| Name | iloveapi JSON |
| Version |
0.1.4
JSON |
| download |
| home_page | None |
| Summary | Python api client made for iLoveIMG & iLovePDF based on iLoveAPI (https://www.iloveapi.com/docs/api-reference). |
| upload_time | 2024-12-20 09:35:35 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.9 |
| license | MIT |
| keywords |
iloveapi
iloveimg
ilovepdf
api
sdk
client
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# iloveapi-python
Python api client made for iLoveIMG & iLovePDF based on iLoveAPI (https://www.iloveapi.com/docs/api-reference).
## Features
- Fully typed code
- Asyncio support
- REST API & workflow API encapsulation
## Installation
```shell
pip install iloveapi
```
## Getting Started
Simply compress image:
```python
from iloveapi import ILoveApi
client = ILoveApi(
public_key="<project_public_******>",
secret_key="<secret_key_******>",
)
task = client.create_task("compressimage")
task.process_files("p1.png")
task.download("output.png")
```
Multiple images:
```python
task = client.create_task("compressimage")
task.process_files(
"p1.png",
("custom_name.png", "p2.png"),
("custom_name.png", b"..PNG..."),
{
"file": b"..PNG...",
"filename": "custom_name.png",
"rotate": 2, # add image parameter
"password": "xxx", # for PDF
}
)
task.download("output.zip") # zip format
```
Async support:
```python
task = await client.create_task_async("compressimage")
await task.process_files_async("p1.png")
await task.download_async("output.png")
```
Directly call REST API:
```python
response = client.rest.start("compressimage") # getting httpx response
response = await client.rest.start_async("compressimage") # async
```
## TODO
- [ ] Typed parameter for all processing tools
- [ ] Command-line interface
## Why not pydantic?
Image / PDF processing tools usually focus on results rather than JSON data, as data type validation is not important to the user.
Raw data
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