# jupyterlite-simple-cors-proxy
Simple CORS proxy wrapper for making http requests from JupyterLite. Uses https://corsproxy.io/
## Installation
```bash
pip install jupyterlite-simple-cors-proxy
```
## Usage
```python
from jupyterlite_simple_cors_proxy.proxy import cors_proxy_get, robust_get_request, furl, xurl
# Set up
url = "https://api.example.com/data"
# Optional params
params = {"key": "value"}
# Get a cross-origin proxied url
cross_origin_url = xurl(url) # xurl(url, params)
# Get a file like object
# (Make the request, then create a file like object
# from the response)
file_ob = furl(url) # furl(url, params)
# Make a request
response = cors_proxy_get(url, params)
# Use like requests
print(response.text)
data = response.json()
raw = response.content
```
The `robust_get_request()` will first try a simple request, then a proxied request: `robust_get_request(url, params)`
## Features
- Simple CORS proxy wrapper
- Requests response object
- Support for URL parameters
## `fastf1` cors proxy
A monkey patch for `fastf1` is provided as:
```python
import fast f1
from jupyterlite_simple_cors_proxy.fastf1_proxy import enable_cors_proxy
enable_cors_proxy(
# domains=["api.formula1.com", "livetiming.formula1.com"],
# debug=True,
# proxy_url="https://corsproxy.io/",
)
```
## `CorsProxy` with cache facility
Via `claude.ai`, the package is now further enriched.
*Note that `pyodide` sqlite can't write to `/drive` so the cache path dir needs to be something like `/tmp` or a dir created on `/`.*
*I'm not convinced the following works in `pyodide` and `xeus-python` yet - `requests-cache` dependency issues etc. `requests-cache` has requirements `attrs`, `cattrs`,`platformdirs`, `url-normalize`.*
```python
from simple_cors_proxy.proxy import CorsProxy
# Create a cached proxy instance
proxy = CorsProxy(use_cache=True, expire_after=3600) # Cache for 1 hour
# Use furl directly from your proxy instance
file_like = proxy.furl('https://example.com/somefile.csv')
#----
import pandas as pd
from simple_cors_proxy.cacheproxy import CorsProxy
proxy = CorsProxy(use_cache=True)
file_like = proxy.furl('https://example.com/data.csv')
df = pd.read_csv(file_like)
#----
from simple_cors_proxy.proxy import create_cached_proxy
proxy = create_cached_proxy(cache_name='my_cache', expire_after=86400) # Cache for 1 day
file_like = proxy.furl('https://example.com/somefile.csv')
```
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"description": "# jupyterlite-simple-cors-proxy\nSimple CORS proxy wrapper for making http requests from JupyterLite. Uses https://corsproxy.io/\n\n## Installation\n\n```bash\npip install jupyterlite-simple-cors-proxy\n```\n\n## Usage\n\n```python\nfrom jupyterlite_simple_cors_proxy.proxy import cors_proxy_get, robust_get_request, furl, xurl\n\n# Set up\nurl = \"https://api.example.com/data\"\n# Optional params\nparams = {\"key\": \"value\"}\n\n# Get a cross-origin proxied url\ncross_origin_url = xurl(url) # xurl(url, params)\n\n# Get a file like object\n# (Make the request, then create a file like object\n# from the response)\nfile_ob = furl(url) # furl(url, params)\n\n# Make a request\nresponse = cors_proxy_get(url, params)\n\n# Use like requests\nprint(response.text)\ndata = response.json()\nraw = response.content\n```\n\nThe `robust_get_request()` will first try a simple request, then a proxied request: `robust_get_request(url, params)`\n\n## Features\n\n- Simple CORS proxy wrapper\n- Requests response object\n- Support for URL parameters\n\n## `fastf1` cors proxy\n\nA monkey patch for `fastf1` is provided as:\n\n```python\nimport fast f1\nfrom jupyterlite_simple_cors_proxy.fastf1_proxy import enable_cors_proxy\n\nenable_cors_proxy(\n# domains=[\"api.formula1.com\", \"livetiming.formula1.com\"],\n# debug=True,\n# proxy_url=\"https://corsproxy.io/\",\n)\n```\n\n## `CorsProxy` with cache facility\n\nVia `claude.ai`, the package is now further enriched.\n\n*Note that `pyodide` sqlite can't write to `/drive` so the cache path dir needs to be something like `/tmp` or a dir created on `/`.*\n\n*I'm not convinced the following works in `pyodide` and `xeus-python` yet - `requests-cache` dependency issues etc. `requests-cache` has requirements `attrs`, `cattrs`,`platformdirs`, `url-normalize`.*\n\n```python\nfrom simple_cors_proxy.proxy import CorsProxy\n\n# Create a cached proxy instance\nproxy = CorsProxy(use_cache=True, expire_after=3600) # Cache for 1 hour\n\n# Use furl directly from your proxy instance\nfile_like = proxy.furl('https://example.com/somefile.csv')\n\n#----\nimport pandas as pd\nfrom simple_cors_proxy.cacheproxy import CorsProxy\n\nproxy = CorsProxy(use_cache=True)\nfile_like = proxy.furl('https://example.com/data.csv')\ndf = pd.read_csv(file_like)\n\n#----\n\nfrom simple_cors_proxy.proxy import create_cached_proxy\n\nproxy = create_cached_proxy(cache_name='my_cache', expire_after=86400) # Cache for 1 day\nfile_like = proxy.furl('https://example.com/somefile.csv')\n```\n",
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