search
HomeBackend DevelopmentPython TutorialCreating a Local Environment to Operate GCS Emulator from Flask

Creating a Local Environment to Operate GCS Emulator from Flask

When creating an application that manipulates GCS (Google Cloud Storage) through Flask on Cloud Run, I wanted to use a GCS emulator in the local environment. This document describes how to set up such an environment.

Emulator to Use

  • fsouza/fake-gcs-server

Sample code

I created sample code in the following repository. By following the instructions in README.md, you can use the GCS emulator in a local environment to upload, download, and delete files.

Since you can start everything simply by cloning the repository and running make up, setup is straightforward.

  • flask-gcs

Contents of docker-compose.yml

To use the GCS emulator in the Flask container, the STORAGE_EMULATOR_HOST environment variable is set:

services:
  app:
    environment:
      - STORAGE_EMULATOR_HOST=http://gcs:4443

Configuring Flask’s StorageClient

The STORAGE_EMULATOR_HOST environment variable is checked to determine whether to use the emulator:

def get_storage_client():
    emulator_host = Config.STORAGE_EMULATOR_HOST

    if emulator_host:
        client = storage.Client(
            credentials=AnonymousCredentials(),
            project="test",
        )
    else:
        client = storage.Client()

    return client

Conclusiuon

When building an application on Cloud Run that manipulates GCS through Flask, you might want to use a GCS emulator in your local environment. These are the setup steps. Note that in production you will not use the GCS emulator, so simply do not set the STORAGE_EMULATOR_HOST environment variable, specify your BUCKET_NAME, and grant the appropriate permissions to Cloud Run.

The above is the detailed content of Creating a Local Environment to Operate GCS Emulator from Flask. For more information, please follow other related articles on the PHP Chinese website!

Statement
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn
How to Use Python to Find the Zipf Distribution of a Text FileHow to Use Python to Find the Zipf Distribution of a Text FileMar 05, 2025 am 09:58 AM

This tutorial demonstrates how to use Python to process the statistical concept of Zipf's law and demonstrates the efficiency of Python's reading and sorting large text files when processing the law. You may be wondering what the term Zipf distribution means. To understand this term, we first need to define Zipf's law. Don't worry, I'll try to simplify the instructions. Zipf's Law Zipf's law simply means: in a large natural language corpus, the most frequently occurring words appear about twice as frequently as the second frequent words, three times as the third frequent words, four times as the fourth frequent words, and so on. Let's look at an example. If you look at the Brown corpus in American English, you will notice that the most frequent word is "th

How Do I Use Beautiful Soup to Parse HTML?How Do I Use Beautiful Soup to Parse HTML?Mar 10, 2025 pm 06:54 PM

This article explains how to use Beautiful Soup, a Python library, to parse HTML. It details common methods like find(), find_all(), select(), and get_text() for data extraction, handling of diverse HTML structures and errors, and alternatives (Sel

How to Perform Deep Learning with TensorFlow or PyTorch?How to Perform Deep Learning with TensorFlow or PyTorch?Mar 10, 2025 pm 06:52 PM

This article compares TensorFlow and PyTorch for deep learning. It details the steps involved: data preparation, model building, training, evaluation, and deployment. Key differences between the frameworks, particularly regarding computational grap

Mathematical Modules in Python: StatisticsMathematical Modules in Python: StatisticsMar 09, 2025 am 11:40 AM

Python's statistics module provides powerful data statistical analysis capabilities to help us quickly understand the overall characteristics of data, such as biostatistics and business analysis. Instead of looking at data points one by one, just look at statistics such as mean or variance to discover trends and features in the original data that may be ignored, and compare large datasets more easily and effectively. This tutorial will explain how to calculate the mean and measure the degree of dispersion of the dataset. Unless otherwise stated, all functions in this module support the calculation of the mean() function instead of simply summing the average. Floating point numbers can also be used. import random import statistics from fracti

Serialization and Deserialization of Python Objects: Part 1Serialization and Deserialization of Python Objects: Part 1Mar 08, 2025 am 09:39 AM

Serialization and deserialization of Python objects are key aspects of any non-trivial program. If you save something to a Python file, you do object serialization and deserialization if you read the configuration file, or if you respond to an HTTP request. In a sense, serialization and deserialization are the most boring things in the world. Who cares about all these formats and protocols? You want to persist or stream some Python objects and retrieve them in full at a later time. This is a great way to see the world on a conceptual level. However, on a practical level, the serialization scheme, format or protocol you choose may determine the speed, security, freedom of maintenance status, and other aspects of the program

What are some popular Python libraries and their uses?What are some popular Python libraries and their uses?Mar 21, 2025 pm 06:46 PM

The article discusses popular Python libraries like NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, Django, Flask, and Requests, detailing their uses in scientific computing, data analysis, visualization, machine learning, web development, and H

Scraping Webpages in Python With Beautiful Soup: Search and DOM ModificationScraping Webpages in Python With Beautiful Soup: Search and DOM ModificationMar 08, 2025 am 10:36 AM

This tutorial builds upon the previous introduction to Beautiful Soup, focusing on DOM manipulation beyond simple tree navigation. We'll explore efficient search methods and techniques for modifying HTML structure. One common DOM search method is ex

How to Create Command-Line Interfaces (CLIs) with Python?How to Create Command-Line Interfaces (CLIs) with Python?Mar 10, 2025 pm 06:48 PM

This article guides Python developers on building command-line interfaces (CLIs). It details using libraries like typer, click, and argparse, emphasizing input/output handling, and promoting user-friendly design patterns for improved CLI usability.

See all articles

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

AI Hentai Generator

AI Hentai Generator

Generate AI Hentai for free.

Hot Article

Hot Tools

PhpStorm Mac version

PhpStorm Mac version

The latest (2018.2.1) professional PHP integrated development tool

Dreamweaver Mac version

Dreamweaver Mac version

Visual web development tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

MinGW - Minimalist GNU for Windows

MinGW - Minimalist GNU for Windows

This project is in the process of being migrated to osdn.net/projects/mingw, you can continue to follow us there. MinGW: A native Windows port of the GNU Compiler Collection (GCC), freely distributable import libraries and header files for building native Windows applications; includes extensions to the MSVC runtime to support C99 functionality. All MinGW software can run on 64-bit Windows platforms.

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)