b2b48f61b0
* [WIP] Torrent Generation on not found error As asked in #1517, it allows on-the-fly torrent generation. Since it uses magnet links, it needs some time to connect to peers. So it can't be instant generation, we need the user to wait and try after a minute at least. * Replace Fatal by simple error * attempt at fixing travis * del * Add Anacrolyx dependency * Add back difflib * Remove .torrent suffix in the url example * Add some explanations when file missing page shown * Ignore downloads directory * Either use cache (third-party site) or own download directory * Wrong import * If there is an error then it means we aren't generating a torrent file May it be "torrent not found" or "We do not store torrent files" which are the two only existing errors for this page * hash is never empty * TorrentLink may be empty at times So we add a /download/:hash link if it is * Update README.md * Made a mistake here, need to check if false * Update en-us.all.json * Update CHANGELOG.md * Torrent file generation can be triggered by click on button if JS enabled * Update download.go * Update download.go * Use c.JSON instead of text/template * Return to default behavior if we don't generate the file * Don't do the query if returned to default behavior * Add "Could not generate torrent file" error * Fix JS condition & lower delay until button updates * Start download automatically once torrent file is generated * Fix torrentFileExists() constantly returning false if external torrent download URL * torrent-view-data is two tables instead of one This allows the removal of useless things without any problem (e.g Website link), but also a better responsibe design since the previous one separated stats after a certain res looking very wonky * CSS changes to go along * Remove useless <b></b> * Update main.css * In torrentFileExists, check if filestorage path exists instead of looking at the domain in torrent link When checking if the file is stored on another server i used to simply check if the domain name was inside the torrent link, but we can straight up check for filestorage length * Fix JS of on-demand stat fetching * ScrapeAge variable accessible through view.jet.html Contains last scraped time in hours, is at -1 is torrent has never been scraped Stats will get updated if it's either at -1 or above 1460 (2 months old) * Refresh stats if older than two months OR unknown and older than 24h Show last scraped date even if stats are unknown * Add StatsObsolete variable to torrent Indicating if: - They can be shown - They need to be updated * Update scraped data even if Unknown, prevent users from trying to fetch stats every seconds * Torrent file stored locally by default * no need to do all of that if no filestorage * fix filestorage path * Fix torrent download button stuck on "Generating torrent file" at rare times * fix some css rules that didn't work on IE * Fix panic error Seems like this error is a known bug from anacrolyx torrent https://github.com/anacrolix/torrent/issues/83 To prevent it, I'm creating a single client and modifying the socket.go to make it not raise a panic but a simple error log. |
||
|---|---|---|
| .. | ||
| .gitignore | ||
| .travis.yml | ||
| bloom.go | ||
| LICENSE | ||
| Makefile | ||
| README.md | ||
| VERSION | ||
Bloom filters
A Bloom filter is a representation of a set of n items, where the main requirement is to make membership queries; i.e., whether an item is a member of a set.
A Bloom filter has two parameters: m, a maximum size (typically a reasonably large multiple of the cardinality of the set to represent) and k, the number of hashing functions on elements of the set. (The actual hashing functions are important, too, but this is not a parameter for this implementation). A Bloom filter is backed by a BitSet; a key is represented in the filter by setting the bits at each value of the hashing functions (modulo m). Set membership is done by testing whether the bits at each value of the hashing functions (again, modulo m) are set. If so, the item is in the set. If the item is actually in the set, a Bloom filter will never fail (the true positive rate is 1.0); but it is susceptible to false positives. The art is to choose k and m correctly.
In this implementation, the hashing functions used is murmurhash, a non-cryptographic hashing function.
This implementation accepts keys for setting and testing as []byte. Thus, to
add a string item, "Love":
n := uint(1000)
filter := bloom.New(20*n, 5) // load of 20, 5 keys
filter.Add([]byte("Love"))
Similarly, to test if "Love" is in bloom:
if filter.Test([]byte("Love"))
For numeric data, I recommend that you look into the encoding/binary library. But, for example, to add a uint32 to the filter:
i := uint32(100)
n1 := make([]byte, 4)
binary.BigEndian.PutUint32(n1, i)
filter.Add(n1)
Finally, there is a method to estimate the false positive rate of a particular bloom filter for a set of size n:
if filter.EstimateFalsePositiveRate(1000) > 0.001
Given the particular hashing scheme, it's best to be empirical about this. Note that estimating the FP rate will clear the Bloom filter.
Discussion here: Bloom filter
Godoc documentation: https://godoc.org/github.com/willf/bloom
Installation
go get -u github.com/willf/bloom
Contributing
If you wish to contribute to this project, please branch and issue a pull request against master ("GitHub Flow")
This project include a Makefile that allows you to test and build the project with simple commands. To see all available options:
make help
Running all tests
Before committing the code, please check if it passes all tests using (note: this will install some dependencies):
make deps
make qa