Unlock the cheat code of the universe

backend/app.py

@@ -1,83 +1,8 @@
-from flask import Flask, request
-from flask_cors import CORS
 from waitress import serve
-from http import HTTPStatus
 
-from backend.request import ClassificationRequest
-from backend.response import ClassificationResponse
-from backend.spectrogram_generator import SpectrogramGenerator
-from classification.parser import get_raw_array
-from classification.exceptions import ClassificationError
-from classification.config.constants import Sex, ALLOWED_FILE_EXTENSIONS
-from classification.model import SleepStagesClassifier
-from classification.features.preprocessing import preprocess
+from web import App
 
-app = Flask(__name__)
-sleep_stage_classifier = SleepStagesClassifier()
-
-
-def allowed_file(filename):
-    return filename.lower().endswith(ALLOWED_FILE_EXTENSIONS)
-
-
-@app.route("/")
-def status():
-    return ""
-
-
-@app.route('/analyze-sleep', methods=['POST'])
-def analyze_sleep():
-    """
-    Request payload example
-    {
-        "file": File(...),
-        "device": "CYTON",
-        "sex": "F",
-        "age": "23",
-        "stream_start": 1602895800000,
-        "bedtime": 1602898320000,
-        "wakeup": 1602931800000
-    }
-    """
-    if 'file' not in request.files:
-        return 'Missing file', HTTPStatus.BAD_REQUEST
-    file = request.files['file']
-
-    if file.filename == '':
-        return 'No selected file', HTTPStatus.BAD_REQUEST
-
-    if not allowed_file(file.filename):
-        return 'File format not allowed', HTTPStatus.BAD_REQUEST
-
-    form_data = request.form.to_dict()
-    raw_array = get_raw_array(file)
-
-    try:
-        classification_request = ClassificationRequest(
-            age=int(form_data['age']),
-            sex=Sex[form_data['sex']],
-            stream_start=int(form_data['stream_start']),
-            bedtime=int(form_data['bedtime']),
-            wakeup=int(form_data['wakeup']),
-            raw_eeg=raw_array,
-        )
-    except (KeyError, ValueError, ClassificationError):
-        return 'Missing or invalid request parameters', HTTPStatus.BAD_REQUEST
-
-    preprocessed_epochs = preprocess(classification_request)
-    predictions = sleep_stage_classifier.predict(preprocessed_epochs, classification_request)
-    spectrogram_generator = SpectrogramGenerator(preprocessed_epochs)
-    classification_response = ClassificationResponse(
-        classification_request, predictions, spectrogram_generator.generate()
-    )
-
-    return classification_response.response
-
-
-CORS(app,
-     resources={r'/*': {"origins": '*'}},
-     allow_headers='Content-Type')
-app.config['CORS_HEADERS'] = 'Content-Type'
+app = App()
 
 if __name__ == '__main__':
     serve(app, host='0.0.0.0', port=8080)

backend/classification/parser/constants.py

@@ -8,6 +8,4 @@
 
 FILE_COLUMN_OFFSET = 1
 
-SESSION_FILE_HEADER_NB_LINES = 4
-
 RETAINED_COLUMNS = tuple(range(FILE_COLUMN_OFFSET, len(EEG_CHANNELS) + 1))

backend/classification/parser/csv.py

@@ -1,11 +1,12 @@
 import pandas as pd
+from io import StringIO
 
 from classification.exceptions import ClassificationError
 
 
-def read_csv(file, rows_to_skip=0, columns_to_read=None):
+def read_csv(file_content, rows_to_skip=0, columns_to_read=None):
     try:
-        raw_array = pd.read_csv(file,
+        raw_array = pd.read_csv(StringIO(file_content),
                                 skiprows=rows_to_skip,
                                 usecols=columns_to_read
                                 ).to_numpy()

backend/classification/parser/file_type.py

@@ -12,11 +12,10 @@ def __init__(self, parser):
         self.parser = parser
 
 
-def detect_file_type(file) -> FileType:
+def detect_file_type(file_content) -> FileType:
     """Detects file type
     - file: received as an input file
     Returns:
     - FileType of the input file
     """
-    first_line = file.readline().decode("utf-8")
-    return FileType.SessionFile if "EEG Data" in first_line else FileType.SDFile
+    return FileType.SessionFile if "EEG Data" in file_content else FileType.SDFile

backend/classification/parser/sample_rate.py

@@ -1,28 +1,22 @@
 import re
 
 from classification.parser.file_type import FileType
-from classification.parser.constants import SESSION_FILE_HEADER_NB_LINES
 from classification.exceptions import ClassificationError
 
 OPENBCI_CYTON_SD_DEFAULT_SAMPLE_RATE = 250
 
 SAMPLE_RATE_STRING = "Sample Rate"
-SAMPLE_RATE_REGEX = fr"^%{SAMPLE_RATE_STRING} = (\d+)"
+SAMPLE_RATE_REGEX = fr"%{SAMPLE_RATE_STRING} = (\d+)"
 
