos)
            .HasForeignKey(e => e.idEstudo);

        modelBuilder.Entity<Estudos>()
            .HasMany(e => e.PrecedenciasEstudos1)
            .WithRequired(e => e.Estudos1)
            .HasForeignKey(e => e.idEstudoPrecedencia)
            .WillCascadeOnDelete(false);

        modelBuilder.Entity<Estudos>()
            .HasMany(e => e.RegistosCAD)
            .WithRequired(e => e.Estudos)
            .HasForeignKey(e => e.idEstudo);

        modelBuilder.Entity<GruposAcesso>()
            .HasMany(e => e.Acessos)
            .WithRequired(e => e.GruposAcesso)
            .HasForeignKey(e => e.idGruposAcesso);

        modelBuilder.Entity<GruposAcesso>()
            .HasMany(e => e.MembrosGruposAcesso)
            .WithRequired(e => e.GruposAcesso)
            .HasForeignKey(e => e.idGrupoAcesso);

        modelBuilder.Entity<Paises>()
            .HasMany(e => e.Projetos)
            .WithOptional(e => e.Paises)
            .HasForeignKey(e => e.id_Pais);

        modelBuilder.Entity<Programas>()
            .HasMany(e => e.Acessos)
            .WithRequired(e => e.Programas)
            .HasForeignKey(e => e.idPrograma);

        modelBuilder.Entity<Programas>()
            .HasMany(e => e.CircuitoAprovacoes)
            .WithRequired(e => e.Programas)
            .HasForeignKey(e => e.idPrograma);

        modelBuilder.Entity<Programas>()
            .HasMany(e => e.Estudos)
            .WithRequired(e => e.Programas)
            .HasForeignKey(e => e.idProgramas);

        modelBuilder.Entity<Programas>()
            .HasMany(e => e.PrecedenciasProgramas)
            .WithRequired(e => e.Programas)
            .HasForeignKey(e => e.idProgramaPrecedencia);

        modelBuilder.Entity<Programas>()
            .HasMany(e => e.PrecedenciasProgramas1)
            .WithRequired(e => e.Programas1)
            .HasForeignKey(e => e.idPrograma)
            .WillCascadeOnDelete(false);

        modelBuilder.Entity<Projetos>()
            .HasMany(e => e.Caracteristicas)
            .WithRequired(e => e.Projetos)
            .HasForeignKey(e => e.id_projeto);

        modelBuilder.Entity<Projetos>()
            .HasMany(e => e.Estudos)
            .WithRequired(e => e.Projetos)
            .HasForeignKey(e => e.idProjetos);

        modelBuilder.Entity<TiposEstadoEstudo>()
            .HasMany(e => e.EstadosEstudo)
            .WithRequired(e => e.TiposEstadoEstudo)
            .HasForeignKey(e => e.idEstado);

        modelBuilder.Entity<TiposMensagem>()
            .HasMany(e => e.HistoricoDetalhadoEstudo)
            .WithRequired(e => e.TiposMensagem)
            .HasForeignKey(e => e.idTipoMensagem);

        modelBuilder.Entity<TiposProjeto>()
            .HasMany(e => e.Programas)
            .WithRequired(e => e.TiposProjeto)
            .HasForeignKey(e => e.idTiposProjeto);

        modelBuilder.Entity<TiposProjeto>()
            .HasMany(e => e.Projetos)
            .WithRequired(e => e.TiposProjeto)
            .HasForeignKey(e => e.id_Tipo)
            .WillCascadeOnDelete(false);
    }
}

Now this is the class Estudos:

public partial class Estudos
{
    [System.Diagnostics.CodeAnalysis.SuppressMessage("Microsoft.Usage", "CA2214:DoNotCallOverridableMethodsInConstructors")]
    public Estudos()
    {
        EstadosEstudo = new HashSet<EstadosEstudo>();
        HistoricoDetalhadoEstudo = new HashSet<HistoricoDetalhadoEstudo>();
        PrecedenciasEstudos = new HashSet<PrecedenciasEstudos>();
        PrecedenciasEstudos1 = new HashSet<PrecedenciasEstudos>();
        RegistosCAD = new HashSet<RegistosCAD>();
    }

    public int id { get; set; }
    public int idProjetos { get; set; }
    public int idProgramas { get; set; }

    [Required]
    [StringLength(25)]
    public string NomeEstudo { get; set; }

    [Required]
    [StringLength(5)]
    public string Utilizador { get; set; }

    public DateTime DataInicial { get; set; }

    public DateTime? DataFinal { get; set; }

    public bool Producao { get; set; }

    [System.Diagnostics.CodeAnalysis.SuppressMessage("Microsoft.Usage", "CA2227:CollectionPropertiesShouldBeReadOnly")]
    public virtual ICollection<EstadosEstudo> EstadosEstudo { get; set; }

    public virtual Programas Programas { get; set; }

    public virtual Projetos Projetos { get; set; }

    [System.Diagnostics.CodeAnalysis.SuppressMessage("Microsoft.Usage", "CA2227:CollectionPropertiesShouldBeReadOnly")]
    public virtual ICollection<HistoricoDetalhadoEstudo> HistoricoDetalhadoEstudo { get; set; }

