Metadata-Version: 2.1
Name: jira-agile-metrics
Version: 0.1
Summary: Agile metrics and summary data extracted from JIRA
Home-page: https://github.com/optilude/jira-agile-metrics
Author: Martin Aspeli
Author-email: optilude@gmail.com
License: MIT
Description: # JIRA Agile Metrics
        
        A tool to extract Agile metrics and charts from JIRA projects.
        
        ## Installation
        
        Requires Python 3.6 or later.
        
        Install Python 3 and the `pip` package manager. Then run:
        
            $ pip install jira-agile-metrics
        
        You can do this globally, but you may want to use a virtual Python environment
        (`venv`) instead to keep things self-contained.
        
        See [The Hitchhiker's Guide to Python](http://python-guide.org/en/latest/) for
        the full details about how to install Python and venvs.
        
        This should install a binary called `jira-agile-metrics` in the relevant `bin`
        directory. You can test it using:
        
            $ jira-agile-metrics --help
        
        ... which should print a help message with a whole slew of options. More on
        those below.
        
        ### Using Docker
        
        If you prefer, you can use [Docker](http://docker.com) to install and run
        `jira-agile-metrics` with all the relevant dependencies in place. After
        installing Docker, run:
        
            $ docker run -it --rm -v $PWD:/data optilude/jira-agile-metrics config.yml
        
        This will run `jira-agile-metrics` with the configuration file `config.yml` from
        the current directory, writing outputs also to the current directory. The
        argument `-v $PWD:/data` mounts the `/data` volume, where output files will be
        written, to the current working directory. You can of course specify a
        different bind mount.
        
        ## Usage
        
        The basic usage pattern is to run `jira-agile-metrics` with a configuration
        file, written in YAML format (see below), which describes:
        
          - how to connect to a remote JIRA instance;
          - what metrics (spreadsheet-like data files, charts as images) to output;
          - various settings used to calculate those metrics; and
          - a description of the stages of the workflow the relevant JIRA tickets go
            through.
        
        The tool will then connect to JIRA using its web services API, run a query to
        the relevant tickets and their history, and calculate the requierd metrics.
        
        The outputs are written to local filesystem files. Data files can be written in
        CSV, XLSX or JSON formats (depending on the extension of the desired output
        file), whilst charts are written as PNG images.
        
        Most of the options in the configuration file can be overridden using command
        line arguments. For a full list, run:
        
            $ jira-agile-metrics --help
        
        ### Server mode
        
        `jira-agile-metrics` comes with a simple web server that can be used to produce
        metrics by uploading a configuration file and downloading a ZIP file with data
        and charts. To start it, run:
        
            $ jira-agile-metrics --server 5000
        
        This will start a server on port `5000` (you can also specify a bind host name
        or IP address, e.g. `0.0.0.0:5000`). Visit this address in a web browser and
        upload a file.
        
        In this mode, all other command line options are ignored.
        
        **Note:** The web server is designed for low-volume usage only, and does not
        have a sophisticated security model. It is simply a more accessible front end
        to the features of the command line tool. The server will wait, synchronously,
        whilst JIRA is queried and charts are produced, which can take a long time.
        During this time, the browser will wait, and threads will block.
        
        **Warning:** The web server does not encrypt requests, which means that by
        default JIRA credentials are transmitted in plain-text. You are strongly adviced
        to configure a reverse proxy (e.g. `nginx`) with SSL enabled in front of it.
        
        #### Using Docker to run the web server
        
        There is a separate Docker image for running the web server, which uses `nginx`
        and `uwsgi` for improved performance and stability (but still not SSL, which
        would need to be configured with a domain-specific certificate):
        
            $ docker run -d --rm -p 8080:80 --name jira_metrics optilude/jira-agile-metrics:server
        
        This will run the server in daemon mode and bind it to port `8080` on the local
        host. To stop it, run:
        
            $ docker stop jira_metrics
        
        See the [Docker documentation](https://docs.docker.com) for more details.
        
