DEV Community: Suttipong Kullawattana

How to upload files with Flask API

Suttipong Kullawattana — Tue, 18 Oct 2022 14:01:24 +0000

In this article, I will present code with python about how to upload files with flask API. Before you will start development, I want to you checkup and install the python library , Preparing to set up a virtual environment (env) for development with $ python3 -m venv venv and the active environment with $ source venv/bin/activate

Next step, We will install flask with $ pip install flask and create a folder in the project.

app.py
/ static
  => css
     / style.css
  => img
     / upload_icon.png
     / success_icon.png
/ templates
  => index.html
  => download.html

For the last one, I will install $ pip3 install -r requirements.txt and freeze the library with $ pip freeze > requirements.txt to finish the setup.

After finishing setting up, I will be imported JSON, flask template, and utils of the secure file name. You can follow up on the code below.

import os
import json
from flask import Flask, request, render_template, flash, redirect, url_for, send_from_directory
from werkzeug.utils import secure_filename

In the second step, I have to provide constants that allow checking file format extensions (example: for checking ".txt" file)

ALLOWED_EXTENSIONS = {'txt'}

In the third step, I have to create a new instance for the configuration file format on the code below.

application = Flask(__name__)
application.secret_key = os.urandom(24)
application.config['UPLOAD_FOLDER'] = 'data'
application.config['MAX_CONTENT_LENGTH'] = 4 * 1024 * 1024  # 4MB max-limit.

And I have to create an extension for checking allowed files with ALLOWED_EXTENSIONS

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

The fourth step, I have to create API for uploading files with the browser. If It has a user request to upload the file with localhost IP http://127.0.0.1:5000/, the system will be checking the file part and read the text in document.

# home page
@application.route('/', methods=['POST', 'GET'])
def upload_file():
    if request.method == 'POST':
       if 'file' not in request.files:
          flash('No file part')
          return redirect(request.url)

       file = request.files['file']

       read_text = []
       for text in request.files.get('file'):
          read_text.append(str(text).replace("b'",""))
       print(read_text[0])

       # if the user does not select a file, the browser submits an empty file without a filename.
       if file.filename == '':
         flash('No selected file')
         return redirect(request.url)

       # if the user submits a file with the correct format
       if file and allowed_file(file.filename):
         filename = secure_filename(file.filename)
         file.save(os.path.join(application.config['UPLOAD_FOLDER'], filename))
         os.remove(os.path.join(application.config['UPLOAD_FOLDER'], filename))
         return redirect(url_for('download_file'))

    return render_template('index.html')

After creating the upload file API already. So, I will create a download file API.

# download page
@application.route('/download', methods=['POST', 'GET'])
def download_file():
    if request.method == 'POST':
        if request.form['Download Result File'] == 'Download File':
            return send_from_directory(application.config['UPLOAD_FOLDER'], 'result_file.txt')

For the HTML side, I have to create index.html and download.html on templates folder.

index.html

<!DOCTYPE html>
<html lang="en">

<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <link rel="stylesheet" href="https://www.w3schools.com/w3css/4/w3.css">
    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/css/bootstrap-theme.min.css" integrity="sha384-rHyoN1iRsVXV4nD0JutlnGaslCJuC7uwjduW9SVrLvRYooPp2bWYgmgJQIXwl/Sp" crossorigin="anonymous">
    <title>Download File</title>
</head>

<body>
    <div class="container">
        <section class="vh-100 gradient-custom">
            <div class="text-center justify-content-between py-4 px-4 px-xl-5 bg-dark">
                <div class="text-white mb-2 mb-md-0">
                    <p>Download File</p>
                </div>
            </div>
            <div class="container-fluid h-custom py-4">
                <div class="h-100">
                    <div class="row d-flex justify-content-center align-items-center h-100">
                        <div class="col-12 col-md-9 col-lg-7 col-xl-6">
                            <div class="card" style="border-radius: 15px;">
                                <div class="card-body p-5">
                                    <form method=post enctype=multipart/form-data>
                                        <div style="text-align:center;">
                                            <div class="form-outline mb-4">
                                                <input type=file name=file>
                                            </div>
                                            <div class="form-outline mb-4">
                                                <button type=submit class="btn btn-primary">Upload</button>
                                            </div>
                                        </div>
                                    </form>

