Hopefully this trip report will be coherent, but I only got 4 hours of sleep after shroomin' last night before I had to wake up for work (where I'm writing this from). I'm glad my job isn't one that requires a whole lot of responsibility
...
So my buddy back home sent a 4 gram bag of dried mushrooms my way. He told me they were very potent, and looking at the bag I could see no reason to doubt him. The bag contained the following:
18 full mushrooms
10 stems
1 big cap
a little bit of shroom shake
In my limited experience, a whole lot of little shrooms is a much better deal than a few big ones. Speaking of my limited experience, I've shroomed about 5 times. I've never eaten much more than 2 dried grams. It is known to all my trip buddies that I am somewhat sensitive to tryptamines, and I have never been 'dissapointed' with any mushroom trip on account of it being too weak.
My lovely girlfriend Psilosara also enjoys mushrooms. I'm pretty sure they're her favorite drug. So we lay out our 18 shrooms + 10 stems + 1 big cap + a little bit of shroom shake and took turns individually choosing the shrooms we would eat, and putting them in our respective piles... then the stems... then I took the shake and gave her the big cap. We broke up our shrooms and mixed them with honey to mask the flavor. It was a little tough swallowing the honey without chewing, but I've gone through much worse to get high (think cactus) so I wasn't complaining. Anyway I guess my overall dose was about 13 small-to-medium sized cubensis shrooms because Psilosara and I both donated a little bit of our shroom-honey mix to our friend T.
So we finished eating them around 9:00pm. By 9:15 I noticed a definite mood lift. By 9:30 I was shroom-buzzed. A couple of my friends were hanging out in my room and I soon found this hard to deal with because 1) Their conversation seemed very chaotic, and 2) They kept cranking up my stereo. I normally find shroom come-ups to be a little difficult, and this was no exception. Fortunately they wanted to smoke some pot so we went outside to toke. Psilosara and I both had one toke, mostly to help deal with the empty, uncomfortable feeling that shrooms tend to give my stomach. We stood around outside for a while while T and W packed bowls, but their conversation and laughter was only making me uncomfortable. I knew what I had to do...
I excused myself and went up to my room to be alone. I sat down on my bed and felt so much better to be in a calm and peaceful environment. I felt the waves of relaxation and release wash over me. Ahhhh, this was just what I needed... to live in a more relaxed state, and at a slower pace. I spent some time melting into my sheets and enjoying the visuals. The entire room had come to life. Nothing was still. The walls were breathing and furniture looked like it was sliding across the floor and coming closer to me. I've tripped enough that these visuals normally wouldn't entertain me so much, except that with the mushrooms I could *feel* them as well...
You see, the whole time I was aware of shifting gravity-like currents moving about the room. These currents pulled my 'center' around the room, which felt like my brain and life-force-energy was being gently (yet intensely) pulled in different directions. Sometimes these currents would swirl around within each other, and I could see how these currents were affecting the room by bending them. It's hard to explain, but what I was feeling and what I was seeing was directly connected. In this way the mushrooms made me feel very connected to the natural world around me. The buzz at this point was very intense, but relaxing at the same time and never *too* intense.
After a while of enjoying the serenity, Psilosara came upstairs to see what's up. She had also been sitting in her room enjoying the peace for a while, and when she came in she recommended I turn off the lights.
What an incredible idea! The darkness felt so much more natural and calming, and I realized I must be enjoying darkness for the same reason I needed to get away from chaotic conversation and noise. I noticed that the dark seemed to increase my visuals... I could see the currents much more clearly now.
Soon T and W came back. T was tripping very happily on the small dose we gave him, and W was baked as hell. They talked about some stuff with Psilosara but I wasn't really interested in much conversation. Psilosara and I both agreed it was time to smoke a spliff. It took me about 15 minutes to motivate myself to get the herb and papers, and another 20 minutes to roll it. Like I said, I was compelled to do everything at a slow and peaceful pace.
So we went outside to smoke. Afterwards Psilosara and I split up with T and W again and went back upstairs to enjoy the quiet and darkness. Now we were both VERY high and feeling great. So we sat up on my bed and talked about how peaceful we felt and how great shrooms are, etc. Then we started having some cool conversation about human evolution:
We thought it would be nice to walk barefoot more often, and also we wondered why people didn't use their feet for more tasks besides just stepping on them. If we did start using our feet more, we'd probably have to be crouched down like monkeys. This would allow us also to be closer to the earth. However, our bodies aren't made for being crouched down any more, and surely we'd all develop serious back problems if we tried doing that. Our species would have to evolve very quickly in order for humans to survive this self-imposed crouching. I thought, 'Wouldn't we just revert back into really smart monkeys?' But Psilosara argued that we could evolve in any number of ways, and we could turn into something totally different, and more connected to the earth. We both loved the idea of this self-imposed genetic revolution.
Psilosara wanted her water bottle so she turned on the light to find it. I closed my eyes to prepare myself for the bright light. When she turned it on I saw the most amazing psychedelic imagery behind my eyes, like dancing fields of diamonds surrounded by flames all in completely unnatural and vibrant colors.  What developed were probably the most beautiful CEVs I've ever seen. Just when I was in doubt if I still thought mushrooms had the best CEVs after a couple of recent LSD trips, I was reminded clearly and obviously that nothing compares to the complexity, beauty, and life of mushrooms CEVs. My mind's eye was overtaken by living and dancing psychedelic landscapes. I kept my eyes closed for a while and enjoyed this thoroughly!
We spent a good deal of time enjoying ourselves in this peaceful environment and having conversation... sometimes deep, sometimes rediculous. We probably spent about 15 minutes watching each other's faces melt and contort and laughing at that.
A little while later we went out for another spliff, then on Psilosara's request we retreated back to her room. We kissed and it took about 5 seconds before we were making out with max intensity. I've been with this girl for almost three years and I'm still amazed at how hot she is... absolutely bangin' body and the most beautiful, loving face in the world.  Needless to say the next hour and a half was amazing. In our embrace she experienced us as a blooming flower, fully wrapped up in this experience until she realized she didn't 'have a stem'.
By 2:00am I was pretty damn tired, and I knew I had to wake up at 6:45am for work, so we fell asleep. I was mostly come-down by that point. It was a relatively short trip, I guess, but it felt much longer because of the slow pace and peacefulness of the evening.
Then I woke up, went to work, and wrote this to keep myself from falling asleep on the job
I don't really think the trip could have gone much better...
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Black to Play 45
b3-w4/5(Cr)
pips Black=164 White=158
(CorrectAnswer= 0/0, ErrorScore= 0)
1. Bar/16* eq:+0.344 54.28% (G:12.92% B:1.65%) 45.72% (G:13.59% B:1.62%) 2. Bar/20 24/20 eq:+0.270 (-0.074) 52.41% (G:11.11% B:0.77%) 47.59% (G:11.24% B:1.13%) 3. Bar/20 9/5* eq:+0.262 (-0.082) 49.36% (G:13.76% B:1.53%) 50.64% (G:18.75% B:2.18%) 4. Bar/20 13/9 eq:+0.189 (-0.155) 48.03% (G:11.44% B:0.59%) 51.97% (G:14.11% B:0.51%) 5. Bar/21 6/1* eq:+0.147 (-0.197) 45.21% (G:12.14% B:0.64%) 54.79% (G:16.14% B:1.01%)