        ### An important note about passwords
        
        The tool uses a simple username/password combination to connect to JIRA. You
        need to ensure this user exists in the remote JIRA instance, and has the
        required permissions.
        
        There are three ways to provide the credentials for JIRA -- in particular, the
        password, which should be kept scret. You should think carefully about which
        approach makes most sense for you.
        
          - The safest option is to not set it in either the configuration file, or as
            a command line option. In this case, you will be prompted to input a
            password (and username, if you didn't set this either) each time the tool
            is run.
          - You can use the `--username` and/or `--password` command line options to set
            credentails when you invoke the `jira-agile-metrics` command. This keeps
            them out of the configuration file, but if you do this in an interactive
            shell that records command history (i.e. virtually all of them), your
            password will likely be stored in plain text in the command history!
          - If you are confident you can keep the configuration file secret, you can
            store them there, under the `Connection` section (see below).
        
        ### What issues should you include?
        
        The most common use case is to calculate metrics for a team using a JIRA issue
        type called something like `Story`, going through a workflow with stages like
        `Backlog`, `Committed`, `Elaboration`, `Build`, `Code review`, `Test`, and `Done`,
        and allowing a set of resolutions like `Completed`, `Withdrawn`, and `Duplicate`.
        
        `jira-agile-metrics` lets you use JIRA JQL syntax to specify which issues you
        are interested in. See the JIRA documentation for more details (or construct a
        search using the JIRA UI and then have JIRA show you the corresponding JQL).
        
        ### Creating a configuration file
        
        Here is an example configuration file for a basic example using the workflow
        above:
        
            # How to connect to JIRA. Can also include `Username` and `Password`
            Connection:
                Domain: https://myjira.atlassian.net # your JIRA instance
        
            # What issues to search for. Uses JQL syntax.
            Query: Project=ABC AND IssueType=Story AND (Resolution IS NULL OR Resolution IN (Completed, Withdrawn))
        
            # The workflow we want to analyse. By convention, the first stage should be
            # the backlog / initial state, and the final stage should indicate the work
            # is done.
            #
            # We map analytics names to JIRA status names. It's possible to collapse
            # multiple JIRA statuses into a single workflow stage, as with `QA` below.
            Workflow: 
                Backlog: Backlog
                Committed: Committed
                Elaboration: Elaboration
                Build: Build
                QA:
                    - Code review
                    - Test
                Done: Done
            
            # What outputs to produce. These are all optional. If an option isn't set
            # the relevant metric will not be produced.
        
            Output:
        
                # CSV files with raw data for input to other tools or further analysis in a spreadsheet
                # If you use .json or .xslx as the extension, you can get JSON data files or Excel
                # spreadsheets instead
        
                Cycle time data: cycletime.csv
                CFD data: cfd.csv
                Scatterplot data: scatterplot.csv
                Histogram data: histogram.csv
                Throughput data: throughput.csv
                Percentiles data: percentiles.csv
        
                # Various charts
        
                Scatterplot chart: scatterplot.png
                Scatterplot chart title: Cycle time scatter plot
                
                Histogram chart: histogram.png
                Histogram chart title: Cycle time histogram
                
                CFD chart: cfd.png
                CFD chart title: Cumulative Flow Diagram
                
                Throughput chart: throughput.png
                Throughput chart title: Throughput trend
                
                Burnup chart: burnup.png
                Burnup chart title: Burn-up
        
                Burnup forecast chart: burnup-forecast.png
                Burnup forecast chart title: Burn-up forecast
                Burnup forecast chart trials: 100 # number of Monte Carlo trials to run to estimate completion date
        
                # Burnup forecast chart throughput window: 60 # Days in the past to use for calculating historical throughput
                # Burnup forecast chart throughput window end: 2018-06-01 # Calculate throughput window to this date (defaults to today)
                # Burnup forecast chart target: 100 # items to complete in total; by default uses the current size of the backlog
                # Burnup forecast chart deadline: 2018-06-01 # deadline date, in ISO format; if not set, no deadline is drawn.
                # Burnup forecast chart deadline confidence: .85 # percentile to use to compare forecast to deadline
                
                WIP chart: wip.png
                WIP chart title: Work in Progress
        
                Ageing WIP chart: ageing-wip.png
                Ageing WIP chart title: Ageing WIP
        
                Net flow chart: net-flow.png
                Net flow chart title: Net flow
        
        Hint: If you prefer to manage your queries as saved filters in JIRA, you can
        use the special JQL syntax of `filter=123`, where `123` is the filter ID.
        
