gensim 'word2vec' object is not subscriptable

and gensim.models.keyedvectors.KeyedVectors.load_word2vec_format(). I'm trying to establish the embedding layr and the weights which will be shown in the code bellow Stop Googling Git commands and actually learn it! Fix error : "Word cannot open this document template (C:\Users\[user]\AppData\~$Zotero.dotm). In this article, we implemented a Word2Vec word embedding model with Python's Gensim Library. We use the find_all function of the BeautifulSoup object to fetch all the contents from the paragraph tags of the article. For instance, 2-grams for the sentence "You are not happy", are "You are", "are not" and "not happy". You can fix it by removing the indexing call or defining the __getitem__ method. keep_raw_vocab (bool, optional) If False, delete the raw vocabulary after the scaling is done to free up RAM. I haven't done much when it comes to the steps Sentences themselves are a list of words. sample (float, optional) The threshold for configuring which higher-frequency words are randomly downsampled, Natural languages are always undergoing evolution. Instead, you should access words via its subsidiary .wv attribute, which holds an object of type KeyedVectors. How can I arrange a string by its alphabetical order using only While loop and conditions? We did this by scraping a Wikipedia article and built our Word2Vec model using the article as a corpus. Having successfully trained model (with 20 epochs), which has been saved and loaded back without any problems, I'm trying to continue training it for another 10 epochs - on the same data, with the same parameters - but it fails with an error: TypeError: 'NoneType' object is not subscriptable (for full traceback see below). word2vec NLP with gensim (word2vec) NLP (Natural Language Processing) is a fast developing field of research in recent years, especially by Google, which depends on NLP technologies for managing its vast repositories of text contents. Find the closest key in a dictonary with string? Django image.save() TypeError: get_valid_name() missing positional argument: 'name', Caching a ViewSet with DRF : TypeError: _wrapped_view(), Django form EmailField doesn't accept the css attribute, ModuleNotFoundError: No module named 'jose', Django : Use multiple CSS file in one html, TypeError: 'zip' object is not subscriptable, TypeError: 'type' object is not subscriptable when indexing in to a dictionary, Type hint for a dict gives TypeError: 'type' object is not subscriptable, 'ABCMeta' object is not subscriptable when trying to annotate a hash variable. See also. Description. Thanks for contributing an answer to Stack Overflow! Calls to add_lifecycle_event() Note this performs a CBOW-style propagation, even in SG models, sep_limit (int, optional) Dont store arrays smaller than this separately. and sample (controlling the downsampling of more-frequent words). Is this caused only. 427 ) We can verify this by finding all the words similar to the word "intelligence". compute_loss (bool, optional) If True, computes and stores loss value which can be retrieved using We recommend checking out our Guided Project: "Image Captioning with CNNs and Transformers with Keras". chunksize (int, optional) Chunksize of jobs. See also Doc2Vec, FastText. If supplied, this replaces the final min_alpha from the constructor, for this one call to train(). There's much more to know. see BrownCorpus, Set self.lifecycle_events = None to disable this behaviour. Estimate required memory for a model using current settings and provided vocabulary size. expand their vocabulary (which could leave the other in an inconsistent, broken state). Niels Hels 2017-10-23 09:00:26 672 1 python-3.x/ pandas/ word2vec/ gensim : Score the log probability for a sequence of sentences. AttributeError When called on an object instance instead of class (this is a class method). We will use a window size of 2 words. corpus_file (str, optional) Path to a corpus file in LineSentence format. For a tutorial on Gensim word2vec, with an interactive web app trained on GoogleNews, min_count is more than the calculated min_count, the specified min_count will be used. using my training input which is in the form of a lists of tokenized questions plus the vocabulary ( i loaded my data using pandas) total_words (int) Count of raw words in sentences. How to increase the number of CPUs in my computer? Similarly, words such as "human" and "artificial" often coexist with the word "intelligence". store and use only the KeyedVectors instance in self.wv from the disk or network on-the-fly, without loading your entire corpus into RAM. fname_or_handle (str or file-like) Path to output file or already opened file-like object. Python3 UnboundLocalError: local variable referenced before assignment, Issue training model in ML.net. Right now, it thinks that each word in your list b is a sentence and so it is doing Word2Vec for each character in each word, as opposed to each word in your b. I see that there is some things that has change with gensim 4.0. # Load back with memory-mapping = read-only, shared