Jack Ma, 马云(馬雲), 마윈

 





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Using the MinIO API via curl

Using the MinIO API via curl is straightforward, as MinIO is compatible with Amazon S3 API, so most commands follow a similar syntax. Here’s a guide on how to use curl with the MinIO API for some common operations like uploading, downloading, and managing objects. Prerequisites Access Key and Secret Key : Obtain your MinIO Access Key and Secret Key. MinIO Endpoint : Know your MinIO server endpoint, e.g., http://localhost:9000 . Bucket : You may need an existing bucket name, or create a new one using the commands below. Authentication Header For requests to work with MinIO, you need to include authentication in the headers. MinIO uses AWS Signature Version 4 for signing requests. Common Examples 1. List Buckets To list all buckets in your MinIO account, use: curl -X GET \ - -url "http://localhost:9000/" \ - H "Authorization: AWS <AccessKey>:<Signature>" 2. Create a Bucket To create a new bucket, use: curl -X PUT \ - -url "htt...
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max_active_runs of Airflow

In Apache Airflow, if you want to ensure that a new run of a DAG doesn’t start before the previous one has completed, you can use the max_active_runs parameter in the DAG definition. Setting this parameter to 1 ensures that only one instance of the DAG is running at any given time. Setting max_active_runs for a DAG Here’s an example of how to set up a DAG with max_active_runs=1 : from airflow import DAG from airflow.operators.dummy_operator import DummyOperator from datetime import datetime # Define the DAG with DAG( 'my_dag' , description= 'A sample DAG' , schedule_interval= '@daily' , # Set your schedule start_date=datetime( 2023 , 1 , 1 ), catchup= False , max_active_runs= 1 # This prevents new runs before the previous run completes ) as dag: # Define tasks start = DummyOperator(task_id= 'start' ) end = DummyOperator(task_id= 'end' ) # Define task dependencies ...
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Create fixed rounded button by Tailwind

To create a fixed, rounded button using Tailwind CSS , you can combine Tailwind's fixed utility (for positioning) with the rounded classes (for rounding the button). This is useful if you want a button that stays in a fixed position on the screen, such as at the bottom-right corner. Here’s how to do it: Example of a Fixed Rounded Button <button class="fixed bottom -4 right -4 bg-blue -500 text-white px -6 py -3 rounded-full shadow-lg"> Fixed Button </button> Explanation: fixed : Positions the button fixed relative to the viewport. It will stay in the same position even when the user scrolls. bottom-4 : Positions the button 1rem (16px) from the bottom of the screen. right-4 : Positions the button 1rem (16px) from the right side of the screen. bg-blue-500 : Sets the background color to blue. text-white : Sets the text color to white. px-6 py-3 : Adds horizontal ( px-6 ) and vertical ( py-3 ) padding for sizing the button. rounded-full : Mak...
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DEFAULT_KEY_SERDE_CLASS_CONFIG in Kafka

The DEFAULT_KEY_SERDE_CLASS_CONFIG is a configuration property in Apache Kafka Streams. It specifies the default serializer/deserializer (Serde) to be used for the keys of messages in your Kafka Streams application. What Is a Serde? A Serde is a combination of a serializer and a deserializer : Serializer : Converts objects into a byte array to send over Kafka. Deserializer : Converts the byte array back into an object. Kafka Streams requires Serdes to know how to handle data when reading from and writing to topics. Usage of DEFAULT_KEY_SERDE_CLASS_CONFIG This property allows you to specify the default Serde class for the key of messages processed by Kafka Streams. For example, if your keys are strings, you would set the default key Serde to Serdes.String() . Example Configuration in Java: Properties props = new Properties(); props . put (StreamsConfig.DEFAULT_KEY_SERDE_CLASS_CONFIG, Serdes.String().getClass()); props . put (StreamsConfig.DEFAULT_VALUE_SERDE_CLASS_CON...
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Install and run an FTP server using Docker

To install and run an FTP server using Docker, follow these steps. We’ll use the popular stilliard/pure-ftpd image, which is a lightweight and widely used FTP server. Step 1: Install Docker Make sure Docker is installed on your machine. If it isn’t, install it using the instructions below: Ubuntu/Debian: sudo apt update sudo apt install docker.io -y Mac: Install Docker Desktop from Docker's website . Windows: Install Docker Desktop from Docker's website . Verify Docker is installed: docker --version Step 2: Pull the FTP Server Docker Image Use the stilliard/pure-ftpd image, which is a simple and effective FTP server. docker pull stilliard/ pure -ftpd Step 3: Run the FTP Server Run the FTP server container using the following command: docker run -d --name ftp-server \ - p 21 : 21 -p 30000 - 30009 : 30000 - 30009 \ - e FTP_USER_NAME=testuser \ - e FTP_USER_PASS=testpass \ - e FTP_USER_HOME= /home/testuser \ stilliard/pure-ftpd Explanation...
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Getting start with Puppeteer