                                    {% with messages = get_flashed_messages() %} {% if messages %}
                                    <ul class=flashes>
                                        {% for message in messages %}
                                        <li>{{ message }}</li>
                                        {% endfor %}
                                    </ul>
                                    {% endif %} {% endwith %}
                                </div>
                            </div>
                        </div>
                    </div>
                </div>
            </div>
        </section>
    </div>
</body>

</html>

download.html

<!DOCTYPE html>
<html lang="en">

<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <link rel="stylesheet" href="https://www.w3schools.com/w3css/4/w3.css">
    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/css/bootstrap-theme.min.css" integrity="sha384-rHyoN1iRsVXV4nD0JutlnGaslCJuC7uwjduW9SVrLvRYooPp2bWYgmgJQIXwl/Sp" crossorigin="anonymous">
    <title>Download File Success</title>
</head>

<body>
    <div class="container">
        <section class="vh-100 gradient-custom">
            <div class="container-fluid h-custom py-4">
                <div class="h-100">
                    <div class="row d-flex justify-content-center align-items-center h-100">
                        <div class="col-12 col-md-9 col-lg-7 col-xl-6">
                            <div class="card" style="border-radius: 15px;">
                                <div class="card-body p-5">
                                    <h2 class="text-uppercase text-center mb-5">Download result file</h2>
                                    <form method=post>
                                        <div style="text-align:center;">
                                            <div class="form-outline mb-4">
                                                <input type="submit" name="Download Result File" value="Download BPMN File">
                                            </div>
                                        </div>
                                    </form>
                                    <div style="text-align:center;">
                                        <a href="{{url_for('upload_file')}}">Back to Upload File</a>
                                    </div>
                                </div>
                            </div>
                        </div>
                    </div>
                </div>
            </div>
        </section>
    </div>
</body>

</html>

Result app.py

import os
import json
from flask import Flask, request, render_template, flash, redirect, url_for, send_from_directory
from werkzeug.utils import secure_filename

ALLOWED_EXTENSIONS = {'txt'}

application = Flask(__name__)
application.secret_key = os.urandom(24)
application.config['UPLOAD_FOLDER'] = 'data'
application.config['MAX_CONTENT_LENGTH'] = 4 * 1024 * 1024  # 4MB max-limit.

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

# home page
@application.route('/', methods=['POST', 'GET'])
def upload_file():
    if request.method == 'POST':
       if 'file' not in request.files:
          flash('No file part')
          return redirect(request.url)

       file = request.files['file']

       read_text = []
       for text in request.files.get('file'):
          read_text.append(str(text).replace("b'",""))
       print(read_text[0])

       # if the user does not select a file, the browser submits an empty file without a filename.
       if file.filename == '':
         flash('No selected file')
         return redirect(request.url)

       # if the user submits a file with the correct format
       if file and allowed_file(file.filename):
         filename = secure_filename(file.filename)
         file.save(os.path.join(application.config['UPLOAD_FOLDER'], filename))
         os.remove(os.path.join(application.config['UPLOAD_FOLDER'], filename))
         return redirect(url_for('download_file'))

    return render_template('index.html')

# download page
@application.route('/download', methods=['POST', 'GET'])
def download_file():
    if request.method == 'POST':
        if request.form['Download Result File'] == 'Download File':
            return send_from_directory(application.config['UPLOAD_FOLDER'], 'result_file.txt')

How to extract sentence from spaCy

Suttipong Kullawattana — Tue, 18 Oct 2022 06:11:17 +0000

In the part of NLP, I have some sections to complexity extract words from dependency inform to (nsubj, VERB, dobj etc.) from simple sentences and complex sentences.

For Example



Simple Sentence
- Subject <- VERB -> dobj

A complex sentence has many layers of dependency
# has many subject
- (nsubj -> nsubj) <- VERB -> dobj
# has many verb
- (nsubj -> nsubj) <- VERB -> dobj, VERB -> VERB
# has many object
- (nsubj ->nsubj) <- VERB -> dobj, VERB -> VERB -> dobj

I have to introduce a method for extracting the sentence with python from spaCy, Analyzing grammar structure by creating step rules for extracting words.

