<jupyter_start><jupyter_text>Required Installations<jupyter_code>!pip install numpy
!pip install textacy
from google.colab import drive
drive.mount('/gdrive')
import csv
import textacy
texts = textacy.io.read_text('/gdrive/My Drive/Colab Notebooks/data/Email_Subject_Dump.csv', lines=True)
en = textacy.load_spacy('en_core_web_sm', disable=('parser',))
for index in range(50):
  text = next(texts)
  text = textacy.preprocess_text(text, lowercase=True, no_punct=True)
  doc = textacy.Doc(text, lang=en)
  print(doc.text, list(textacy.extract.pos_regex_matches(doc, '(<ADJ> <PUNCT>? <CONJ>?)* (<NOUN>|<PROPN> <PART>?)+')))<jupyter_output>email subject [email subject]
guidewire consultants us citizen gc or gc ead in neenah wi [guidewire consultants, ead, neenah wi]
sr business analysts w cms or medicare experience in columbia md local only [business analysts, cms, medicare experience, columbia]
peoplesoft financials technical developer local to chicago usc gc ead gc [financials, technical developer, usc, ead gc]
need weblogic pure administrator at sunnyvale ca [weblogic pure administrator, sunnyvale]
sr sql dba with power shell and aws exp at new york contract [dba, power shell, aws, new york contract]
dynamics 365 testing at wilmington ma contract [dynamics, testing, wilmington, ma contract]
need sap developer with bw and hana at westborough ma [sap developer, bw, hana, westborough ma]
web developer at sanfrancisco ca contract [web developer, sanfrancisco]
urgent req net developer at bohemia ny [urgent req, net developer, bohemia]
java ui developer w hands on analytics experience at prussia pa contract [java, developer[...]
{'fraction_non_alphanumeric': 0.09013398294762484, 'fraction_numerical': 0.0030450669914738123, 'mean_word_length': 6.269911504424779, 'pattern_counts': {'":': 0, '<': 10, '<?xml version=': 0, '>': 10, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '26449', 'license': 'MIT', 'n_tokens_mistral': 539, 'n_tokens_neox': 519, 'n_words': 193, 'path': 'testing_worksheet.ipynb', 'repo_name': 'sagarkarnati/Automated-Resume-Screening-System', 'size': '1642'}