        If you save this file as e.g. `config.yaml`, you can run:
        
            $ jira-agile-metrics config.yaml
        
        This should prompt you for a username and password, and then connect to your
        JIRA instance, fetch the issues matching the query, calculate metrics, and
        write a number of CSV and PNG files to the current directory.
        
        When testing configuration, it is often helpful to fetch just a small number of
        issues to speed things up. You can either do this by making your query more
        restrictive, or by using the `-n` flag to limit the number of issues fetched:
        
            $ jira-agile-metrics -n 20 config.yaml
        
        If you want more information about what's going on, use the `-v` flag:
        
            $ jira-agile-metrics -v config.yaml
         
        
        ## Available metrics
        
        `jira-agile-metrics` can produce a number of data files and charts, which can
        be enabled in the `Output` section of the configuration file, or with a
        corresponding command line option.
        
        **Note:** In the configuration file, you can specify output file *names*, but
        not absolute or relative paths. Files will always be written to the current
        working directory. This is to prevent unexpeced behaviour and the potential of
        overwriting other files when configuration files are moved around or used on
        a remote machine. No such restriction applies to output files specified in
        command line arguments.
        
        ### Cycle time details
        
        Details about each ticket and the date it entered each stage of the workflow.
        Both the CSV and JSON versions of this file can be used by the
        [Actionable Agile Analytics](http://actionableagile.com/) tool, which offers
        powerful, interactive analysis of Agile flow.
        
        In the configuration file:
        
            Output:
                Cycle time data: cycletime.csv
        
        You can also use `.json` or `.xlsx` formats.
        
        ### Cumulative Flow Diagram (CFD)
        
        Raw data for creating a valid Cumulative Flow Diagram, in spreadsheet format,
        and/or an image file of the same. The CFD shows the number of work items in
        each stage of the flow as a stacked area chart, day by day. This allows us to
        visualise WIP, cycle time, and throughput.
        
        In the configuration file:
        
            Output:
                CFD data: cfd.csv
                CFD chart: cfd.png
                CFD chart title: Cumulative Flow Diagram
        
        You can also use `.json` or `.xlsx` formats for the data file.
        
        ### Cycle time scatter plot
        
        Raw data for creating a valid Cycle Time scatter plot graph, and/or an image
        file of the same. This chart plots the end-to-end cycle time (excluding time
        spent in the backlog) for each work item against its completion date, and
        overlays quantiles (e.g. 85% of tickets took 18 days or fewer)
        
        In the configuration file:
        
            Output:
                Scatterplot data: scatterplot.csv
                Scatterplot chart: scatterplot.png
                Scatterplot chart title: Cycle time scatter plot
        
        You can also use `.json` or `.xlsx` formats for the data file.
        
        By default, the quantiles used are the 50th, 85th and 95th percentile, but you
        can specify a different list with the `Quantiles` option under `Output`:
        
                Quantiles:
                    - 0.3
                    - 0.5
                    - 0.75
                    - 0.85
                    - 0.95
        
        Note that this option affects all charts that use quantiles.
        
        To get the quantile values (number of day at each quantile) in a data file, use:
        
                Percentiles data: percentiles.csv
        
        ### Cycle time histogram
        
        This is a different view of the cycle time , calculatd and/or plotted as a
        histogram.
        
        In the configuration file:
        
            Output:
                Histogram data: histogram.csv
                Histogram chart: histogram.png
                Histogram chart title: Cycle time histogram
        
        You can also use `.json` or `.xlsx` formats for the data file.
        