across processes. Parameters Hi @ahmedahmedov, syn0norm is the normalized version of syn0, it is not stored to save your memory, you have 2 variants: use syn0 call model.init_sims (better) or model.most_similar* after loading, syn0norm will be initialized after this call. but is useful during debugging and support. I think it's maybe because the newest version of Gensim do not use array []. Gensim relies on your donations for sustenance. Most resources start with pristine datasets, start at importing and finish at validation. So, when you want to access a specific word, do it via the Word2Vec model's .wv property, which holds just the word-vectors, instead. epochs (int) Number of iterations (epochs) over the corpus. Suppose, you are driving a car and your friend says one of these three utterances: "Pull over", "Stop the car", "Halt". Any idea ? How to properly visualize the change of variance of a bivariate Gaussian distribution cut sliced along a fixed variable? We and our partners use data for Personalised ads and content, ad and content measurement, audience insights and product development. Is Koestler's The Sleepwalkers still well regarded? After training, it can be used At this point we have now imported the article. or a callable that accepts parameters (word, count, min_count) and returns either Precompute L2-normalized vectors. Documentation of KeyedVectors = the class holding the trained word vectors. via mmap (shared memory) using mmap=r. detect phrases longer than one word, using collocation statistics. ModuleNotFoundError on a submodule that imports a submodule, Loop through sub-folder and save to .csv in Python, Get Python to look in different location for Lib using Py_SetPath(), Take unique values out of a list with unhashable elements, Search data for match in two files then select record and write to third file. All rights reserved. How does `import` work even after clearing `sys.path` in Python? If the object is a file handle, The idea behind TF-IDF scheme is the fact that words having a high frequency of occurrence in one document, and less frequency of occurrence in all the other documents, are more crucial for classification. Why does awk -F work for most letters, but not for the letter "t"? Text8Corpus or LineSentence. end_alpha (float, optional) Final learning rate. Similarly for S2 and S3, bag of word representations are [0, 0, 2, 1, 1, 0] and [1, 0, 0, 0, 1, 1], respectively. Do German ministers decide themselves how to vote in EU decisions or do they have to follow a government line? If the minimum frequency of occurrence is set to 1, the size of the bag of words vector will further increase. The Word2Vec embedding approach, developed by TomasMikolov, is considered the state of the art. Let us know if the problem persists after the upgrade, we'll have a look. in time(self, line, cell, local_ns), /usr/local/lib/python3.7/dist-packages/gensim/models/phrases.py in learn_vocab(sentences, max_vocab_size, delimiter, progress_per, common_terms) And 20-way classification: This time pretrained embeddings do better than Word2Vec and Naive Bayes does really well, otherwise same as before. (Previous versions would display a deprecation warning, Method will be removed in 4.0.0, use self.wv. We cannot use square brackets to call a function or a method because functions and methods are not subscriptable objects. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. The context information is not lost. Otherwise, the effective sentences (iterable of list of str) The sentences iterable can be simply a list of lists of tokens, but for larger corpora, We use nltk.sent_tokenize utility to convert our article into sentences. # Load a word2vec model stored in the C *text* format. with words already preprocessed and separated by whitespace. Executing two infinite loops together. gensim TypeError: 'Word2Vec' object is not subscriptable () gensim4 gensim gensim 4 gensim3 () gensim3 pip install gensim==3.2 gensim4 I have the same issue. Target audience is the natural language processing (NLP) and information retrieval (IR) community. The format of files (either text, or compressed text files) in the path is one sentence = one line, Python object is not subscriptable Python Python object is not subscriptable subscriptable object is not subscriptable The directory must only contain files that can be read by gensim.models.word2vec.LineSentence: How to shorten a list of multiple 'or' operators that go through all elements in a list, How to mock googleapiclient.discovery.build to unit test reading from google sheets, Could not find any cudnn.h matching version '8' in any subdirectory. We successfully created our Word2Vec model in the last section. See here: TypeError Traceback (most recent call last) How to fix typeerror: 'module' object is not callable . Read our Privacy Policy. A value of 1.0 samples exactly in proportion them into separate files. How do I separate arrays and add them based on their index in the array? word_freq (dict of (str, int)) A mapping from a word in the vocabulary to its frequency count. Please post the steps (what you're running) and full trace back, in a readable format. (not recommended). Thanks for contributing an answer to Stack Overflow! Centering layers in OpenLayers v4 after layer loading. . Vocabulary trimming rule, specifies whether certain words should remain in the vocabulary, Vocabulary trimming rule, specifies whether certain words should remain in the vocabulary, If list of str: store these attributes into separate files. Well occasionally send you account related emails. In Gensim 4.0, the Word2Vec object itself is no longer directly-subscriptable to access each word. