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https://github.com/jamormoussa/build-simple-api-using-flask-tutorial
https://github.com/jamormoussa/build-simple-api-using-flask-tutorial
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- Host: GitHub
- URL: https://github.com/jamormoussa/build-simple-api-using-flask-tutorial
- Owner: JamorMoussa
- Created: 2024-04-12T17:18:09.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2024-04-19T14:22:23.000Z (8 months ago)
- Last Synced: 2024-12-16T04:17:17.358Z (9 days ago)
- Language: Python
- Size: 1000 KB
- Stars: 2
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Model Deployment Tutorial
In this tutorial, we'll explore how to deploy pretrained models using Streamlit, Django, and Flask. This tutorial is designed for first-year students and aims to provide a basic understanding of networking concepts such as requests, responses, JSON, APIs, and the Fetch API in Python.
**Objectives:**
- Understand fundamental networking concepts.
- Learn to build APIs and endpoints using Flask and Django.
- Create a website for model deployment using Streamlit.
### Setting up the environment
First install `virtualenv` by running :
```
pip install virtualenv
```
Then, create a virtual enviroment:
```
virtualenv env
```
After virtual env is created. Then, following command to activate it:
```
source ./env/bin/activate
```
Then, install the requirements:
```
pip install -r requirements.txt
```
## Flask
A basic flask app
```python
# app.py
from flask import Flask
app = Flask(__name__)
@app.route("/", methods=["GET"])
def hello_word():
return "Hello, World"
if __name__ == "__main__":
app.run(debug=True)
```
In order to run the flask app, run the following command
```bash
python3 app.py # app.py file name
```
## TODO:
- Materials About, basic concepts of Networking
- [ ] API, HTTP, JSON, HTTP Methods (GET, POST, ..,) [here](https://github.com/JamorMoussa/model-deployment-tuto/blob/main/docs/basic-concepts-of-networking.md)
- [x] apply these concepts in `Flask`.
- [ ] Build a simple TODO APP.
- Fetch APIs:
- [ ] Looking for available APIs (ex. Github API)
- [ ] Materials About: using the `requests` library, fetch website & APIs.
- ML Models:
- [ ] Looking for pre-trained models, to use in this tuto.
- [ ] Work with different data type: text, images, json ,etc.