lean+

dataset/README.md

@@ -1,2 +1 @@
-This folder contains all the sensor data uploaded to the server
+Barcode generator
-

docker-compose.yml

@@ -2,26 +2,11 @@ version: '3.7'
 
 services:
 
-  ## TODO: Add true proxy WSGI Server instead of running the builtin
+  ean13generator:
-  uploadtool:
     build: .
     restart: unless-stopped
-    volumes:
-      - /mnt/storage/dataset-neo:/app/dataset
     labels:
       - traefik.enable=true
-      - traefik.http.routers.sdc-uploader.entryPoints=web-secure
+      - traefik.http.routers.ean13generator.entryPoints=web-secure
-      - traefik.http.routers.sdc-uploader.rule=Host(`upload.med.upct.es`)
+      - traefik.http.routers.ean13generator.rule=Host(`ean13.fosc.space`)
-      - traefik.http.routers.sdc-uploader.tls.certresolver=default
+      - traefik.http.routers.ean13generator.tls.certresolver=default
-
-  download:
-    image: abiosoft/caddy
-    restart: unless-stopped
-    volumes:
-      - /mnt/storage/dataset-neo:/srv
-    labels:
-      - traefik.enable=true
-      - traefik.http.routers.sdc-download.entryPoints=web-secure
-      - traefik.http.routers.sdc-download.rule=Host(`download.med.upct.es`)
-      - traefik.http.routers.sdc-download.tls.certresolver=default
-      - traefik.http.services.sdc-download.loadbalancer.server.port=2015

main.py

@@ -1,12 +1,10 @@
 from flask import Flask, render_template, request
 from datetime import datetime
-from probeutils import utils as probeutils
 import re
 import fnmatch
 import os
 import meinheld
 
-
 app = Flask(__name__)
 
 app.config['UPLOAD_FOLDER'] = "./dataset/"
@@ -14,41 +12,10 @@ app.config['UPLOAD_FOLDER'] = "./dataset/"
 app.config['MAX_CONTENT_LENGTH'] = 10000000000  # 10GB
 meinheld.set_max_content_length(100*1024*1024)
 
-app.config['DOWNLOADS_URL'] = "https://download.med.upct.es/"
-
-probes = [{
-    'sensor': 'SUNA',
-    'img': 'suna.jpg',
-    'active': ['SATSLF0037'],
-    'stations': ['M1', 'M2', 'M3']
-}, {
-    'sensor': 'FIRe',
-    'img': 'fire.jpg',
-    'active': ['SATFIS0006'],
-    'stations': ['M1', 'M2', 'M3']
-}, {
-    'sensor': 'PhycoCTD',
-    'img': 'phycoctd.jpg',
-    'active': ['phyco_v1', 'phyco_v2'],
-    'stations': ['M1', 'M2', 'M3']
-}, {
-    'sensor': 'CastAway',
-    'img': 'castaway.jpg',
-    'active': ['CC1326008'],
-    'stations': ['M1', 'M2', 'M3']
-}
-#,{
-#    'sensor': 'GoPro',
-#    'img': 'gopro.png',
-#    'active': ['gopro1'],
-#    'stations': ['M1', 'M2', 'M3']
-#}
-]
-
 # Return our beautiful Bootstrap webpage. That we totally have.
 @app.route('/')
 def upload():
-    return render_template('upload.html', probes=probes)
+    return render_template('upload.html')
 
 # What happens when the files just don't fit 
 @app.errorhandler(413)
@@ -66,131 +33,13 @@ def upload_file():
     if request.method == 'POST':
         f = request.files['file']
 
-        # Get which probe the user uploaded
-        probe = request.form.get('probe')
         
