Flask TypeError:视图函数未返回有效响应.该函数返回None或不返回return语句而结束 [英] Flask TypeError : The view function did not return a valid response. The function either returned None or ended without a return statement

问题描述

我正在制作一个应该生成摘要的Flask应用程序.但是，flask告诉我，我有一个不返回任何内容的函数.我仔细检查了一下，发现找不到任何未返回任何功能的函数.

I'm making a flask app that is supposed to generate a summary. However, flask is telling me that i have a function that doesn't return anything. I double checked and i can't find any function that isn't returning something.

app = Flask(__name__)

@app.route('/',methods=['GET'])
def index():
    return render_template('index.html')

UPLOAD_FOLDER = '/path_to_directory/SUMM-IT-UP/Uploads'
ALLOWED_EXTENSIONS = set(['txt', 'pdf'])

app = Flask(__name__)
app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER

model = None
nlp = None

# @app.route('/load', methods=['GET'])
# def _load_model():
#     model = load_model()
#     return True

def load_model():
    nlp = en_coref_md.load()
    print "coref model loaded"

    VOCAB_FILE = "skip_thoughts_uni/vocab.txt"
    EMBEDDING_MATRIX_FILE = "skip_thoughts_uni/embeddings.npy"
    CHECKPOINT_PATH = "skip_thoughts_uni/model.ckpt-501424"
    encoder = encoder_manager.EncoderManager()
    print "loading skip model"
    encoder.load_model(configuration.model_config(),
                        vocabulary_file=VOCAB_FILE,
                        embedding_matrix_file=EMBEDDING_MATRIX_FILE,
                        checkpoint_path=CHECKPOINT_PATH)
    print "loaded"
    return encoder,nlp

def convertpdf (fname, pages=None):
    if not pages:
        pagenums = set()
    else:
        pagenums = set(pages)

    output = StringIO()
    manager = PDFResourceManager()
    converter = TextConverter(manager, output, laparams=LAParams())
    interpreter = PDFPageInterpreter(manager, converter)

    infile = file(fname, 'rb')
    for page in PDFPage.get_pages(infile, pagenums):
        interpreter.process_page(page)
    infile.close()
    converter.close()
    text = output.getvalue()
    output.close
    return text 

def readfiles (file):
    with open(file, 'r') as f:
        contents = f.read()
    return contents

def preprocess (data):
    data = data.decode('utf-8')
    data = data.replace("\n", "")
    data = data.replace(".", ". ")
    sentences = ""
    for s in sent_tokenize(data.decode('utf-8')):
        sentences= sentences + str(s.strip()) + " "
    return sentences

def coref_resolution (data,nlp):
    sent = unicode(data, "utf-8")
    doc = nlp(sent)
    if(doc._.has_coref):
        data = str(doc._.coref_resolved)
    return data

def generate_embed (encoder,data):
    sent = sent_tokenize(data)
    embed = encoder.encode(sent)
    x = np.isnan(embed)
    if (x.any() == True):
        embed = Imputer().fit_transform(embed)
    return sent, embed

def cluster (embed,n):
    n_clusters = int(np.ceil(n*0.33))
    kmeans = KMeans(n_clusters=n_clusters, random_state=0)
    kmeans = kmeans.fit(embed)

    array = []
    for j in range(n_clusters):
        array.append(list(np.where(kmeans.labels_ == j)))

    arr= []
    for i in range (n_clusters):
        ratio = float(len(array[i][0]))/float(n)
        sent_num = int(np.ceil(float(len(array[i][0]))*ratio))
        if (sent_num > 0):
            arr.append([i,sent_num])

    return array,arr

def sent_select (arr, array, sentences,embed):
    selected = []
    for i in range(len(arr)):
        sentences_x = []
        for j in range(len(array[arr[i][0]][0])):
                    sentences_x.append(sentences[array[arr[i][0]][0][j]])

        sim_mat = np.zeros([len(array[arr[i][0]][0]), len(array[arr[i][0]][0])])
        for k in range(len(array[arr[i][0]][0])):
            for l in range(len(array[arr[i][0]][0])):
                if k != l:
                    sim_mat[k][l] = cosine_similarity(embed[k].reshape(1,2400), embed[l].reshape(1,2400))

        nx_graph = nx.from_numpy_array(sim_mat)
        scores = nx.pagerank(nx_graph)
        ranked = sorted(scores)
        x = arr[i][1]  
        for p in range(x):
                selected.append(sentences_x[ranked[p]])

