Regular Expressions jobs

We are looking for some assistance with advanced custom dimension scripting in Google Data Studio (using a type of REGEX code). We have a partially built dashboard that requires a few basic custom scripting pieces in order to be finished, including the following: - Grouping of some variables, for a filter function - Separating a string using delimeters - Flagging variables outside of a date range - Flagging variables that don't fall within a defined list Feel free to contact me with any further questions. A more specific task list is attached.

Need Here is a comma separated line in the log.I want to crop each portion like total order received and order rejected in a tabular form.I mean the dashboard is Data table and want to use grok pattern to filter the data from log and represent in the table

I need help with an extension in [url removed, login to view] details will be provided once you [url removed, login to view] apply only if you are good at understanding json,regex(pcre) and civicrm codes,

I need to crawl the real estate section of a local marketplace website which has an awful html structure, for market research purposes. Furthermore, the crawler should be uploaded to [url removed, login to view] for scheduling weekly jobs. This project must be deployed with: - Python 3.6 - Scrapy - Shub (for deployment) Other things to take into account: - The website is in spanish - CSS selectors won't work - The comments section of the listings is variable - The website has no [url removed, login to view] nor API The starting url is: [url removed, login to view]

It is about constructing the forward and inverted indexes using the given datasets. Using the porter stemmer algorithm for stemming and removing the stopwords(Provided).

we do presentations and am tired of repeating myself. we have a power point with scrip Can you get some one to read out the scrip and have it installed in the power point Let me know the cost

see the objective file for all the objective. Refer to pseudo code . Scanner and parser.c are mostly complete only some functions are to be implemented .

Stock Auto-Trading System with backtesting historic data and signal generation, with charts. Stock Data will need to be scraped from the web

Hi there Friend! Can you fix this Regexp match for me? ---> (?:(?:http|https)://)?(?:www.)?[url removed, login to view]/(?:(?:w)*#!/)?(?:pages/)?([w-]*)? A full test-set is given in a link below and can be tested out here ->: [url removed, login to view] (Where you can modify the actual Regex code and see the results immediately): Click here to get access to 1092 Facebook Profiles: ----> [url removed, login to view] ----------------------------------------------------------------------------------------------------------------------------------------- For example: Using "[url removed, login to view]" It captures only this: --> [url removed, login to view] (Which is not good enough) It should also include the numerical part at the end: [url removed, login to view] [url removed, login to view] captures only [url removed, login to view] (wrong) [url removed, login to view] captures only [url removed, login to view] (wrong) [url removed, login to view] captures only [url removed, login to view] (wrong) It doesn't need to capture the last unneccessary endings, only what is required for the Facebook Profile. /?fref=nf , or ?fref=ts, or ?ref=hl

Hi, I am looking for wireshark expert to analyze the traffic patterns using filtering techniques.

Need someone to write some simple regex for me

Hi dora1993, I noticed your profile and would like to offer you my project. We can discuss any details over chat.

working out a finite state transducer

We are looking for developer who is good at regular expression. We need to scrap web site and gather some data to database. Here is test file. Please bid with answer.(regexp)

Mam poniższe wyrażenie regularne walidujące numer telefonu w formularzu: /^(?:(?+?48)?(?:[-.()s]*(d)){9})?$/ Potrzebuję rozszerzyć regułę tak, aby poza obecnym działaniem: 1. Przepuszczała tylko numery zaczynające się od liczb: 5,6,7,8 (pozwalając dalej na przedrostek 48 lub 48 lub (48) lub (+48). 2. Blokowała wersje: 111 1111 111, 222 222 222 itp... (ze spacjami i myślnikami) 3. Blokowała wersje typu: 123 123 123, 111 222 333

Resume Parsing, known as CV Parsing, Resume Extraction or CV Extraction, is the conversion of a free-form CV/resume document into structured information in JSON or XML format — suitable for storage, reporting and manipulation. Input:This parser will be used to parse thousands of UNSTRUCTURED resumes in html, word (doc, docx), rtf, text, rtf and pdf formats. Resumes will be in English language to start with but the parser should be capable of parsing resumes in other languages. Output: JSON or XML format files of the resume when all the words from resume are parsed and structured correctly. Parser should also output the report and metric on what worked and what did not. This report should help in further tuning the parser. Accuracy: We areexpecting a high degree of accuracy. Ideally the parser should be able to reach maintain 95% accuracy. We are expecting minimum of 90% accuracy for each resume. Method: We are not looking at keyword based parser. We are looking for a parser that can be trained and improve its accuracy over a period. Also, the fields parsed should be configurable and we should be able to extend the parser in a fashion that we can add more fields to be parsed with little effort. Parser should be able to do Fuzzy look up Resume Parser should be written such that in can eventually be invoked using a web based application. In order to identify information from CVs and profiles, the extraction engine should learn to create “rules” within its machine-learning algorithms by analysing the data. Fields that need to be parsed – Not all the resumes will have all the fields – Also the parsing should not limit to just these fields. 1. First Name 2. Middle Name 3. Last Name 4. Email Address 5. Mobile Number 6. Date of Birth 7. Picture/Image 8. Social media profile links 9. Gender 10. Nationality 11. Address 12. City 13. State 14. Country 15. Zip Code 16. Summary/Objective 17. Achievements 18. Current Location 19. Skills(top to bottom) 20. Current Company Name 21. Current Company Designation 22. Current Company Start Date 23. Current Company End Date 24. Current Company Roles & Responsibilities 25. Previous Company Name 26. Previous Company Designation 27. Previous Company Start Date 28. Previous Company End Date 29. Previous Company Roles & Responsibilities 30. Education 31. Year of passing 32. Board/university 33. Certification 34. Marital Status 35. Language Known 36. Interest/Hobbies 37. References 38. Soft Skills 39. Training courses Output of the parser should be an xml or JSON tagged file, one xml file for each parsed resume, output file name to be the same as the input file name with extension. All the parsed fields will be used to upload into a MySQL database. Parser is also required to do the database insertion as part of the parsing process. We will supply a sample set of resumes, as many as you need to be successful.

Basically I need you to add the collection and organization of the data I need. The script to scan the site I already have, but I have only the raw data. Attached follows my code that should be added to the regular expression (or another method that is more efficient since CPU time is important here). Also attached is a document detailing the site being scanned and where the data is arranged and also an example file of how the output should be organized.

Basically I need you to add the collection and organization of the data I need. The script to scan the site I already have, but I have only the raw data. Attached follows my code that should be added to the regular expression (or another method that is more efficient since CPU time is important here). Also attached is a document detailing the site being scanned and where the data is arranged and also an example file of how the output should be organized.

Basically I need you to add the collection and organization of the data I need. The script to scan the site I already have, but I have only the raw data. Attached follows my code that should be added to the regular expression (or another method that is more efficient since CPU time is important here). Also attached is a document detailing the site being scanned and where the data is arranged and also an example file of how the output should be organized.

have to wirte regular expressions for date and misspellings