IMRPhenomPv3HM
IMRPhenomPv3HM
IMRPhenomPv3HM
The figures below show the plots for IMRPhenomPv3HM
H1_matched_filter_snr
The figures below show the summary plots for the run
H1_optimal_snr
The figures below show the summary plots for the run
L1_matched_filter_snr
The figures below show the summary plots for the run
L1_optimal_snr
The figures below show the summary plots for the run
V1_matched_filter_snr
The figures below show the summary plots for the run
V1_optimal_snr
The figures below show the summary plots for the run
a_1
The figures below show the summary plots for the run
a_2
The figures below show the summary plots for the run
chi_1_in_plane
The figures below show the summary plots for the run
chi_2_in_plane
The figures below show the summary plots for the run
chi_eff
The figures below show the summary plots for the run
chi_p
The figures below show the summary plots for the run
chirp_mass
The figures below show the summary plots for the run
chirp_mass_source
The figures below show the summary plots for the run
comoving_distance
The figures below show the summary plots for the run
cos_theta_jn
The figures below show the summary plots for the run
cos_tilt_1
The figures below show the summary plots for the run
cos_tilt_2
The figures below show the summary plots for the run
dec
The figures below show the summary plots for the run
geocent_time
The figures below show the summary plots for the run
log_likelihood
The figures below show the summary plots for the run
luminosity_distance
The figures below show the summary plots for the run
mass_1
The figures below show the summary plots for the run
mass_1_source
The figures below show the summary plots for the run
mass_2
The figures below show the summary plots for the run
mass_2_source
The figures below show the summary plots for the run
mass_ratio
The figures below show the summary plots for the run
phase
The figures below show the summary plots for the run
phi_1
The figures below show the summary plots for the run
phi_12
The figures below show the summary plots for the run
phi_2
The figures below show the summary plots for the run
phi_jl
The figures below show the summary plots for the run
psi
The figures below show the summary plots for the run
ra
The figures below show the summary plots for the run
recalib_H1_amplitude_0
The figures below show the summary plots for the run
recalib_H1_amplitude_1
The figures below show the summary plots for the run
recalib_H1_amplitude_2
The figures below show the summary plots for the run
recalib_H1_amplitude_3
The figures below show the summary plots for the run
recalib_H1_amplitude_4
The figures below show the summary plots for the run
recalib_H1_amplitude_5
The figures below show the summary plots for the run
recalib_H1_amplitude_6
The figures below show the summary plots for the run
recalib_H1_amplitude_7
The figures below show the summary plots for the run
recalib_H1_amplitude_8
The figures below show the summary plots for the run
recalib_H1_amplitude_9
The figures below show the summary plots for the run
recalib_H1_frequency_0
The figures below show the summary plots for the run
recalib_H1_frequency_1
The figures below show the summary plots for the run
recalib_H1_frequency_2
The figures below show the summary plots for the run
recalib_H1_frequency_3
The figures below show the summary plots for the run
recalib_H1_frequency_4
The figures below show the summary plots for the run
recalib_H1_frequency_5
The figures below show the summary plots for the run
recalib_H1_frequency_6
The figures below show the summary plots for the run
recalib_H1_frequency_7
The figures below show the summary plots for the run
recalib_H1_frequency_8
The figures below show the summary plots for the run
recalib_H1_frequency_9
The figures below show the summary plots for the run
recalib_H1_phase_0
The figures below show the summary plots for the run
recalib_H1_phase_1
The figures below show the summary plots for the run
recalib_H1_phase_2
The figures below show the summary plots for the run
recalib_H1_phase_3
The figures below show the summary plots for the run
recalib_H1_phase_4
The figures below show the summary plots for the run
recalib_H1_phase_5
The figures below show the summary plots for the run
recalib_H1_phase_6
The figures below show the summary plots for the run
recalib_H1_phase_7
The figures below show the summary plots for the run
recalib_H1_phase_8
The figures below show the summary plots for the run
recalib_H1_phase_9
The figures below show the summary plots for the run
recalib_L1_amplitude_0
The figures below show the summary plots for the run
recalib_L1_amplitude_1
The figures below show the summary plots for the run
recalib_L1_amplitude_2
The figures below show the summary plots for the run
recalib_L1_amplitude_3
The figures below show the summary plots for the run
recalib_L1_amplitude_4
The figures below show the summary plots for the run
recalib_L1_amplitude_5
The figures below show the summary plots for the run
recalib_L1_amplitude_6
The figures below show the summary plots for the run
recalib_L1_amplitude_7
The figures below show the summary plots for the run
recalib_L1_amplitude_8
The figures below show the summary plots for the run
recalib_L1_amplitude_9
The figures below show the summary plots for the run
recalib_L1_frequency_0
The figures below show the summary plots for the run
recalib_L1_frequency_1
The figures below show the summary plots for the run
recalib_L1_frequency_2
The figures below show the summary plots for the run
recalib_L1_frequency_3
The figures below show the summary plots for the run
recalib_L1_frequency_4
The figures below show the summary plots for the run
recalib_L1_frequency_5
The figures below show the summary plots for the run
recalib_L1_frequency_6
The figures below show the summary plots for the run
recalib_L1_frequency_7
The figures below show the summary plots for the run
recalib_L1_frequency_8
The figures below show the summary plots for the run
recalib_L1_frequency_9
The figures below show the summary plots for the run
recalib_L1_phase_0
The figures below show the summary plots for the run
recalib_L1_phase_1
The figures below show the summary plots for the run
recalib_L1_phase_2
The figures below show the summary plots for the run
recalib_L1_phase_3
The figures below show the summary plots for the run
recalib_L1_phase_4
The figures below show the summary plots for the run
recalib_L1_phase_5
The figures below show the summary plots for the run
recalib_L1_phase_6
The figures below show the summary plots for the run
recalib_L1_phase_7
The figures below show the summary plots for the run
recalib_L1_phase_8
The figures below show the summary plots for the run
recalib_L1_phase_9
The figures below show the summary plots for the run
recalib_V1_amplitude_0
The figures below show the summary plots for the run
recalib_V1_amplitude_1
The figures below show the summary plots for the run
recalib_V1_amplitude_2
The figures below show the summary plots for the run
recalib_V1_amplitude_3
The figures below show the summary plots for the run
recalib_V1_amplitude_4
The figures below show the summary plots for the run
recalib_V1_amplitude_5
The figures below show the summary plots for the run
recalib_V1_amplitude_6
The figures below show the summary plots for the run
recalib_V1_amplitude_7
The figures below show the summary plots for the run
recalib_V1_amplitude_8
The figures below show the summary plots for the run
recalib_V1_amplitude_9
The figures below show the summary plots for the run
recalib_V1_frequency_0
The figures below show the summary plots for the run
recalib_V1_frequency_1
The figures below show the summary plots for the run
recalib_V1_frequency_2
The figures below show the summary plots for the run
recalib_V1_frequency_3
The figures below show the summary plots for the run
recalib_V1_frequency_4
The figures below show the summary plots for the run
recalib_V1_frequency_5
The figures below show the summary plots for the run
recalib_V1_frequency_6
The figures below show the summary plots for the run
recalib_V1_frequency_7
The figures below show the summary plots for the run
recalib_V1_frequency_8
The figures below show the summary plots for the run
recalib_V1_frequency_9
The figures below show the summary plots for the run
recalib_V1_phase_0
The figures below show the summary plots for the run
recalib_V1_phase_1
The figures below show the summary plots for the run
recalib_V1_phase_2
The figures below show the summary plots for the run
recalib_V1_phase_3
The figures below show the summary plots for the run
recalib_V1_phase_4
The figures below show the summary plots for the run
recalib_V1_phase_5
The figures below show the summary plots for the run
recalib_V1_phase_6
The figures below show the summary plots for the run
recalib_V1_phase_7
The figures below show the summary plots for the run
recalib_V1_phase_8
The figures below show the summary plots for the run
recalib_V1_phase_9
The figures below show the summary plots for the run
symmetric_mass_ratio
The figures below show the summary plots for the run
theta_jn
The figures below show the summary plots for the run
tilt_1
The figures below show the summary plots for the run
tilt_2
The figures below show the summary plots for the run
time_jitter
The figures below show the summary plots for the run
total_mass
The figures below show the summary plots for the run
total_mass_source
The figures below show the summary plots for the run
H1_matched_filter_abs_snr
The figures below show the summary plots for the run
H1_matched_filter_snr_angle
The figures below show the summary plots for the run
L1_matched_filter_abs_snr
The figures below show the summary plots for the run
L1_matched_filter_snr_angle
The figures below show the summary plots for the run
V1_matched_filter_abs_snr
The figures below show the summary plots for the run
V1_matched_filter_snr_angle
The figures below show the summary plots for the run
inverted_mass_ratio
The figures below show the summary plots for the run
iota
The figures below show the summary plots for the run
spin_1x
The figures below show the summary plots for the run
spin_1y
The figures below show the summary plots for the run
spin_1z
The figures below show the summary plots for the run
spin_2x
The figures below show the summary plots for the run
spin_2y
The figures below show the summary plots for the run
spin_2z
The figures below show the summary plots for the run
final_spin
The figures below show the summary plots for the run
peak_luminosity
The figures below show the summary plots for the run
final_mass
The figures below show the summary plots for the run
redshift
The figures below show the summary plots for the run
final_mass_source
The figures below show the summary plots for the run
radiated_energy
The figures below show the summary plots for the run
network_optimal_snr
The figures below show the summary plots for the run
network_matched_filter_snr
The figures below show the summary plots for the run
cos_iota
The figures below show the summary plots for the run
final_spin_non_evolved
The figures below show the summary plots for the run
peak_luminosity_non_evolved
The figures below show the summary plots for the run
final_mass_non_evolved
The figures below show the summary plots for the run
final_mass_source_non_evolved
The figures below show the summary plots for the run
radiated_energy_non_evolved
The figures below show the summary plots for the run
H1_time
The figures below show the summary plots for the run
L1_time
The figures below show the summary plots for the run
V1_time
The figures below show the summary plots for the run