    [System.Diagnostics.CodeAnalysis.SuppressMessage("Microsoft.Usage", "CA2227:CollectionPropertiesShouldBeReadOnly")]
    public virtual ICollection<PrecedenciasEstudos> PrecedenciasEstudos { get; set; }

    [System.Diagnostics.CodeAnalysis.SuppressMessage("Microsoft.Usage", "CA2227:CollectionPropertiesShouldBeReadOnly")]
    public virtual ICollection<PrecedenciasEstudos> PrecedenciasEstudos1 { get; set; }

    [System.Diagnostics.CodeAnalysis.SuppressMessage("Microsoft.Usage", "CA2227:CollectionPropertiesShouldBeReadOnly")]
    public virtual ICollection<RegistosCAD> RegistosCAD { get; set; }
}

And the class Projetos:

public partial class Projetos
{
    [System.Diagnostics.CodeAnalysis.SuppressMessage("Microsoft.Usage", "CA2214:DoNotCallOverridableMethodsInConstructors")]
    public Projetos()
    {
        Caracteristicas = new HashSet<Caracteristicas>();
        Estudos = new HashSet<Estudos>();
    }

    public int id { get; set; }

    [Required]
    [StringLength(15)]
    public string projeto { get; set; }

    public int id_Tipo { get; set; }

    [StringLength(50)]
    public string Cliente { get; set; }

    [StringLength(50)]
    public string Designacao { get; set; }

    public int? id_Pais { get; set; }

    public int? CalculoEletrico { get; set; }

    [System.Diagnostics.CodeAnalysis.SuppressMessage("Microsoft.Usage", "CA2227:CollectionPropertiesShouldBeReadOnly")]
    public virtual ICollection<Caracteristicas> Caracteristicas { get; set; }

    [System.Diagnostics.CodeAnalysis.SuppressMessage("Microsoft.Usage", "CA2227:CollectionPropertiesShouldBeReadOnly")]
    public virtual ICollection<Estudos> Estudos { get; set; }

    public virtual Paises Paises { get; set; }

    public virtual TiposProjeto TiposProjeto { get; set; }
}

One thing that I noticed, is when I query the Database for a "Estudo" I don't get the navigation property "Projetos", but when I ask the database for a "Projeto" I get the navigation property "Estudos".

Another thing is that when I query the database for a "Estudo" I don't get the navigation property "Projetos", but if then I query the database for a "Projeto" where id = Estudo.idProjetos, the navigation property "Projetos" in "Estudos" that was null before, automatically fills up with the value of associated "Projeto".

So, anyone have some tips to solve this issue?

Appreciate your help.

ANSWER

Answered 2020-Aug-22 at 02:06

In your Estudos entity, can you add ForeignKey attribute to Programas and Projetos properties.

[ForeignKey("idProgramas")]
public virtual Programas Programas { get; set; }

[ForeignKey("idProjetos")]
public virtual Projetos Projetos { get; set; }

And when querying Estudos include Programas and Projetos.

db.Estudos
  .Include(x => x.Programas)
  .Include(x => x.Projetos)
  .ToList();

Source https://stackoverflow.com/questions/63531493

QUESTION

Conditionally render JSX on specific routes

Asked 2020-Aug-21 at 03:35

I built a React Component Layout for SplitScreen pages (the bottom layout design on the screen shot).

The problem is that the LoginPage layout (the top layout design on the screen shot) I won't need the backArrowIcon at to top, as you can better see on the second screen shot.

I also would have to change the Left<->Right split display on the screen on the LoginPage container.

Anyone has a clue of what can I do to solve my two problems?

Here's also my SplitScreen Component code:

import React from 'react';
import { Link, useHistory, withRouter } from 'react-router-dom';

import logoImg from '../../assets/images/logo.svg';
import backIcon from '../../assets/images/icons/back.svg';

import './styles.css';

function SplitScreen(props: { children: React.ReactNode; }) {
  return (
    <section className="split-page-container">
      <div className="right-side">
        <Link
          className="back-arrow"                 // Here's the backArrowIcon
          to="/">
          <img src={backIcon} alt="Voltar" />
        </Link>
        <div className="proffy">
          <div className="proffy-fundo">
            <img src={logoImg} alt="Proffy Logo" />
            <h2>Sua plataforma de <br /> estudos online.</h2>
          </div>
        </div>
      </div>

      <div className="left-side">
        <div className="content-box">
          {props.children}
        </div>
      </div>
    </section>
  );
}

export default SplitScreen;

and here's my CSS:

