File packages/color.py changed (mode: 100644) (index 4176e08..f62715e) |
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""" |
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Author: Sebastian Fricke |
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License: GPL v3 |
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Company: Panasiam |
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Process colors unknown for plentymarkets, by providing a list of similar |
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values and uploading new values. |
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""" |
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import csv |
import csv |
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import re |
import re |
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from packages import barcode |
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def missingColor(flatfile, attributefile): |
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# check the attribute export from PlentyMarkets for similar color names |
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# _____________________________ |
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import sys |
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from packages import barcode, error |
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def missing_color(flatfile, attributefile): |
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""" |
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Detect any color names that are not found on PlentyMarkets. |
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Generate a list of similar color names and find the highest |
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position number of the color attributes. |
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Parameters: |
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flatfile [csv] - Amazon Flatfile format of product data |
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attributefile [csv] - Plentymarkets Export with the values: |
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* AttributeValue.position |
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* AttributeValue.backendName |
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Return: |
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missing_colors [dict] - mapped similar names and highest position |
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for each new color |
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""" |
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color_list = set() |
color_list = set() |
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missing_colors = dict() |
missing_colors = dict() |
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# Open the attribute file to get all color names |
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# Get the highest position number |
# Get the highest position number |
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highest_number = int(0) |
highest_number = int(0) |
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with open(attributefile['path'], mode = 'r', encoding=attributefile['encoding']) as item: |
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with open(attributefile['path'], mode='r', |
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encoding=attributefile['encoding']) as item: |
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reader = csv.DictReader(item, delimiter=';') |
reader = csv.DictReader(item, delimiter=';') |
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for row in reader: |
for row in reader: |
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try: |
try: |
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if(int(row['AttributeValue.position']) > highest_number): |
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if int(row['AttributeValue.position']) > highest_number: |
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highest_number = int(row['AttributeValue.position']) |
highest_number = int(row['AttributeValue.position']) |
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except KeyError as err: |
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print("ERROR @ reading attribute file: {0}".format(err)) |
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if('AttributeValue.backendName' in [*row]): |
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color_list.add(row['AttributeValue.backendName']) |
color_list.add(row['AttributeValue.backendName']) |
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else: |
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print("Wrong Columns in the attribute file!\n{0}\n".format(",".join([*row]))) |
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except KeyError as err: |
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error.errorPrint(msg="invalid attribute file", err=err, |
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linenumber=sys.exc_info()[2].tb_lineno) |
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missing_colors_columns = ['color_name', 'similar_names', 'highest-position'] |
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missing_colors_columns = ['color_name', 'similar_names', |
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'highest-position'] |
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# Open the flatfile to check which names are not in the color_list |
# Open the flatfile to check which names are not in the color_list |
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with open(flatfile['path'], mode='r', encoding=flatfile['encoding']) as item: |
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reader = csv.DictReader(item, delimiter = ';') |
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with open(flatfile['path'], mode='r', |
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encoding=flatfile['encoding']) as item: |
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reader = csv.DictReader(item, delimiter=';') |
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color_set = set() |
color_set = set() |
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for num, row in enumerate( reader ): |
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for num, row in enumerate(reader): |
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color_name = row['color_name'] |
color_name = row['color_name'] |
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if(not( color_name in color_list ) and not(color_name in color_set)): |
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if not color_name in color_list and not color_name in color_set: |
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color_set.add(color_name) |
color_set.add(color_name) |
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values = [color_name, [], highest_number] |
values = [color_name, [], highest_number] |
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missing_colors[str(num)] = dict(zip(missing_colors_columns, values)) |
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missing_colors[str(num)] =\ |
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dict(zip(missing_colors_columns, values)) |
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# Open the attribute file to check for similar names to the missing ones |
# Open the attribute file to check for similar names to the missing ones |
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with open(attributefile['path'], mode = 'r', encoding=attributefile['encoding']) as item: |
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reader = csv.DictReader(item, delimiter = ';') |
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with open(attributefile['path'], mode='r', |
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encoding=attributefile['encoding']) as item: |
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reader = csv.DictReader(item, delimiter=';') |
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for row in reader: |
for row in reader: |
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for color in missing_colors: |
for color in missing_colors: |
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try: |
try: |
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if(re.search( missing_colors[color]['color_name'][1:], row['AttributeValue.backendName'] )): |
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missing_colors[color]['similar_names'].append(row['AttributeValue.backendName']) |
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if(re.search(missing_colors[color]['color_name'][1:], |
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row['AttributeValue.backendName'])): |
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missing_colors[color]['similar_names'].append( |
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row['AttributeValue.backendName']) |
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except KeyError as err: |
except KeyError as err: |
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print("ERROR @ similar name search: {0}".format(err)) |
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''' |
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for row in missing_colors: |
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print("COLOR: {0}\n".format( missing_colors[row]['color_name'] )) |
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for name in missing_colors[row]['similar_names']: |
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print("similar to {0}: {1}".format(missing_colors[row]['color_name'], name)) |
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''' |
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error.errorPrint(msg="invalid attribute file", err=err, |
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linenumber=sys.exc_info()[2].tb_lineno) |
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return missing_colors |
return missing_colors |
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def create_attributesync(color_dict, path): |
def create_attributesync(color_dict, path): |
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column_names = ['Attribute.id','AttributeValue.backendName','AttributeValue.position','AttributeValueName.name'] |
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Data = {} |
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""" |
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Create a Elastic Sync (import) file for Plentymarkets. |
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Parameters: |
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color_dict [dict] - Combination of a new color name and |
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it's position within the attributes |
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path [str] - Path of the Upload folder |
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""" |
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column_names = ['Attribute.id', 'AttributeValue.backendName', |
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'AttributeValue.position', 'AttributeValueName.name'] |
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data = {} |
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values = [] |
values = [] |
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for index, row in enumerate(color_dict): |
for index, row in enumerate(color_dict): |
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try: |
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values = ['4', color_dict[row]['color_name'], int(float(color_dict[row]['highest-position'])) + int(index + 1), color_dict[row]['color_name']] |
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except KeyError as err: |
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print(color_dict[row]) |
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print("ERROR @ attribute sync creation: {0}".format(err)) |
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Data[color_dict[row]['color_name']] = dict(zip(column_names, values)) |
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values = [ |
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'4', color_dict[row]['color_name'], |
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int(float(color_dict[row]['highest-position'])) + int(index + 1), |
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color_dict[row]['color_name'] |
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] |
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barcode.writeCSV(dataobject=Data, name="Color_Sync", columns=column_names, upload_path=path, item="") |
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data[color_dict[row]['color_name']] = dict(zip(column_names, values)) |
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barcode.writeCSV(dataobject=data, name="Color_Sync", |
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columns=column_names, upload_path=path, item="") |