Changed to difflib instead of Lavenshtein
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1 changed files with 99 additions and 94 deletions
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@ -1,94 +1,99 @@
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# THIS SOFTWARE IS A PART OF FREE COMPETITOR PROJECT
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# 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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# THE FOLLOWING SOURCE CODE I UNDER THE GNU
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# AGPL LICENSE V3 OR ANY LATER VERSION.
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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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# 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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# 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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# your ability to set it up and running.
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import os
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import os
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import json
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import json
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import Levenshtein
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from difflib import SequenceMatcher
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def similar(a, b):
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def search_app(name):
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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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# This function output a json of an app that's the closest
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# it an issue for some people to install.
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# match to the requested name.
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return SequenceMatcher(None, a, b).ratio()
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closest = {}
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def search_app(name):
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match = 0
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# This function output a json of an app that's the closest
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all_apps = []
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# match to the requested name.
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for i in os.listdir("apps"):
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if i.endswith(".json"):
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closest = {}
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match = 0
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try:
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with open("apps/"+i) as json_file:
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all_apps = []
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idata = json.load(json_file)
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for i in os.listdir("apps"):
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except Exception as e:
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if i.endswith(".json"):
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print("Error!", i, e)
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idata = {}
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try:
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with open("apps/"+i) as json_file:
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all_apps.append(idata)
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idata = json.load(json_file)
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# Round 1. By the name
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except Exception as e:
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print("Error!", i, e)
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for i in all_apps:
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idata = {}
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for n in i.get("names",[]):
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m = Levenshtein.jaro_winkler(n.lower(), name.lower())
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all_apps.append(idata)
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if m > match and m > 0.49:
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# Round 1. By the name
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closest = i
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match = m
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for i in all_apps:
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for n in i.get("names",[]):
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if closest:
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m = similar(n.lower(), name.lower())
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return closest
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if m > match and m > 0.49:
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closest = i
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# Round 2. By Generic name
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match = m
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for i in all_apps:
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if closest:
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for n in i.get("generic_name",[]):
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return closest
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m = Levenshtein.jaro_winkler(n.lower(), name.lower())
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if m > match:
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# Round 2. By Generic name
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closest = i
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match = m
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for i in all_apps:
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for n in i.get("generic_name",[]):
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if closest:
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m = similar(n.lower(), name.lower())
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return closest
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if m > match:
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closest = i
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def suggest(json_data):
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match = m
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# This function will suggest
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if closest:
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return closest
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found = []
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def suggest(json_data):
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all_apps = []
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for i in os.listdir("apps"):
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# This function will suggest
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if i.endswith(".json"):
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try:
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found = []
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with open("apps/"+i) as json_file:
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all_apps = []
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idata = json.load(json_file)
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for i in os.listdir("apps"):
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except Exception as e:
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if i.endswith(".json"):
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print("Error!", i, e)
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idata = {}
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try:
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with open("apps/"+i) as json_file:
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all_apps.append(idata)
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idata = json.load(json_file)
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except Exception as e:
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for i in all_apps:
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print("Error!", i, e)
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score = 0
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idata = {}
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for c in ["generic_name", "networks_read", "networks_write", "formats_read", "formats_write"]:
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all_apps.append(idata)
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for b in json_data.get(c, []):
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if b in i.get(c, []):
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for i in all_apps:
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score += 1
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score = 0
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print(score, i.get("names",["no name"])[0], "SCORE")
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for c in ["generic_name", "networks_read", "networks_write", "formats_read", "formats_write"]:
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found.append([score, i])
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for b in json_data.get(c, []):
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try:
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if b in i.get(c, []):
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found.sort(key=lambda x: x[0])
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score += 1
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found = list(reversed(found))
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print(score, i.get("names",["no name"])[0], "SCORE")
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except Exception as e:
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found.append([score, i])
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print("Found problem:", e)
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fount = []
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try:
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found.sort(key=lambda x: x[0])
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return found
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found = list(reversed(found))
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except Exception as e:
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print("Found problem:", e)
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fount = []
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return found
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