Step 1: Import spaCy

Step 2: Create class Phrases() for extracting sentence. You can followup on the code below.



import spacy

class Phrases():
   def __init__(self, sentence):
       self.nlp = spacy.load('en_core_web_sm')
       self.sentence = str(sentence)
       self.doc = self.nlp(self.sentence)
       self.sequence = 0
       self.svos = []

Step 3: Create a method for merging phrases of a sentence. You can followup on the code below.



def merge_phrases(self):
    with self.doc.retokenize() as retokenizer:
        for np in list(self.doc.noun_chunks):
                attrs = {
                    "tag": np.root.tag_,
                    "lemma": np.root.lemma_,
                    "ent_type": np.root.ent_type_,
                }
                retokenizer.merge(np, attrs=attrs)
    return self.doc

We create a new tokenizer object called retokenizer.
We loop through all the noun chunks in the document.
We merge the noun chunks into a single token.
We return the document. The doc object is being returned.

Step 4: Create a method for merging the punctuation of sentences. You can followup on the code below.



def merge_punct(self):
        spans = []
        for word in self.doc[:-1]:
            if word.is_punct or not word.nbor(1).is_punct:
                continue
            start = word.i
            end = word.i + 1
            while end < len(self.doc) and self.doc[end].is_punct:
                end += 1
            span = self.doc[start:end]
            spans.append((span, word.tag_, word.lemma_, word.ent_type_))
        with self.doc.retokenize() as retokenizer:
            for span, tag, lemma, ent_type in spans:
                attrs = {"tag": tag, "lemma": lemma, "ent_type": ent_type}
                retokenizer.merge(span, attrs=attrs)
        return self.doc

If the word is a punctuation mark, or if the next word is not a punctuation mark, then skip it.
Otherwise, start with the current word, and keep adding words to the span until you reach the end of the document, or until you reach a word that is not a punctuation mark.
Then, merge the span into a single token. The doc is being returned.

Step 5: Create a method for extracting the grammar of sentences. In the first step, I will get the text on the sentence parameter, Initialize NLP, Analyze the sentence and keep it in the doc object. You can followup on the code below.



def get_svo(self, sentence):
   doc = self.nlp(sentence)
   doc = self.merge_phrases()
   doc = self.merge_phrases()

From this method, I have to extend checking passive and active sentences with doc object, find all the main verbs and child of a verb, find the subject with the main verb, find the subject with the conjunction of the subject, find the object with the main verb, find prepositional modifier with the main verb, extract S, V, O and prepare SVO to finalize the list.

In the first part of checking passive and active sentences, I have to check passive or active sentences by getting the token from doc.



Simple Sentence
#Subject <- VERB -> dobj

In the sample sentence, We found the "auxpass" in the dependency of the sentence.
#Subject <- auxpass <- VERB -> dobj



def is_passive(self, tokens):
   for tok in tokens:
      if tok.dep_ == "auxpass":
        return True
   return False

On the finding of verbs method, I have got all the main verbs. You can followup the code below.



def _is_verb(self, token):
   return token.dep_ in ["ROOT", "xcomp", "appos", "advcl", "ccomp", "conj"] and token.tag_ in ["VB", "VBZ", "VBD", "VBN", "VBG", "VBP"]

def find_verbs(self, tokens):
   verbs = [tok for tok in tokens if self._is_verb(tok)]
   return verbs

On the finding of the subjects, I have got all the subjects from verbs. You can follow up on the code below.



def get_all_subs(self, v):
   #get all subjects
   subs = [tok for tok in v.lefts if tok.dep_ in ["ROOT", "nsubj", "nsubjpass"] and tok.tag_ in ["NN" , "NNS", "NNP"]]
   if len(subs) == 0:
     #get all subjects from the left of verb ("nsubj" <= "preconj" <= VERB)
     subs = [tok for tok in v.lefts if tok.dep_ in ["preconj"]]
     for sub in subs:
        rights = list(sub.rights)
        right_dependency = [tok.lower_ for tok in rights]
        if len(right_dependency) > 0:
           subs = right_dependency[0]
   return subs

On the finding of the objects, I got all the objects from verbs. You can follow up on the code below.