-        # Get selected probe
-        activeProbe = request.form.get('activeProbe')
-
-        # Check if its a valid file to upload
-        # TODO: Implement this method
-        # probeutils.check(probe, f)
-
-        # Check if folder exists
-        try:
-            if not os.path.exists(
-                    os.path.join(app.config['UPLOAD_FOLDER'], probe)):
-                os.makedirs(os.path.join(app.config['UPLOAD_FOLDER'], probe))
-
-            if not os.path.exists(
-                    os.path.join(app.config['UPLOAD_FOLDER'], probe, 'raw')):
-                os.makedirs(os.path.join(
-                    app.config['UPLOAD_FOLDER'], probe, 'raw'))
-        except Exception:
-            return render_template('error.html')
-
-        # Strip station
-        # if forceStation is checked, override all station parsing
-        if (request.form.get("forceStation" + probe) != None):
-            station = request.form.get("stations" + probe)
-        else:
-            if (fnmatch.fnmatch((f.filename).upper(), '*M1*') or fnmatch.fnmatch((f.filename).upper(), 'M1*')):
-                station = 'M1'
-            elif (fnmatch.fnmatch((f.filename).upper(), "*M2*") or fnmatch.fnmatch((f.filename).upper(), "M2*")):
-                station = 'M2'
-            elif (fnmatch.fnmatch((f.filename).upper(), "*M3*") or fnmatch.fnmatch((f.filename).upper(), "M3*")):
-                station = 'M3'
-
-        # Date Parser of filename
-        match1 = re.search('\d{4}-\d{2}-\d{2}', f.filename)
-        if (match1 == None):
-            match1 = re.search('\d{2}-\d{2}-\d{4}', f.filename)
-            try:
-                date = datetime.strptime(match1.group(), '%d-%m-%Y').date()
-            except Exception:
-                # Error! More strange data format XD
-                match1 = re.search('\d{4}\d{2}\d{2}', f.filename)
-                if (match1 == None):
-                    match1 = re.search('\d{2}\d{2}\d{4}', f.filename)
-                    date = datetime.strptime(match1.group(), '%d%m%Y').date()
-                else:
-                    date = datetime.strptime(match1.group(), '%Y%m%d').date()
-        else:
-            date = datetime.strptime(match1.group(), '%Y-%m-%d').date()
-
-        # Crafting the real overpowered name!!!!
-        filename = probe + '-' + station + '-'+ activeProbe + '-'+ date.strftime("%Y-%m-%d") + '.csv'
-        #print(filename)
-
-        # Setting the filePath and saving it
-        finalFilename = 'raw-'+filename 
-        rawFilePath = os.path.join(app.config['UPLOAD_FOLDER'], probe, 'raw', finalFilename)
-        f.save(rawFilePath)
-
-        # Start with probe definition
-        if (probe == 'CastAway'):
-            ''' CastAway Files '''
-
-            df_table = probeutils.process_castaway(rawFilePath)
-
-        elif (probe == 'SUNA'):
-            ''' SUNA Files '''
-
-            df_table = probeutils.process_suna(rawFilePath)
-
-        elif (probe == 'FIRe'):
-            ''' FIRe Files '''
-
-            df_table = probeutils.process_fire(rawFilePath)
-
-        elif (probe == 'PhycoCTD'):
-            ''' PhycoCTD Files '''
-
-            df_table = probeutils.process_phyco(rawFilePath)
-        else:
-            ''' Empty probe '''
-            
-            df_table = "<div></div>"
-
-        # Save file on raw folder and create URL download
-        url_download = app.config['DOWNLOADS_URL'] + probe + "/" + finalFilename
 
         # Return success webpage
-        return render_template('successful.html', url=url_download, tables=df_table)
+        return render_template('successful.html')
     else:
         # No POST Found
         return render_template('error.html')
 
-## Force regenerate QC
-@app.route('/regenerate')
-def regenerate():
-    error_list = []
-    #for each file in raw folder, execute all QC
-    PATH = './dataset/FIRe/raw'
-    for filename in os.listdir(PATH):
-        try:
-            filename_nn = probeutils.execution_NN(filename)
-            probeutils.execution_PAR(filename_nn)
-        except Exception as err:
-            #print(filename)
-            #print(repr(err))
-            error_list.append([filename, repr(err)])
-    
-    #print('Regenerate FIRe done')
-
-    PATH = './dataset/PhycoCTD/raw'
-    for filename in os.listdir(PATH):
-        try:
-            probeutils.check_if_old_phyco(filename)
-            probeutils.execution_pb_phyco(filename)
-        except Exception as err:
-            #print(filename)
-            #print(repr(err))
-            error_list.append([filename, repr(err)])
-
-    #print('Regenerate Phyco done')
-
-    return render_template('regenerate.html', error_list=error_list)
-
 if __name__ == '__main__':
     app.run()

