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PyWebIO vs. Flask

Python3
  • Seit einigen Monaten, entwickle ich zum Lernen mit Flask. Davor habe ich schon mal PyWebIO eingesetzt. Beides sind Webframeworks. Was sind so meine Gedanken dazu.

    Code Beispiel PyWebIO

    @use_scope('backup')
        def backup():
            clear_scope()
            BackupList.load_json()
    
            # we build header and tdata for table
            tab_init = []
    
            # Print data from backups
            for count, value in enumerate(backups):
                # print("Control", count, backups[value].name)
    
                if count == 0:
                    tab_init.append(['No.', 'Backup name of the restic data backup', 'Actions'])
    
                if backups[value].init == "1":
                    button_list = {"label": 'Init', "value": 'Init', "color": 'primary', "disabled": True}
                    tab_init.append([count + 1,
                                     backups[count].name,
                                     put_buttons([
                                          button_list],
                                         onclick=partial(actions, count + 1))
                                     ])
                else:
                    button_list = {'label': 'Init', 'value': 'Init', 'color': 'primary', "disabled": False}
                    tab_init.append([count + 1,
                                     backups[count].name,
                                     put_buttons([
                                          button_list],
                                         onclick=partial(actions, count + 1))
                                     ])
    

    PyWebIO - Pro

    Contra

    • Nur für kleine Projekte geeignet
    • Kleine Community

    Code Beispiel Flask

    @home.route('/dashboard', methods=['GET'])
    @login_required
    def dashboard():
        refreshed = False
        refreshed = 'refreshed' in request.args
        # print("Refreshed", refreshed)
    
        data2 = all_data.get_all_stocks()
    
        data = sorted(data2.values(), key=lambda x: x['name_stock'], reverse=False)
    
        sums = []
        total_sum = all_data.get_total_sum('total_sum')
        sums.append(float(total_sum) if total_sum is not None else 0.0)
        old_total_sum = all_data.get_total_sum('old_total_sum')
        sums.append(float(old_total_sum) if total_sum is not None else 0.0)
        # print("SUMS", sums)
    
        return render_template('dashboard.html',
                               refreshed=refreshed,
                               data=data,
                               sums=sums,
                               active_menu='dashboard',
                               test_mode=config.TEST_MODE)
    

    Flask - Pro

    • Auch für große Projekte geeignet
    • Gute Dokumentation
    • Große aktive Community

    Contra

    • Leider muss man sich auch viel mit HTML, CSS & Javascript beschäftigen

    Fazit

    An PyWebIO hat mir sehr gut gefallen, das man so ziemlich alles mit Python Code machen kann, bis man an die Grenzen stößt. Mit Flask kann man wesentlich komplexere Webanwendungen bauen, dank Blueprints kann man das auch ordentlich strukturieren. Was mich sofort an Flask genervt hat ist, das man nun wieder HTML, CSS & Javascript drauf haben sollte. Aber, das ist halt auch der große Vorteil gegenüber PyWebIO, man ist wesentlich flexibler.

    Ich habe mir vorgenommen, mein vorhandenes Projekt ResticUI auf Flask umzubauen. Mal schauen, wie sich das so entwickelt. Mein aktuelles privates Flask Projekt (portfolio) ist mittlerweile gut ausgereift ist aber leider zu sehr auf meine privaten Anforderungen zugeschnitten, so dass ich es nicht public stellen kann. Evtl. baue ich das später mal entsprechend um.

    Happy Coding!

  • Mist, jetzt habe ich auch noch Streamlit gefunden. Jetzt geht mir langsam die Zeit aus...

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    FrankMF

    Hab ChatGPT nochmal nach der Installation auf einem Production Server befragt.

    ChatGPT

    Certainly! Here's a short example of the steps you can follow to deploy a Flask application on a production server using Nginx and Gunicorn:

    Prepare your server:

    Set up a server (e.g., using a cloud provider like AWS, DigitalOcean, or a dedicated server) and ensure it has a clean, up-to-date installation of a Linux distribution (e.g., Ubuntu or CentOS).

    Install required software:

    Install necessary software packages on your server. You'll need Python, pip (Python package manager), Nginx, and Gunicorn. You can use your distribution's package manager (e.g., apt for Ubuntu or yum for CentOS) to install these dependencies.

    Deploy your Flask application:

    Copy your Flask application code and any required dependencies to your server.

    Set up a virtual environment (optional but recommended):

    Create a virtual environment for your Flask application to isolate its dependencies. You can use venv or virtualenv for this purpose.

    Install Flask and any required Python packages within your virtual environment:

    pip install flask

    Test your Flask application:

    Ensure your Flask application runs correctly within your server's virtual environment.