def get_all_objs(self, v, is_pas):
   #get list the right of dependency with VERB (VERB => "dobj" or "pobj")
   rights = list(v.rights)
   objs = [tok for tok in rights if tok.dep_ in ["dobj", "dative", "attr", "oprd", "pobj"] or (is_pas and tok.dep_ == 'pobj')]
   #get all objects from the right of dependency (VERB => "dobj" or "pobj")
   for obj in objs:
      #on the right of dependency, you can get objects from prepositions (VERB => "dobj" => "prep" => "pobj")
      rights = list(obj.rights) 
      objs.extend(self._get_objs_from_prepositions(rights, is_pas))
   return v, objs

** You can get objects from prepositions **



def _get_objs_from_prepositions(self, deps, is_pas):
   objs = []
   for dep in deps:
      if dep.pos_ == "ADP" and (dep.dep_ == "prep" or (is_pas and dep.dep_ == "agent")):
         objs.extend([tok for tok in dep.rights if tok.dep_  in ["dobj", "dative", "attr", "oprd", "pobj"] or (tok.pos_ == "PRON" and tok.lower_ == "me") or (is_pas and tok.dep_ == 'pobj')])
   return objs

Finally, I have to step the extraction SVO on the method.



def get_svo(self, sentence):
   doc = self.nlp(sentence)
   doc = self.merge_phrases()
   doc = self.merge_phrases()

   #check passive and active sentence
   is_pas = self.is_passive(doc)

   #find the main verb and child of a verb
   verbs = self.find_verbs(doc) 

   #more than verb
   for verb in verbs:
      self.sequence += 1

      #find the subject with the main verb
      subject = self.get_all_subs(verb)

      #find the object with the main verb                
      verb, obj = self.get_all_objs(verb, is_pas)

      #find prepositional modifier with the main verb  
      to_pobj = self.main_get_to_pobj(verb)

      #find prepositional modifier with the main verb
      if to_pobj is not None:
        self.svos.append((self.sequence, subject, verb, obj, to_pobj))
      else:
        self.svos.append((self.sequence, subject, verb, obj, ""))

Final Class



import spacy

class Phrases():
    def __init__(self, sentence):
       self.nlp = spacy.load('en_core_web_sm')
       self.sentence = str(sentence)
       self.doc = self.nlp(self.sentence)
       self.sequence = 0
       self.svos = []

    def merge_phrases(self):
        with self.doc.retokenize() as retokenizer:
            for np in list(self.doc.noun_chunks):
                    attrs = {
                        "tag": np.root.tag_,
                        "lemma": np.root.lemma_,
                        "ent_type": np.root.ent_type_,
                    }
                    retokenizer.merge(np, attrs=attrs)
        return self.doc

    def merge_punct(self):
        spans = []
        for word in self.doc[:-1]:
            if word.is_punct or not word.nbor(1).is_punct:
                continue
            start = word.i
            end = word.i + 1
            while end < len(self.doc) and self.doc[end].is_punct:
                end += 1
            span = self.doc[start:end]
            spans.append((span, word.tag_, word.lemma_, word.ent_type_))
        with self.doc.retokenize() as retokenizer:
            for span, tag, lemma, ent_type in spans:
                attrs = {"tag": tag, "lemma": lemma, "ent_type": ent_type}
                retokenizer.merge(span, attrs=attrs)
        return self.doc

    def is_passive(self, tokens):
        for tok in tokens:
            if tok.dep_ == "auxpass":
                return True
        return False

    def _is_verb(self, token):
        return token.dep_ in ["ROOT", "xcomp", "appos", "advcl", "ccomp", "conj"] and token.tag_ in ["VB", "VBZ", "VBD", "VBN", "VBG", "VBP"]

    def find_verbs(self, tokens):
        verbs = [tok for tok in tokens if self._is_verb(tok)]
        return verbs

    def get_all_subs(self, v):
        #get all subjects
        subs = [tok for tok in v.lefts if tok.dep_ in ["ROOT", "nsubj", "nsubjpass"] and tok.tag_ in ["NN" , "NNS", "NNP"]]
        if len(subs) == 0:
            #get all subjects from the left of verb ("nsubj" <= "preconj" <= VERB)
            subs = [tok for tok in v.lefts if tok.dep_ in ["preconj"]]
            for sub in subs:
                rights = list(sub.rights)
                right_dependency = [tok.lower_ for tok in rights]
                if len(right_dependency) > 0:
                    subs = right_dependency[0]
        return subs

