# 🎩 AlfredClient
Simplest Alfred Client that I use my own projects.
## Usage
```bash
pip install alfred5
```
- Projects dir structure
- Put your codes and `requirements.txt` to `src` folders
- Install `alfred5` via
```bash
pip install alfred5 --target=src/lib
```
- If u want to use different `--target` for ex `.` use `WorkflowClient.run(packagedir=".")`
- Sample of default structure:
- 
- **If u install all of requirements, dont need to create `requirements.txt` file in `src`**
- Via `SnippetsClient` API create custom snippets programmaically
- Via `WorkflowClient` API create custom alfred workflow
- Craete `requirements.txt` file for your python project to let `alfred5` installs them if needed 🙃
- To install `from requirements.txt` do all import packages inside `main`
- Use `global` 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` to `requirements.txt`
- Use `WorkflowClient.log` to log your message to alfred debugger
- [debugging alfred workflow](https://www.alfredapp.com/help/workflows/utilities/debug/)
- [why this project use stderr for all logging operation](https://www.alfredforum.com/topic/14721-get-the-python-output-back-to-alfred/?do=findComment&comment=75303)
- 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
## ⭐️ Example Project

```python
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 instead of old style that below
# 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 instead of old style that below
# 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)
```
## 🔰 How to Create Workflow




## 🪪 License
```
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.
```