Tasks

FrePPLe provides a list of commands that perform actions on the database, the input data and/or the output data.

The commands can be accessed in three different ways:

This section provides an overview of the available actions:

The list can be extended with custom commands from extension modules.

Data commands

Group and schedule tasks

With this option a user can execute a sequence of steps together as a group.

The execution of the task group can be triggered manually. Or it can be scheduled automatically based on a predefined schedule.

Optionally, a email can be sent out upon failure or success of the execution.

For this task to be available some configuration may be required. On Windows this task is a front-end for the Windows Task Scheduler, and you need to assure the user running the web server has access to use it. On Linux this task is a front-end for the at-command, and you need to edit the /etc/at.allow or /etc/at.deny file to grant access for the user running the apache web server.

  • Execution screen:

    Execution screen - Group and schedule tasks
  • Command line:

    frepplectl scheduletasks --schedule=my_task_sequence
    
  • Web API:

    POST /execute/api/scheduletasks/?schedule=my_task_sequence
    

Export a spreadsheet

This task allows you to download the complete model as a single spreadsheet file. The spreadsheet can be opened with Excel or Open Office.

A separate sheet in the workbook is used for each selected entity.

The exported file can be imported back with the task described just below.

Optionally, you can make your dataset anonymous during the export to hide sensitive company data. All entities then get a new name during the export. It remains ABSOLUTELY NECESSARY to carefully review the generated spreadsheet and to remove any sensitive data that is still left, such as descriptions, categories, custom attributes, cost information.

This command is available only in the user interface:

  • Execution screen:

    Execution screen - Spreadsheet export

Import a spreadsheet

This task allows you to import an Excel spreadsheet.

A separate sheet in the workbook is used for each selected entity.

The sheet must have the right names - in English or your language. The first row in each sheet must contain the column names.

This command is available only in the user interface:

  • Execution screen:

    Execution screen - Spreadsheet import

Export plan result to folder

This task allows exporting data to a set of files in CSV or Excel format. The purpose of this task is to help the exchange of information with other systems.

The command can easily by customized to export the results you need.

The files are all placed in a folder UPLOADFILEFOLDER/export/, which can be configured per scenario with the UPLOADFILEFOLDER value in the djangosettings.py file.

The exported files can be accessed from the user interface, or through over a HTTP(S) web interface.

This command is available in the user interface, the command line and the web API:

  • Execution screen:

    Execution screen - Export plan data to folder
  • Command line:

    frepplectl exporttofolder
    
  • Web API:

    Export the planning result files:
    POST /execute/api/exporttofolder/
    
    Retrieve one of the exported files:
    GET /execute/downloadfromfolder/1/<filename>/
    

Email exported reports

Reports that have been exported using Export plan result to folder command can be emailed to one or more recipients.

Recipients have to be separated by a comma in the Emails field.

Selected reports are zipped into a reports.zip file that is attached to the email.

In order to have this command working, the EMAIL parameters in the djangosettings.py file must be properly configured.

This command is available in the user interface, the command line and the web API:

  • Execution screen:

    Execution screen - Email exported reports
  • Command line:

    frepplectl emailreport [--sender] --recipient --report
    
  • Web API:

    Email exported reports:
    POST /execute/api/emailreport/?recipient=recipient1,recipient2...&report=report1,report2,report3...
    

Import data files from folder

This task allows importing data from a set of CSV-formatted files (eventually GZ-compressed). The purpose of this task is to help the exchange of information with other systems.

The files are all placed in a folder that is configurable per scenario with the UPLOADFILEFOLDER in the djangosettings.py configuration file. The log file records all data imports, in addition to any data errors identified during their processing.

The data files to be imported must meet the following criteria:

  • The name must match the data object they store: eg demand.csv, item.csv, item.xlsx, item.csv.gz
    This is important for frePPLe to understand the correct processing order of the files.
  • Multiple files for the same entity can be provided. They will be processed in alphabetical order: eg “demand (1).xlsx”, “demand (2).csv”, “demand.1.csv”, “demand.2.csv”, “demand.extra.xlsx”, “demand.postprocessing.sql”
  • The first line of the file should contain the field names. The field name can be in English or the default language configured with the LANGUAGE_CODE setting.