Contact
Say Hello
Have a cool project? Want to get in contact or just want to say hello? Drop me a line.
Partner portal is a product that connects us to our partners, and our partners to our consumers. Through portal, partners can update their community information, report move ins, and manage their referrals.
Understanding this project takes a little understanding of the senior care industry. We refer customers to senior care providers and are paid a small fee for the referral. You can think of this the same way a real estate agent is paid a comission from landlords for finding them tenants. When partners go in to Portal to mark a referral as moved in, they were getting a negative and confusing experience. Because of this, they weren't reporting move ins. They didn't know how to use the interface and would get frustrated and give up. To fix this, we wanted to do a re-design of the report move in flow.
I was given a set of business goals that I translated to better human experiences. Focusing on these human experiences is like the northern light for my design process. For me, that starts with getting to know the people that will be using our product. I sat with the PM and had casual conversations with some users to just get a feel of how they felt about Partner Portal and how it tied in with their job and what motivates them. In our initial conversations, we focused on the big picture. We let this be the foundation for our product and later dug deeper to add the details.
The first step of the flow is the Referrals page. The problem with this page is that attention is unfocused. There's a lot going on in the page and the user isn't sure what they're supposed to do.
When the click the "report move ins" button they get a pop up modal that asks them to click "report move ins" again. It also doesn't make sense here why there is a "report no move ins" option after clicking "report move ins".
The next step takes them to a page that looks a lot like the first referrals page except with even more going on. The user has no idea what to do here and most drop off at this point. The tutorial at the top was meant to help them, but they didn't understand it and would often click the tutorial more than the actual buttons on the page.
The last step of the flow asks for OPTIONAL rent and care information but the way it's deisnged it seemes like this informaton is necessary in order to report the move in. Most partners wouldn't have that information at the time of reporting and would cancel out of the flow.
So the first step I took to fix this was look at the flow map.
It seemed unnecesary to me to have the second and third step in there.
So I made both actions immediately available to them on the referrals page. They would be able to report referrals as moved in, or report no move ins for the month directly on the referrals page. I also removed all color from the page to better direct attention towards the most important actions that we wanted the user to take. I figured that power users would be able to use the other features on the page without color ques. I also changed the headline of the page to ensure users would know exactly what to do on the page and what the page was for.
Seniors need a lot of hand holding when it comes to technology, but I believe interfaces should be self explanatory instead of having tutorials or wizards. So we got rid of the tutorial and reframed title text to be questions, with action buttons as answers. The flow would walk the user through it step by step, Turbo Tax style.
Optional care and rent cost items would be placed at the end of the flow and made clear that they were optional. It was more clicks, but clearer decisions for the user.
I also created a new reporting section that would always live on the left hand side of the page. This allowed users to see what they and others sharing their account, had already reported for the month and submit that when the month was over. The button would be a different color from the report button to indicate that this was a different action that needed attention.
The button here would be smart. The copy in it would change depending on the state. The copy would also better reflect what the user was thinking at the time to reduce cognitive load and so they would be more confident in clicking.
I used this opportunity to also capture other information about the referral if they didn't move in, for example was the budget not a good fit? Did the care needs not match? This was something we hadn't done before.
Here's the new flow in action:
We had an overall 31% increase in the number of partners reporting their move ins through portal, which meant a whole lot of nagging from our operations team, which in turn meant a better relationship with our partners. Not only did we save a whole lot in operations costs, but we were also able to gather valuable information about the referral if they did not move in, which meant we could send our partners better referrals in the future making both customers and partners happier.
Portal was one of the first big projects I worked on in my time here and it had a lot of eyes on it. Design is much more than just creating flows and pretty visuals, it's also about collaboration and communication. Managing expectations with stakeholders and working with them every step of the way, made them feel personally invested in my designs and when something didn't work the way we expected it to, blame was not passed around. Instead, there was a collective effort to reinvent and improve.
View on BehanceHave a cool project? Want to get in contact or just want to say hello? Drop me a line.


