Metadata-Version: 2.1
Name: azure-devops-pyspark
Version: 1.0.4
Summary: A productive library to extract data from Azure Devops and apply agile metrics.
Home-page: UNKNOWN
Author: Guilherme Silva dos Santos
Author-email: gusantos.ok@gmail.com
License: GNU General Public License v3.0
Description: 
        ## Azure Devops PySpark:  A productive library to extract data from Azure Devops and apply agile metrics.
        
        ## What is it?
        
        Azure Devops PySpark is a Python package that provides the most productive way to extract data from Azure Devops and build agile metrics.
        It runs on PySpark, enabling all the features the technology makes available.
        
        ## Main Features
        
        - Get authenticated quickly and simply.
        
        - All columns of the project are automatically mapped, use the filter_columns method to filter only those you want to form your dataframes with.
        - SparkSession already created in spark variable.
        - Get all your organization's backlogs with the method **backlog**.
        - Get all your organization's items with the method **items**.
        - Get all your organization's iterations with the method **iterations**.
        - Get all your organization's members with the method **members**.
        - Get all your organization's tags with the method **tags**.
        - Get all your organization's teams with the method **teams**.
        - Explore the simplicity of Agile class to build powerful metrics for your organization.
        
        ## Quick example
        
        ```python
        from AzureDevopsPySpark import Azure, Agile
        from pyspark.sql.functions import datediff #use in agile metrics
        
        devops = Azure('ORGANIZATION', 'PROJECT', 'PERSONAL ACCESS TOKENS')
        ```
        
        ```python
        ## Filter columns
        devops.filter_columns([
            'IterationPath', 'Id', 'State', 'WorkItemType',
            'CreatedDate', 'ClosedDate', 'Iteration_Start_Date', 'Iteration_End_Date'
        ])
        
        
        ## Pyspark Dataframe
        df_backlog = devops.backlog()
        df_items = devops.items()
        df_iterations = devops.iterations()
        df_members = devops.members()
        df_tags = devops.tags()
        df_teams = devops.teams()
        ```
        
        ```python
        ## Agile Metrics
        agile = Agile()
        
        ## A new dataframe
        df_agil = df.items.join(df_iterations, 'IterationPath')
        
        ## Metrics
        
        ## Average time between CreatedDate and ClosedDate of items in the last 90 days.
        lead_time = agile.avg(
            df=df_agil,
            ref=[datediff, 'ClosedDate', 'CreatedDate'], # The day difference between the CreatedDate and ClosedDate of each item.
            iteration_path='IterationPath', # GroupBy.
            new='LeadTimeDays', # New column name.
            literal_filter=['ClosedDate >= 90'], # Filtering items from the last 90 days.
            filters={'WorkItemType': 'Task', 'State': 'Closed'} # Custom filters for metric.
        ).df
        ```
        
        ## Author
        
        The Azure-Devops-PySpark library was written by Guilherme Silva <<https://www.linkedin.com/in/gusantosdev/>> in 2022.
        
        https://github.com/gusantos1/Azure-Devops-Spark
        
        ## License
        
        GNU General Public License v3.0.
        
Keywords: Azure AzureDevops WorkItems PySpark Agile
Platform: UNKNOWN
Description-Content-Type: text/markdown