The following file formats are accepted:

  • Excel:
    The file name must end with .xlsx
  • CSV:
    The file name must end with .csv (or .csv.gz when compressed with gzip).
    Some specific notes on the CSV format:
    • The separator in your CSV-files varies with the chosen language: If in your language a comma is used as a decimal separator for numbers, the CSV file will use a semicolon (;) as delimiter. Otherwise a comma (,) is used. See http://en.wikipedia.org/wiki/Decimal_mark

    • The date format expected by frePPLe is ‘YYYY-MM-DD HH:MM:SS’.

    • The data file is expected to be encoded in the character encoding defined by the setting CSV_CHARSET (default UTF-8).

  • PostgreSQL copy files:
    The file name must end with .cpy (or .cpy.gz when compressed with gzip).
    Uploading in this format goes MUCH quicker than the other formats. It has some limitations however: a) the validation of the input data is not as extensive as the other formats, b) a single faulty record will abort the upload and c) it only supports adding new records and not updating existing records.
    This method is therefore only recommended for loading very large data files with clean data.
  • SQL:
    The file name must end with .sql (or .sql.gz when compressed with gzip).
    For security reasons a database role with a minimal set of permissions must be define. The setting DATABASES / SQL_ROLE needs to refer to this role.

In this option you can see a list of files present in the specified folder, and download each file by clicking on the arrow down button, or delete a file by clicking on the red button. The arrow up button will give the user the possibility of selecting multiple files to upload to that folder.

This command is available in the user interface, the command line and the web API:

  • Execution screen:

    Execution screen - Import data files from folder
  • Command line:

    frepplectl importfromfolder
    
  • Web API:

    Upload a data file:
    POST /execute/uploadtofolder/0/ with data files in multipart/form-data format
    
    Import the data files:
    POST /execute/api/importfromfolder/
    

Scenario management

This option allows a user to either create copies of a dataset into a what-if scenario or promote the data from a scenario into Production database.

When the data is successfully copied, the status changes from ‘Free’ to ‘In use’. The access to the newly copied scenario is limited to 1) the user who performed the copy plus 2) all superusers of the source scenario.

When the user doesn’t need the what-if scenario any more, it can be released again.

Releasing a scenario can be done from any scenario while copying and promoting actions can only be performed from current scenario to destination scenario.

The label of a scenario, which is displayed in the dropdown list in the upper right hand corner, can also be updated here.

This command is available in the user interface, the command line and the web API:

  • Execution screen:

    Execution screen - what-if scenarios
  • Command line:

    To copy scenario scenario1 into scenario scenario2:
    frepplectl scenario_copy [--force --promote] scenario1 scenario2
    
    To release scenario scenario1:
    frepplectl scenario_release --database=scenario1
    
  • Web API:

    To copy a scenario (including Production) into another scenario:
    * POST /execute/api/scenario_copy/?copy=1&source=scenario1&destination=scenario2&force=1
    
    To release a scenario named scenario1:
    * POST /scenario1/execute/api/scenario_copy/?release=1
    
    To promote a scenario named scenario1 into Production (where "default" is the Production name):
    * POST /execute/api/scenario_copy/?promote=1&source=scenario1&destination=default
    

Back up database

This task dumps the contents of the current database schema to a backup file. The file is created in the log folder configured in the configuration files djangosettings.py. It can be downloaded from the browser.

For security reasons the command is only available to users listed in the setting SUPPORT_ACCOUNTS. By default this is an empty list.

The command also removes dumps older than a month to limit the disk space usage. If you want to keep dumps for a longer period of time, you’ll need to copy the backup files to a different location.

This command is available in the user interface, the command line and the web API:

  • Execution screen:

    Execution screen - backup
  • Command line:

    frepplectl backup
    
  • Web API:

    Create a backup:
    POST /execute/api/backup/
    
    Download the backup file:
    GET /execute/logdownload/<task identifier>/
    

Empty the database

This will delete all data from the current scenario (except for some internal tables for users, permissions, task log, etc…).

This command is available in the user interface, the command line and the web API:

  • Execution screen:

    Execution screen - erase
  • Command line:

    frepplectl empty --models=input.demand,input.operationplan
    
  • Web API:

    POST /execute/api/empty/?models=input.demand,input.operationplan
    

Administrator commands

Load a dataset in the database

A number of demo datasets are packaged with frePPLe. Using this action you can load one of those in the database.