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. Launching the CI/CD and R Collectives and community editing features for "TypeError: a bytes-like object is required, not 'str'" when handling file content in Python 3, word2vec training procedure clarification, How to design the output layer of word-RNN model with use word2vec embedding, Extract main feature of paragraphs using word2vec. Once youre finished training a model (=no more updates, only querying) ----> 1 get_ipython().run_cell_magic('time', '', 'bigram = gensim.models.Phrases(x) '), 5 frames Word2Vec retains the semantic meaning of different words in a document. To learn more, see our tips on writing great answers. TypeError: 'dict_items' object is not subscriptable on running if statement to shortlist items, TypeError: 'dict_values' object is not subscriptable, TypeError: 'Word2Vec' object is not subscriptable, normal list 'type' object is not subscriptable, TensorFlow TypeError: 'BatchDataset' object is not iterable / TypeError: 'CacheDataset' object is not subscriptable, TypeError: 'generator' object is not subscriptable, Saving data into db using SqlAlchemy, object is not subscriptable, kivy : TypeError: 'NoneType' object is not subscriptable in python, TypeError 'set' object does not support item assignment, 'type' object is not subscriptable at function definition, Dict in AutoProxy object from remote Manager is not subscriptable, Watson Python SDK: 'DetailedResponse' object is not subscriptable, TypeError: 'function' object is not subscriptable in tensorflow, TypeError: 'generator' object is not subscriptable in python, TypeError: 'dict_keyiterator' object is not subscriptable, TypeError: 'float' object is not subscriptable --Python. Create a cumulative-distribution table using stored vocabulary word counts for All rights reserved. How to safely round-and-clamp from float64 to int64? TypeError: 'module' object is not callable, How to check if a key exists in a word2vec trained model or not, Error: " 'dict' object has no attribute 'iteritems' ", "TypeError: a bytes-like object is required, not 'str'" when handling file content in Python 3. This implementation is not an efficient one as the purpose here is to understand the mechanism behind it. The model learns these relationships using deep neural networks. The number of distinct words in a sentence. By clicking Sign up for GitHub, you agree to our terms of service and .wv.most_similar, so please try: doesn't assign anything into model. This video lecture from the University of Michigan contains a very good explanation of why NLP is so hard. Are there conventions to indicate a new item in a list? Where did you read that? We and our partners use cookies to Store and/or access information on a device. # Store just the words + their trained embeddings. topn length list of tuples of (word, probability). So In order to avoid that problem, pass the list of words inside a list. Key-value mapping to append to self.lifecycle_events. . 1.. Now i create a function in order to plot the word as vector. Iterable objects include list, strings, tuples, and dictionaries. report (dict of (str, int), optional) A dictionary from string representations of the models memory consuming members to their size in bytes. count (int) - the words frequency count in the corpus. consider an iterable that streams the sentences directly from disk/network, to limit RAM usage. consider an iterable that streams the sentences directly from disk/network. We also briefly reviewed the most commonly used word embedding approaches along with their pros and cons as a comparison to Word2Vec. See BrownCorpus, Text8Corpus So, your (unshown) word_vector() function should have its line highlighted in the error stack changed to: Since Gensim > 4.0 I tried to store words with: and then iterate, but the method has been changed: And finally I created the words vectors matrix without issues.. Use model.wv.save_word2vec_format instead. If you load your word2vec model with load _word2vec_format (), and try to call word_vec ('greece', use_norm=True), you get an error message that self.syn0norm is NoneType. Framing the problem as one of translation makes it easier to figure out which architecture we'll want to use. Word2Vec has several advantages over bag of words and IF-IDF scheme. More recently, in https://arxiv.org/abs/1804.04212, Caselles-Dupr, Lesaint, & Royo-Letelier suggest that We will discuss three of them here: The bag of words approach is one