probeutils/utils.py

@@ -1,293 +0,0 @@
-from datetime import datetime
-from shutil import copy2
-import pandas as pd
-import numpy as np
-import os, csv
-
-UPLOAD_FOLDER = './dataset/'
-tableClass = 'table table-striped table-sm table-responsive'
-
-def get_date(probe, file):
-    ''' Test utils file '''
-    return datetime.now().strftime("%Y-%m-%d-%H:%M:%S")
-
-# TODO:
-#   - Check if is a good file
-#
-#def checkUploadedFile(probe, file): 
-#    return 1
-
-# TODO:
-#   - clean the head of csv, need to extract info an remove the %% (maybe new file with metadata info?) [done]
-#   - create the empty csv, first row with headers [done]
-#   - desviation and more data things 
-def process_castaway(file):
-    
-    try:
-        # Copy raw file to process folder
-        with open(file) as CastAwayFile:
-            filename = os.path.basename(CastAwayFile.name).strip('raw-')
-            processFilePath = os.path.join(
-                UPLOAD_FOLDER, 'CastAway', filename)
-            #copy2(file, processFilePath)
-
-        # Getting some metadata info 
-        #with open(file, newline='') as castfile:
-        #    lines = castfile.readlines()
-        #    device = lines[0].split(',')[1].replace('\r\n', '')
-        #    filename = lines[1].split(',')[1].replace('\r\n', '')
-        #    start_latitude = lines[9].split(',')[1].replace('\r\n', '')
-        #    start_longitude = lines[10].split(',')[1].replace('\r\n', '')
-        #    start_altitude = lines[11].split(',')[1].replace('\r\n', '')
-        #    castfile.close()
-
-        # Opening the csv with pandas
-        df = pd.read_csv(file, skiprows=28)
-
-        # Extract perfil bajada, el 1 es por el header
-        index_max = df['Depth (Meter)'].idxmax() + 1
-        #df_perfilBajada = df[df['depth'].between(0, df['depth'].max())]       # No funciona muy bien
-        # Limitamos a solo el perfil de bajada
-        df_perfilBajada = df[:index_max]
-
-        # Guardamos solo el perfilBajada en carpeta PB
-        if not os.path.exists(os.path.join(UPLOAD_FOLDER, 'CastAway', 'PB')):
-            os.makedirs(os.path.join(UPLOAD_FOLDER, 'CastAway', 'PB'))
-
-        filenamePB = filename.strip('.csv') + '-PB.csv'
-        perfilBajadaFilePath = os.path.join(
-            UPLOAD_FOLDER, 'CastAway', 'PB', filenamePB)
-        df_perfilBajada.to_csv(perfilBajadaFilePath, index=False)
-
-        # Trying to show Dataframe on webpage
-        return df.to_html(classes=tableClass)
-    
-    except Exception as ex:
-        print('Exception: '+repr(ex))
-        return ex
-
-def process_suna(file):
-    try:
-        df = pd.read_csv(file, encoding="ISO-8859-1", header=None)
-
-        #df.columns = ['fechaHora', 'INSTRUMENT', 'Start-time', 'Nitrato(uMol/L)','Nitrato(MG/L)', 'ERROR', 'T_lamp', ]
-
-        #if not os.path.exists(os.path.join(UPLOAD_FOLDER, 'SUNA', 'HEAD')):
-        #    os.makedirs(os.path.join(UPLOAD_FOLDER, 'SUNA', 'HEAD'))
-
-        # Return webpage
-        return df.to_html(classes=tableClass)
-    except Exception as ex:
-        print('Exception: '+repr(ex))
-        return ex
-
-# TODO:
-# - Ask for FIRe examples, actually only bin files found (done)
-# - Extract file to process folder (done)
-# - Save a File with PAR info
-# - Headers on email (ask for new headers)[done]
-# - Remove negative values (this, done)
-# - Arrange similar windows depth and do measure
-def process_fire(file):
-    ''' Processing FIRe '''
-    
-    try:
-        # Copy raw file to process folder
-        with open(file) as FIReFile:
-            filename_raw = os.path.basename(FIReFile.name)
-            filename = os.path.basename(FIReFile.name).strip('raw-')
-            #raw_file_path = os.path.join(UPLOAD_FOLDER, 'FIRe', 'raw', filename_raw)
-            processFilePath = os.path.join(
-                UPLOAD_FOLDER, 'FIRe', filename)
-            #copy2(file, processFilePath)