--- layout: post title: 'Mobile isn''t PC' date: 2004-07-28 00:00:00 category: mobile ---
"It's essential for developers such as yourself to realize that the interaction between mobile users and their devices is fundamentally different from that of a PC user. "
Forget what you know: mobile multimedia development tips


Below, you can change your printer's displayed name and IP address/hostname.
The API key can be found on your printer's control screen under Utilities -> Network -> API QR Code. The QA code is also available on your printer's web dashboard under Settings -> API.
You can optionally view your printer's webcam (if connected) via the app as well. This lets you monitor your print job. To do this, the app needs to know the URL of the webcam.
If you know the webcam URL, you can enter it below.
Click the Save button to complete your printer's profile.


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Understanding how an application behaves when deployed is crucial to scaling the application and providing a reliable service. In a Kubernetes cluster, application performance can be examined at many different levels: containers, pods, services, and whole clusters. As part of Kubernetes we want to provide users with detailed resource usage information about their running applications at all these levels. This will give users deep insights into how their applications are performing and where possible application bottlenecks may be found. In comes Heapster, a project meant to provide a base monitoring platform on Kubernetes.
Heapster is a cluster-wide aggregator of monitoring and event data. It currently supports Kubernetes natively and works on all Kubernetes setups. Heapster runs as a pod in the cluster, similar to how any Kubernetes application would run. The Heapster pod discovers all nodes in the cluster and queries usage information from the nodes’ Kubelets, the on-machine Kubernetes agent. The Kubelet itself fetches the data from cAdvisor. Heapster groups the information by pod along with the relevant labels. This data is then pushed to a configurable backend for storage and visualization. Currently supported backends include InfluxDB (with Grafana for visualization) and Google Cloud Monitoring. The overall architecture of the service can be seen below:
Let’s look at some of the other components in more detail.
cAdvisor is an open source container resource usage and performance analysis agent. It is purpose built for containers and supports Docker containers natively. In Kubernetes, cadvisor is integrated into the Kubelet binary. cAdvisor auto-discovers all containers in the machine and collects CPU, memory, filesystem, and network usage statistics. cAdvisor also provides the overall machine usage by analyzing the ‘root’? container on the machine.
On most Kubernetes clusters, cAdvisor exposes a simple UI for on-machine containers on port 4194. Here is a snapshot of part of cAdvisor’s UI that shows the overall machine usage:
The Kubelet acts as a bridge between the Kubernetes master and the nodes. It manages the pods and containers running on a machine. Kubelet translates each pod into its constituent containers and fetches individual container usage statistics from cAdvisor. It then exposes the aggregated pod resource usage statistics via a REST API.
A Grafana setup with InfluxDB is a very popular combination for monitoring in the open source world. InfluxDB exposes an easy to use API to write and fetch time series data. Heapster is setup to use this storage backend by default on most Kubernetes clusters. A detailed setup guide can be found here. InfluxDB and Grafana run in Pods. The pod exposes itself as a Kubernetes service which is how Heapster discovers it.
The Grafana container serves Grafana’s UI which provides an easy to configure dashboard interface. The default dashboard for Kubernetes contains an example dashboard that monitors resource usage of the cluster and the pods inside of it. This dashboard can easily be customized and expanded. Take a look at the storage schema for InfluxDB here.
Here is a video showing how to monitor a Kubernetes cluster using heapster, InfluxDB and Grafana:
Here is a snapshot of the default Kubernetes Grafana dashboard that shows the CPU and Memory usage of the entire cluster, individual pods and containers:
Google Cloud Monitoring is a hosted monitoring service that allows you to visualize and alert on important metrics in your application. Heapster can be setup to automatically push all collected metrics to Google Cloud Monitoring. These metrics are then available in the Cloud Monitoring Console. This storage backend is the easiest to setup and maintain. The monitoring console allows you to easily create and customize dashboards using the exported data.
Here is a video showing how to setup and run a Google Cloud Monitoring backed Heapster:
Here is a snapshot of the a Google Cloud Monitoring dashboard showing cluster-wide resource usage.
Now that you’ve learned a bit about Heapster, feel free to try it out on your own clusters! The Heapster repository is available on GitHub. It contains detailed instructions to setup Heapster and its storage backends. Heapster runs by default on most Kubernetes clusters, so you may already have it! Feedback is always welcome. Please let us know if you run into any issues via the troubleshooting channels.
Authors: Vishnu Kannan and Victor Marmol, Google Software Engineers. This article was originally posted in Kubernetes blog.