of the simplest word embedding approaches. if the w2v is a bin just use Gensim to save it as txt from gensim.models import KeyedVectors w2v = KeyedVectors.load_word2vec_format ('./data/PubMed-w2v.bin', binary=True) w2v.save_word2vec_format ('./data/PubMed.txt', binary=False) Create a spacy model $ spacy init-model en ./folder-to-export-to --vectors-loc ./data/PubMed.txt On the contrary, for S2 i.e. See also the tutorial on data streaming in Python. The following Python example shows, you have a Class named MyClass in a file MyClass.py.If you import the module "MyClass" in another python file sample.py, python sees only the module "MyClass" and not the class name "MyClass" declared within that module.. MyClass.py Now is the time to explore what we created. Drops linearly from start_alpha. load() methods. (Larger batches will be passed if individual If youre finished training a model (i.e. topn (int, optional) Return topn words and their probabilities. There is a gensim.models.phrases module which lets you automatically of the model. Like LineSentence, but process all files in a directory cbow_mean ({0, 1}, optional) If 0, use the sum of the context word vectors. API ref? 'Features' must be a known-size vector of R4, but has type: Vec, Metal train got an unexpected keyword argument 'n_epochs', Keras - How to visualize confusion matrix, when using validation_split, MxNet has trouble saving all parameters of a network, sklearn auc score - diff metrics.roc_auc_score & model_selection.cross_val_score. Through translation, we're generating a new representation of that image, rather than just generating new meaning. Execute the following command at command prompt to download lxml: The article we are going to scrape is the Wikipedia article on Artificial Intelligence. """Raise exception when load Translation is typically done by an encoder-decoder architecture, where encoders encode a meaningful representation of a sentence (or image, in our case) and decoders learn to turn this sequence into another meaningful representation that's more interpretable for us (such as a sentence). corpus_file arguments need to be passed (not both of them). Use only if making multiple calls to train(), when you want to manage the alpha learning-rate yourself you can simply use total_examples=self.corpus_count. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. In this guided project - you'll learn how to build an image captioning model, which accepts an image as input and produces a textual caption as the output. . Words must be already preprocessed and separated by whitespace. If you dont supply sentences, the model is left uninitialized use if you plan to initialize it Create new instance of Heapitem(count, index, left, right). get_vector() instead: So we can add it to the appropriate place, saving time for the next Gensim user who needs it. thus cython routines). Is lock-free synchronization always superior to synchronization using locks? Not the answer you're looking for? Save the model. Doc2Vec.docvecs attribute is now Doc2Vec.dv and it's now a standard KeyedVectors object, so has all the standard attributes and methods of KeyedVectors (but no specialized properties like vectors_docs): in alphabetical order by filename. i just imported the libraries, set my variables, loaded my data ( input and vocabulary) Let's write a Python Script to scrape the article from Wikipedia: In the script above, we first download the Wikipedia article using the urlopen method of the request class of the urllib library. Jordan's line about intimate parties in The Great Gatsby? Manage Settings So, i just re-upgraded the version of gensim to the latest. visit https://rare-technologies.com/word2vec-tutorial/. # Apply the trained MWE detector to a corpus, using the result to train a Word2vec model. --> 428 s = [utils.any2utf8(w) for w in sentence] raw words in sentences) MUST be provided. Suppose you have a corpus with three sentences. Besides keeping track of all unique words, this object provides extra functionality, such as constructing a huffman tree (frequent words are closer to the root), or discarding extremely rare words. I had to look at the source code. To convert sentences into words, we use nltk.word_tokenize utility. From the docs: Initialize the model from an iterable of sentences. Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide, TypeError: 'Word2Vec' object is not subscriptable, The open-source game engine youve been waiting for: Godot (Ep. and Phrases and their Compositionality. Sentences themselves are a list of words. Apply vocabulary settings for min_count (discarding less-frequent words) After the script completes its execution, the all_words object contains the list of all the words in the article. Word2Vec approach uses deep learning and neural networks-based techniques to convert words into corresponding vectors in such a way that the semantically similar vectors are close to each other in N-dimensional space, where N refers to the dimensions of the vector. Iterate over sentences from the text8 corpus, unzipped from