 
-def detect_sample_rate(file, filetype):
+def detect_sample_rate(file_content, filetype):
     if filetype == FileType.SDFile:
         return OPENBCI_CYTON_SD_DEFAULT_SAMPLE_RATE
 
-    for _ in range(SESSION_FILE_HEADER_NB_LINES):
-        line = file.readline().decode("utf-8")
-        if SAMPLE_RATE_STRING not in line:
-            continue
-
-        try:
-            sample_rate_raw = re.search(SAMPLE_RATE_REGEX, line).group(1)
-            return int(sample_rate_raw)
-        except BaseException:
-            raise ClassificationError('Invalid sample rate')
+    try:
+        sample_rate_raw = re.search(SAMPLE_RATE_REGEX, file_content).group(1)
+        return int(sample_rate_raw)
+    except BaseException:
+        raise ClassificationError('Invalid sample rate')
 
     raise ClassificationError("Couldn't find sample rate")

backend/requirements.txt

@@ -1,5 +1,4 @@
-Flask==1.1.2
-Flask-Cors==1.10.3
+falcon==3.0.0a2
 waitress==1.4.4
 
 mne==0.21.0

backend/web/__init__.py

@@ -0,0 +1,16 @@
+import falcon
+
+from web.ping import Ping
+from web.analyze_sleep import AnalyzeSleep
+
+
+def App():
+    app = falcon.App(cors_enable=True)
+
+    ping = Ping()
+    app.add_route('/', ping)
+
+    analyze = AnalyzeSleep()
+    app.add_route('/analyze-sleep', analyze)
+
+    return app

backend/web/analyze_sleep.py

@@ -0,0 +1,81 @@
+import json
+import falcon
+
+from backend.request import ClassificationRequest
+from backend.response import ClassificationResponse
+from backend.spectrogram_generator import SpectrogramGenerator
+from classification.parser import get_raw_array
+from classification.exceptions import ClassificationError
+from classification.config.constants import Sex, ALLOWED_FILE_EXTENSIONS
+from classification.model import SleepStagesClassifier
+from classification.features.preprocessing import preprocess
+
+sleep_stage_classifier = SleepStagesClassifier()
+
+
+class AnalyzeSleep:
+    @staticmethod
+    def _validate_file(file_content):
+        if file_content is None:
+            raise ClassificationError("Missing file")
+
+    @staticmethod
+    def _validate_filename(filename):
+        if not filename.lower().endswith(ALLOWED_FILE_EXTENSIONS):
+            raise ClassificationError('File format not allowed')
+
+    @staticmethod
+    def _parse_form(form):
+        form_data = {}
+        file_content = None
+
+        for part in form:
+            if part.name == 'file':
+                AnalyzeSleep._validate_filename(part.filename)
+                file_content = part.stream.read().decode('utf-8')
+            else:
+                form_data[part.name] = part.text
+
+        AnalyzeSleep._validate_file(file_content)
+
+        return form_data, file_content
+
+    def on_post(self, request, response):
+        """
+        Request payload example
+        {
+            "file": File(...),
+            "device": "CYTON",
+            "sex": "F",
+            "age": "23",
+            "stream_start": 1602895800000,
+            "bedtime": 1602898320000,
+            "wakeup": 1602931800000
+        }
+        """
+
+        try:
+            form_data, file = self._parse_form(request.get_media())
+            raw_array = get_raw_array(file)
+            classification_request = ClassificationRequest(
+                age=int(form_data['age']),
+                sex=Sex[form_data['sex']],
+                stream_start=int(form_data['stream_start']),
+                bedtime=int(form_data['bedtime']),
+                wakeup=int(form_data['wakeup']),
+                raw_eeg=raw_array,
+            )
+        except (KeyError, ValueError, ClassificationError):
+            response.status = falcon.HTTP_400
+            response.content_type = falcon.MEDIA_TEXT
+            response.body = 'Missing or invalid request parameters'
+            return
+
+        preprocessed_epochs = preprocess(classification_request)
+        predictions = sleep_stage_classifier.predict(preprocessed_epochs, classification_request)
+        spectrogram_generator = SpectrogramGenerator(preprocessed_epochs)
+        classification_response = ClassificationResponse(
+            classification_request, predictions, spectrogram_generator.generate()
+        )
+
+        response.body = json.dumps(classification_response.response)

backend/web/ping.py

@@ -0,0 +1,7 @@
+import falcon
+
+
+class Ping:
+    def on_get(self, request, response):
+        response.content_type = falcon.MEDIA_TEXT
+        response.body = ''

web/src/views/analyze_sleep/upload_form/index.js

@@ -166,7 +166,7 @@ const UploadForm = () => {
                             // prettier-ignore
                             const streamStart = new Date(`${getValues('stream_start_date')} ${getValues('stream_start_time')}`);
                             const bedTime = new Date(`${getValues('bedtime_date')} ${getValues('bedtime_time')}`);
-                            if (streamStart > bedTime) {
+                            if (streamStart >= bedTime) {
                               return 'Stream start must be prior to bedtime.';
                             }
                           },