    Configure Gunicorn:

    Create a Gunicorn configuration file (e.g., gunicorn_config.py) to specify the settings for running your Flask application. Here's a simple example: workers = 4 # Number of Gunicorn worker processes bind = '0.0.0.0:8000' # The address and port Gunicorn should listen on

    Start Gunicorn:

    Start Gunicorn with your Flask application: gunicorn -c gunicorn_config.py your_app:app

    Configure Nginx:

    Create an Nginx server block (often located in /etc/nginx/sites-available) to define how Nginx should handle incoming requests. Here's a simplified example: server { listen 80; server_name your_domain.com www.your_domain.com; location / { proxy_pass http://127.0.0.1:8000; # Pass requests to Gunicorn proxy_set_header Host $host; proxy_set_header X-Real-IP $remote_addr; } }

    Enable the Nginx server block and restart Nginx:

    sudo ln -s /etc/nginx/sites-available/your_config /etc/nginx/sites-enabled/ sudo nginx -t # Test Nginx configuration sudo systemctl restart nginx

    Configure your DNS:

    Point your domain name to your server's IP address.

    Secure your server (optional but recommended):

    Set up SSL/TLS certificates for your domain to enable HTTPS. You can use Let's Encrypt for free SSL certificates.

    Monitor your application:

    Set up monitoring tools and logs to keep track of your application's performance and troubleshoot any issues.

    These are the basic steps to deploy a Flask application on a production server with Nginx and Gunicorn. Please note that this is a simplified example, and there are many additional considerations, such as database configuration, security, and optimization, depending on your specific application and requirements. It's also important to keep your server and software up to date and follow security best practices to ensure the stability and security of your production environment.

    Das werde ich doch mal ausprobieren 😎

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    FrankMF

    Hier noch ein Test von DMZ / LAN und andersrum.

    frank@frank-MS-7C37:~$ iperf3 -c 192.168.5.15 Connecting to host 192.168.5.15, port 5201 [ 5] local 192.168.3.213 port 44052 connected to 192.168.5.15 port 5201 [ ID] Interval Transfer Bitrate Retr Cwnd [ 5] 0.00-1.00 sec 114 MBytes 952 Mbits/sec 314 153 KBytes [ 5] 1.00-2.00 sec 112 MBytes 937 Mbits/sec 259 205 KBytes [ 5] 2.00-3.00 sec 111 MBytes 929 Mbits/sec 210 212 KBytes [ 5] 3.00-4.00 sec 111 MBytes 934 Mbits/sec 235 202 KBytes [ 5] 4.00-5.00 sec 112 MBytes 936 Mbits/sec 263 153 KBytes [ 5] 5.00-6.00 sec 111 MBytes 935 Mbits/sec 255 209 KBytes [ 5] 6.00-7.00 sec 112 MBytes 937 Mbits/sec 313 129 KBytes [ 5] 7.00-8.00 sec 111 MBytes 932 Mbits/sec 296 209 KBytes [ 5] 8.00-9.00 sec 111 MBytes 934 Mbits/sec 258 208 KBytes [ 5] 9.00-10.00 sec 111 MBytes 934 Mbits/sec 292 201 KBytes - - - - - - - - - - - - - - - - - - - - - - - - - [ ID] Interval Transfer Bitrate Retr [ 5] 0.00-10.00 sec 1.09 GBytes 936 Mbits/sec 2695 sender [ 5] 0.00-10.00 sec 1.09 GBytes 935 Mbits/sec receiver iperf Done. frank@frank-MS-7C37:~$ iperf3 -R -c 192.168.5.15 Connecting to host 192.168.5.15, port 5201 Reverse mode, remote host 192.168.5.15 is sending [ 5] local 192.168.3.213 port 44058 connected to 192.168.5.15 port 5201 [ ID] Interval Transfer Bitrate [ 5] 0.00-1.00 sec 109 MBytes 911 Mbits/sec [ 5] 1.00-2.00 sec 109 MBytes 912 Mbits/sec [ 5] 2.00-3.00 sec 109 MBytes 912 Mbits/sec [ 5] 3.00-4.00 sec 109 MBytes 912 Mbits/sec [ 5] 4.00-5.00 sec 109 MBytes 912 Mbits/sec [ 5] 5.00-6.00 sec 108 MBytes 903 Mbits/sec [ 5] 6.00-7.00 sec 109 MBytes 912 Mbits/sec [ 5] 7.00-8.00 sec 109 MBytes 912 Mbits/sec [ 5] 8.00-9.00 sec 109 MBytes 912 Mbits/sec [ 5] 9.00-10.00 sec 109 MBytes 912 Mbits/sec - - - - - - - - - - - - - - - - - - - - - - - - - [ ID] Interval Transfer Bitrate Retr [ 5] 0.00-10.00 sec 1.06 GBytes 913 Mbits/sec 114 sender [ 5] 0.00-10.00 sec 1.06 GBytes 911 Mbits/sec receiver iperf Done.
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