.split-page-container {
  width: 100vw;
  height: 100vh;

  display: flex;
  flex-flow: column nowrap;
}

.left-side, .right-side {
  display: flex;
  flex-direction: column;
  flex: 1;
  align-items: center;
  justify-content: center;
}

.left-side {
  background: var(--color-background);
}

.right-side {
  background: var(--color-primary);
}

.content-box {
  padding: 5.6rem 3.2rem;
}

.back-arrow {
  align-self: flex-start;
  padding: 1.2rem 1.8rem;
  height: 0;
  color: var(--color-text-in-primary);
}

.right-side a {
  transition: opacity 0.2s;
}

.right-side a:hover {
  opacity: 0.6;
}

.proffy {
  height: 37.9rem;
  display: flex;
  flex-direction: column;
  align-items: center;
  justify-content: center;
}

.proffy-fundo {
  display: flex;
  flex-flow: column;
  align-items: center;
  justify-content: center;
  width: 23.8rem;
  height: 26.6rem;
  background-image: url('../../assets/images/success-background.svg');
  background-position: center;
  background-size: contain;
}

.proffy-fundo img {
  width: 16rem;
}

.proffy-fundo h2 {
  width: 16rem;
  
  text-align: left;
  font-weight: 500;
  font-size: 1.6rem;
  margin-top: 0.8rem;

  color: var(--color-text-in-primary);
}

@media (min-width: 1100px) {
  .split-page-container {
    flex-flow: row-reverse nowrap;       // How can I delete this .split-page-container styling on
  }                                      // my LoginPage container?

  .back-arrow {
    color: var(--color-primary-darker);
    transform: translate(-39vw, -23vh);
  }

  .right-side a {
    transition: opacity 0.2s;
  }
  
  .right-side a:hover {
    opacity: 0.8;
  }

  .proffy-fundo {
    width: 40rem;
    height: 58.4rem;
  }

  .proffy-fundo img {
    width: 33.4rem;
  }

  .proffy-fundo h2 {
    width: 33.4rem;

    text-align: left;
    font-weight: 500;
    font-size: 2.4rem;
    line-height: 3.4rem;
    margin-top: 0.8rem;
  }
}

ANSWER

Answered 2020-Aug-21 at 03:35

You can use the location pathname and check if on your login route.

useLocation

If not on your login route then conditionally render the back button.

import React from 'react';
import { Link, useLocation, useHistory, withRouter } from 'react-router-dom';

import logoImg from '../../assets/images/logo.svg';
import backIcon from '../../assets/images/icons/back.svg';

import './styles.css';

function SplitScreen(props: { children: React.ReactNode; }) {
  const { pathname } = useLoction();

  const showBack = !pathname.startsWith("/login");

  return (
    <section className="split-page-container">
      <div className="right-side">
        {showBack && (
          <Link
            className="back-arrow"
            to="/">
            <img src={backIcon} alt="Voltar" />
          </Link>
        )}
        <div className="proffy">
          <div className="proffy-fundo">
            <img src={logoImg} alt="Proffy Logo" />
            <h2>Sua plataforma de <br /> estudos online.</h2>
          </div>
        </div>
      </div>

      <div className="left-side">
        <div className="content-box">
          {props.children}
        </div>
      </div>
    </section>
  );
}

If you simply want to swap the left and right sides you can swap the classnames.

function SplitScreen(props: { children: React.ReactNode; }) {
  const { pathname } = useLoction();

  const showBack = !pathname.startsWith("/login");

  return (
    <section className="split-page-container">
      <div className="left-side"> // <-- now the left side
        {showBack && (
          <Link
            className="back-arrow"
            to="/">
            <img src={backIcon} alt="Voltar" />
          </Link>
        )}
        <div className="proffy">
          <div className="proffy-fundo">
            <img src={logoImg} alt="Proffy Logo" />
            <h2>Sua plataforma de <br /> estudos online.</h2>
          </div>
        </div>
      </div>

      <div className="right-side"> // <-- now the right side
        <div className="content-box">
          {props.children}
        </div>
      </div>
    </section>
  );
}

Source https://stackoverflow.com/questions/63515982

QUESTION

Converting a block of code into a function results in error

Asked 2020-Jun-19 at 01:07

i was trying to clean up a snippet of code but when migrate a part of code into a function it started pushing me an exception, see as below:

Here is the snippet which I want to clean up:

import pandas as pd
import os

df = pd.read_csv('winequality-red.csv', sep=';')

labels = list(df.columns)
for index, label in enumerate(labels):
    labels[index] = labels[index].replace(' ', '_')


substance = 'pH'
median = df[substance].mean()
for index, substance in enumerate(df[substance]):
    if substance >= median:
        df.loc[index, substance] = 'high'
    else:
        df.loc[index, substance] = 'low'
print(df.groupby(substance).quality.mean())