The dataset is loaded incrementally in the database, without erasing any previous data. In most cases you’ll want to erase the data before loading any of these datasets.

You can use the dumpdata command to export a model to the appropriate format and create your own predefined datasets.

This command is available in the user interface, the command line and the web API:

  • Execution screen:

    Execution screen - load a dataset
  • Command line:

    frepplectl loaddata manufacturing_demo
    
  • Web API:

    POST /execute/api/loaddata/?fixture=manufacturing_demo
    

Generate time buckets

Many output reports are displaying the plan results aggregated into time buckets. These time buckets are defined with the tables dates and bucket dates.

This tasks allows you to populate these tables in an easy way with buckets with daily, weekly, monthly, quarterly and yearly granularity. Existing bucket definitions for these granularities will be overwritten.

The following arguments are used:

  • Start date, end date:
    Definition of the horizon to generate buckets for.
  • Week start: Defines the first date of a week.

  • Day name, week name, month name, quarter name, year name:
    Template used to generate a name for the buckets.

    Any character can be used in the names and the following format codes can be used:

    • %a: Weekday as locale’s abbreviated name. Eg: Sun, Mon, …

    • %A: Weekday as locale’s full name. Eg: Sunday, Monday, …

    • %w: Weekday as a decimal number, where 0 is Sunday and 6 is Saturday.

    • %d: Day of the month as a zero-padded decimal number. Eg: 01, 02, …, 31

    • %b: Month as locale’s abbreviated name. Eg: Jan, Feb, …

    • %B: Month as locale’s full name. Eg: January, February, …

    • %m: Month as a zero-padded decimal number. Eg: 01, 02, …, 12

    • %q: Quarter as a decimal number. Eg: 1, 2, 3, 4

    • %y: Year without century as a zero-padded decimal number. Eg: 00, 01, …, 99

    • %Y: Year with century as a decimal number. Eg: 2018, 2019, …

    • %j: Day of the year as a zero-padded decimal number. Eg: 001, 002, …, 366

    • %U: Week number of the year as a zero padded decimal number. Eg: 00, 01, …

    • %W: Week number of the year as a decimal number. Eg: 0, 1, …

    • %%: A literal ‘%’ character.

This command is available in the user interface, the command line and the web API:

  • Execution screen:

    Execution screen - generate time buckets
  • Command line:

    frepplectl createbuckets --start=2012-01-01 --end=2020-01-01 --weekstart=1
    
  • Web API:

    POST /execute/api/createbuckets/?start=2012-01-01&end=2020-01-01&weekstart=1
    

Create the PostgreSQL database(s)

This command will create the PostgreSQl databases for frePPLe.

If the database already exists you will be prompted to confirm whether you really to loose all data in the existing database. When confirmed that database will dropped and recreated.

This command is available on the command line only:

# Create all scenario databases
frepplectl createdatabase

# Recreate only a single database
frepplectl createdatabase --database=scenario3

Create or migrate the database schema

Update the database structure to the latest release

This command is available on the command line only:

# Migrate the main database
frepplectl migrate

# Migrate a scenario database
frepplectl migrate --database=scenario1

Restore a database backup

This command is available on the command line only:

frepplectl restore database_dump_file

Create a new superuser

This command creates a new user with full access rights.

This action is possible in the user interface and the command line:

Change a user’s password

This command changes the password of a certain user.

This action is possible in the user interface and the command line:

Remove all database objects

This command completely empties all tables in the database, including all log, users, user preferences, permissions, etc…

A complete reset of the database is not very common. In most situations the command described above to empty the database is sufficient. It empties the data tables, but leaves the important configuration information intact.

This command is available on the command line only:

frepplectl flush

Developer commands

Database shell prompt

This command runs an interactive SQL session on the PostgreSQL database.

frepplectl dbshell --database=default

Python command prompt

This command runs an interactive Python interpreter session.

frepplectl shell

Run the test suite

Run the test suite for the user interface.

frepplectl test freppledb

Run the development web server

Run a development web server, which automatically reloads when code is changed.

For production use this web server doesn’t scale enough.

frepplectl runserver