Just 3 days after publishing this blog post GitHub made a new blog post:
Pull request reviews are a great way to share the weight of building software, and with review requests you can get the exact feedback you need.
To make it easier to find the pull requests that need your attention, you can now filter by review status from your repository pull request index.
Source: Filter pull request reviews and review requests
I have tried this out and it’s great! Like most everything else on GitHub it’s very intuitive and simple to use. I won’t steal their thunder and describe it all here. So go check out the blog post for yourself and read up on the details (screenshots included!).
Continue reading if you’re still interested in incorporating this kind of filtering and labeling into your Gmail account.
I’ve been looking for a way to filter my GitHub Pull Request lists under the condition that a review is requested of me. The online docs didn’t show any filter options for this, so I checked out the @GitHubHelp twitter account. The answer was there on the front page — they don’t support filtering PRs by review-requested-by:me
yet:
@zaghnaboot Adding a filter for reviewers is definitely on our radar, though I don’t have a specific timeline to share. –SJ
— GitHub Support (@GitHubHelp) January 19, 2017
So what is one to do? I’m using Gmail so I began considering what filter options were available to me there. My objectives were to clearly label and highlight:
@mention
‘dInterested in knowing more? Read on after the break for all the setup details.
bitmath is a Python module I wrote which simplifies many facets of interacting with file sizes in various units as python objects. A few weeks ago version 1.3.1 was released with a few small updates.
This new function accepts inputs using non-standard prefix units such as single-letter, or mis-capitalized units. For example, parse_string
will not accept a short unit like ‘100k‘, whereas parse_string_unsafe
will gladly accept it:
Several broken, moved, or redirecting links have been fixed. Wording and examples are more consistent. The documentation also lands correctly when installed via package.
bitmath-1.3.1 is available through several installation channels:
Ubuntu builds have not been prepared yet due to issues I’ve been having with Launchpad and new package versions.
It’s been quite a while since I’ve posted any bitmath updates (bitmath is a Python module I wrote which simplifies many facets of interacting with file sizes in various units as python objects) . In fact, it seems that the last time I wrote about bitmath here was back in 2014 when 1.0.8 was released! So here is an update covering everything post 1.0.8 up to 1.3.0.
bitmath
, you can use to do simple conversions right in your shell [docs]!To help with the Fedora Python3 Porting project, bitmath now comes in two variants in Fedora/EPEL repositories (BZ1282560). The Fedora and EPEL updates are now in the repos. TIP: python2-bitmath
will obsolete the python-bitmath
package. Do a dnf
/yum
‘update
‘ operation just to make sure you catch it.
The PyPi release has already been pushed to stable.
Back in bitmath-1.0.8 we had 150 unit tests. The latest release has almost 200! Go testing! :confetti:
The project I work on uses X509 certificates with custom extensions to manage content access on the Red Hat CDN. The basic idea is that Candlepin issues X509 certificates with an extension saying what content the certificate is good for. Client systems then use that certificate for TLS client authentication when connecting to the CDN. If the content they are requesting (deduced from the request URL) matches the content available to them in the certificate, then access is granted.
This system works well in practice except for one problem: every time content for a particular product changes, the content data in the X509 extension becomes obsolete. We have to revoke the obsolete certificates and issue new ones. The result is an extremely large certificate revocation list (CRL).
For our cryptography needs, Candlepin uses the venerable Legion of the Bouncy Castle Java library. This library anticipates normal CRL usage so when building a CRL object from an existing file, the entire structure is read into memory at once. This approach doesn’t scale well with the numbers of revoked certificates we are dealing with, so we needed to devise a way to stream the CRL. Moreover, the only thing we really care about for our purposes is the revoked certificate’s serial number.
Streaming the CRL means we need to dissect the ASN1 that describes the CRL one piece at a time. RFC 5280 to the rescue! Looking at the description of the ASN1 for a CRL reveals that before the sequence containing the revocation entries, there will be a thisUpdate
and optionally nextUpdate
field of either type UTCTime or GeneralizedTime. We need to descend in the ASN1 until we get to the thisUpdate
field, look for and discard the optional nextUpdate
field and then walk through the revokedCertificates
sequence reading the serial numbers.
That procedure is not exactly a walk in the park, so in the hope that someone else may find it useful, here is the solution I came up with. Keep in mind that the code does not check the signature on the CRL so this code should not be used for any CRL that you do not trust implicitly.
The end results are pretty dramatic. The benchmarking toolkit I’m using shows an improvement in execution time by an order of magnitude (from around 7 seconds to .7 seconds) and memory usage drops by about 30%. You can see the GC statistics in the graph below.
and the benchmarking results are
Benchmark Mode Cnt Score Error Units CRLBenchmark.inMemory avgt 20 7493.602 ± 941.592 ms/op CRLBenchmark.stream avgt 20 669.084 ± 91.382 ms/op
In writing this, A Layman’s Guide to a Subset of ASN.1, BER, and DER was of invaluable assistance to me as was the Wikipedia page on X.690. I recommend reading them both.