-        
-        # First, need to check the csv headers
-        # Open the process file with pandas
-        df = pd.read_csv(file, header=None)
-
-        # Headers (now working fine)
-        df.columns = ['fechaHora', 'estacion', 'fecha', 'hora', 'profundidad', 'Fo', 'Fm', 'Fv', 'Fv/Fm', 'p', 'Abs_rel', 'Abs_abs', 'led_light', 'ETR', 'coma1', 'coma2', 'coma3', 'coma4', 'coma5', 'coma6','error_norm', 'PAR', 'V', 'cero1', 'cero2', 'cero3', 'cero4', 'raro']
-        df.loc[:, 'coma1'] = 0
-        df.loc[:, 'coma2'] = 0
-        df.loc[:, 'coma3'] = 0
-        df.loc[:, 'coma4'] = 0
-        df.loc[:, 'coma5'] = 0
-        df.loc[:, 'coma6'] = 0
-
-        # Fixing empty values
-        #df.to_csv(os.path.join(UPLOAD_FOLDER, 'FIRe', 'raw', 'raw-'+filename), index=False)
-
-        filename_nn = execution_NN(filename_raw)
-
-        execution_PAR(filename_nn)
-
-        return df.to_html(classes=tableClass)
-
-    except Exception as ex:
-        print('Exception: '+repr(ex))
-        return ex
-
-# TODO:
-# - Only perfil bajada (done)
-def process_phyco(file):
-    ''' Processing PhycoCTD'''
-    
-    try:
-        # Copy raw file to process folder
-        with open(file, "r+") as phycoFile:
-            # Sustract raw- of filename
-            filename_raw = os.path.basename(phycoFile.name)
-            filename = os.path.basename(phycoFile.name).strip('raw-')
-            processFilePath = os.path.join(
-                UPLOAD_FOLDER, 'PhycoCTD', filename)
-            #copy2(file, processFilePath)
-        
-        # Working with the process file
-        df = pd.read_csv(file, delimiter=';')
-
-        check_if_old_phyco(filename_raw)
-        execution_pb_phyco(filename_raw)
-
-        # Return webpage
-        return df.to_html(classes=tableClass)
-    except Exception as ex:
-        print('Exception: '+repr(ex))
-        return ex
-
-def check_if_old_phyco(filename):
-    # Checking if old file csv
-    PATH = os.path.join(UPLOAD_FOLDER, 'PhycoCTD', 'raw', filename)
-    with open(PATH, "r+") as phycoFile:
-        # Check if old version
-        line = phycoFile.readline()
-        if (',' in line):
-            old = True
-        else:
-            old = False
-
-    if (old == True):
-        df_old = pd.read_csv(PATH, header=None, skiprows=1)
-        if (len(df_old.columns) == 16):
-            df_old.columns = ['station', 'latitude', 'longitude', 'time', 'depth', 'temp1', 'temp2', 'cdom[gain]',
-                              'cdom[ppb]', 'cdom[mv]', 'pe[gain]', 'pe[ppb]', 'pe[mv]', 'chl[gain]', 'chl[ppb]', 'chl[mv]']
-        else:
-            df_old.columns = ['station', 'time', 'depth', 'temp1', 'temp2', 'cdom[gain]', 'cdom[ppb]',
-                              'cdom[mv]', 'pe[gain]', 'pe[ppb]', 'pe[mv]', 'chl[gain]', 'chl[ppb]', 'chl[mv]']
-        raw_path = os.path.join(UPLOAD_FOLDER, 'PhycoCTD', 'raw', filename)
-        df_old.to_csv(raw_path, index=False, sep=';')
-
-def execution_pb_phyco(filename):
-    # Guardamos solo el perfilBajada
-    if not os.path.exists(os.path.join(UPLOAD_FOLDER, 'PhycoCTD', 'PB')):
-        os.makedirs(os.path.join(UPLOAD_FOLDER, 'PhycoCTD', 'PB'))
-
-    PATH = os.path.join(UPLOAD_FOLDER, 'PhycoCTD', 'raw', filename)
-    df = pd.read_csv(PATH, delimiter=';')
-
-    # Checking if NaN values exists [for hack lab version csv upload]
-    if (df['temp2'].isnull().sum() > 0):
-        df.loc[:, 'temp2'] = 0
-        df = df.dropna()
-
-    # Extract perfil bajada, el 1 es por el header
-    index_max = df['depth'].idxmax() + 1
-    #df_perfilBajada = df[df['depth'].between(0, df['depth'].max())]       # No funciona muy bien
-    # Limitamos a solo el perfil de bajada
-    df_pb= df[:index_max]
-
-    filename_pb = filename.strip('raw-').strip('.csv') + '-PB.csv'
-    pb_path = os.path.join(UPLOAD_FOLDER, 'PhycoCTD', 'PB', filename_pb)