        This also respects the `Quantiles` option (see above).
        
        ### Throughput data
        
        Weekly throughput, i.e. the number of items completed week by week. The chart
        also shows a trend line.
        
        In the configuration file:
        
            Output:
                Throughput data: throughput.csv
                Throughput chart: throughput.png
                Throughput chart title: Throughput trend
        
        You can also use `.json` or `.xlsx` formats for the data file.
        
        To change the frequency from weekly to something else, use:
        
                Throughput frequency: 1D
        
        Here, `1D` means daily. The default is `1W-MON`, which means weekly starting on
        Mondays.
        
        ### WIP box plot
        
        Shows a box plot of WIP, week by week (or some other frequency).
        
        In the configuration file:
        
                WIP chart: wip.png
                WIP chart title: Work in Progress
        
        To change the frequency from weekly to something else, use:
        
                WIP chart frequency: 1D
        
        Here, `1D` means daily. The default is `1W-MON`, which means weekly starting on
        Mondays.
        
        ### Net flow chart
        
        Shows the difference between arrivals and departures week on week. In a
        perfectly stable system, the net flow would be 0.
        
        In the configuration file:
        
                Net flow chart: net-flow.png
                Net flow chart title: Net flow
        
        To change the frequency from weekly to something else, use:
        
                Net flow chart frequency: 1D
        
        Here, `1D` means daily. The default is `1W-MON`, which means weekly starting on
        Mondays.
        
        ### Ageing WIP chart
        
        Shows the cycle time to date for each work item, grouped into the stages of
        the workflow. This can help identify slow-moving tickets.
        
        In the configuration file:
        
                Ageing WIP chart: ageing-wip.png
                Ageing WIP chart title: Ageing WIP
        
        ### Burn-up chart
        
        A basic Agile burn-up chart, based on a count of items completed and in the
        backlog.
        
        In the configuration file:
        
                Burnup chart: burnup.png
                Burnup chart title: Burn-up
        
        ### Burn-up chart with forecast line
        
        A more advanced version of the burn-up chart, which will run a Monte Carlo
        simulation based on historical throughput to forecast a completion date for
        the scope.
        
        The simulation can be calibrated with a series of options to set:
        
            - The number of trials to run. Each trial will be drawn as a hypotehtical
              burn-up to completion.
            - The window of time from which to sample historical throughput. This should
              be representative of the near future, and ideally about 6-12 weeks long.
            - The target to aim for, as a number of stories to have completed. Defaults
              to the size of the backlog, but can be set to an assumed figure.
            - A deadline date, which, if set, can be compared to a forecast at a given
              confidence interval.
        
        In the configuration file:
        
                Burnup forecast chart: burnup-forecast.png
                Burnup forecast chart title: Burn-up forecast
                Burnup forecast chart trials: 100 # number of Monte Carlo trials to run to estimate completion date
        
                Burnup forecast chart throughput window: 60 # Days in the past to use for calculating historical throughput
                Burnup forecast chart throughput window end: 2018-06-01 # Calculate throughput window to this date (defaults to last day of burnup)
                Burnup forecast chart target: 100 # items to complete in total; by default uses the current size of the backlog
                Burnup forecast chart deadline: 2018-06-01 # deadline date, in ISO format; if not set, no deadline is drawn.
                Burnup forecast chart deadline confidence: .85 # percentile to use to compare forecast to deadline
        
        ## More details about the configuration file format
        
        The configuration file is written in YAML format. If you are unfamiliar with
        YAML, know that:
        
        * Comments start with `#`
        * Sections are defined with a name followed by a colon, and then an indented
          block underneath. `Connection`, `Output`, `Workflow` and `Attributes` area
          all sections in the example above.
        * Indentation has to use spaces, not tabs!
        * Single values can be set using `Key: value` pairs. For example,
          `Burnup chart: burnup.png` above sets the key `Burnup chart` to the value
          `burnup.png`.
        * Lists of values can be set by indenting a new block and placing a `-` in front
          of each list value. In the example above, the `QA` list contains
          the values `Code review` and `Test`.
        