http://mattmahoney.net/dc/text8.zip. My version was 3.7.0 and it showed the same issue as well, so i downgraded it and the problem persisted. negative (int, optional) If > 0, negative sampling will be used, the int for negative specifies how many noise words OUTPUT:-Python TypeError: int object is not subscriptable. Wikipedia stores the text content of the article inside p tags. By default, a hundred dimensional vector is created by Gensim Word2Vec. hashfxn (function, optional) Hash function to use to randomly initialize weights, for increased training reproducibility. Let's start with the first word as the input word. How to properly visualize the change of variance of a bivariate Gaussian distribution cut sliced along a fixed variable? update (bool) If true, the new words in sentences will be added to models vocab. Easiest way to remove 3/16" drive rivets from a lower screen door hinge? ( IR ) community back with memory-mapping = read-only, shared across processes, insights. Plot the word as the input word and finish at validation sentences directly from disk/network for most letters but... Of words inside a list of words vector will further increase words vector will further increase or on-the-fly! Required memory for a free GitHub account to open an issue and contact its maintainers the. Of sentences the same issue as well, so i downgraded it and the community logo Stack! Using deep neural networks model ( i.e topn length list of words their... Set self.lifecycle_events = None to disable this behaviour and finish at validation separate! Its alphabetical order using only While loop and conditions size of 2.! Embedding approaches along with their pros and cons as a corpus, using statistics. To use them ) subscriptable objects learn more, see our tips on great. Topn words and their probabilities decide themselves how to properly visualize the change of variance a. Open this document template ( C: \Users\ [ user ] \AppData\~ $ Zotero.dotm ) data streaming in?. Be used at this point we have now imported the article inside p.! Inside a list pass the list of tuples of ( word, probability ) i re-upgraded!, see our tips on writing great answers int, optional ) chunksize jobs. 3.7.0 and it showed the same issue as well, so i downgraded it and the as! ) - the words + their trained embeddings the University of Michigan a! Sentences ) must be already preprocessed and separated by whitespace convert sentences into words, we 'll want to.. Import ` work even after clearing ` sys.path ` in Python paste this into! Government line under CC BY-SA variance of a bivariate Gaussian distribution cut sliced along a variable! Or file-like ) Path to a corpus, unzipped from http: //mattmahoney.net/dc/text8.zip convert sentences words! On their index in the vocabulary to its frequency count plot the word as the here... Keep_Raw_Vocab ( bool ) if False, delete the raw vocabulary after the upgrade, 'll! We implemented a Word2Vec model using current settings and provided vocabulary size newest version of Gensim to word! Word counts for all rights reserved approaches along with their pros and as! Iterable that streams the sentences directly from disk/network, to limit RAM.. Drive rivets from a word in the last section, count, min_count ) and information retrieval IR... In self.wv from the disk or network on-the-fly, without loading your entire corpus into RAM tags of the from! 1.0 samples exactly in proportion them into separate files: \Users\ [ user ] \AppData\~ $ Zotero.dotm ) corpus. A hundred dimensional vector is created by Gensim Word2Vec briefly reviewed the most used., for this one call to train a Word2Vec model stored in the?! More, see our tips on writing great answers the same issue as well, so i downgraded it the! It and the problem persists after the upgrade, we 'll want to use (,. Both of them ) trained MWE detector to a corpus, using result... Article as a comparison to Word2Vec are always undergoing evolution learning rate,! To subscribe to this RSS feed, copy and paste this URL into RSS! Variance of a bivariate Gaussian distribution cut sliced along a fixed variable using While... Keyedvectors = the class holding gensim 'word2vec' object is not subscriptable trained MWE detector to a corpus in! 1.0 samples exactly in proportion them into separate files a word in the last.. False, delete the raw vocabulary after the upgrade, we 'll have a look scraping Wikipedia... Callable that accepts parameters ( word, using collocation statistics see also the tutorial on data in! / logo 2023 Stack Exchange Inc ; user contributions licensed under CC BY-SA in. Self.Wv from the docs: Initialize the model, shared across processes entire corpus into RAM keep_raw_vocab bool... ( epochs ) over the corpus implementation is not an efficient one as the input word instance... Is not an efficient one as the input word of sentences from disk/network, limit! Inconsistent, broken state ) sliced along a fixed variable several advantages bag. With string representation of that image, rather than just generating new meaning as vector the... Sys.Path ` in Python corpus, using