Ticket Price of TRAIN : ₨
Room Price of HOTEL : ₨
DEPARTURE DATE :
ARRIVAL DATE :
TOTAL AMOUNT :
₨ 2700 ADDED FOR TAXI RENTAL
Departure Date
TRANSPORT
Arrival Date


Functions | |
| int | bit_count (unsigned long long b) |
| Count the number of bits set to one in an unsigned long long. | |
| int | bit_weighted_count (const unsigned long long v) |
| count the number of discs, counting the corners twice. | |
| int | first_bit (unsigned long long b) |
| Search the first bit set. | |
| int | next_bit (unsigned long long *b) |
| Search the next bit set. | |
| int | last_bit (unsigned long long b) |
| Search the last bit set (same as log2()). | |
| unsigned long long | transpose (unsigned long long b) |
| Transpose the unsigned long long (symetry % A1-H8 diagonal). | |
| unsigned long long | vertical_mirror (unsigned long long b) |
| Mirror the unsigned long long (exchange the lines A - H, B - G, C - F & D - E.). | |
| unsigned long long | horizontal_mirror (unsigned long long b) |
| Mirror the unsigned long long (exchange the line 1 - 8, 2 - 7, 3 - 6 & 4 - 5). | |
| unsigned short | bswap_short (unsigned short s) |
| Swap bytes of a short (little <-> big endian). | |
| unsigned int | bswap_int (unsigned int i) |
| Mirror the unsigned int (little <-> big endian). | |
| int | get_rand_bit (unsigned long long b, Random *r) |
| Get a random set bit index. | |
| void | bitboard_write (const unsigned long long b, FILE *f) |
| Print an unsigned long long as a board. |
Variables | |
| const unsigned long long | X_TO_BIT [] |
| const unsigned long long | NEIGHBOUR [] |
Bitwise operations. Several algorithms manipulating bits are presented here. Quite often, a macro needs to be defined to chose between different flavors of the algorithm.
| int bit_count | ( | unsigned long long | b | ) |
Count the number of bits set to one in an unsigned long long.
This is the classical popcount function. Since 2007, it is part of the instruction set of some modern CPU, (>= barcelona for AMD or >= nelhacem for Intel). Alternatively, a fast SWAR algorithm, adding bits in parallel is provided here. This function is massively used to count discs on the board, the mobility, or the stability.
| b | 64-bit integer to count bits of. |
| int bit_weighted_count | ( | const unsigned long long | v | ) |
count the number of discs, counting the corners twice.
This is a variation of the above algorithm to count the mobility and favour the corners. This function is usefull for move sorting.
| v | 64-bit integer to count bits of. |
| void bitboard_write | ( | const unsigned long long | b, |
| FILE * | f | ||
| ) |
Print an unsigned long long as a board.
Write a 64-bit long number as an Othello board.
| b | The unsigned long long. |
| f | Output stream. |
| unsigned int bswap_int | ( | unsigned int | i | ) |
Mirror the unsigned int (little <-> big endian).
| i | An unsigned int. |
| unsigned short bswap_short | ( | unsigned short | s | ) |
Swap bytes of a short (little <-> big endian).
| s | An unsigned short. |
| int first_bit | ( | unsigned long long | b | ) |
Search the first bit set.
On CPU with AMD64 or EMT64 instructions, a fast asm code is provided. Alternatively, a fast algorithm based on magic numbers is provided.
| b | 64-bit integer. |
| int get_rand_bit | ( | unsigned long long | b, |
| Random * | r | ||
| ) |
Get a random set bit index.
| b | The unsigned long long. |
| r | The pseudo-number generator. |
| unsigned long long horizontal_mirror | ( | unsigned long long | b | ) |
Mirror the unsigned long long (exchange the line 1 - 8, 2 - 7, 3 - 6 & 4 - 5).
| b | An unsigned long long. |
| int last_bit | ( | unsigned long long | b | ) |
Search the last bit set (same as log2()).
On CPU with AMD64 or EMT64 instructions, a fast asm code is provided. Alternatively, a fast algorithm based on magic numbers is provided.
| b | 64-bit integer. |
| int next_bit | ( | unsigned long long * | b | ) |
Search the next bit set.
In practice, clear the first bit set and search the next one.
| b | 64-bit integer. |
| unsigned long long transpose | ( | unsigned long long | b | ) |
Transpose the unsigned long long (symetry % A1-H8 diagonal).
| b | An unsigned long long |
| unsigned long long vertical_mirror | ( | unsigned long long | b | ) |
Mirror the unsigned long long (exchange the lines A - H, B - G, C - F & D - E.).
| b | An unsigned long long |
| const unsigned long long NEIGHBOUR[] |
Conversion array: neighbour bits
| const unsigned long long X_TO_BIT[] |
coordinate to bit table converter


| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final String |
CYCLE_TRIED_TIMES |
"_cycle_tried_times" |
| Modifier and Type | Constant Field | Value |
|---|---|---|
protected static final int |
STAT_INIT |
0 |
protected static final int |
STAT_RUNNING |
1 |
protected static final int |
STAT_STOPPED |
2 |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final String |
FORM |
"application/x-www-form-urlencoded" |
public static final String |
JSON |
"application/json" |
public static final String |
MULTIPART |
"multipart/form-data" |
public static final String |
XML |
"text/xml" |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final String |
URL_LIST |
"http://www\\.alexandermcqueen\\.cn/.*" |
public static final String |
URL_POST |
"http://www\\.alexandermcqueen\\.cn/cn/\\w+/.*\\.html" |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final String |
URL_LIST |
"http://blog\\.sina\\.com\\.cn/s/articlelist_1487828712_0_\\d+\\.html" |
public static final String |
URL_POST |
"http://blog\\.sina\\.com\\.cn/s/blog_\\w+\\.html" |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final int |
INITIAL_CAPACITY |
5 |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final String |
REFERER |
"Referer" |
public static final String |
USER_AGENT |
"User-Agent" |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final String |
CONNECT |
"CONNECT" |
public static final String |
DELETE |
"DELETE" |
public static final String |
GET |
"GET" |
public static final String |
HEAD |
"HEAD" |
public static final String |
POST |
"POST" |
public static final String |
PUT |
"PUT" |
public static final String |
TRACE |
"TRACE" |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final int |
CODE_200 |
200 |
Copyright © 2017. All rights reserved.