-    df_pb.to_csv(pb_path, sep=';', index=False)
-
-def execution_NN(filename):
-    
-    PATH = os.path.join(UPLOAD_FOLDER, 'FIRe', 'raw', filename)
-    df = pd.read_csv(PATH, header=None)
-
-    # Headers (now working fine)
-    df.columns = ['fechaHora', 'estacion', 'fecha', 'hora', 'profundidad', 'Fo', 'Fm', 'Fv', 'Fv/Fm', 'p', 'Abs_rel', 'Abs_abs', 'led_light',
-                  'ETR', 'coma1', 'coma2', 'coma3', 'coma4', 'coma5', 'coma6', 'error_norm', 'PAR', 'V', 'cero1', 'cero2', 'cero3', 'cero4', 'raro']
-    df.loc[:, 'coma1'] = 0
-    df.loc[:, 'coma2'] = 0
-    df.loc[:, 'coma3'] = 0
-    df.loc[:, 'coma4'] = 0
-    df.loc[:, 'coma5'] = 0
-    df.loc[:, 'coma6'] = 0
-    
-    # NonNegative values rutine
-    if not os.path.exists(os.path.join(UPLOAD_FOLDER, 'FIRe', 'NN')):
-        os.makedirs(os.path.join(UPLOAD_FOLDER, 'FIRe', 'NN'))
-
-    # Remove rows with negatives values
-    df_nn = df[(df.iloc[:, 4:27] >= 0).all(1)]
-    filename_nn = filename.strip('raw-').strip('.csv') + '-NN.csv'
-    nonnegative_path = os.path.join(UPLOAD_FOLDER, 'FIRe', 'NN', filename_nn)
-    df_nn.to_csv(nonnegative_path, index=False)
-    
-    return filename_nn
-
-def execution_PAR(filename):
-    # PAR rutine
-    if not os.path.exists(os.path.join(UPLOAD_FOLDER, 'FIRe', 'PAR')):
-        os.makedirs(os.path.join(UPLOAD_FOLDER, 'FIRe', 'PAR'))
-
-    PATH = os.path.join(UPLOAD_FOLDER, 'FIRe', 'NN', filename)
-    df = pd.read_csv(PATH)
-
-    # PAR execution
-    PAR_columns = ['estacion', 'fecha', 'profundidad', 'Fo', 'Fm', 'Fv', 'Fv/Fm', 'p', 'Abs_rel', 'Abs_abs', 'led_light',
-                       'ETR', 'error_norm', 'PAR']
-
-    df_PAR = pd.DataFrame(columns=PAR_columns)
-
-    index_max = df['profundidad'].idxmax()
-    index_min = df['profundidad'].idxmin() + 1
-    depth_list = df[index_max:index_min]['profundidad'].to_list()
-
-    last_value = df['profundidad'].max()
-    similar_depth = []
-    for i in range(len(depth_list)):
-    #print(depth_list[i])
-
-        if (abs(last_value - depth_list[i]) <= 2000):
-            last_value = depth_list[i]
-            similar_depth.append(depth_list[i])
-        elif (abs(last_value - depth_list[i]) >= 6000):
-            ## Save the actual list to DataFrame
-            #print(similar_depth)
-            index_first = pd.to_numeric(df.index[df['profundidad'] == similar_depth[0]])[0]
-            index_last = pd.to_numeric(df.index[df['profundidad'] == similar_depth[-1]])[0] + 1
-            df_range = df.iloc[index_first:index_last]
-
-            # Working with df_range
-            estacion = df['estacion'][0]
-            fecha = df['fecha'][0]
-            profundidad = df_range['profundidad'].mean()
-            Fo = df_range['Fo'].mean()
-            Fm = df_range['Fm'].mean()
-            Fv = df_range['Fv'].mean()
-            FvFm = df_range['Fv/Fm'].mean()
-            p = df_range['p'].mean()
-            Abs_rel = df_range['Abs_rel'].mean()
-            Abs_abs = df_range['Abs_abs'].mean()
-            led_light = df_range['led_light'].mean()
-            ETR = df_range['ETR'].mean()
-            error_norm = df_range['error_norm'].mean()
-            PAR = df_range['PAR'].mean()
-            data = [estacion, fecha, profundidad, Fo, Fm, Fv, FvFm, p, Abs_rel, Abs_abs, led_light, ETR, error_norm, PAR]
-            row = pd.Series(data, index=PAR_columns)
-            df_PAR = df_PAR.append(row, ignore_index=True)
-
-            ## Empty the list
-            similar_depth = []
-            last_value = depth_list[i]
-
-            ## Adding to the new list
-            similar_depth.append(depth_list[i])
-
-    # Saving the DataFrame
-    # TODO: check last values, around 400 depth
-    filenamePAR = filename.strip('-NN.csv') + '-PAR.csv'
-    PARFilePath = os.path.join(UPLOAD_FOLDER, 'FIRe', 'PAR', filenamePAR)
-    df_PAR.to_csv(PARFilePath, index=False)
-