The idea is to create two functions instead and call them anytime i need to evaluate a substance, with that in mind i did:

def substance_mean(substance):
    return df[substance].mean()

def substance_evaluation(substance):
    for index, substance in enumerate(df[substance]):
        if substance >= substance_mean(substance):
            df.loc[index, substance] = 'high'
        else:
            df.loc[index, substance] = 'low'
    print(df.groupby(substance).quality.mean())

substance_evaluation('pH')

When i ran the code the following exception is thrown:

Traceback (most recent call last):
  File "/home/atila/Desktop/estudos/udacity/aws_ML/venv-ml/lib/python3.6/site-packages/pandas/core/indexes/base.py", line 2646, in get_loc
    return self._engine.get_loc(key)
  File "pandas/_libs/index.pyx", line 111, in pandas._libs.index.IndexEngine.get_loc
  File "pandas/_libs/index.pyx", line 138, in pandas._libs.index.IndexEngine.get_loc
  File "pandas/_libs/hashtable_class_helper.pxi", line 1619, in pandas._libs.hashtable.PyObjectHashTable.get_item
  File "pandas/_libs/hashtable_class_helper.pxi", line 1627, in pandas._libs.hashtable.PyObjectHashTable.get_item
KeyError: 3.51

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/atila/Desktop/estudos/udacity/aws_ML/app.py", line 34, in <module>
    substance_evaluation('pH')
  File "/home/atila/Desktop/estudos/udacity/aws_ML/app.py", line 28, in substance_evaluation
    if substance >= substance_mean(substance):
  File "/home/atila/Desktop/estudos/udacity/aws_ML/app.py", line 24, in substance_mean
    return df[substance].mean()
  File "/home/atila/Desktop/estudos/udacity/aws_ML/venv-ml/lib/python3.6/site-packages/pandas/core/frame.py", line 2800, in __getitem__
    indexer = self.columns.get_loc(key)
  File "/home/atila/Desktop/estudos/udacity/aws_ML/venv-ml/lib/python3.6/site-packages/pandas/core/indexes/base.py", line 2648, in get_loc
    return self._engine.get_loc(self._maybe_cast_indexer(key))
  File "pandas/_libs/index.pyx", line 111, in pandas._libs.index.IndexEngine.get_loc
  File "pandas/_libs/index.pyx", line 138, in pandas._libs.index.IndexEngine.get_loc
  File "pandas/_libs/hashtable_class_helper.pxi", line 1619, in pandas._libs.hashtable.PyObjectHashTable.get_item
  File "pandas/_libs/hashtable_class_helper.pxi", line 1627, in pandas._libs.hashtable.PyObjectHashTable.get_item
KeyError: 3.51

ANSWER

Answered 2020-Jun-19 at 01:07

I can't run it but all your problem is that inside substance_evaluation() you use the same name substance for two variables which should keep different values.

First you have substance in

 def substance_evaluation(substance)

and this variable should keep "ph" but later you use

 for ..., substance in ...:

which assign different value to this variable (in place of "ph") and later you use

 ... >= substance_mean(substance)

to calculate mean for "ph" but in this moment substance doesn't have value "ph" but 3.51 (as show error KeyError: 3.51)

You wouldn't have this problem if in function you would keep

 median = df[substance].mean()

and

 if substance >= median:

Besides using function to run single line of code is waste of time.

And keeping this line you calculate median only once - before loop. Using function inside loop you calculate the same value many times - and it is also waste of time.

I think in both version (with and without function) you can still have problem with substance because you use it also in df.loc[index, substance] so it may try to do df.loc[index, 3.51] instead of df.loc[index, "ph"]. You should use different name ie. value

for ..., value in ...:
    if value >= median:

You should have one function like this:

def substance_evaluation(substance):

    median = df[substance].mean()

    for index, value in enumerate(df[substance]):
        if value >= median:
            df.loc[index, substance] = 'high'
        else:
            df.loc[index, substance] = 'low'

    print(df.groupby(substance).quality.mean())

But I think you could write it simple.

def substance_evaluation(substance):

    median = df[substance].mean()

    mask = (df[substance] >= mediam)

    df[substance][  mask ] = 'high'
    df[substance][ ~mask ] = 'low'

    print(df.groupby(substance).quality.mean())

Eventually with np.where()

def substance_evaluation(substance):

    median = df[substance].mean()

    mask = (df[substance] >= mediam)

    df[substance] = np.where(mask, 'high', 'low')

    print(df.groupby(substance).quality.mean())

In this version you can easily create new column with values

    df["new column"] = np.where(mask, 'high', 'low')