Here
For doing so you need to have a Universal image of OS. Download link Will be added shortly for universal images of windows OS.
You can install windows xp using this universal image within 5 minutes. First you have to built universal image. Follow the tutorial to build your own or Download from here (Link will be added shortly).
How to Run Windows 10 From Micro SD Card


--- title: fast.ai ULMFiT with SentencePiece from pretraining to deployment keywords: fastai sidebar: home_sidebar nb_path: "lib_nbs/index.ipynb" ---
Motivation: Why even bother with a non-BERT / Transformer language model? Short answer: you can train a state of the art text classifier with ULMFiT with limited data and affordable hardware. The whole process (preparing the Wikipedia dump, pretrain the language model, fine tune the language model and training the classifier) takes about 5 hours on my workstation with a RTX 3090. The training of the model with FP16 requires less than 8 GB VRAM - so you can train the model on affordable GPUs.
I also saw this paper on the roadmap for fast.ai 2.3 Single Headed Attention RNN: Stop Thinking With Your Head which could improve the performance further.
This Repo is based on:
| Language | (local) | code | Perplexity | Vocab Size | Tokenizer | Download (.tgz files) |
|---|---|---|---|---|---|---|
| German | Deutsch | de | 16.1 | 15k | SP | https://bit.ly/ulmfit-dewiki |
| German | Deutsch | de | 18.5 | 30k | SP | https://bit.ly/ulmfit-dewiki-30k |
| Dutch | Nederlands | nl | 20.5 | 15k | SP | https://bit.ly/ulmfit-nlwiki |
| Russian | Русский | ru | 29.8 | 15k | SP | https://bit.ly/ulmfit-ruwiki |
| Portuguese | Português | pt | 17.3 | 15k | SP | https://bit.ly/ulmfit-ptwiki |
| Vietnamese | Tiếng Việt | vi | 18.8 | 15k | SP | https://bit.ly/ulmfit-viwiki |
| Japanese | 日本語 | ja | 42.6 | 15k | SP | https://bit.ly/ulmfit-jawiki |
| Italian | Italiano | it | 23.7 | 15k | SP | https://bit.ly/ulmfit-itwiki |
| Spanish | Español | es | 21.9 | 15k | SP | https://bit.ly/ulmfit-eswiki |
| Korean | 한국어 | ko | 39.6 | 15k | SP | https://bit.ly/ulmfit-kowiki |
| Thai | ไทย | th | 56.4 | 15k | SP | https://bit.ly/ulmfit-thwiki |
| Hebrew | עברית | he | 46.3 | 15k | SP | https://bit.ly/ulmfit-hewiki |
| Arabic | العربية | ar | 50.0 | 15k | SP | https://bit.ly/ulmfit-arwiki |
| Mongolian | Монгол | mn | see: Github: RobertRitz |
Download with wget
# to preserve the filenames (.tgz!) when downloading with wget use --content-disposition
wget --content-disposition https://bit.ly/ulmfit-dewiki
I've written a small library around this repo, to easily use the pretrained models. You don't have to bother with model, vocab and tokenizer files and paths - the following functions will take care of that.
Tutorial: fastai_ulmfit_pretrained_usage.ipynb
Installation
pip install fastai-ulmfit
Usage
# import
from fastai_ulmfit.pretrained import *
url = 'http://bit.ly/ulmfit-dewiki'
# get tokenizer - if pretrained=True, the SentencePiece Model used for language model pretraining will be used. Default: False
tok = tokenizer_from_pretrained(url, pretrained=False)
# get language model learner for fine-tuning
learn = language_model_from_pretrained(dls, url=url, drop_mult=0.5).to_fp16()
# save fine-tuned model for classification
path = learn.save_lm('tmp/test_lm')
# get text classifier learner from fine-tuned model
learn = text_classifier_from_lm(dls, path=path, metrics=[accuracy]).to_fp16()
`
from fastai_ulmfit.embeddings import SentenceEmbeddingCallback
se = SentenceEmbeddingCallback(pool_mode='concat')
_ = learn.get_preds(cbs=[se])
feat = se.feat
pca = PCA(n_components=2)
pca.fit(feat['vec'])
coords = pca.transform(feat['vec'])
fastai-2.2.7
fastcore-1.3.19
sentencepiece-0.1.95
fastinference-0.0.36
Install packages
pip install -r requirements.txt
The trained language models are compatible with other fastai versions!
The Wikipedia-dump preprocessing requires docker https://docs.docker.com/get-docker/.
.
├── we Docker image for the preperation of the Wikipedia-dump / wikiextractor
└── data
└── {language-code}wiki
├── dump downloaded Wikipedia dump
│ └── extract extracted wikipedia-articles using wikiextractor
├── docs
│ ├── all all extracted Wikipedia articles as single txt-files
│ ├── sampled sampled Wikipedia articles for language model pretraining
│ └── sampled_tok cached tokenized sampled articles - created by fastai / sentencepiece
└── model
├── lm language model trained in step 2
│ ├── fwd forward model
│ ├── bwd backwards model
│ └── spm SentencePiece model
│
├── ft fine tuned model trained in step 3
│ ├── fwd forward model
│ ├── bwd backwards model
│ └── spm SentencePiece model
│
└── class classifier trained in step 4
├── fwd forward learner
└── bwd backwards learner
ULMFiT can be peretrained on relativly small datasets - 100 million tokens are sufficient to get state-of-the art classification results (compared to Transformer models as BERT, which need huge amounts of training data). The easiest way is to pretrain a language model on Wikipedia.
The code for the preperation steps is heavily inspired by / copied from the fast.ai NLP-course: https://github.com/fastai/course-nlp/blob/master/nlputils.py
I built a docker container and script, that automates the following steps: 1) Download Wikipedia XML-dump 2) Extract the text from the dump 3) Sample 160.000 documents with a minimum length of 1800 characters (results in 100m-120m tokens) both parameters can be changed - see the usage below
The whole process will take some time depending on the download speed and your hardware. For the 'dewiki' the preperation took about 45 min.
Run the following commands in the current directory
# build the wikiextractor docker file
docker build -t wikiextractor ./we
# run the docker container for a specific language
# docker run -v $(pwd)/data:/data -it wikiextractor -l <language-code>
# for German language-code de run:
docker run -v $(pwd)/data:/data -it wikiextractor -l de
...
sucessfully prepared dewiki - /data/dewiki/docs/sampled, number of docs 160000/160000 with 110699119 words / tokens!
# To change the number of sampled documents or the minimum length see
usage: preprocess.py [-h] -l LANG [-n NUMBER_DOCS] [-m MIN_DOC_LENGTH] [--mirror MIRROR] [--cleanup]
# To cleanup indermediate files (wikiextractor and all splitted documents) run the following command.
# The Wikipedia-XML-Dump and the sampled docs will not be deleted!
docker run -v $(pwd)/data:/data -it wikiextractor -l <language-code> --cleanup
Notebook: 2_ulmfit_lm_pretraining.ipynb
To get the best result, you can train two seperate language models - a forward and a backward model. You'll have to run the complete notebook twice and set the backwards
parameter accordingly. The models will be saved in seperate folders (fwd / bwd). The same applies to fine-tuning and training of the classifier.
Change the following parameters according to your needs:
lang = 'de' # language of the Wikipedia-Dump
backwards = False # Train backwards model? Default: False for forward model
bs=128 # batch size
vocab_sz = 15000 # vocab size - 15k / 30k work fine with sentence piece
num_workers=18 # num_workers for the dataloaders
step = 'lm' # language model - don't change
model.json
contains the parameters the language model was trained with and the statistics (looses and metrics) of the last epoch
{
"lang": "de",
"step": "lm",
"backwards": false,
"batch_size": 128,
"vocab_size": 15000,
"lr": 0.01,
"num_epochs": 10,
"drop_mult": 0.5,
"stats": {
"train_loss": 2.894167184829712,
"valid_loss": 2.7784812450408936,
"accuracy": 0.46221256256103516,
"perplexity": 16.094558715820312
}
}
history.csv
log of the training metrics (epochs, losses, accuracy, perplexity)
epoch,train_loss,valid_loss,accuracy,perplexity,time
0,3.375441551208496,3.369227886199951,0.3934227228164673,29.05608367919922,23:00
...
9,2.894167184829712,2.7784812450408936,0.46221256256103516,16.094558715820312,22:44
Notebook: 3_ulmfit_lm_finetuning.ipynb
To improve the performance on the downstream-task, the language model should be fine-tuned. We are using a Twitter dataset (GermEval2018/2019), so we fine-tune the LM on unlabled tweets.
To use the notebook on your own dataset, create a .csv
-file containing your (unlabled) data in the text
column.
Files required from the Language Model (previous step):
I am not reusing the SentencePiece-Model from the language model! This could lead to slightly different tokenization but fast.ai (-> language_model_learner()) and the fine-tuning takes care of adding and training unknown tokens! This approch gave slightly better results than reusing the SP-Model from the language model.
Notebook: 4_ulmfit_train_classifier.ipynb
The (fine-tuned) language model now can be used to train a classifier on a (small) labled dataset.
To use the notebook on your own dataset, create a .csv
-file containing your texts in the text
and labels in the label
column.
Files required from the fine-tuned LM (previous step):
Results with an ensemble of forward + backward model (see the inference notebook). Neither the fine-tuning of the LM, nor the training of the classifier was optimized - so there is still room for improvement.
Official results: https://ids-pub.bsz-bw.de/frontdoor/deliver/index/docId/9319/file/Struss_etal._Overview_of_GermEval_task_2_2019.pdf
Classes: OTHER, OFFENSE
Accuracy: 79,68 F1: 75,96 (best BERT 76,95)
Classes: OTHER, PROFANITY, INSULT, ABUSE
Accuracy: 74,56 % F1: 52,54 (best BERT 53.59)
Compared result with: https://arxiv.org/pdf/1912.09582.pdf
Dataset https://github.com/benjaminvdb/DBRD
Accuracy 93,97 % (best BERT 93,0 %)
Copared results with:
Livedoor news corpus
Accuracy 97,1% (best BERT ~98 %)
Compared with: https://github.com/namdori61/BERT-Korean-Classification Dataset: https://github.com/e9t/nsmc Accuracy 89,6 % (best BERT 90,1 %)
.


