| Commit message (Collapse) | Author | Age |
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I wasn't sure if the plugins were downloaded from the Internet or not.
This makes sure that there is no regression in the plugin detection.
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zita-njbridge: init at 0.4.4
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bazel-watcher: init at 0.5.0
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tsung: init at 1.7.0
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Signed-off-by: Tim Dysinger <tim@dysinger.net>
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Signed-off-by: Tim Dysinger <tim@dysinger.net>
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Signed-off-by: Tim Dysinger <tim@dysinger.net>
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https://sourceforge.net/projects/fldigi/
Signed-off-by: Tim Dysinger <tim@dysinger.net>
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gcc-arm-embedded: 6-2017-q2-update -> 7-2018-q2-update
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+ update blackmagic to latest commit which includes gcc7 fixes
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libimagequant: init at 2.12.1
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* Version 4.01.17 works fine for me on NixOS, driving both a Samsung ML-2165w
and a Samsung ML-2510 printer successfully.
* Version 4.00.39 is broken. The build shows errors, but doesn't abort. The
generated binaries don't work, because they are lacking rpaths to their
library dependencies.
* Renamed old default.nix file to 1.00.37.nix. That version wasn't the default
and it feels like a bad idea to mix versioned and unversioned file names in
the same directory.
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Staging next
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Hydra: ?compare=1480463
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This was added when 3.9 was the only one with llvm-dsymutil, but now
almost all of them have it, so the default works fine.
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The ‘mesa-darwin’ stuff was very out of date (2012). This moves darwin
to use the newer mesa. Stuff seems to build okay. Needs more testing
on other stuff though (libraries work). No drivers build but that is
how it should work on macOS.
/cc @cstrahan @Anton-Latukha
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* wmfocus: init at 1.0.2
* wmfocus: fix buildInputs
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crystal: 0.26.1 and introduce 0.25.1
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We also start carrying the previous versions as crystal is under rapid
development.
Instead of pulling the binary builder each time, create a derivation that we can
use to build the various versions.
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hyperscrypt-font: init at 1.1
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It was required for gitlab < 9 which is not supported anymore since some time.
While removinf the V1 the patch was refreshed to cleanly work with version 11.x
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* uftrace: init at 0.9
* Dropped dependency leftovers.
* patchShebang needed for sandboxed build
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Multi-Layered Docker Images
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Using a simple algorithm, convert the references to a path in to a
sorted list of dependent paths based on how often they're referenced
and how deep in the tree they live. Equally-"popular" paths are then
sorted by name.
The existing writeReferencesToFile prints the paths in a simple
ascii-based sorting of the paths.
Sorting the paths by graph improves the chances that the difference
between two builds appear near the end of the list, instead of near
the beginning. This makes a difference for Nix builds which export a
closure for another program to consume, if that program implements its
own level of binary diffing.
For an example, Docker Images. If each store path is a separate layer
then Docker Images can be very efficiently transfered between systems,
and we get very good cache reuse between images built with the same
version of Nixpkgs. However, since Docker only reliably supports a
small number of layers (42) it is important to pick the individual
layers carefully. By storing very popular store paths in the first 40
layers, we improve the chances that the next Docker image will share
many of those layers.*
Given the dependency tree:
A - B - C - D -\
\ \ \ \
\ \ \ \
\ \ - E ---- F
\- G
Nodes which have multiple references are duplicated:
A - B - C - D - F
\ \ \
\ \ \- E - F
\ \
\ \- E - F
\
\- G
Each leaf node is now replaced by a counter defaulted to 1:
A - B - C - D - (F:1)
\ \ \
\ \ \- E - (F:1)
\ \
\ \- E - (F:1)
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\- (G:1)
Then each leaf counter is merged with its parent node, replacing the
parent node with a counter of 1, and each existing counter being
incremented by 1. That is to say `- D - (F:1)` becomes `- (D:1, F:2)`:
A - B - C - (D:1, F:2)
\ \ \
\ \ \- (E:1, F:2)
\ \
\ \- (E:1, F:2)
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\- (G:1)
Then each leaf counter is merged with its parent node again, merging
any counters, then incrementing each:
A - B - (C:1, D:2, E:2, F:5)
\ \
\ \- (E:1, F:2)
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\- (G:1)
And again:
A - (B:1, C:2, D:3, E:4, F:8)
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\- (G:1)
And again:
(A:1, B:2, C:3, D:4, E:5, F:9, G:2)
and then paths have the following "popularity":
A 1
B 2
C 3
D 4
E 5
F 9
G 2
and the popularity contest would result in the paths being printed as:
F
E
D
C
B
G
A
* Note: People who have used a Dockerfile before assume Docker's
Layers are inherently ordered. However, this is not true -- Docker
layers are content-addressable and are not explicitly layered until
they are composed in to an Image.
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csa: init at 0.5.100810
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snipes: init at 20180930
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