requirements.txt

@@ -1,3 +1,4 @@
 Flask
 pandas
 meinheld
+python-barcode

static/img/placeholder.svg

@@ -1 +0,0 @@
-<svg width="200" height="200" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 200 200" preserveAspectRatio="none"><defs><style type="text/css">#holder_171aa8443cc text { fill:rgba(255,255,255,.75);font-weight:normal;font-family:Helvetica, monospace;font-size:10pt } </style></defs><g id="holder_171aa8443cc"><rect width="200" height="200" fill="#777"></rect><g><text x="74.41666603088379" y="104.25000009536743">200x200</text></g></g></svg>

templates/upload.html

@@ -1,69 +1,12 @@
-{% extends "base.html" %}
+{% extends "base.html" %} {% block title %}Subida{% endblock %} {% block content %}
-{% block title %}Subida{% endblock %}
-
-{% block content %}
 
 <!-- Row Header -->
 <div class="px-3 py-3 pt-md-5 pb-md-4 mx-auto text-center">
-    <h1 class="display-4">Sensores</h1>
+    <h1 class="display-4">Upload</h1>
 </div>
 
 <div class="container">
-    <div class="card-deck mb-3 text-center"></div>
+    <form class="list-group list-group-flush" action="{{pagename}}/uploader" method="POST" enctype="multipart/form-data">
-
-    <!-- Sensors row -->
-    <div class="row">
-        {% for i in probes %}
-        <div class="col-sm">
-            <div class="card mb-4 shadow-sm">
-                <div class="card-header">
-                    <h4 class="my-0 font-weight-normal">{{ i.sensor }}</h4>
-                </div>
-
-                <div class="card-body">
-                    <div class="text-center">
-                        <img src="{{ url_for('static',filename='img/'+i.img) }}" class="rounded" alt="..."
-                            height="200px" width="200px" />
-                    </div>
-                </div>
-
-                <button type="button" class="btn btn-primary" data-toggle="modal" data-target="#upload{{i.sensor}}">
-                    Subir datos
-                </button>
-            </div>
-        </div>
-        {% endfor%}
-    </div>
-
-    <!-- Setting up the modal foreach probe -->
-    {% for i in probes %}
-    <div class="modal fade" id="upload{{i.sensor}}" role="dialog">
-        <div class="modal-dialog modal-lg">
-
-            <!-- Modal content-->
-            <div class="modal-content">
-                <div class="modal-header">
-                    <h4 class="modal-title">Subir datos de {{ i.sensor }}</h4>
-
-                    <button type="button" class="close" data-dismiss="modal">
-                        &times;
-                    </button>
-                </div>
-
-                <div class="modal-body">
-
-                    <!-- Modal header -->
-                    <div class="upload-header px-3 py-3 pt-md-5 pb-md-4 mx-auto text-center">
-                        <h2 class="display-5">{{ i.sensor }}</h2>
-                    </div>
-
-                    <div class="container">
-                        <div class="text-center">
-
-                            <!-- Modal form -->
-                            <form class="list-group list-group-flush" action="{{pagename}}/uploader" method="POST"
-                                enctype="multipart/form-data">
-
         <!-- File input -->
         <div class="list-group-item" style="padding-left: 50px;">
             <input type="file" class="form-control-file" name="file" />
@@ -71,8 +14,8 @@
 