EDIT: Minimal working code for test

import pandas as pd
import random
import numpy as np
import time

def version1(df, substance):
    median = df[substance].mean()
    for index, value in enumerate(df[substance]):
        if value >= median:
            df.loc[index, substance] = 'high'
        else:
            df.loc[index, substance] = 'low'

def version2(df, substance):
    median = df[substance].mean()
    mask = (df[substance] >= median)
    df[substance][  mask ] = 'high'
    df[substance][ ~mask ] = 'low'

def version3(df, substance):
    median = df[substance].mean()
    mask = (df[substance] >= median)
    df[substance] = np.where(mask, 'high', 'low')

# ---

random.seed(0) # to generate always the same values

df = pd.DataFrame({'pH': [random.randint(0,7) for _ in range(5)]})

substance = 'pH'

print('--- before ---')
print(df)

# ---

df1 = df.copy()
start = time.time()

version1(df1, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

# ---

df2 = df.copy()
start = time.time()

version2(df2, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

# ---

df3 = df.copy()
start = time.time()

version3(df3, substance)

end = time.time()
print('--- after --- time:', end-start)
print(df1)

Source https://stackoverflow.com/questions/62459053

QUESTION

Python numpy error: only integer scalar arrays can be converted to a scalar index

Asked 2020-Jun-05 at 16:17

I'm trying to simulate a simple pendulum using pylot. For that, I created the class Pendulum and, in one of the methods, I keep getting the same error.

def __init__(self, L = 1, M = 1, G = 9.8, origin = (0, 0), init = [60, 0]):
    self.init_state = np.array(init, dtype = 'float')
    self.params = (L, M, G)
    self.origin = origin
    self.time = 0
    self.state = self.init_state * (np.pi/180.)

def dstate_dt(self, state, t):
    """compute the derivative of the given state"""
    (L, M, G) = self.params

    dydx = np.zero_lie(state)
    dydx[0] = state[1]
    dydx[1] = -(G/L)*np.sin(state[0])

    return dydx

The error code reads:

File "C:\Users\Lucas\Anaconda3\envs\Spyder\lib\site-packages\numpy\core\fromnumeric.py", line 47, in _wrapit result = getattr(asarray(obj), method)(*args, **kwds)

TypeError: only integer scalar arrays can be converted to a scalar index

Going into the refered line, in a folder called 'fromnumeric.pi', the given function reads:

def _wrapit(obj, method, *args, **kwds):
try:
    wrap = obj.__array_wrap__
except AttributeError:
    wrap = None
result = getattr(asarray(obj), method)(*args, **kwds)
if wrap:
    if not isinstance(result, mu.ndarray):
        result = asarray(result)
    result = wrap(result)
return result

What triggered this error and how can I fix it? The full traceback is this:

File "C:\Users\Lucas\Desktop\Estudos\Python\Simple Pendulum.py", line 86, in animate(0)

File "C:\Users\Lucas\Desktop\Estudos\Python\Simple Pendulum.py", line 80, in animate line.set_data(pendulum.position())

File "C:\Users\Lucas\Desktop\Estudos\Python\Simple Pendulum.py", line 27, in position x = np.cumsum(self.origin[0], L*np.sin(self.state[0]))

File "<array_function internals>", line 6, in cumsum

File "C:\Users\Lucas\Anaconda3\envs\Spyder\lib\site-packages\numpy\core\fromnumeric.py", line 2423, in cumsum return _wrapfunc(a, 'cumsum', axis=axis, dtype=dtype, out=out)

File "C:\Users\Lucas\Anaconda3\envs\Spyder\lib\site-packages\numpy\core\fromnumeric.py", line 58, in _wrapfunc return _wrapit(obj, method, *args, **kwds)

File "C:\Users\Lucas\Anaconda3\envs\Spyder\lib\site-packages\numpy\core\fromnumeric.py", line 47, in _wrapit result = getattr(asarray(obj), method)(*args, **kwds)

TypeError: only integer scalar arrays can be converted to a scalar index

ANSWER

Answered 2020-Jun-05 at 16:17

The traceback shows that the error occurs in this line (from your code)

File "C:\Users\Lucas\Desktop\Estudos\Python\Simple Pendulum.py", line 27, in 
position x = np.cumsum(self.origin[0], L*np.sin(self.state[0]))

I don't see that use of cumsum in your code sample! The posted methods don't appear at all in the traceback.

You pass cumsum two arguments

self.origin[0]
L*np.sin(self.state[0]

But if you take time to check the docs for cumsum you'll see:

numpy.cumsum(a, axis=None, dtype=None, out=None)[source]

It takes one array argument a. The second argument is axis, which can only be a scalar, a single number. That's the error is complaining about!

I can't suggest a fix because I don't know what you intend with the cumsum call.

Source https://stackoverflow.com/questions/62216861

QUESTION

Running C++ client/server for parallel processing using MPI

Asked 2020-Apr-13 at 17:45

Introduction

In order to parallelize numerical integration in C++, I want to use a client/server approach on my local machine. For this, I am using the message passing interface for C++.

