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07.06.2019
-jdk-alpine
02
03 RUN apk add --no-cache git openssh-client curl bash # for Jenkins AWT
04 ttf-dejavu
05
06 ARG JENKINS_USER=jenkins
07 ARG UID=1000
08 ARG HTTP_PORT=8080
09 ARG JENKINS
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variable "site_author" {
07 type = "string"
08 default = "Jon Doe"
09 }
10 variable "site_container" {}
11 variable "do_token" {
12 type = "string"
13 }
14 variable "key_path" {}
15 variable "ssh
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17.02.2015
return float(val)
08 except:
09 return None
10
11 with open(sys.argv[1]) as csvfile:
12 collec = MongoClient()["galaxy"]["comets"]
13 for row in csv.reader(csvfile, delimiter="\t"):
14 try
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15.08.2016
,MULTICAST,UP,LOWER_UP> mtu 1500 qdisc pfifo_fast state UP group default qlen 1000
09 inet 192.168.1.123/24 scope global eth1
10 valid_lft forever preferred_lft forever
11
12 $ ip netns exec ns1 ip route add default
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03.08.2023
: "routers",
"value": "192.168.2.254"
}],
"reservations": [{
"hw-address": "00:11:22:33:44:55",
"ip-address": "192.168.2.60",
hostname: "host-2-60"
}, {
"hw-address": "00
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21.03.2017
# ===================
09 #
10 if __name__ == '__main__':
11
12 f = h5py.File("mytestfile.hdf5", "w")
13
14 dset = f.create_dataset("mydataset", (100,), dtype='i')
15
16 dset[...] = np.arange(100)
17
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17.06.2017
array"
09 ! Do some computing
10 DEALLOCATE( a )
11 END PROGRAM TEST1
Allocatable arrays use heap memory and not stack memory, so you can use a lot more memory. For almost any large arrays, I
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25.09.2023
-rf /var/lib/apt/lists/*
09
10 RUN >/etc/machine-id
11 RUN >/var/lib/dbus/machine-id
12
13 EXPOSE 22
14
15 RUN systemctl set-default multi-user.target
16 RUN systemctl mask dev-hugepages.mount sys
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10.04.2015
]
09 }
The next step is to define what action to trigger. The syntax is:
watchman -- trigger /opt/repos 'repos-sync' \
-- /usr/local/sbin/sync.sh /opt/repos
Where 'repos
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03.12.2015
.8, the Django formtools
[5] were part of this project and all was well. However, a decision was then made to outsource this part. Although this doesn't necessarily have to be a problem, Fedora 22 no longer
