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Yunus Emre edited this page Feb 10, 2023
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Simplest Alfred Client that I use my own projects
- Via
SnippetsClient
API create custom snippets programmaically - Via
WorkflowClient
API create custom alfred workflow - Use
WorkflowClient.log
to log your message to alfred debugger
from re import sub
from urllib.parse import quote_plus
from alfred5 import WorkflowClient
async def main(client: WorkflowClient):
query = client.query
client.log(f"my query: {query}") # use it to see your log in workflow debug panel
# Use cache system to quick response
if client.load_cached_response():
return
char_count = str(len( query))
word_count = str(len(query.split(" ")))
line_count = str(len(query.split("\n")))
encoded_string = quote_plus(query)
remove_dublication = " ".join(dict.fromkeys(query.split(" ")))
upper_case = query.upper()
lower_case = query.lower()
capitalized = query.capitalize()
template = sub(r"[a-zA-Z0-9]", "X", query)
client.add_result(encoded_string, "Encoded", arg=encoded_string)
client.add_result(remove_dublication, "Remove dublication", arg=remove_dublication)
client.add_result(upper_case, "Upper Case", arg=upper_case)
client.add_result(lower_case, "Lower Case", arg=lower_case)
client.add_result(capitalized, "Capitalized", arg=capitalized)
client.add_result(template, "Template", arg=template)
client.add_result(char_count, "Characters", arg=char_count)
client.add_result(word_count, "Words", arg=word_count)
client.add_result(line_count, "Lines", arg=line_count)
client.cache_response() # to cache result for query (if u work with static results (not dynamic; coin price etc.))
if __name__ == "__main__":
WorkflowClient.run(main)
Welcome to the alfred5 wiki! for people that are new in Alfred workflow, let's show how to create python workflow for Alfred 🙋♂️
Copyright 2023 Yunus Emre Ak ~ YEmreAk.com
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
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