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nestjs testing

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Restu Wahyu Saputra answered on August 2, 2022 Popularity 7/10 Helpfulness 1/10

answer nestjs testing

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nestjs testing

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import { Test, TestingModule } from '@nestjs/testing';
import { HttpStatus, INestApplication } from '@nestjs/common';
import * as request from 'supertest';
import { HealthcheckController } from './healthcheck.controller';

describe('HealthcheckController', () => {
    let controller: HealthcheckController;
    let app: INestApplication;

    beforeEach(async () => {
        const module: TestingModule = await Test.createTestingModule({
            controllers: [HealthcheckController],
        }).compile();

        app = module.createNestApplication();
        controller = module.get<HealthcheckController>(HealthcheckController);

        await app.init();
    });

    afterEach(() => {
        jest.clearAllMocks();
    });

    afterAll(async () => {
        await app.close();
    });

    describe('healthcheck', () => {
        it('should return "OK" string', async () => {
            const result = controller.healthcheck();
            expect(result).toBe('OK');
        });
    });
});

Popularity 7/10 Helpfulness 1/10 Language typescript

Source: Grepper

Tags: nestjs-testing typescript

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Contributed on Oct 02 2024

Restu Wahyu Saputra

0 Answers Avg Quality 2/10

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pandas apply

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import pandas as pd

s = pd.Series([1,2,3,4,5])
  
# adding 5 to each value
new = s.apply(lambda num : num + 5)
  
# printing elements of old and new series
print(s.head().values,"\n",new.head().values)
#  [1 2 3 4 5] 
#  [6 7 8 9 10]

Popularity 10/10 Helpfulness 3/10 Language python

Source: Grepper

Tags: apply appl

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Contributed on Aug 02 2022

Clean Cottonmouth

0 Answers Avg Quality 2/10

pandas apply

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# This function doubles the input value
def double(x):
  return 2*x
 
# Apply this function to double every value in a specified column
df.column1 = df.column1.apply(double)
 
# Lambda functions can also be supplied to `apply()`
df.column2 = df.column2.apply(lambda x : 3*x)
 
# Applying to a row requires it to be called on the entire DataFrame
df['newColumn'] = df.apply(lambda row: 
  row['column1'] * 1.5 + row['column2'],
  axis=1
)

Popularity 10/10 Helpfulness 3/10 Language python

Source: www.codecademy.com

Tags: pandas-apply pandas-app

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Contributed on Aug 03 2023

Wide-eyed Wren

0 Answers Avg Quality 2/10

nestjs test fails

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Nestjs testing module not found

{
  ...
  "moduleNameMapper": {
    "^@Shared/(.)*$": "<rootDir>/src/app/shared/$1"
  }
}

If you're coming from google then this can also happen if VSCode autocompletes your imports as src/xyz/abc/service.ts instead of ../xyz/abc/service.ts.

When running tests the test code won't be able to locate the correct service(s) at run-time. It needs fully relative paths without an absolute 'src/' at the beginning.

As you are using typescript's path mapping, you need to also update your jest config with the mapped paths as well. Your jest config needs to have the following added:Assuming that your is set to be . and not ./src. You can find more info on it here. https://kulshekhar.github.io/ts-jest/user/config/#paths-mapping

Popularity 10/10 Helpfulness 2/10 Language javascript

Source: stackoverflow.com

Tags: javascript j

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Contributed on Jan 30 2023

barisx

0 Answers Avg Quality 2/10

pandas apply

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import pandas as pd
 
# Function to add
def add_values(row):
    return row['A'] + row['B'] + row['C']
 
def main():
    # Create a dictionary with three fields each
    data = {
        'A': [1, 2, 3],
        'B': [4, 5, 6],
        'C': [7, 8, 9]}
 
    # Convert the dictionary into DataFrame
    df = pd.DataFrame(data)
    print("Original DataFrame:\n", df)
 
    # Apply the user-defined function to every row
    df['add'] = df.apply(add_values, axis=1)
 
    print('\nAfter Applying Function: ')
    # Print the new DataFrame
    print(df)
 
if __name__ == '__main__':
    main()

Popularity 6/10 Helpfulness 1/10 Language python

Source: www.geeksforgeeks.org

Tags: pandas-apply python

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Contributed on Oct 02 2024

Innocent Iguana

0 Answers Avg Quality 2/10

python etl

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import pandas as pd
import psycopg2
from sqlalchemy import create_engine

# The Extract phase: Just load the data using pd.read_csv, pd.read_parquet, pd.read_json etc
# The Transform phase
def transform(sql_query, dbname='hr', user='postgres', password='postgres', port='5432', host='localhost'):
    # Create a connection to the PostgreSQL database using psycopg2
    conn = psycopg2.connect(dbname=dbname, user=user, password=password, host=host, port=port)
    df = pd.read_sql(sql_query, conn) # Execute the query and load the results into a DataFrame
    conn.close() # Close the psycopg2 connection
    return df # Return the DataFrame

# The Load phase
def load(df, table_name, dbname='hr', user='postgres', password='postgres', port='5432', host='localhost'):
    # Create a connection to the PostgreSQL database using SQLAlchemy for to_sql
    engine = create_engine(f'postgresql://{user}:{password}@{host}:{port}/{dbname}')

    # Persist the DataFrame to the SQL table
    df.to_sql(table_name, engine, if_exists='append', index=False) # if_exists='replace' for replacement

    print(f"DataFrame persisted to table '{table_name}' successfully!")

# transform the data from PostgreSQL
query_result = transform('SELECT * FROM jobs')
# Load or Persist the result in the PostgreSQL database
load(query_result, 'final_table')

Popularity 9/10 Helpfulness 1/10 Language python

Source: Grepper

Tags: etl

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Contributed on Oct 02 2024

Innocent Iguana

0 Answers Avg Quality 2/10

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