Search Results for "key value"

...You have been warned - use at your own risk. Just like in Rails, you can filter the values of sensitive parameters by setting the filter_parameters to an array of (lower case) keys. The value for "password" is filtered by default. Please note that this will only filter the request data with well-formed parameters (in the URL, the headers, and the request data) but not the response. It does not currently filter JSON request data either, just standard "key=value" pairs in the request body.

...The main change is dropping yield from support and using async/await everywhere. Farewell, Python 3.4. You often want to send some sort of data in the URL’s query string. If you were constructing the URL by hand, this data would be given as key/value pairs in the URL after a question mark, e.g. httpbin.org/get?key=val. Requests allows you to provide these arguments as a dict, using the params keyword argument. aiohttp internally performs URL canonicalization before sending request.

...International domains and URLs, keep-alive and connection pooling, sessions with cookie persistence, browser-style SSL verification. Basic/digest authentication, elegant key/value cookies, automatic decompression. Automatic content decoding, unicode response bodies, multipart file uploads, HTTP(S) proxy support. Connection timeouts, streaming downloads, .netrc support, and chunked requests. For more advanced topics, see the Advanced Usage section, the async support section, or the HTTP/2 section. The Developer Interface provides a comprehensive API reference.

Faraday is an HTTP client library abstraction layer that provides a common interface over many adapters (such as Net::HTTP) and embraces the concept of Rack middleware when processing the request/response cycle. You probably don't want to use Faraday directly in your project, as it will lack an actual client library to perform requests. Instead, you probably want to have a look at Awesome Faraday for a list of available adapters. The best starting point is the Faraday Website, with its...

...Let's take a large linear data stream, split it into variable-sized chunks (the size of each being a function of the chunk's contents), and store these chunks in individual, compressed files in some directory, each file named after a strong hash value of its contents, so that the hash value may be used to as key for retrieving the full chunk data. Let's call this directory a "chunk store". At the same time, generate a "chunk index" file that lists these chunk hash values plus their respective chunk sizes in a simple linear array. The chunking algorithm is supposed to create variable, but similarly sized chunks from the data stream.