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Yunus Emre edited this page Apr 13, 2023
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Simplest Alfred Client that I use my own projects.
pip install alfred5
- Via
SnippetsClient
API create custom snippets programmaically - Via
WorkflowClient
API create custom alfred workflow- Craete
requirements.txt
file for your python project to letalfred5
installs them if needed 🙃 - To install
from requirements.txt
do all import packages insidemain
- Useglobal
keyword to access imported packages globally-
client.query
is the query string -
client.page_count
is the page count for pagination results
-
- Dont need to add
alfred5
torequirements.txt
- Craete
- Use
WorkflowClient.log
to log your message to alfred debugger - Use
WorkflowClient(main, cache=True)
method to use caching system- Just do it for static (not timebased nor any dynamic stuff) response
- Db path is
db/results.yml
also you can see it from workflow debug panel
from re import sub
from urllib.parse import quote_plus
from alfred5 import WorkflowClient
async def main(client: WorkflowClient):
# To auto install requirements all import operation must be in here
global get
from requests import get
query = client.query
client.log(f"my query: {query}") # use it to see your log in workflow debug panel
# (use cache=True) 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)
# (use cache=True) to cache result for query (if u work with static results (not dynamic; coin price etc.))
# client.cache_response()
if __name__ == "__main__":
WorkflowClient.run(main) # WorkflowClient.run(main, cache=True)
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.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.