MrSnippets

A complete collection of common code snippets

Getting Started

To get started install the package using below command on your machine.

pip install MrSnippets

Sample Usage,

from MrSnippets.helpers import *
print(get_numbers_from_string('1a2b3e'))

Helper Module

Its an collection of commonly used functions to minimize the code and time.

List of supported functions,

• get_clean_text(string:str)
• get_numbers_from_string(string:str)
• get_alpha_from_string(string:str)
• get_string_from_html(soup)
• join_string(source_list:list, separator:str='')
• compare_string(string_one,string_two)
• get_clean_list(list_x:list)
• compare_list(first:list, second:list)
• find_list_duplicates(list:list)
• get_clean_dict(dict:dict)
• modify_jsondata(abbreviations_dict:dict,target_dict:dict)
• refine_name(name:str)
• split_name(name_string:str,reverse_it:bool=False,**kwargs)

Soup Wrapper

Its an simple implementation of css selector using Beautifulsoup. The selectors are stright forward and simple.

There are list of pre-defined selector functions. For example selecting a single element from chunk as follows.

from MrSnippets.soup_wrapper import  *
name = get_element(html_chunk,'div','class','people_name')
name = get_element_by_tag(html_chunk,'<div class="people_name">')

List of fucntions supported now,

• get_element(soup, tag="div", attributeName='class', attributeValue='profile')
• get_elements(soup, tag="div", attributeName='class', attributeValue='profiles')
• get_element_by_tag(soup,selector_string:str)
• get_elements_by_tag(soup,selector_string:str)
• get_sibling_text(soup, child:str, sibling:str, contains_string:str, sibling_type="prev|next")
• extract_hyper_link(soup_chunk,patterns:list,**kwargs)
• extract_social_links(self, html_source)
• extract_vcard_link(soup_chunk,**kwargs)
• extract_image_link(soup_chunk,**kwargs)
• extract_vcard_data(vcard_text:str)
• extract_meta_data(self, html_source)
• extract_email_addresses(string)
• extract_phone_numbers(html_chunk)

Mongo Wrapper

Its an collection of commonly used functions to minimize the code and time for mongo related operations.

To Setup the Client IP do follow the below steps,

Enter Below piece of code

1. from MrSnippets.mongo_wrapper import MONGO_CLIENT_IP
2. Now, CTRL + Right Click on MONGO_CLIENT_IP
3. Update this 'xx.xx.xx.xxx' to Your IP (195.16.20.335:27017)

MONGO_CLIENT_IP = 'xx.xx.xx.xxx:27017'

post update we will something like this,

MONGO_CLIENT_IP = '195.16.20.335:27017'

List of fucntions supported now,

• get_mongo_client(database_name, collection_name)
• list_db()
• list_collections(db:str)
• get_summarize(db:str,collection:str)
• get_sample(db:str,collection:str,query_by:str,value:str,limit:int=1)
• update_record(connection:dict,query_by:str,query_by_value,data:dict)
• create_index(connection:dict,index_attributes:list,ascending:bool=True)
• update_attribute(connection:dict,query_by:str,query_by_value,data:dict,attributes:list)

MySQL Wrapper

Its an collection of commonly used functions to minimize the code and time for MySQL related operations.

List of fucntions supported now,

• get_mysql_client(host_ip, username, pwd,db_name)
• query_actions(connection_obj, query, query_type)

Example usage,

get_mysql_client

from MrSnippets.mysql_wrapper import *
conn = get_mysql_client('190.10.30.160', 'root', 'password', 'profile')

SQL Wrapper

Its an collection of commonly used functions to minimize the code and time for SQL related operations.

List of fucntions supported now,

• get_sql_client(server_ip,database,userName,pwd)
• query_actions(db_object, query, query_type)
• insert_records(connection_obj, table_data:dict, data_dict: dict, unique_columns:list)

Example usage,

sql_insert_records

from MrSnippets.mysql_wrapper import *
db_object = get_sql_client('195.16.40.82', 'SampleDB', 'root', 'password')
sample_data = {'name':'dharan','phone_no':'023456789'}
table_meta = {'db_name':'informationSystem','table_name':'contactInfo'}
insert_records(db_object, table_data:dict, sample_data, ["phone_no"])

query_actions

__author__ = 'dhamodharan.k'
from MrSnippets.sql_wrapper import *
db_object = get_sql_client('xx.xx.xx.xx', 'employeeData', 'root', 'pass')
find_q = 'select emp_id,age from employee_info where emp_id in (4213958, 4213959)'
rows = query_actions(db_object, find_q, 'select')
for row in rows:
    content = str(row[1] + 1)
    update_query = "update employee_info set agePlus = '{}' where emp_id = {}".format(content,row[0])
    query_actions(db_object,update_query,'update')