    def get_all_objs(self, v, is_pas):
        #get list the right of dependency with VERB (VERB => "dobj" or "pobj")
        rights = list(v.rights)
        objs = [tok for tok in rights if tok.dep_ in ["dobj", "dative", "attr", "oprd", "pobj"] or (is_pas and tok.dep_ == 'pobj')]
        #get all objects from the right of dependency (VERB => "dobj" or "pobj")
        for obj in objs:
            #on the right of dependency, you can get objects from prepositions (VERB => "dobj" => "prep" => "pobj")
            rights = list(obj.rights) 
            objs.extend(self._get_objs_from_prepositions(rights, is_pas))
        return v, objs

    def _get_objs_from_prepositions(self, deps, is_pas):
        objs = []
        for dep in deps:
            if dep.pos_ == "ADP" and (dep.dep_ == "prep" or (is_pas and dep.dep_ == "agent")):
                objs.extend([tok for tok in dep.rights if tok.dep_  in ["dobj", "dative", "attr", "oprd", "pobj"] or (tok.pos_ == "PRON" and tok.lower_ == "me") or (is_pas and tok.dep_ == 'pobj')])
        return objs

    def get_svo(self, sentence):
        doc = self.nlp(sentence)
        doc = self.merge_phrases()
        doc = self.merge_phrases()

        #check passive and active sentence
        is_pas = self.is_passive(doc)

        #find the main verb and child of a verb
        verbs = self.find_verbs(doc) 

        #more than verb
        for verb in verbs:
            self.sequence += 1

            #find the subject with the main verb
            subject = self.get_all_subs(verb)

            #find the object with the main verb                
            verb, obj = self.get_all_objs(verb, is_pas)

            #find prepositional modifier with the main verb  
            to_pobj = self.main_get_to_pobj(verb)

            #You can continue create method for extract word ...

            #finally, we can find prepositional modifier with the main verb
            if to_pobj is not None:
                #result SVO
                self.svos.append((self.sequence, subject, verb, obj, to_pobj))
            else:
                #result SVO
                self.svos.append((self.sequence, subject, verb, obj, ""))

Try to test with the sentence.

First sentence: CSO, a workflow controller handle assigned incidents.

Extraction result: [(1, [a workflow controller], handle, [assigned incidents], '')]

Second sentence: Call the help desk and make a request.

Extraction result: [(1, [], Call, [the help desk], ''), (2, [], make, [a request], '')]

Third sentence: Receipt department returns the good to the vendor and system sends notification to the purchase department.

Extraction result: [(1, [Receipt department], returns, [the good], ['the vendor']), (2, [], sends, [notification, the purchase department], '')]

RESTful Webservice, gRPC, ApacheThrift for Microservices

Suttipong Kullawattana — Thu, 11 Aug 2022 08:21:00 +0000

How to create microservices

We will create a RESTful Webservice using request URI/URL to search and process and respond in XML, HTML, JSON format.

Commands are followed by HTTP verbs, which are

- GET: performs fetching within a given URI.
- POST: for generating data.
- PUT: is used to edit information.
- DELETE: to delete data.

How to create API naming convention

The API naming convention should be named as a group of nouns to indicate that it is a group of Resources.

How to checking request and response with tool

I recommend the gRPC tool. It is an open source framework that will perform request service and response that requests come in.

In thai reference have many talk how to use gRPC

How to improve performance transmission data with tool

How to talk through the service with a Binary method, which will make the transmission efficiency faster It recommends a tool called ApacheThrift. Suitable for use in Big Data applications where most applications are synchronous. If the destination system has a timeout, it should not be called.

The process of uploading the application to the Google Play Store

Suttipong Kullawattana — Thu, 11 Aug 2022 07:06:00 +0000

In this article, I will summarize how to get apps on the Google Play Store.

Must have a Google Account.
Apply for Google Wallet with the account in item 1. to use for payment of fees. (one-time payment) 25$
Once you have an account to spend money, go to apply for Google Play Developer Console by filling in the details. (If not a company, choose Individual)
When filling in the details until the last part, it will pay with the above Google Wallet.