         <!-- Sensor select -->
         <div class="form-group required" style="padding-top: 10px;">
-                                    <label class="form-check-label" for="activeProbe" style="padding-left: 5px;">Escoge
+            <label class="form-check-label" for="activeProbe" style="padding-left: 5px;">Escoge el sensor utilizado</label
-                                        el sensor utilizado</label>
+      >
       <select name="activeProbe" id="activeProbe">
         {% for j in i.active %}
         <option value="{{ j }}">{{ j }}</option>
@@ -82,16 +25,23 @@
 
     <!-- Force station -->
     <div class="form-group">
-                                    <input class="form-check-input" type="checkbox" name="forceStation{{i.sensor}}"
+      <input
+        class="form-check-input"
+        type="checkbox"
+        name="forceStation{{i.sensor}}"
         id="forceStation{{i.sensor}}"
-                                        onchange="toggleSelect('forceStation{{i.sensor}}', 'stations{{i.sensor}}')">
+        onchange="toggleSelect('forceStation{{i.sensor}}', 'stations{{i.sensor}}')"
-                                    <label class="form-check-label" for="forceStation{{i.sensor}}"
+      />
-                                        style="padding-left: 5px;">
+      <label
+        class="form-check-label"
+        for="forceStation{{i.sensor}}"
+        style="padding-left: 5px;"
+      >
         Forzar estación
       </label>
 
-                                    <label class="form-check-label" for="stations{{i.sensor}}"
+            <label class="form-check-label" for="stations{{i.sensor}}" style="padding-left: 5px;">Selecciona la estación utilizada</label
-                                        style="padding-left: 5px;">Selecciona la estación utilizada</label>
+      >
       <select name="stations{{i.sensor}}" id="stations{{i.sensor}}" disabled>
         {% for j in i.stations %}
         <option value="{{ j }}">{{ j }}</option>
@@ -101,27 +51,28 @@
 
     <!-- Apply quality control -->
     <div class="list-group-item" style="padding-bottom: 50px;">
-                                    <input class="form-check-input" type="checkbox" id="autoSizingCheck" checked>
+      <input
-                                    <label class="form-check-label" for="autoSizingCheck" style="padding-left: 5px;">
+        class="form-check-input"
+        type="checkbox"
+        id="autoSizingCheck"
+        checked
+      />
+      <label
+        class="form-check-label"
+        for="autoSizingCheck"
+        style="padding-left: 5px;"
+      >
         Aplicar control de calidad
       </label>
         </div>
 
         <!-- Submit -->
         <input type="hidden" value="{{i.sensor}}" name="probe" />
-                                <button type="submit" class="btn btn-primary btn-lg btn-block">Subir CSV</button>
+        <button type="submit" class="btn btn-primary btn-lg btn-block">
-
+      Subir CSV
+    </button>
     </form>
-
+</div>
-                        </div>
+<!-- Close container field -->
-                    </div> <!-- Close Modal Container Body -->
-                </div> <!-- Close Modal Body -->
-            </div> <!-- Close Modal Content -->
-        </div> <!-- Close Modal dialog -->
-    </div> <!-- Close Modal -->
-    {% endfor %}
-    <!-- End Sensors Modals -->
-
-</div> <!-- Close container field -->
 
 {% endblock %}