Metadata-Version: 1.0
Name: pandas_access
Version: 0.0.1
Summary: A tiny, subprocess-based tool for reading a MS Access database(.rdb) as a Pandas DataFrame.
Home-page: https://github.com/jbn/pandas_access
Author: John Bjorn Nelson
Author-email: jbn@abreka.com
License: License :: OSI Approved :: MIT License
Description: # What is this?
        
        A tiny, `subprocess`-based tool for reading a 
        [MS Access](https://products.office.com/en-us/access) 
        database (`.rdb`) as a [Pandas](http://pandas.pydata.org/) 
        [DataFrame](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html). 
        
        ## Installation
        
        To read the database, this package (thinly!) wraps 
        [MDBTools](http://mdbtools.sourceforge.net/). Since I assume you're already 
        using Pandas, it should be your only installation requirement. 
        
        If you are on `OSX`, install it via [Homebrew](http://brew.sh/):
        
        ```sh
        $ brew install mdbtools
        ```
        Then, do,
        ```sh
        $ pip install pandas_access
        ```
        
        ## Usage
        
        ```python
        import pandas_access as mdb
        
        # Listing the tables.
        for tbl in mdb.list_tables("my.mdb"):
            print(tbl)
            
        # Read a small table.
        df = pandas_access.read_table("my.mdb", "MyTable")
        
        # Read a huge table.
        accumulator = []
        for chunk in pandas_access.read_table("my.mdb", "MyTable", chunksize=10000):
            accumulator.append(f(chunk))
        ```
        
        If you need more power than this, see: 
        [pyodbc](https://github.com/mkleehammer/pyodbc).
        
        ## Testing
        
        I needed this code in a quick pinch -- I had no access to MS Access, and I had
        a single `.mdb` file. If someone with Access would like to create a tiny 
        database for unit-testing purposes, I'd be much obliged. 
        
        
Platform: UNKNOWN
