163 lines
4.6 KiB
Python
163 lines
4.6 KiB
Python
# THIS SOFTWARE IS A PART OF FREE COMPETITOR PROJECT
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# THE FOLLOWING SOURCE CODE I UNDER THE GNU
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# AGPL LICENSE V3 OR ANY LATER VERSION.
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# This project is not for simple users, but for
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# web-masters and a like, so we are counting on
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# your ability to set it up and running.
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##################################################
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# This file is importart, since it's important to
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# keep track of software that the users are
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# searching, but not getting any answers to.
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# The idea is very simple. If the score of any
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# search is below 60%, we add the search term into
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# a list. But instead of it being a dumb list, it's
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# a smart list.
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# Using the similar() function we can group very
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# similar terms together. So the users could misspel
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# certain names. For example we might group '3D Max'
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# '3DSMax' into the same data-structure. Using the
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# simple count of how much users spell this or that
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# name more often, we will make a suggestion for the
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# maintainer. So the maintainer could add the missing
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# names into the data. Or at least report them to us.
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##################################################
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import os
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import json
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from difflib import SequenceMatcher # checks how similar are two strings
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def similar(a, b):
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# I guess it simpifies the syntax for SequenceMatcher
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# In the previous version we use Lavenshtain but it made
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# it an issue for some people to install.
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return SequenceMatcher(None, a, b).ratio()
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def add(name):
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# This function will add a datapoint into the missing
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# This shows up way too often. And will show up. Untill we
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# will desing a logo.
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if name == "favicon.ico":
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return
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# first we need to make sure that the file exists
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try:
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with open("data/missing.json") as json_file:
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missing = json.load(json_file)
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# Reverse the old file
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if type(missing) == dict:
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missing = []
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except:
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missing = []
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# There could be a problem with writing so we look into it
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# for a very close match. Up to about 60%. No more.
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match_missing = 0
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closest_missing = 0
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found = False
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for ind, n in enumerate(missing):
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for i in n:
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sim = similar(name, i)
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if sim > 0.6: # At least 60% match
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found = True
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if match_missing < sim:
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match_missing = sim
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closest_missing = ind
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if not found:
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missing.append({name:1})
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else:
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if not name in missing[closest_missing]:
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missing[closest_missing][name] = 1
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else:
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missing[closest_missing][name] += 1
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# Now we save the file
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with open("data/missing.json", 'w') as f:
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json.dump(missing, f, indent=4, sort_keys=True)
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def remove(name):
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# This function will remove a datapoint from the missing
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try:
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with open("data/missing.json") as json_file:
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missing = json.load(json_file)
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# Reverse the old file
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if type(missing) == dict:
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missing = []
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except:
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missing = []
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# There could be a problem with writing so we look into it
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# for a very close match. Up to about 60%. No more.
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match_missing = 0
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closest_missing = 0
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found = False
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for ind, n in enumerate(missing):
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for i in n:
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sim = similar(name, i)
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if sim > 0.6: # At least 60% match
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found = True
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if match_missing < sim:
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match_missing = sim
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closest_missing = ind
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if found:
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del missing[closest_missing]
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# Now we save the file
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with open("data/missing.json", 'w') as f:
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json.dump(missing, f, indent=4, sort_keys=True)
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def List():
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# This function will list missing in markdown format
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try:
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with open("data/missing.json") as json_file:
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missing = json.load(json_file)
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# Reverse the old file
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if type(missing) == dict:
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missing = []
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except:
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missing = []
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print("| Done | Best Name | Other Names |")
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print("| --- | --- | --- |")
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for i in missing:
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i = sorted(i.items(), key=lambda x:x[1])
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i = dict(i)
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s = "| | **"+list(i.keys())[0]+"**"
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if len(i) > 1:
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s = s + " | "
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for b in i:
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if b == list(i.keys())[0]:
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continue
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comma = ", "
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if b == list(i.keys())[-1]:
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comma = ""
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s = s + b + comma
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s = s + " |"
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else:
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s = s + " | |"
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print(s)
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