To develop a program that collects data from a Single Page Application (SPA) using Puppeteer, you'll need to install Puppeteer and set up a script that navigates the SPA, interacts with elements, and extracts the desired data. Puppeteer is a Node.js library that provides a high-level API to control Chrome or Chromium browsers. Follow the steps below to create your data collection program: Step 1: Set up Node.js and Puppeteer Make sure you have Node.js installed on your machine. If not, download and install it from the official website ( https://nodejs.org/ ). Create a new Node.js project by running the following commands in your terminal: mkdir spa_data_collector cd spa_data_collector npm init - y npm install puppeteer Step 2: Create the data collection script Create a new file in the project directory, e.g., dataCollector.js , and add the following code: const puppeteer = require ( 'puppeteer' ); ( async ( ) => { try { // Launch the browser const...
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Chromium development gclient

gclient is a command-line tool used primarily in the context of Chromium development. It is part of the depot_tools suite, which is a collection of tools maintained by the Chromium project team to aid in managing large codebases like Chromium. Here are some key aspects of gclient : Source Code Management : gclient is used to manage the source code repositories that make up Chromium and its dependencies. It handles tasks such as cloning repositories, fetching updates, and managing dependencies. Synchronization : It helps synchronize the source code across different repositories and ensures that all dependencies are up to date. This is crucial in a project like Chromium, which consists of multiple interconnected modules and libraries. Usage with fetch : The most common use of gclient is in conjunction with the fetch command. For example, fetch chromium will clone the Chromium repository and all necessary dependencies into a specified directory ( src by default). Configura...
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[Ubuntu] Apache2.4.x 설치

Apache2.4.x 버전부터는 APR 과 APR-util을 별로도 설치하여야 한다. 하위버전에서는 설치파일에 포함되어 있었으나 버전 업이 되면서 삭제되어 configure를 실행하면 아래와 같은 에러메시지를 발생하면서 종료된다. Configuring Apache Portable Runtime library ... Checking for APR... no Confgirue: error: APR not found. Please read the documentation http://apr.apache.org/   에서 다운받아 설치함 *APR(Apache Portable Runtime) 설치 $ wget http://mirror.sdunix.com/apache//apr/apr-1.4.6.tar.gz $ tar xvf apr-1.4.6.tar.gz ~/apr-1.4.6$ ./configure ~/apr-1.4.6$ ./make ~/apr-1.4.6$ ./sudo make install *ARP-Util 설치 $ wget http://apache.tt.co.kr//apr/apr-util-1.4.1.tar.gz $ tar xvf apr-util-1.4.1.tar.gz ~/apr-util-1.4.1$ ./configure --with-apr=/usr/local/apr ~/apr-util-1.4.1$ make ~/apr-util-1.4.1$ sudo make install Apache 재설치시 Error 발생. configure: error: pcre-config for libpcre not found.PCRE is required and available from http://pcre.org/ *PCRE(Perl Compatible Regular Expressions) 설치 $ ...
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Python program to convert an .xlsx file to JSON using the openpyxl library

Here’s a Python program to convert an .xlsx file to JSON using the openpyxl library. Make sure you have the openpyxl library installed. If you don't have it yet, install it using: pip install openpyxl Program to Convert XLSX to JSON import openpyxl import json def xlsx_to_json (file_path, sheet_name=None) : try : # Load the workbook and select a sheet workbook = openpyxl.load_workbook(file_path) sheet = workbook[sheet_name] if sheet_name else workbook.active # Extract data from the sheet data = [] headers = [cell.value for cell in next(sheet.iter_rows(min_row= 1 , max_row= 1 ))] for row in sheet.iter_rows(min_row= 2 , values_only= True ): entry = {headers[i]: row[i] for i in range(len(headers))} data.append(entry) # Convert the data to JSON format json_data = json.dumps(data, indent= 4 ) # Save the JSON to a file json_file = file_path.repla...
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Spring Boot with Kafka Streams

Using Spring Boot with Kafka Streams simplifies the process further. Spring Boot provides excellent support for Kafka through Spring Kafka , allowing seamless integration and management. Here’s a step-by-step guide to building a Kafka Streams application with Spring Boot: 1. Setup Your Spring Boot Application Add Dependencies Include the necessary dependencies in your pom.xml : < dependency > < groupId > org.springframework.boot </ groupId > < artifactId > spring-boot-starter </ artifactId > </ dependency > < dependency > < groupId > org.springframework.kafka </ groupId > < artifactId > spring-kafka </ artifactId > </ dependency > < dependency > < groupId > com.google.code.gson </ groupId > < artifactId > gson </ artifactId > < version > 2.8.9 </ version > <!-- Version may vary --> </ dependency > 2. Configure Ka...
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