Get your data and files ready.

Part 1: **Prepare an image to be displayed on the Google Play page.
- Screenshot: At least 2 images, the size available is 320x480, 480x800, 480x854, 1280x720, 1280x800 extension PNG or JPEG.
- Icon: Size 512 x 512, extension PNG or JPEG only
- Feature Graphic: is a cover image on our app page, size 1024x500

Part 2: Prepare files to upload to Google Play

1.Check the code in AndroidManifest.xml is correct. This will determine the version. This will allow the app to be updated automatically. An example is

When uploading for the first time, it must be
android:versionCode="1"
android:versionName="1.0"

When a new code is modified and wants to upgrade to replace the original version, modify it to
android:versionCode="2"
android:versionName=”1.1"

2.Once all code is correct, right click on our project on the left side -> Android Tools -> Export Signed Application Package.

3.Check if our project name is correct or not, if yes, click Next.

4.In this section, it will ask our keystore. First, if you don't have it yet, choose to create a new keystore and choose the address to save. The file name created must have a .keystore extension, for example, testapp.keystore, etc. Then enter the password. Press Next

VERY IMPORTANT Do not lose the keystore file and remember the password carefully. Because it will be needed when uploading the app next time. (recommended to store it on cloud server)

5.In this section, enter your name, password (recommended to be the same as item 4 so you don't forget it) in the Validity field, then enter the expiration date of 100 years. The rest is up to you.

6.Specify the address to save our apk file (files used to upload to Google Play) by specifying the extension is .apk.

7.Go to Google Play Developer Console page link and click on Upload Application and select APK file and Upload.

Publishing status

Near the top of individual apps' pages on your Developer Console, you can see your app's latest publishing status. Whether you're publishing an app for the first time or making an update, you can use your publishing status to understand your app's availability on Google Play. Here are the different statuses that can be displayed for your app:

- Draft: App hasn't been published on Google Play.

Note: If the Publish app option isn't available, click Why can't I publish? for more information or check your app's pages on the left menu to make sure you've included all required information for your app.

- Pending publication: App is currently being processed for publishing.
- Published: App is published and available on Google Play.
- Rejected: App has been rejected and wasn't published due to a violation of Google Play policies. More information about the violation is available near the top of your app's pages on the Developer Console. Once you make a change to your app to address the violation, you can submit it again.
- Suspended: App is suspended due to a violation of Google Play Policies (Content Policy, Developer Distribution Agreement).

An email with details about the suspension is sent to the account owner.

How to Extract Tree by spaCy

Suttipong Kullawattana — Wed, 10 Aug 2022 14:00:00 +0000

In this article, I will present the process of reading a document. for the analysis of the natural language structure of the tree These processes are useful for those working in the analysis of natural language structure from documents. This may lead to applications with applications to process language structures to prepare data. (Pre-Processing) in the process of doing Data Science, which is very important. if we can't handle the initial modeling process effectively It may be a model that has no quality.

which the algorithm to process There are steps as follows.

Import libraries spaCy, NLTK for natural language. processing, I will import pos_tag (Part-of-Speech Processing), word_tokenize (reading words from the Token), and Tree (drawing a tree structure).
Import a natural language processing model from the spaCy library using “en_core_web_sm”, a smaller language processing model. Suitable for general language processing.
read text from the text file.
Methods to draw tree structures It uses the tree node reading method, which uses the Tree algorithm to draw it.
Calling the Plot tree structure from an imported language readable from a file.
Determining the pattern of words and drawing (result.draw()) by checking words from Token.

The result of drawing a tree from a language structure.

*Sentence 1: * “A small company manufactures customized bicycles.”

Drawing the sentence structure “A small company manufactures customized bicycles.” with NLTK.

Drawing the sentence structure “A small company manufactures customized bicycles.” with spaCy.

*Sentence 2: * “Whenever the sales department receives an order, a new process instance is created.”

Drawing a sentence structure “Whenever the sales department receives an order, a new process instance is created.” with NLTK.

Drawing a sentence structure “Whenever the sales department receives an order, a new process instance is created.” with spaCy.