| Name | AcodisApiHandler JSON |
| Version |
0.3.7
JSON |
| download |
| home_page | |
| Summary | A simple API handler for Python |
| upload_time | 2024-01-18 16:49:49 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.8.12 |
| license | MIT License |
| keywords |
api
handler
python
acodis
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
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No Travis.
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|
# Acodis API Handler
This package provides easy to use python classes and functions to communicate with Acodis API (https://acodis.io).
Acodis is an IDP solution that focuses on extracting and structuring complex documents (PDFs, Images)
## Installation
```bash
pip install AcodisApiHandler
```
## Usage
This package is particularly useful for programmatic access, since ACODIS' API structure requires a different
**user** and **password** for every export step. Hence, if you have to manage multiple exports
(e.g. multiple workflows), you just need to update the main class `user` and `password` attribute,
and call the `authenticate()` method.
```python
from AcodisApiHandler import AcodisApiHandler
# Set up your credentials
ACODIS_BASE_URL = "https://<YOUR-ACOIDS-INSTANCE-URL>/workbench/api/transaction"
ACODIS_USER = "<YOUR-EXPORT-USERNAME>"
ACODIS_PASSWORD = "<YOUR-EXPORT-PASSWORD>"
# Create an instance of the AcodisApiHandler class
handler = AcodisApiHandler(ACODIS_BASE_URL)
# Set the credentials
handler.user = ACODIS_USER
handler.password = ACODIS_PASSWORD
# Authenticate with the API
handler.authenticate()
handler.workflow(pdf_path="<PATH-TO-PDF-FILE>")
# The extraction result is an ElementTree XML object stored in the handler.result variable
# You can check it by:
print(handler.result)
```
## Utils
This package also provides some utils to help you with the extraction process.
### Extracting tagged data points
Tags are used to identify the data points that you want to extract from the document.
This function will create a dictionary with the tags as keys and the extracted data as values.
```python
from AcodisApiHandler import extract_tags
tags_list = ["example_tag_1", "example_tag_1", "example_tag_1"]
# Using the precviously created handler instance
tagged_data = extract_tags(handler, tags_list)
```
If we print the `tagged_data` variable we will get:
```python
{
"example_tag_1": "Example data 1",
"example_tag_2": "Example data 2",
"example_tag_3": "Example data 3"
}
```
## License
[MIT](https://choosealicense.com/licenses/mit/)
## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
## Roadmap
- [ ] Additional utils: parsing tables, extracting images, etc.
- [ ] Add unit tests
- [ ] Add batch processing and parallelization
Raw data
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"description": "# Acodis API Handler\nThis package provides easy to use python classes and functions to communicate with Acodis API (https://acodis.io).\nAcodis is an IDP solution that focuses on extracting and structuring complex documents (PDFs, Images)\n\n## Installation\n```bash\npip install AcodisApiHandler\n```\n\n## Usage\nThis package is particularly useful for programmatic access, since ACODIS' API structure requires a different \n**user** and **password** for every export step. Hence, if you have to manage multiple exports \n(e.g. multiple workflows), you just need to update the main class `user` and `password` attribute,\nand call the `authenticate()` method.\n```python\nfrom AcodisApiHandler import AcodisApiHandler\n\n# Set up your credentials\nACODIS_BASE_URL = \"https://<YOUR-ACOIDS-INSTANCE-URL>/workbench/api/transaction\"\nACODIS_USER = \"<YOUR-EXPORT-USERNAME>\"\nACODIS_PASSWORD = \"<YOUR-EXPORT-PASSWORD>\"\n\n# Create an instance of the AcodisApiHandler class\nhandler = AcodisApiHandler(ACODIS_BASE_URL)\n\n# Set the credentials\nhandler.user = ACODIS_USER\nhandler.password = ACODIS_PASSWORD\n\n# Authenticate with the API\nhandler.authenticate()\n\nhandler.workflow(pdf_path=\"<PATH-TO-PDF-FILE>\")\n\n# The extraction result is an ElementTree XML object stored in the handler.result variable\n# You can check it by:\nprint(handler.result)\n```\n\n## Utils\nThis package also provides some utils to help you with the extraction process.\n\n### Extracting tagged data points\nTags are used to identify the data points that you want to extract from the document.\nThis function will create a dictionary with the tags as keys and the extracted data as values.\n```python\nfrom AcodisApiHandler import extract_tags\n\ntags_list = [\"example_tag_1\", \"example_tag_1\", \"example_tag_1\"]\n\n# Using the precviously created handler instance\ntagged_data = extract_tags(handler, tags_list)\n```\n\nIf we print the `tagged_data` variable we will get:\n```python\n{\n \"example_tag_1\": \"Example data 1\",\n \"example_tag_2\": \"Example data 2\",\n \"example_tag_3\": \"Example data 3\"\n}\n```\n\n## License\n[MIT](https://choosealicense.com/licenses/mit/)\n\n## Contributing\nPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.\n\n## Roadmap\n- [ ] Additional utils: parsing tables, extracting images, etc.\n- [ ] Add unit tests\n- [ ] Add batch processing and parallelization\n",
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