Web Client

Its an collection of commonly used function for inracting on Internet

List of fucntions supported now,

• get_user_agent(**kwargs)
• extract_domain_name(url)
• downloader(url,dir,file_name,extension)
• get_response(url, response_type, attempt=0, **kwargs)

available arguments for this function

data = kwargs.get('data',{})
params = kwargs.get('params',{})
timeout = kwargs.get('time_out', 60)
verify = kwargs.get('verify', True)
method = kwargs.get('method', None)
domain = kwargs.get('domain', '')
headers = kwargs.get('headers',{})
allow_redirects = kwargs.get('allow_redirects', True)
proxy =  kwargs.get('proxy', True)
stream =  kwargs.get('stream', False)
dom_parser = kwargs.get('dom_parser','html5lib')

Sample Usage:

response = get_response(url,'json',method='post', data = payload, headers=headers, timeout=100, verify=False)

Natural Language Processing

Collection of functions to minimize the code and time for NLP related operations.

List of fucntions supported now,

• clean_my_html(html_source)
• get_top_keywords(self, html_source)
• get_word_frequency(html_source, search_words)
• get_tokenized(string:str,ignore_stopwords:bool=False)
• get_lemmatize_data(tokens:list)
• get_standardize_words(tokens:list,lookup_dict:dict)
• generate_ngrams(tokens:list,n)

search_words = ['programmer','dhamodharanrk']
frequency = get_word_frequency(html_source, search_words)
search_words = {'name': 'john,ram', 'brand': 'apple,nokia,samsung'}
frequency = get_word_frequency(html_source, search_words)
lookup_dict = {'rt':'Retweet', 'dm':'direct message', "awsm" : "awesome", "luv" :"love"}
standardize_words = get_standardize_words(tokens,lookup_dict )

Image Processing

Collection of functions to minimize the code and time for image processing tasks

List of fucntions supported now,

• adjust_brightness(input_image, output_image, factor)
• adjust_contrast(input_image, output_image, factor)
• adjust_sharpness(input_image, output_image, factor)
• resize_image(input_image_path,output_image_path,size)
• scale_image(input_image_path,output_image_path,width=None,height=None)
• black_and_white(input_image_path,output_image_path)
• rotateImage(image_path, degrees_to_rotate, saved_location)
• flipImage(image_path, saved_location,direction)
• cropImage(image_path, coords, saved_location)

Misc Functions

Collection of functions to minimize the code and time for day to day tasks

List of fucntions supported now,

• read_text_file(file_name)
• write_text_file(filepath, filename, content)
• write_csv_file(filepath,filename,content:dict,headers:list)
• get_base64Image(encoded_data,path_to_store,file_name)
• get_city_list()
• get_state_list()
• get_city_info_obj()
• get_sizeof(num, suffix='o')
• get_current_user()
• get_parsed_url(url_to_parse)
• get_filename(file_name)
• move_to(source,destination,filename)
• copy_to(source,destination,filename)
• list_files(diretory,ext:str='')

Prerequisites

Nothing but a basic knowlege of python

Contributing

Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.

Authors

• Dhamodharan - (https://github.com/dhamodharanrk)

License

This project is licensed under the MIT License - see the LICENSE.md file for details

Required Libraries

• beautifulsoup4>=4.3.3
• PyMySQL>=0.9.3
• pymongo>=3.8.0
• user_agent>=0.1.9
• ftfy>=5.5.1
• tldextract>=2.2.1
• bleach>=3.1.0
• python-csv>=0.0.11
• requests>=2.18.4
• html5lib>=1.0b10
• pytest-shutil>=1.6.0
• Pillow>=2.2.1
• pyodbc>=4.0.26

Acknowledgments

• This module has been actively developed.
• More and more features will be realised on upcomming days.
• This entire code is based on my experiance and scenarios crossed. Door open for any suggestions.
• Active contributors are welcome