Metadata-Version: 2.1
Name: FedTools
Version: 0.0.3
Summary: An open source library for the extraction of Federal Reserve Data.
Home-page: https://github.com/David-Woroniuk/FedTools
Author: David Woroniuk
Author-email: david.j.woroniuk@durham.ac.uk
License: MIT License
Description: # FedTools
        
        An open source Python library for the scraping of Federal Reserve data.
        
        By default, all modules within FedTools use 10 threads to increase scraping speed. By default, the Output is a 
        Pandas DataFrame, indexed by release date of the materials. Additional serialised storage methods are optional.
        
        ## Installation
        
        From Python:
        ```
        pip install FedTools
        
        from FedTools import MonetaryPolicyCommittee
        from FedTools import BeigeBooks
        ```
        
        ## Usage
        
        From Python:
        ```
        pip install FedTools
        from FedTools import MonetaryPolicyCommittee
        dataset = MonetaryPolicyCommittee().find_statements()
        
        MonetaryPolicyCommittee().pickle_data("DIRECTORY")
        ```
        Returns a Pandas DataFrame 'dataset', which contains all Meeting Minutes, indexed by Date and a '.pkl' file saved within "DIRECTORY".
        
        ```
        pip install FedTools
        from FedTools import BeigeBooks
        dataset = BeigeBooks().find_beige_books()
        
        BeigeBooks().pickle_data("DIRECTORY")
        ```
        Returns a Pandas DataFrame 'dataset', which contains all Beige Books, indexed by Date and a '.pkl' file saved within "DIRECTORY".
        
        
        
        
        To edit input default arguments:
        ```sh
        monetary_policy = MonetaryPolicyCommittee(
                    main_url = 'https://www.federalreserve.gov', 
                    calendar_url = 'https://www.federalreserve.gov/monetarypolicy/fomccalendars.htm',
                    historical_split = 2014,
                    verbose = True,
                    thread_num = 10)
                    
        dataset = monetary_policy.find_statements()
        
        # serialise, save to "DIRECTORY":
        monetary_policy.pickle_data("DIRECTORY")
        
        
        or
        
        beige_books = BeigeBooks(
                    main_url = 'https://www.federalreserve.gov', 
                    beige_book_url='https://www.federalreserve.gov/monetarypolicy/beige-book-default.htm',
                    historical_split = 2019,
                    verbose = True,
                    thread_num = 10)
                    
                    
        dataset = beige_books.find_beige_books()
        
        # serialise, save to "DIRECTORY":
        beige_books.pickle_data("DIRECTORY")
        ```
        
        All parameters above are optional, with a short explanation of each parameter outlined below:
        
        | Argument | Description |
        | ------ | --------- |
        | main_url | Federal Reserve Open Monetary Policy (FOMC) website URL. (str) |
        | calendar_url | URL containing a list of FOMC Meeting dates. (str) |
        | historical_split | first year considered as historical ([Check Here for FOMC][hist] or [Check Here for Beige Books][hist1]). (int)  |
        | verbose | boolean determining printing during scraping. (bool) |
        | thread_num | the number of threads to use for web scraping. (int)   |
        
        
        
        
        
        
        
           [hist]: <https://www.federalreserve.gov/monetarypolicy/fomc_historical_year.htm>
           [hist1]: <https://www.federalreserve.gov/monetarypolicy/beige-book-archive.htm>
        
        
        
        
        
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Description-Content-Type: text/markdown
