Flask
MongoDB
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Flask | MongoDB | |
---|---|---|
135 | 247 | |
66,287 | 25,384 | |
0.7% | 1.0% | |
8.7 | 10.0 | |
4 days ago | 5 days ago | |
Python | C++ | |
BSD 3-clause "New" or "Revised" License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Flask
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Ask HN: High quality Python scripts or small libraries to learn from
I'd suggest Flask or some of the smaller projects in the Pallets ecosystem:
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Rapid Prototyping with Flask, Bootstrap and Secutio
#!/usr/bin/python # # https://flask.palletsprojects.com/en/3.0.x/installation/ # from flask import Flask, jsonify, request contacts = [ { "id": "1", "firstname": "Lorem", "lastname": "Ipsum", "email": "[email protected]", }, { "id": "2", "firstname": "Mauris", "lastname": "Quis", "email": "[email protected]", }, { "id": "3", "firstname": "Donec Purus", "lastname": "Purus", "email": "[email protected]", } ] app = Flask(__name__, static_url_path='', static_folder='public',) @app.route("/contact//save", methods=["PUT"]) def save_contact(id): data = request.json contacts[id - 1] = data return jsonify(contacts[id - 1]) @app.route("/contact/", methods=["GET"]) @app.route("/contact//edit", methods=["GET"]) def get_contact(id): return jsonify(contacts[id - 1]) @app.route('/') def root(): return app.send_static_file('index.html') if __name__ == '__main__': app.run(debug=True)
- Microdot "The impossibly small web framework for Python and MicroPython"
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Why do all the popular projects use relative imports in __init__ files if PEP 8 recommends absolute?
I was looking at all the big projects like numpy, pytorch, flask, etc.
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10 Github repositories to achieve Python mastery
Explore here.
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Ask HN: What would you use to build a mostly CRUD back end today?
I may use Flask-Admin initially to offload the "CRUD" operations to have an initial prototype fast but then drop it ASAP because I don't want to write a "flask-admin application" to fight against later on. If the application is mainly "CRUD", then Flask-Admin is suitable.
Now...
Would you do a breakdown/list of all the jobs you've done by sector/vertical and by function/role and by application functionality?
- [0]: https://flask.palletsprojects.com
- [1]: https://flask-admin.readthedocs.io/en/latest
- [2]: https://flask.palletsprojects.com/en/2.3.x/patterns/celery
- [3]: https://sentry.io
- [4]: https://posthog.com
- [5]: https://www.docker.com
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Implementing continuous delivery pipelines with GitHub Actions
In the lab to follow, we will be setting up an end-to-end DevOps workflow for a Flask microservice with GitHub Actions, using a self-managed custom runner for maximal control over the pipeline execution environment and automating deployments to a local Kubernetes cluster. Furthermore, we will construct separate pipelines for our "development" and "production" environments to further elaborate on the concepts of continuous deployment and delivery.
- How do you iterate on a library built locally?
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Flask Application Load Balancing using Docker Compose and Nginx
Flask Micro web Framework: You will use Flask to build a Flask web application.
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Open Source Flask-based web applications
In an earlier post I mentioned a bunch of Open Source web applications. Let's now focus on the ones written in Python using Flask the light-weight web framework.
MongoDB
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Understanding SQL vs. NoSQL Databases: A Beginner's Guide
On the other hand, NoSQL databases are non-relational databases. They store data in flexible, JSON-like documents, key-value pairs, or wide-column stores. Examples include MongoDB, Couchbase, and Cassandra.
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Building Llama as a Service (LaaS)
I built each API with Node.js, Express, and Docker. Services connected to a NoSQL MongoDB database.
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Time Series Blob Data: ReductStore vs. MongoDB
In edge computing, managing time series blob data efficiently is critical for performance-sensitive applications. This blog post will compare ReductStore, a specialized time series database for unstructured data, and MongoDB, a widely-used NoSQL database.
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Build Your Own Uptime Monitor with MeteorJS + Fetch + Plotly.js ☄️🔭
MongoDB to store our data as documents, close to JS objects
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How to choose the right type of database
MongoDB: Known for its ease of development and strong community support, MongoDB is effective in scenarios where flexible schema and rapid iteration are more critical than strict ACID compliance.
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How to create a dynamic AI Discord bot with TypeScript
MongoDB
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Mastering Microservices: A Hands-On Tutorial with Node.js, RabbitMQ, Nginx, and Docker
Ensure you have MongoDB installed for data storage. You can download MongoDB Community Server from MongoDB's official website or use the cloud cluster.
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How to Build & Deploy Scalable Microservices with NodeJS, TypeScript and Docker || A Comprehesive Guide
We will be using MongoDB as a database on both the Auth microservice and notifications microservice, sign up for a MongoDB Atlas account here incase you donot have one and donot have its desktop application(mongodb campass) installed and would like to use mongodb atlas. This cloud-based database service offers a free tier and simplifies the process of managing MongoDB databases.
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Build a GraphQL API with NodeJS and TypeScript || A Comprehensive Guide
Head over to MongoDB and create an account or login to grab your connection string.
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Uploading and Serving Images from MongoDB in Golang
MongoDB, a document-oriented NoSQL database, will be our data powerhouse. We'll utilize the mongo-driver library to seamlessly connect our Golang application to MongoDB. This section will cover essential database interactions, including creating collections, storing metadata, and efficiently querying for image-related data. Understanding these fundamentals is crucial for building a robust image storage and retrieval system.
What are some alternatives?
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
mongo-express - Web-based MongoDB admin interface, written with Node.js and express
Django - The Web framework for perfectionists with deadlines.
Marten - .NET Transactional Document DB and Event Store on PostgreSQL
AIOHTTP - Asynchronous HTTP client/server framework for asyncio and Python
LiteDB - LiteDB - A .NET NoSQL Document Store in a single data file
quart - An async Python micro framework for building web applications.
LevelDB - LevelDB is a fast key-value storage library written at Google that provides an ordered mapping from string keys to string values.
starlette - The little ASGI framework that shines. 🌟
SQLAlchemy - The Database Toolkit for Python
Tornado - Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed.
Apache Ignite - Apache Ignite