My code

So I first tried a hello world setup, where I will send a message from the client to the server. For this I have two files in the same directory. Here is the code for the Server, server.cpp:

#include<mpi.h>
#include<stdio.h>
#include<stdlib.h>

int size, rank, msg;

int main(int argc, char *argv[]){
    MPI_Comm client;
    MPI_Status status;
    char portname[MPI_MAX_PORT_NAME];

    MPI_Init(&argc,&argv);
    MPI_Comm_size(MPI_COMM_WORLD,&size);
    MPI_Comm_rank(MPI_COMM_WORLD,&rank);

    MPI_Open_port(MPI_INFO_NULL, portname);
    printf("portname: %s\n", portname);
    MPI_Comm_accept(portname, MPI_INFO_NULL, 0, MPI_COMM_SELF, &client);
    printf("client connected\n");
    MPI_Recv(&msg, 1, MPI_INT, MPI_ANY_SOURCE, MPI_ANY_TAG, client, &status);
    printf("msg: %d\n", msg);
    MPI_Comm_free(&client);
    MPI_Close_port(portname);
    MPI_Finalize();
}

Here is the code for the Client, client.cpp:

#include<mpi.h>
#include<stdio.h>
#include<stdlib.h>
#include<string.h>

int size, rank;
int main(int argc, char *argv[]){
    MPI_Comm server;
    int msg, tag, dest;
    char portname[MPI_MAX_PORT_NAME];

    MPI_Init(&argc,&argv);
    MPI_Comm_size(MPI_COMM_WORLD,&size);
    MPI_Comm_rank(MPI_COMM_WORLD,&rank);
    if (argc >= 2){
        printf("Trying connect to %s\n", argv[1]);
        strcpy(portname, argv[1]);
        MPI_Comm_connect(portname, MPI_INFO_NULL, 0, MPI_COMM_WORLD, &server);
        msg = 42; tag = 0; dest = 0;
        MPI_Send(&msg, 1, MPI_INT, dest, tag, servidor);
        MPI_Comm_disconnect(&server);
    }
    MPI_Finalize();
}

How I tried to run my code

I compiled both client and server using mpiCC -g -Wall -o client.out client.cpp and mpiCC -g -Wall -o server.out server.cpp respectively.

Now I open two different terminals and I use mpirun -np 1 ./server.out in the first terminal to run the server. This gives me the portname so I can use mpirun -np 1 ./client.out <PORTNAME> in the second terminal to run the client. However, I get the following error:

Trying connect to <PORTNAME>
--------------------------------------------------------------------------
The user has called an operation involving MPI_Connect and/or MPI_Accept
that spans multiple invocations of mpirun. This requires the support of
the ompi-server tool, which must be executing somewhere that can be
accessed by all participants.

Please ensure the tool is running, and provide each mpirun with the MCA
parameter "pmix_server_uri" pointing to it.
--------------------------------------------------------------------------
--------------------------------------------------------------------------
Your application has invoked an MPI function that is not supported in
this environment.

  MPI function: MPI_Comm_connect
  Reason:       Underlying runtime environment does not support accept/connect functionality
--------------------------------------------------------------------------
[ubuntu-workstation:00101] *** An error occurred in MPI_Comm_connect
[ubuntu-workstation:00101] *** reported by process [23056836,0]
[ubuntu-workstation:00101] *** on communicator MPI_COMM_WORLD
[ubuntu-workstation:00101] *** MPI_ERR_INTERN: internal error
[ubuntu-workstation:00101] *** MPI_ERRORS_ARE_FATAL (processes in this communicator will now abort,
[ubuntu-workstation:00101] ***    and potentially your MPI job)

What I tried

I found this blog post, where a very similar error occurs.

It seems I only have to start this ominous "ompi-server tool", however, being new to MPI, I have no idea where to find this tool and how to start it... So how can I fix the error?

ANSWER

Answered 2020-Apr-13 at 17:45

Unfortunately, it appears that the latest version of Open MPI that has working accept/connect functionality is Open MPI 1.6.5. Starting with v1.7 the support is broken and with ORTE 2.x the required support is missing altogether and its implementation is low priority as indicated in the issue. You should either somehow implement your solution without client/server functionality, downgrade to Open MPI 1.6.5, or simply switch to MPICH or Intel MPI. The latter is now free for use as part of oneAPI and I just tested that your code works with it after fixing the typo in client.cpp (server instead of servidor).