        The sections for `Workflow` is required. Additionally, you must either specfiy a
        single `Query`, or a block of `Queries` (see below). Connection details must
        be set either in the `Connection` file or as command line arguments.
        
        Under `Workflow`, at least two steps are required. Specify the steps in order.
        You may either specify a single workflow value or a list (as shown for `QA`
        above), in which case multiple JIRA statuses will be collapsed into a single
        state for analytics purposes.
        
        The file, and values for things like workflow statuses and attributes, are case
        insensitive.
        
        ### Extracting additional attributes
        
        You may want to add additional fields to the cycle time output data. Use an
        `Attributes` block to do this:
        
            Attributes:
                Priority: Priority
                Release: Fix version/s
                Team: Team name
        
        Here, three additional columns will be added: `Priority`, `Release` and `Team`,
        corresponding to the JIRA fields `Priority`, `Fix version/s` and `Team name`,
        respectively.
        
        When specifying attributes, use the *name* of the field (as rendered on screen
        in JIRA), not its id (as you might do in JQL), so e.g. use `Component/s` not
        `components`.
        
        The attributes `Type` (issue type), `Status` and `Resolution` are always
        included.
        
        ### Multi-valued fields
        
        Some fields in JIRA can contain multiple values, e.g. `fixVersion`. By default,
        the extractor will use the first value in such a field if one is specified in
        the `Attributes` block. However, you may want to extract only specific values.
        
        To do so, add a block like the following::
        
            Attributes:
                Release: Fix version/s
        
            Known values:
                Release:
                    - "R01"
                    - "R02"
                    - "R03"
        
        The extractor will pick the first "known value" found for the field. If none of
        the known values match, the cell will be empty.
        
        ### Combining multiple queries
        
        If it is difficult to construct a single set of criteria that returns all
        required issues, multiple queries can be added into a `Queries` block, like so:
        
            Queries:
                Attribute: Team
                Criteria:
                    - Value: Team 1
                      JQL: (filter=123)
        
                    - Value: Team 2
                      JQL: (filter=124)
        
        In this example, two queries will be run, based on the two filters `123` and
        `124` (you can use any valid JQL).
        
        In the cycle time output, a new column called `Team` will be added, as specified
        by the `Attribute` field under `Queries`. For all items returned by
        the first query, the value will be `Team 1` as per the `Value` field, and for
        all items returned by the second query, it will be `Team 2`.
        
        ## Troubleshooting
        
        * If Excel complains about a `SYLK` format error, ignore it. Click OK. See
          https://support.microsoft.com/en-us/kb/215591.
        * JIRA error messages may be printed out as HTML in the console. The error is
          in there somewhere, but may be difficult to see. Most likely, this is either
          an authentication failure (incorrect username/password or blocked account),
          or an error in the `Query` option resulting in invalid JQL.
        * If you aren't getting the issues you expected to see, use the `-v` option to
          see the JQL being sent to JIRA. Paste this into the JIRA issue filter search
          box ("Advanced mode") to see how JIRA evaluates it.
        * Old workflow states can still be part of an issue's history after a workflow
          has been modified. Use the `-v` option to find out about workflow states that
          haven't been mapped.
        * Excel sometimes picks funny formats for data in CSV files. Just set them to
          whatever makes sense.
        * If you are on a Mac and you get an error about Python not being installed as
          a framework, try to create a file `~/.matplotlib/matplotlibrc` with the
          following contents::
        
            backend : Agg
        * To install the charting dependencies on a Mac, you might need to install a
          `gfortran` compiler for `scipy`. Use [Homebrew](http://brew.sh) and install the
          `gcc` brew.
        
        ## Changelog
        
        ### 0.1
        
        * Forked from `jira-agile-metrics`
        
Keywords: agile jira analytics metrics
Platform: UNKNOWN
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