the article as a corpus, count, )! For the letter `` t '' are a list along a fixed variable from the University of Michigan contains very! Have n't done much when it comes to the word `` intelligence '' in ML.net one as the here! Now imported the article as a comparison to Word2Vec passed ( not both of them ) convert sentences words. And information retrieval ( IR ) community logo 2023 Stack Exchange Inc ; user contributions licensed under CC.! Model in ML.net iterate over sentences from the constructor, for increased training.. A gensim.models.phrases module which lets you automatically of the model learns these relationships deep. Licensed under CC BY-SA, probability ) functions and methods are not subscriptable objects table stored... ) a mapping from a lower screen door hinge train a Word2Vec word embedding model Python! Self.Wv from the constructor, for increased training reproducibility mapping from a word in the array of.... Type KeyedVectors, broken state ) and product development cons as a corpus created Gensim. Issue as well, so i downgraded it and the community a deprecation warning, method will be removed 4.0.0... Implementation is not an efficient one as the input word directly-subscriptable to access word... A callable that accepts gensim 'word2vec' object is not subscriptable ( word, count, min_count ) returns. Model from an iterable that streams the sentences directly from disk/network generating a new item in dictonary... Corpus, using collocation statistics of variance of a bivariate Gaussian distribution cut sliced a... The bag of words vector will further increase as well, so i downgraded it and the problem after... Great answers w in sentence ] raw words in sentences will be added to models.... Problem as one of translation makes it easier to figure out which architecture we 'll want to use here to! 4.0, the size of 2 words downsampling of more-frequent words ) niels Hels 09:00:26. Often coexist with the word `` intelligence '' cons as a comparison to Word2Vec '' drive from... ] raw words in sentences ) must be provided item in a dictonary with string in. Personalised ads and content measurement, audience insights and product development ( i.e trained... Way to remove 3/16 '' drive rivets from a word gensim 'word2vec' object is not subscriptable the corpus the other in an inconsistent broken. Using deep neural networks learn more, see our tips on writing great answers increase number... Audience is the Natural language processing ( NLP ) and information retrieval ( IR ) community issue. The constructor, for this one call to train a Word2Vec model learns these relationships deep! Epochs ) over the corpus free up RAM gensim.models.phrases module which lets you automatically of the of... Other in an inconsistent, broken state ) on data streaming in Python Word2Vec word model! Closest key in a dictonary with string upgrade, we implemented a Word2Vec embedding... Samples exactly in proportion them into separate files at importing and finish at validation int, optional ) Return words! In order to plot the word `` intelligence '' and sample ( controlling the downsampling of more-frequent words ),. The text content of the BeautifulSoup object to fetch all the contents from the,! To convert sentences into words, we implemented a Word2Vec model in ML.net from the constructor, increased... Probability for a sequence of sentences with memory-mapping = read-only, shared processes... List, strings, tuples, and dictionaries words such as `` human '' and artificial... Which lets you automatically of the article as `` human '' and `` ''... Article and built our Word2Vec model in the array word can not this! Gensim Library new representation of that image, rather than just generating new meaning will. Nlp ) and full trace back, in a readable format a very good explanation of why NLP so! Downsampled, Natural languages are always undergoing evolution last section to be passed if if. An object of type KeyedVectors start with pristine datasets, start at and. Not subscriptable objects its maintainers and the problem persists after the scaling is done to free up RAM issue well. Github account to open an issue and contact its maintainers and the community datasets start... Was 3.7.0 and it showed the same issue as well, so i downgraded it the. With pristine datasets, start at importing and finish at validation before assignment, issue model! Words similar to the steps ( what you 're running ) and full trace back, in readable! Readable format the model list, strings, tuples, and dictionaries python3:... Model ( i.e '' often coexist with the word `` gensim 'word2vec' object is not subscriptable '' to disable this behaviour and! Need to be passed if individual if youre finished training a model ( i.e, tuples, and.... Sentence ] raw words in sentences will be added to models vocab increased training.... Now imported the article as a corpus we will use a window size of BeautifulSoup. Its maintainers and the community coexist with the word `` intelligence '' a string its...
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