Source https://stackoverflow.com/questions/61191379

QUESTION

Nodejs with sequelize Returns Error Running Update

Asked 2020-Jan-09 at 23:21

I have this update function in user controller:

  async update(req, res) {
    const schema = Yup.object().shape({
      name: Yup.string().required(),
      email: Yup.string().email(),
      oldPassword: Yup.string().min(6),
      password: Yup.string()
        .min(6)
        .when('oldPassword', (oldPassword, field) =>
          oldPassword ? field.required() : field
        ),
       confirmPassword: Yup.string().when('password', (password, field) =>
         password ? field.required().oneOf([Yup.ref('password')]) : field
       ),
    });

    if (!(await schema.isValid(req.body))) {
      return res.status(400).json({ error: 'Validação de entrada falhou' });
    }
    const { email, oldPassword } = req.body;
    console.log(email);
    const user = await User.findByPk(req.userId);
    if (email && email !== user.email) {
      const userExists = await User.findOne({ where: { email } });

      if (userExists) {
        return res.status(400).json({ error: 'E-mail já cadastrado' });
      }
    }

    if (oldPassword && !(await user.checkPassword(oldPassword))) {
      return res.status(401).json({ eror: 'As senhas não são iguais' });
    }

    const { id, name, provider } = await User.update(req.body);
    return res.json({
      id,
      name,
      email,
      provider,
    });
  }

When running node js returns me the following error warning that I have a missing parameter:

(node:2608) UnhandledPromiseRejectionWarning: AssertionError [ERR_ASSERTION]: Missing where attribute in the options parameter
    at Function._optionsMustContainWhere (D:\Estudos\Rocketseat\BootCamp\Módulo 02\backend-gobarber2\node_modules\sequelize\lib\model.js:3427:5)    
    at Function.update (D:\Estudos\Rocketseat\BootCamp\Módulo 02\backend-gobarber2\node_modules\sequelize\lib\model.js:3053:10)
    at update (D:\Estudos\Rocketseat\BootCamp\Módulo 02\backend-gobarber2\src\app\controllers\UserController.js:95:57)

Could someone give me a light on what I'm doing wrong?

bcryptjs: 2.4.3
express: 4.17.1
jsonwebtoken: 8.5.1
multer: 1.4.2
pg: 7.17.0
pg-hstore: 2.3.3
sequelize: 5.21.3
yup": 0.28.0

ANSWER

Answered 2020-Jan-09 at 23:21

You forgot to where attribute. User will be update but which user? You need to change here;

const { id, name, provider } = await User.update(req.body);

like this;

const { id, name, provider } = await User.update(req.body, {
   where: {? : ?}
});

Source https://stackoverflow.com/questions/59654670

QUESTION

How can I remove a large empty space from my page?

Asked 2019-Mar-28 at 22:45

I was working in my page and I have seen that there is a large empty space at right, I can see it moving the scrollbar. How can I remove it?

This is my code:

`<!doctype html>
<html>
<head>
<title>Agenda - Central de Estudos</title>
<meta charset="utf-8">
<meta name="author" content="Bruno M. B. Sdoukos">
<meta name="description" content="Central de estudos. Todas as matérias. Temas abordados em sala de aula.">
<meta name="keywords" content="estudo, matéria, escola">
<link rel="stylesheet" href="G:/TRABALHOS/Central de estudos - Arquivos/header_style.css">
<link rel="stylesheet" href="G:/TRABALHOS/Central de estudos - Arquivos/footer_style.css">
<style>
h1{text-align: center;}
h2{font-size: 18px;}
article{
    margin: 30px;
    height: 721.5px;
}
@font-face{
    font-family: Sepet;
    src: url(G:/Programação/Webdesign/Curso-de-Webdesign/Projeto-Fashion/Fontes/Sepet.ttf);
}
article img{
    width: 700px;
    position: absolute;
    bottom: 250px;
    left: 900px;
}
.handwriting{
    font-family: Sepet;
    font-size: 30px;
    position: relative;
    left: 1000px;
    bottom: 150px;
}
.handwriting a{
    text-decoration: none;
}
</style>
</head>
<body>
    <header>
        <h1>Central de Estudos<span>     <a href="file:///G:/TRABALHOS/Central de Estudos - Arquivos/index-login-on.html">Início</a> <a href="#">Matérias</a> <a href="file:///G:/TRABALHOS/Central%20de%20estudos%20-%20Arquivos/Exerc%C3%ADcios.html">Exercícios</a> <a href="file:///G:/TRABALHOS/Central%20de%20estudos%20-%20Arquivos/Agenda.html">Agenda</a> <a href="file:///G:/TRABALHOS/Central%20de%20estudos%20-%20Arquivos/Login-login-on.html">Login</a></span></h1>
        <img src="https://cdn.pixabay.com/photo/2018/07/20/12/26/earth-3550553_960_720.png" alt="Globo escolar">
    </header>
    <main>
        <article>
            <h1>Agenda</h1>
            <hr>
            <h2>Tarefas</h2>
            <ul>
               <li>25/03/2019 | Ciências | Livro - Pg. 17 Ex. 7</li>
               <li>26/03/2019 | Português | Livro - Pg. 46</li>
               <li>26/03/2019 | Geografia | Caderno - Atividade 07</li>
            </ul>
            <h2>Provas</h2>
            <ul>
                <li>26/03/2019 | Artes | Conteúdos abordados (diversos)</li>
                <li>01/04/2019 | Ciências | O ser humano (visão geral) e a célula (visão geral)</li>
            </ul>
            <h2>Entrega de trabalhos</h2>
            <p>Não há trabalhos para entrega no momento.</p>
            <img src="https://cdn.pixabay.com/photo/2012/04/18/14/41/opened-37229_960_720.png">
            <p class="handwriting"><a href="#">Aulas</a></p>
        </article>
    </main>
    <footer>
        <p>Autoria do site de Bruno M. B. Sdoukos.</p>
        <p>Copyright &copy; 2019</p>
    </footer>
</body>
</html>`

