187 lines
6.4 KiB
Python
187 lines
6.4 KiB
Python
import csv
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from io import StringIO
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from os.path import splitext
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from .filters import *
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from .wms_utils import get_address_from_coordinates, get_point_from_coordinates
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import pdfkit
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import pandas as pd
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from PyPDF2 import PdfFileMerger
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from django.core.files.storage import get_storage_class
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Storage = get_storage_class()
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storage = Storage()
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CSV_FILENAME = 'plants.csv'
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PLANTING_GUIDE_PDF_FILENAME = 'planting_guide.pdf'
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HEADER_FIELDS = ['Names', 'Growth Form / Max Height (m) / Spacing (m) / Forest Position', 'Moisture Preferences',
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'Tolerances (Water / Drought / Frost / Salinity)', 'Ecosystem Services', 'Carbon Sequestration Rate', 'Planting Stage']
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def get_location_filters(params):
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""" Retrives the selected location data from the request.
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"""
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filter_rows = [['LOCATION FILTERS:', ' ']]
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coordinates = params.get('coordinates')
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if coordinates is not None:
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eco_district_layer = ecological_district_coordinate_filter(
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coordinates).first()
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point = get_point_from_coordinates(coordinates)
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address = get_address_from_coordinates(coordinates)
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filter_rows.append(['Point coordinates:', point])
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filter_rows.append(['Ecological region:', eco_district_layer.ecologic_1 or '' ])
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filter_rows.append(['Ecological district:', eco_district_layer.ecologic_2 or ' '])
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filter_rows.append(['Property address:', address['full_address'] if address is not None else ' '])
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else:
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filter_rows.append(["None specified", " "])
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return filter_rows
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def get_soil_filters(params):
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""" Retrives the selected soil type data from the request params.
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"""
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filter_rows = [['SOIL FILTERS:', ' ']]
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soil_variant = params.get('soilVariant')
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coordinates = params.get('coordinates')
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if soil_variant is not None and coordinates is not None:
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soil_order_obj = soil_order_coordinate_filter(coordinates).first()
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filter_rows.append(['Soil Order:', f"{soil_order_obj.name or ' '} ({soil_order_obj.code or ' '})"])
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filter_rows.append(['Soil Variant:', soil_variant])
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else:
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filter_rows.append(["None specified", " "])
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return filter_rows
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def get_site_filters(params):
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""" Retrives the selected site data from the request params
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"""
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filter_rows = [['SITE FILTERS:', ' ']]
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habitat = params.get('habitat')
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zone = params.get('zone')
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if zone is not None and habitat is not None:
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habitat_json = json.loads(habitat)
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zone_json = json.loads(zone)
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filter_rows.append(['Habitat:', habitat_json.get("name", " ")])
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filter_rows.append(['Zone Name:', zone_json.get("name", " ")])
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filter_rows.append(['Zone Variant:', zone_json.get("variant", " ")])
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filter_rows.append(['Zone Refined Variant:', zone_json.get("refined_variant", " ")])
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else:
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filter_rows.append(["None specified", " "])
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return filter_rows
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def get_additional_region_info(params):
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""" If the location coordinates fall within the CHCH or Auckland regions then return a description of where to find more information.
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"""
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coordinates = params.get('coordinates')
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if coordinates is not None:
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if is_in_christchurch(coordinates):
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return [["Your location falls within the ecosystem type covered by the Christchurch Council ecosystem maps - further information can be obtained from Ōtautahi/Christchurch ecosystems map link to: https://ccc.govt.nz/environment/land/ecosystem-map", " "], [' ', ' ']]
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elif is_in_auckland(coordinates):
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return [["Your location falls within the ecosystem type covered by the Auckland Council Tiaki Tāmaki Makaurau Conservation map - further information can be obtained from tiaki Tāmaki Makaurau conservation Auckland - link to https://www.tiakitamakimakaurau.nz/conservation-map/", " "], [' ', ' ']]
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return []
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def get_filter_values(params):
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""" Retrives all selected values/filters from the request parameters
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"""
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filter_rows = []
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# Add all the location filters
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filter_rows += get_location_filters(params)
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filter_rows.append([' ', ' '])
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# Add the soil filters
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filter_rows += get_soil_filters(params)
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filter_rows.append([' ', ' '])
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# Add the project site filters
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filter_rows += get_site_filters(params)
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filter_rows.append([' ', ' '])
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filter_rows += get_additional_region_info(params)
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return filter_rows
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def generate_csv(data: list[list[str]], output_filename: str) -> str:
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with storage.open(output_filename, 'w') as f:
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csv.writer(f).writerows(data)
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return storage.path(output_filename)
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def generate_pdf(data: list[list[str]], output_filename: str):
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""" Generates a pdf from a csv given data and a csv generation method.
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Requires an html file to be generated as an intermediate step.
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"""
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name, _ = splitext(output_filename)
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csv_filepath = generate_csv(data, f"{name}.csv")
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pdf_filepath = storage.path(output_filename)
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with StringIO() as html_buf:
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# Convert csv to html
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pd.read_csv(csv_filepath).to_html(html_buf) # reading from buffer causes segfault :/
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html_buf.seek(0)
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# Convert html to pdf
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pdfkit.from_file(html_buf, pdf_filepath)
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return pdf_filepath
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def merge_pdfs(pdfs: list[str], output_filename):
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"""Merge a list of PDF filenames"""
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output_filepath = storage.path(output_filename)
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merger = PdfFileMerger()
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for pdf in pdfs:
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merger.append(pdf)
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merger.write(output_filepath)
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merger.close()
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return output_filepath
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def serialize_plants_queryset(plants_queryset):
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return [HEADER_FIELDS] + [
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[
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plant.display_name,
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plant.display_growth_form,
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plant.moisture_preferences,
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plant.plant_tolerances,
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plant.ecosystem_services,
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plant.carbon_sequestration,
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plant.stage
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] for plant in plants_queryset
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]
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def create_planting_guide_pdf(filter_data, plant_data, output_filename):
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""" Creates a planting guide pdf document with a pre-generated planting guide with
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filter and plant list tabular informtation appended.
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"""
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# TODO: space values appear as NaN... this should be fixed
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return merge_pdfs(
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[
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storage.path(PLANTING_GUIDE_PDF_FILENAME),
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generate_pdf(filter_data, f"{output_filename}.filters"),
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generate_pdf(plant_data, f"{output_filename}.plants"),
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],
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output_filename,
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)
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