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https://github.com/zerodha/py-frappe-client
Frappe client for humans
https://github.com/zerodha/py-frappe-client
erpnext frappe frappe-bench
Last synced: 2 months ago
JSON representation
Frappe client for humans
- Host: GitHub
- URL: https://github.com/zerodha/py-frappe-client
- Owner: zerodha
- Created: 2018-05-18T10:59:54.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2021-05-27T05:28:16.000Z (over 3 years ago)
- Last Synced: 2024-08-26T08:58:10.625Z (2 months ago)
- Topics: erpnext, frappe, frappe-bench
- Language: Python
- Homepage:
- Size: 23.4 KB
- Stars: 31
- Watchers: 6
- Forks: 18
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-frappe - FrappeClient.py - @zerodha's Python client for making requests to your Frappe Server. (Uncategorized / Uncategorized)
README
# Py-Frappe-Client
## Install
```
pip install py-frappe-client
```
[View on PyPi](https://pypi.org/project/py-frappe-client/)
## Usage
### Token based authentication
```python
>>> from frappe_client import FrappeRequest
>>> client = FrappeRequest(url="http://localhost:8002", api_key="API_KEY", api_secret="API_SECRET")
>>> client.get("method_name")
>>> client.post("method_name")
```
### Session based authentication (Legacy)
#### Initialize
```python
>>> from frappe_client import FrappeRequest
>>> client = FrappeRequest(url="http://localhost:8002", username="user", password="password")
>>> client.__dict__
{
"frappe_session":,
"url":"http://localhost:8002",
"usr":"Administrator",
"pwd":"pass",
"session_data":{
"full_name":"Administrator",
"sid":"6684ed4e173094199b1cc0913d4044fdcec1d87d5d6a74a3728f229b",
"system_user":"yes",
"user_id":"Administrator",
"user_image":""
},
"callback": None
}
```
#### Using Callback
The wrapper checks for a HTTP 403 Response from the server for the first time on every API call. If the server
returns 403, the wrapper attempts to login again. During this login, if a `callback` function is passed by the user
the new `session_data` is passed on to this callback parameter.
```python
# Example Callback function
def store_session_data(data):
print ("Callback function invoked with arg {}".format(data))
>>> client = FrappeRequest(url="http://localhost:8002", username="Administrator", password="pwd", callback=store_session_data)
Callback function invoked with arg {'full_name': 'Administrator', 'sid': '427f585e17c551b9bf70ff64a22a6998064d0415914aaf91beb981f2', 'system_user': 'yes', 'user_id': 'Administrator', 'user_image': ''}
```
#### Get Session Data
`client.session_data`
```python
# Example Output
>>> client.session_data
>>> {
"full_name":"Administrator",
"sid":"427f585e17c551b9bf70ff64a22a6998064d0415914aaf91beb981f2",
"system_user":"yes",
"user_id":"Administrator",
"user_image":""
}
```
#### Storing Session Data
`session_data` is a `dict` object which is returned by `client.session_data` field.
Session Data needs to be stored locally on the client's end (database/redis/file/etc).
On further initializations of the FrappeRequest() class, you should pass `session_data` field
to prevent multiple sessions for the same user.
If `session_data` field is passed, all further API calls will use the same session.
### Invoke GET Endpoint
`client.get(method, params)`
```python
>>> # Example Request
>>> response = client.get(method="acop_process.lead_integration.ping")
>>> response.json()
{'message': 'PONG'}
```
### Invoke POST Endpoint
`client.post(method, data)`
```python
>>> # Example Request
>>> response = client.post(method="acop_process.lead_integration.post_ping", data={'test_param':123})
>>> response.json()
{'message': 'POST PONG success 123'}
```
### Documents API
```python
# Fetch a single resource
>>> response = client.get_doc("Custom Doctype", name="record1")
# Fetch multiple resources
>>> response = client.get_doc("Custom Doctype")
# With filters, fields
>>> response = client.get_doc("Custom Doctype", fields=["field1", "field2"], filters={"field3", ["in", [1, 2, 3]]})
# With page size, fetch 50 records at once
>>> response = client.get_doc("Custom Doctype", limit_page_length=50)
# fetch 50 records starting from offset 50
>>> response = client.get_doc("Custom Doctype", limit_start=50, limit_page_length=50)
# paginated generator
>>> fetch_iter = client.get_doc("Custom Doctype", limit_page_length=10, pagination=True)
>>> for records in fetch_iter:
print(records["data"])
```
### Pagination API
```python
# Fetch in batches of 10 records from API using a generator
>>> fetch_iter = client.get_paginated_doc("Custom Doctype", limit_page_lenth=10)
>>> for records in fetch_iter:
print(records["data"])
```