I think there isn't a problem with margins, I already tried to put "margin: 0" in the "style" but it doesn't solve the problem.

Obs: The page is in a my computer's file, so I can not put here its URL.

ANSWER

Answered 2019-Mar-28 at 22:45

One way to debug this yourself is to add the following CSS rule:

* {
  border: 1px solid red;
}

Doing so will show you immediately which elements are responsible for the scroll.

There are 2 elements causing the horizontal scroll due to their large left property values. Either remove these large values or rethink your layout to fit within the starting viewport.

article img {
  width: 700px;
  position: absolute;
  bottom: 250px;
  left: 900px; /* <-- Causing horizontal scroll */
}
.handwriting {
  font-family: Sepet;
  font-size: 30px;
  position: relative;
  left: 1000px; /* <-- Causing horizontal scroll */
  bottom: 150px;
}

Source https://stackoverflow.com/questions/55407792

QUESTION

Rendering a layout using an example as guide

Asked 2019-Feb-25 at 14:40

I have this component that renders a menu:

import React, { Component } from 'react'
import { BrowserRouter as Router, Route, NavLink } from 'react-router-dom'

import Intro from './Intro'
import Houses from './Houses'
import PortfolioPage from './PortfolioPage'
import Cronology from './Cronology'

var data = require('./db.json');

class PortfolioMenu extends Component {
  constructor(props) {
    super(props)
    this.state = {
      portfolioClass: "",
      interiors: [],
      furnitures: [],
      studies: [],
      houses: []
    }
  }

  componentDidMount() {
    this.setState({
      interiors: data.interiors[0],
      furnitures: data.furnitures[0],
      studies: data.studies[0],
      houses: data.houses
    })
  }        
  render() {      
    return (
      <div>
        <Router>
          <div class="wrapper2">
            <div class="wrapper-portfolio">
              <Route exact path='/portfolio' render={() => <Intro />} />
              <Route exact path='/portfolio/casas' render={() => <Houses data={this.state.houses}/>} />
              <Route exact path='/portfolio/interiores' render={() => <PortfolioPage data={this.state.interiors}/>} />
              <Route exact path='/portfolio/moveis' render={() => <PortfolioPage data={this.state.furnitures}/>} />
              <Route exact path='/portfolio/estudos' render={() => <PortfolioPage data={this.state.studies}/>} />
              <Route exact path='/portfolio/cronologia' render={() => <Cronology />} />
            </div>
            <nav>
              <ul className={`portfolio-menu ${portfolioClass}`}>
                <li><NavLink activeClassName="active" isActive={this.isActive} exact to="/portfolio">• introdução</NavLink></li>
                <li><NavLink activeClassName="active" exact to="/portfolio/casas">• casas</NavLink></li>
                <li><NavLink activeClassName="active" exact to="/portfolio/interiores">• interiores</NavLink></li>
                <li><NavLink activeClassName="active" exact to="/portfolio/moveis">• móveis</NavLink></li>
                <li><NavLink activeClassName="active" exact to="/portfolio/estudos">• estudos</NavLink></li>
                <li><NavLink activeClassName="active" exact to="/portfolio/cronologia">• cronologia</NavLink></li>
              </ul>
            </nav>           
          </div>
        </Router>
      </div>
    )
  }
}


export default PortfolioMenu

And I would like to do the <li> to behave like this example below:

How can I solve it? I would like to render in this exact way that is showing on this example. Doing this distribution of li's elements. I want to make four blocks on the first row and two on the second.

ANSWER

Answered 2019-Feb-25 at 14:40

If you have to use pure CSS (as you mentioned in your comment above), you'll want to use CSS grids.

If you're open to using a third-party JavaScript library, I'd recommend looking into Material-UI. Specifically their Grid component.

Your question makes it look like you're relatively new to front-end development, so I'd recommend the second approach. Material-UI includes many commonly used components that are well tested across multiple browsers. It's a good way to create a nice layout and design without as much headache.

Source https://stackoverflow.com/questions/54868254

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