InvenTree/InvenTree/part/bom.py
Oliver Walters 85e803f345 Create a new part directly from the BOM view
- Pass data through to the part creation
- Populate the new part into the select dropdown
-
2019-07-07 13:06:59 +10:00

209 lines
5.3 KiB
Python

"""
Functionality for Bill of Material (BOM) management.
Primarily BOM upload tools.
"""
from fuzzywuzzy import fuzz
import tablib
import os
from django.utils.translation import gettext_lazy as _
from django.core.exceptions import ValidationError
from InvenTree.helpers import DownloadFile
def IsValidBOMFormat(fmt):
""" Test if a file format specifier is in the valid list of BOM file formats """
return fmt.strip().lower() in ['csv', 'xls', 'xlsx', 'tsv']
def MakeBomTemplate(fmt):
""" Generate a Bill of Materials upload template file (for user download) """
fmt = fmt.strip().lower()
if not IsValidBOMFormat(fmt):
fmt = 'csv'
fields = [
'Part',
'Quantity',
'Overage',
'Reference',
'Notes'
]
data = tablib.Dataset(headers=fields).export(fmt)
filename = 'InvenTree_BOM_Template.' + fmt
return DownloadFile(data, filename)
class BomUploadManager:
""" Class for managing an uploaded BOM file """
# Fields which are absolutely necessary for valid upload
REQUIRED_HEADERS = [
'Part',
'Quantity'
]
# Fields which would be helpful but are not required
OPTIONAL_HEADERS = [
'Reference',
'Notes',
'Overage',
'Description',
'Category',
'Supplier',
'Manufacturer',
'MPN',
'IPN',
]
EDITABLE_HEADERS = [
'Reference',
'Notes'
]
HEADERS = REQUIRED_HEADERS + OPTIONAL_HEADERS
def __init__(self, bom_file):
""" Initialize the BomUpload class with a user-uploaded file object """
self.process(bom_file)
def process(self, bom_file):
""" Process a BOM file """
self.data = None
ext = os.path.splitext(bom_file.name)[-1].lower()
if ext in ['.csv', '.tsv', ]:
# These file formats need string decoding
raw_data = bom_file.read().decode('utf-8')
elif ext in ['.xls', '.xlsx']:
raw_data = bom_file.read()
else:
raise ValidationError({'bom_file': _('Unsupported file format: {f}'.format(f=ext))})
try:
self.data = tablib.Dataset().load(raw_data)
except tablib.UnsupportedFormat:
raise ValidationError({'bom_file': _('Error reading BOM file (invalid data)')})
def guess_header(self, header, threshold=80):
""" Try to match a header (from the file) to a list of known headers
Args:
header - Header name to look for
threshold - Match threshold for fuzzy search
"""
# Try for an exact match
for h in self.HEADERS:
if h == header:
return h
# Try for a case-insensitive match
for h in self.HEADERS:
if h.lower() == header.lower():
return h
# Finally, look for a close match using fuzzy matching
matches = []
for h in self.HEADERS:
ratio = fuzz.partial_ratio(header, h)
if ratio > threshold:
matches.append({'header': h, 'match': ratio})
if len(matches) > 0:
matches = sorted(matches, key=lambda item: item['match'], reverse=True)
return matches[0]['header']
return None
def columns(self):
""" Return a list of headers for the thingy """
headers = []
for header in self.data.headers:
headers.append({
'name': header,
'guess': self.guess_header(header)
})
return headers
def col_count(self):
if self.data is None:
return 0
return len(self.data.headers)
def row_count(self):
""" Return the number of rows in the file.
Ignored the top rows as indicated by 'starting row'
"""
if self.data is None:
return 0
return len(self.data)
def rows(self):
""" Return a list of all rows """
rows = []
for i in range(self.row_count()):
data = [item for item in self.get_row_data(i)]
# Is the row completely empty? Skip!
empty = True
for idx, item in enumerate(data):
if len(str(item).strip()) > 0:
empty = False
try:
# Excel import casts number-looking-items into floats, which is annoying
if item == int(item) and not str(item) == str(int(item)):
print("converting", item, "to", int(item))
data[idx] = int(item)
except ValueError:
pass
if empty:
print("Empty - continuing")
continue
row = {
'data': data,
'index': i
}
rows.append(row)
return rows
def get_row_data(self, index):
""" Retrieve row data at a particular index """
if self.data is None or index >= len(self.data):
return None
return self.data[index]
def get_row_dict(self, index):
""" Retrieve a dict object representing the data row at a particular offset """
if self.data is None or index >= len(self.data):
return None
return self.data.dict[index]