micrometer
Micrometer provides a simple facade over the instrumentation clients for the most popular monitoring systems, allowing you to instrument your JVM-based application code without vendor lock-in. Think SLF4J, but for metrics.
dependency
<dependency>
<groupId>org.jooby</groupId>
<artifactId>jooby-micrometer</artifactId>
<version>1.6.6</version>
</dependency>
exposes
- One or more
MeterRegistry
usage
{
use(new Micrometer());
// Timer example:
use("*", (req, rsp, chain) -> {
MeterRegistry registry = require(MeterRegistry.class);
Timer timer = registry.timer("http.server.requests");
timer.record(() -> chain.next(req, rsp));
});
}
monitoring systems
It is possible to attach one or more monitoring system. Here are some examples:
{
use(new Micrometer()
.atlas(conf -> {
return new AtlasMeterRegistry(conf);
})
.prometheus(PrometheusMeterRegistry::new)
// etc...
);
}
Jooby creates a MeterRegistryConfig
for every available monitoring system. You control configuration properties via .conf
file:
application.conf:
micrometer {
atlas {
uri: "http://localhost:7101/api/v1/publish"
}
prometheus {
step: "PT1M"
}
}
Prometheus expects to scrape or poll individual app instances for metrics. Jooby provides a ready to use prometheus handler:
import org.jooby.micrometer.PrometheusHandler;
{
use(new Micrometer()
.prometheus(PrometheusMeterRegistry::new)
);
get("/metrics", new PrometheusHandler());
}
NOTE: for each additional registry, you must add the corresponding
micrometer
depedency. For Prometheus:
<dependency>
<groupId>io.micrometer</groupId>
<artifactId>micrometer-registry-prometheus</artifactId>
</dependency>
timed annotation
Jooby supports the io.micrometer.core.annotation.Timed
annotation for MVC routes:
@Path("/controller")
class Controller {
@Timed("people.all")
public People list() {
...
}
}
App:
import org.jooby.micrometer.TimedHandler;
{
use(new Micrometer());
use("*", new TimedHandler());
}
The TimedHandler
record all the controller methods with io.micrometer.core.annotation.Timed
annotation.
advanced options
Advanced options are available via doWith
method:
{
use(new Micrometer()
.doWith(registry -> {
//work with registry
})
);
}
That’s all! Happy coding!!


