TinyRetriever: HTTP Requests Made Easy
TinyRetriever is a lightweight synchronous wrapper for AIOHTTP that abstracts away the complexities of making asynchronous HTTP requests. It is designed to be simple, easy to use, and efficient. TinyRetriever is built on top of AIOHTTP and AIOFiles, which are popular asynchronous HTTP client and file management libraries for Python.
📚 Full documentation is available here.
Features
TinyRetriever provides the following features:
- Concurrent Downloads: Efficiently download multiple files simultaneously
- Flexible Response Types: Get responses as text, JSON, or binary data
- Rate Limiting: Built-in per-host connection limiting to respect server constraints
- Streaming Support: Stream large files efficiently with customizable chunk sizes
- Unique Filenames: Generate unique filenames based on query parameters
- Works in Jupyter Notebooks: Easily use TinyRetriever in Jupyter notebooks without any additional setup or dependencies
- Automatic Retries: Exponential backoff with jitter for transient errors (5xx, DNS failures, timeouts)
- Robust Error Handling: Optional status raising and comprehensive error messages
- Performance Optimized: Uses
orjsonwhen available for faster JSON serialization
TinyRetriever does not use nest-asyncio, instead it creates and manages a dedicated
thread for running the event loop. This allows you to use TinyRetriever in Jupyter
notebooks and other environments where the event loop is already running.
There are four main functions in TinyRetriever:
download: Download files concurrently;check_downloads: Validate existing downloaded files against remote file sizes;fetch: Fetch queries concurrently and return responses as text, JSON, or binary;unique_filename: Generate unique filenames based on query parameters.
Installation
Choose your preferred installation method:
Using pip
pip install tiny-retriever
Using micromamba
micromamba install -c conda-forge tiny-retriever
Alternatively, you can use conda or mamba.
Quick Start Guide
Please refer to the documentation for detailed usage instructions and more elaborate examples.
Downloading Files
from pathlib import Path
import tiny_retriever as terry
urls = ["https://example.com/file1.pdf", "https://example.com/file2.pdf"]
paths = [Path("downloads/file1.pdf"), Path("downloads/file2.pdf")]
# or generate unique filenames
paths = (terry.unique_filename(u) for u in urls)
paths = [Path("downloads", p) for p in paths]
# Download files concurrently
terry.download(urls, paths)
Fetching Data
urls = ["https://api.example.com/data1", "https://api.example.com/data2"]
# Get JSON responses
json_responses = terry.fetch(urls, "json")
# Get text responses
text_responses = terry.fetch(urls, "text")
# Get binary responses
binary_responses = terry.fetch(urls, "binary")
Validating Downloads
# Check if previously downloaded files match remote sizes
invalid = terry.check_downloads(urls, paths)
if invalid:
for path, expected_size in invalid.items():
print(f"{path}: local={path.stat().st_size}, expected={expected_size}")
else:
print("All files are valid!")
Generate Unique Filenames
url = "https://api.example.com/data"
params = {"key": "value"}
# Generate unique filename based on URL and parameters
filename = terry.unique_filename(url, params=params, file_extension=".json")
Advanced Usage
Custom Request Parameters
Note that you can also pass a single url and a dictionary of request parameters to the
fetch function. The default network related parameters are conservative and can be
modified as needed.
urls = "https://api.example.com/data"
kwargs = {"headers": {"Authorization": "Bearer token"}}
responses = terry.fetch(
urls,
return_type="json",
request_method="post",
request_kwargs=kwargs,
limit_per_host=2,
timeout=30,
)
Error Handling
from tiny_retriever import fetch, ServiceError
try:
responses = fetch(urls, return_type="json", raise_status=True)
except ServiceError as e:
print(f"Request failed: {e}")
Retry Configuration
All functions retry transient errors (5xx, DNS failures, timeouts) automatically with exponential backoff and jitter. You can control the number of attempts:
# Retry up to 5 times on transient errors
terry.fetch(urls, "json", retries=5)
# Disable retries
terry.download(urls, paths, retries=1)
Configuration
TinyRetriever can be configured through environment variables and function parameters:
MAX_CONCURRENT_CALLS: Maximum number of concurrent requests (default: 10)- Default chunk size for downloads: 1 MB
- Default timeout: 2 minutes for fetch, 10 minutes for download
- Default connections per host: 4
- Default retry attempts: 3
Contributing
We welcome contributions! Please see the contributing section for guidelines and instructions.
License
This project is licensed under the terms of the MIT license.
Metadata
Release files for tiny-retriever 0.3.0
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| tiny_retriever-0.3.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 527.3 kB
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