import re
from collections import defaultdict, Counter
DATA = [
    {
        'title': 'Django',
        'description': 'Django is a high-level Python Web framework that '
            'encourages rapid development and clean, pragmatic design.  Built by '
            'experienced developers, it takes care of much of the hassle of Web '
            'development, so you can focus on writing your app without needing to '
            
    },
    {
        'title': 'Python',
        'description': 'Python is a programming language that lets you work '
            'more quickly and integrate your systems more effectively.'
    },
]

SPLIT_RE = re.compile(r'[^a-zA-Z0-9]')
def tokenize(text):
    yield from SPLIT_RE.split(text)

def text_only(tokens):
    for t in tokens:
        if t.isalnum():
            yield t

def lowercase(tokens):
    for t in tokens:
        yield t.lower()

def stem(tokens):
    for t in tokens:
        if t.endswith('ly'):
            t = t[:-2]
        yield t




def analyze(text):
    tokens = tokenize(text)
    for token_filter in (text_only, lowercase, stem):
        tokens = token_filter(tokens)
    yield from tokens

def index_docs(docs, *fields):
    index = defaultdict(lambda: defaultdict(Counter))
    for id, doc in enumerate(docs):
        for field in fields:
            for token in analyze(doc[field]):
                index[field][token][id] += 1
    return index



index = index_docs(DATA, 'title', 'description')
print(index)


844e3f3cc6513e4fd7f3282bd57a44205bcc8c7c
<mask token>


def text_only(tokens):
    for t in tokens:
        if t.isalnum():
            yield t


def lowercase(tokens):
    for t in tokens:
        yield t.lower()


def stem(tokens):
    for t in tokens:
        if t.endswith('ly'):
            t = t[:-2]
        yield t


def analyze(text):
    tokens = tokenize(text)
    for token_filter in (text_only, lowercase, stem):
        tokens = token_filter(tokens)
    yield from tokens


def index_docs(docs, *fields):
    index = defaultdict(lambda : defaultdict(Counter))
    for id, doc in enumerate(docs):
        for field in fields:
            for token in analyze(doc[field]):
                index[field][token][id] += 1
    return index


<mask token>

<mask token>


def tokenize(text):
    yield from SPLIT_RE.split(text)


def text_only(tokens):
    for t in tokens:
        if t.isalnum():
            yield t


def lowercase(tokens):
    for t in tokens:
        yield t.lower()


def stem(tokens):
    for t in tokens:
        if t.endswith('ly'):
            t = t[:-2]
        yield t


def analyze(text):
    tokens = tokenize(text)
    for token_filter in (text_only, lowercase, stem):
        tokens = token_filter(tokens)
    yield from tokens


def index_docs(docs, *fields):
    index = defaultdict(lambda : defaultdict(Counter))
    for id, doc in enumerate(docs):
        for field in fields:
            for token in analyze(doc[field]):
                index[field][token][id] += 1
    return index


<mask token>

<mask token>


def tokenize(text):
    yield from SPLIT_RE.split(text)


def text_only(tokens):
    for t in tokens:
        if t.isalnum():
            yield t


def lowercase(tokens):
    for t in tokens:
        yield t.lower()


def stem(tokens):
    for t in tokens:
        if t.endswith('ly'):
            t = t[:-2]
        yield t


def analyze(text):
    tokens = tokenize(text)
    for token_filter in (text_only, lowercase, stem):
        tokens = token_filter(tokens)
    yield from tokens


def index_docs(docs, *fields):
    index = defaultdict(lambda : defaultdict(Counter))
    for id, doc in enumerate(docs):
        for field in fields:
            for token in analyze(doc[field]):
                index[field][token][id] += 1
    return index


<mask token>
print(index)

<mask token>
DATA = [{'title': 'Django', 'description':
    'Django is a high-level Python Web framework that encourages rapid development and clean, pragmatic design.  Built by experienced developers, it takes care of much of the hassle of Web development, so you can focus on writing your app without needing to '
    }, {'title': 'Python', 'description':
    'Python is a programming language that lets you work more quickly and integrate your systems more effectively.'
    }]
SPLIT_RE = re.compile('[^a-zA-Z0-9]')


def tokenize(text):
    yield from SPLIT_RE.split(text)


def text_only(tokens):
    for t in tokens:
        if t.isalnum():
            yield t


def lowercase(tokens):
    for t in tokens:
        yield t.lower()


def stem(tokens):
    for t in tokens:
        if t.endswith('ly'):
            t = t[:-2]
        yield t


def analyze(text):
    tokens = tokenize(text)
    for token_filter in (text_only, lowercase, stem):
        tokens = token_filter(tokens)
    yield from tokens


def index_docs(docs, *fields):
    index = defaultdict(lambda : defaultdict(Counter))
    for id, doc in enumerate(docs):
        for field in fields:
            for token in analyze(doc[field]):
                index[field][token][id] += 1
    return index


index = index_docs(DATA, 'title', 'description')
print(index)

import re
from collections import defaultdict, Counter
DATA = [
    {
        'title': 'Django',
        'description': 'Django is a high-level Python Web framework that '
            'encourages rapid development and clean, pragmatic design.  Built by '
            'experienced developers, it takes care of much of the hassle of Web '
            'development, so you can focus on writing your app without needing to '
            
    },
    {
        'title': 'Python',
        'description': 'Python is a programming language that lets you work '
            'more quickly and integrate your systems more effectively.'
    },
]

SPLIT_RE = re.compile(r'[^a-zA-Z0-9]')
def tokenize(text):
    yield from SPLIT_RE.split(text)

def text_only(tokens):
    for t in tokens:
        if t.isalnum():
            yield t

def lowercase(tokens):
    for t in tokens:
        yield t.lower()

def stem(tokens):
    for t in tokens:
        if t.endswith('ly'):
            t = t[:-2]
        yield t




def analyze(text):
    tokens = tokenize(text)
    for token_filter in (text_only, lowercase, stem):
        tokens = token_filter(tokens)
    yield from tokens

def index_docs(docs, *fields):
    index = defaultdict(lambda: defaultdict(Counter))
    for id, doc in enumerate(docs):
        for field in fields:
            for token in analyze(doc[field]):
                index[field][token][id] += 1
    return index



index = index_docs(DATA, 'title', 'description')
print(index)

