mapactionpy-controller 0.5.dev254

Controls the workflow of map and infographic production

About

Master branch

Installing

To install the latest stable release via PyPi:

python -m pip install mapactionpy_controller

To install a specific version for testing see the relevant commandline from here: https://pypi.org/project/mapactionpy-controller/#history

Commandline Usage

Check the compliance with the Data Naming Convention, MXD Naming Convention, MXD Template Naming Convention and Layer Naming Convetion.

> python.exe -m mapactionpy_controller.check_naming_convention /path/to/current/cmf/2019gbr01/cmf_description.json

Using the Data Serach tool from the commandline

> python.exe -m mapactionpy_controller.data_search
usage: data_search [-h] -r FILE -c FILE [-o FILE]
data_search.py: error: the following arguments are required: -r/--recipe-file, -c/--cmf

> python -m mapactionpy_controller.data_search -r example/product_bundle_example.json -c example/cmf_description.json

This command will output an updated recipe file with the If the ouput file parameter (-o) is specified than the updated recipe will be output to that file. Otherwise the updated recipe is sent to stdout.

Programmatic Usage

Using the MapRecipe, CrashMoveFolder and Event classes

There are three classes which are designed for reuse in other modules. For each of these there is a corresponding json representation. There should not be any need for any other code to touch these json files:

• MapRecipe : An object that represents a recipe (as read from a json file).
  This object may be manipulated by (e.g. the data_search tool, updates the datasources fields )
• CrashMoveFolder : An object that describes the CrashMoveFolder and its contents. There should be no need to hardcode any path (absolute or relative) to anywhere in a crash move folder
• Event : This decribes the real-world humanitarian event to which the Crash Move Folder corresponds.

(Note1:) The name Event matches the naming of the equivalent concept on the Map & Data Respository (see https://github.com/mapaction/ckanext-mapactionevent). However it is rather too generic in this context. A more descriptive name for this class would be helpful.

(Note2: in the MapExportTool the information within the CrashMoveFolder and Event used to be encapsulated in the operational_config.xml file. This mixed state about the event/emergency and configuration about the local paths to and within the crash move folder. )

Using the DataNameConvention and related classes

The naming_convention sub-module provides a framework for specifying a naming convention (such as for file or table). A naming convention is specified in a json configuration file and consists of:

1. A regular expression, with named groups
2. For each named group in the regex, details of a class which can provide futher validation of that value in that named group.

Exmples of the naming convention config files are in the examples directory, including MapAction's DataNamingConvention, MXDNamingConvention and LayerfileNamingConvention.

DataNameConvention represents the convention itself. At its core is a regular expression. Each named group (clause) within the Regex as additionally validation, which is implemented by a DataNameClause. DataNameConvention has a dictionary of DataNameClause objects. A individual name is tested by using the .validate(data_name_str) method. If the data name does not match the regex the value None is returned. If the regex matches a DataNameInstance object will be returned, whether or not all of the clauses pass.

DataNameClause is an abstract class. Callers are unlikely to need to directly access this class or any concrete examples. Concrete examples are DataNameFreeTextClause and DataNameLookupClause. When the .validate(data_name_str) method is called on a DataNameConvention object, it will call .validate(clause_str) in each individual DataNameClause obj.

DataNameResult represents the result of a specific data name test and is returned by DataNameConvention.validate(). The .is_valid property indicates whether or not all of the clauses validate. DataNameResult is a namedtuple. The values for individual clauses can be directly accessed using dotted property notation (eg via members such as dnr.datatheme.Description or dnr.source.Organisation. If whether or not the clause validated is returned by the .is_valid property (eg . dnr.datatheme.is_valid).

Example code:

dnc = DataNameConvention(path_to_dnc_json_definition)

# regex does not match
dnr = dnc.validate('abcde')
self.assertIsNone(dnr)

# regex does matches, but some clauses fail lookup in csv file
dnr = dnc.validate(r'aaa_admn_ad3_py_s0_wfp_pp')

if dnr.is_valid:
	print('the dataname is valid')
else:
	print('the dataname is not valid')

# use the `_asdict()` method to loop through all clauses
for clause in dnr._asdict().values():
	clause_details = dni.clause(clause)
	if clause_details:
		print('The extra information associated with clause name {} are {}'.format(clause, clause_details)
	else:
		print('The erroneous value for clause {} was {} '.format(clause, clause_details)

# Use the dnr object in template strings
print('The {dnr.datatheme.Description} data was generously supplied by {dnr.source.Organisation}, downloaded '
	'from {dnr.source.url}'.format(dnr=dnr))

Output:

The erroneous value for clause `geoext` was `aaa`
Extra information associated with clause `scale`:
    Description = Global mapping
    Scale_range = ? 5 000 000
Extra information associated with clause `freetext`:
    text = None
Extra information associated with clause `perm`:
    Description = Data public - Products public
Extra information associated with clause `source`:
    url =
    Organisation = World Food Program
    admn1PCode =
    admn2Name =
    admn2PCode =
    admn1Name =
Extra information associated with clause `datacat`:
    Description = Admin
Extra information associated with clause `geom`:
    Description = Polygon / area
Extra information associated with clause `datatheme`:
    Category = admn
    Description = Administrative boundary (level 3)


The Administrative boundary (level 3) data was generously supplied by World Food Program, downloaded from https://www.wfp.org/