    return selected


def generate_summary(encoder,text):
    sent, embed = generate_embed(encoder,text)
    array , arr = cluster(embed, len(sent))
    selected = sent_select (arr,array,sent,embed)
    summary = ""
    for x in range(len(selected)):
        try:
            summary = summary + selected[x].encode('utf-8') + " "
        except:
            summary = summary + str(selected[x]) + " "
    try:
        sum_sent = sent_tokenize(summary.decode('utf-8'))
    except:
        sum_sent = sent_tokenize(summary)


        summary = ""
        for s in sent:
            for se in sum_sent:
                if (se == s):
                    try:
                        summary = summary + se.encode('utf-8') + " "
                    except:
                        summary = summary + str(se) + " "
    return summary


def allowed_file(filename):
    return '.' in filename and \
           filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS

@app.route('/single-summary', methods=['POST'])
def singleFileInput():
    print(request.files['singleFile'])
    file = request.files['singleFile']

    filename = secure_filename(file.filename)
    file.save(os.path.join(app.config['UPLOAD_FOLDER'], filename))
    uploaded_file_path = os.path.join(UPLOAD_FOLDER, filename)
    text = ""
    # for i in range(1, len(sys.argv)):
    if(".pdf" in uploaded_file_path):
        t = convertpdf(uploaded_file_path)
        t = preprocess(t)
        t = coref_resolution(t, nlp).decode('utf-8')
        text = text + t.decode('utf-8')
    elif(".txt" in uploaded_file_path):
        t = readfiles(uploaded_file_path)
        t = preprocess(t)
        t = coref_resolution(t, nlp).decode('utf-8')
        text = text + t
    summary = generate_summary(model,text)
    return summary


@app.route('/multiple-summary', methods=['POST'])
def multipleFileInput():
    # for f in range(1, len(request.files['multipleFile'])):
    print(request.files['multipleFile'])
    file = request.files['multipleFile']

    filename = secure_filename(file.filename)
    file.save(os.path.join(app.config['UPLOAD_FOLDER'], filename))
    uploaded_file_path = os.path.join(UPLOAD_FOLDER, filename)
    text = ""
    # for i in range(1, len(sys.argv)):
    if(".pdf" in uploaded_file_path):
        t = convertpdf(uploaded_file_path)
        t = preprocess(t)
        t = coref_resolution(t, nlp)
        text = text + t
    elif(".txt" in uploaded_file_path):
        t = readfiles(uploaded_file_path)
        t = preprocess(t)
        t = coref_resolution(t, nlp)
        text = text + t
    summary = generate_summary(model,text)
    return summary

@app.route('/', methods=['GET', 'POST'])
def upload_file():
    if request.method == 'POST':
        # check if the post request has the file part
        if 'file' not in request.files:
            flash('No file part')
            return redirect(request.url)
        file = request.files['file']
        # if user does not select file, browser also
        # submit an empty part without filename
        if file.filename == '':
            flash('No selected file')
            return redirect(request.url)
        if file and allowed_file(file.filename):
            filename = secure_filename(file.filename)
            file.save(os.path.join(app.config['UPLOAD_FOLDER'], filename))
            #return uploaded_file(filename)
            # return redirect(url_for('uploaded_file',
            #                         filename=filename))
    return render_template('index.html')

if __name__ == '__main__':
    global model
    global nlp
    model, nlp = load_model()

    app.run(debug=True)

这是错误堆栈的图像

关于为什么我仍然出现此错误的任何想法吗?

Any ideas as to why i'm still getting this error?

推荐答案

这里的问题是您的函数之一返回None，而不是您的问题中显示的错误所观察到的return语句丢失.

The problem here is that one of your functions returns None and not that a return statement is missing, as observed in the error shown in your question.

为了提供更详细的帮助，您需要提供一个最小，完整和可验证的示例.

In order to provide more detailed help you'd need to provide a Minimal, Complete and Verifiable example.

您的某些计算正在返回None值，并且您正试图将该值作为返回值传递.

Some of your calculations are returning a None value and you are trying to pass that value as a return value.

下面是一个返回无值的函数的示例:

Here's an example of a function returning None:

def lyrics():
    pass
a = lyrics()
print (a)

输出:

None

具体地说，我还在您的代码中看到了

Specifically I also see in your code:

model = None
nlp = None

为进一步调试，我建议使用Flask的日志记录工具，以便在控制台中打印用于操作的变量的值，以跟踪错误.

What I would suggest, for further debugging, is using Flask's logging facility in order to print in the console the values of the variables that you are using for manipulation in order to track down the error.

以下是有关如何在Flask中使用日志记录的相关文档.

Here's the relevant documentation about how to use logging in Flask.

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