The main function for taking an object created by format_driors
and fitting a
model using sraplus
fit_sraplus( driors, include_fit = TRUE, seed = 42, plim = 0.05, model_name = "sraplus_tmb", randos = "log_proc_errors", draws = 1e+05, n_keep = 2000, engine = "sir", cores = 4, chains = 1, cleanup = FALSE, max_treedepth = 10, adapt_delta = 0.8, estimate_shape = FALSE, estimate_qslope = FALSE, estimate_q = TRUE, estimate_proc_error = TRUE, estimate_initial_state = TRUE, estimate_k = TRUE, estimate_f = FALSE, learn_rate = 0.001, analytical_q = FALSE, use_baranov = TRUE, include_m = FALSE, ci = 0.89, try_again = FALSE, eps = 1e-06, max_time = Inf, eval.max = 200, iter.max = 150, rel.tol = 1e-10, loopnum = 1, newtonsteps = 1, tune_prior_predictive = TRUE, index_fit_tuner = "sir", refresh = 250, log_bias_correct = TRUE, workers = workers, thin_draws = FALSE, thin_rate = 0.5, ... )
| driors | a list of driors passed from sraplus::format_driors |
|---|---|
| include_fit | logical indicating whether to return the fitted object |
| seed | seed for model runs |
| plim | cutoff (in units of B/K) for hockey stick PT function |
| model_name | the name of the sraplus TMB version to be run, defaults to "sraplus_tmb" |
| randos | random effects when passing to TMB |
| draws | the number of SIR samples to run |
| n_keep | the number of SIR samples to keep |
| engine | one of 'sir','stan', or 'tmb' |
| cores | number of cores for stan fits |
| chains | number of chains for stan fits |
| cleanup | logical indicating whether to remove the compiled TMB model after running |
| max_treedepth | max_treedepth for models fit using stan |
| adapt_delta | adap_delta for models fit using stan |
| estimate_shape | logical indicating whether to estimate the shape parameter of the Pella-Tomlinson model. If FALSE shape parameter is held at the initial value, either default or supplied |
| estimate_qslope | logical indicating whether to estimate a slope parameter for q in CPUE fitting.
If FALSE q_slope is held at the initial value, either default or supplied. if TRUE, |
| estimate_proc_error | logical indicating whether to estimate process errors. If FALSE process errors are not included in the model |
| ci | confidence/credible interval range for summaries |
| ... |
a fitted sraplus object


Ember.JS test prescription
An introduction to the basics of
unit and acceptance testing in Ember.js
Created by
Andrea Dal Ponte
/
@dalpo
THE END
References:
Ember test guide:
guides.emberjs.com/v2.0.0/testing/
Ember conf:
The unofficial official ember testing guide
Slides at:
github.com/dalpo/ember-test-prescription
About me:
andreadalponte.com


Overview
We design and build an off-road vehicle from scratch. For our competitions, we travel around the country to test our designs against over 200 colleges from around the world. The cars are judged based on design report and analysis, cost, acceleration, braking, hill climb, tractor pull, mud bog, rock crawling, and a 4 hour endurance race. Points earned in each of these events are totaled up to determine the final rankings. We are a completely student run organization with faculty advisers at Georgia Tech.
Design
The student members are responsible for the design, analysis, and fabrication of the car. Members get to see their designs advance through design and fabrication and eventually see them in competition with other teams designs. Manufacturing team members are trained in all of the machining skills they will need to fabricate the parts of the car, so no experience with either cars or machining is necessary to join the team.
More Info
Likewise, design team members are trained in all necessary skills and knowledge to complete their task such as CAD, the design process, engineering analysis methods, and knowledge of the particular subsystem they are working in. There are a few standards that all teams must follow. The most important of these are the strict safety standards set by SAE. Also, all teams are given identical Briggs & Straton 10hp motors that they must use. Aside from that, teams have the freedom to design the car however they want.


Provisional starting grid for Brazilian GP: Sainz at the back, Leclerc's penalty
by Nicolás Quarles van UffordThe Brazilian Grand Prix promises to be another good one, and with one grid penalty to take into account already, here is the provisional starting grid for Sunday's race.
Qualifying recap
The slightly surprising pole-sitter after qualifying was Max Verstappen, who set the quickest time on a Saturday for the second time in three weeks (although his time in Mexico got scrapped).
Verstappen had provisional pole after his first run in Q3 already, and the 22-year-old improved on his time in his second run, setting a blisteringly quick 1:07.506. He was one tenth quicker than second-placed Sebastian Vettel, with Lewis Hamilton completing the top three.
Charles Leclerc might have set the fourth-quickest time, but he'll drop 10 places because of a grid penalty for swapping power units for the fourth time.
Another notable performance is the one from Haas, who got both cars in Q3 for the first time in half a season.
Provisional starting grid
| 1. Max Verstappen (RBR) | |
| 2. Sebastian Vettel (FER) | |
| 3. Lewis Hamilton (MER) | |
| 4. Valtteri Bottas (MER) | |
| 5. Alexander Albon (RBR) | |
| 6. Pierre Gasly (TOR) | |
| 7. Romain Grosjean (HAA) | |
| 8. Kimi Raikkonen (ALF) | |
| 9. Kevin Magnussen (HAA) | |
| 10. Lando Norris (MCL) | |
| 11. Daniel Ricciardo (REN) | |
| 12. Antonio Giovinazzi (ALF) | |
| 13. Nico Hulkenberg (REN) | |
| 14. Charles Leclerc (FER)* | |
| 15. Sergio Perez (RAC) | |
| 16. Daniil Kvyat (TOR) | |
| 17. Lance Stroll (RAC) | |
| 18. George Russell (WIL) | |
| 19. Robert Kubica (WIL) | |
| 20. Carlos Sainz Jr. (MCL) |


montoyamoraga's resume
download current resume
archive of old resumes
resume20180830
resume20180423
resume20170513
back to home


An online community for people to learn about the natural world. We aim to conserve wildlife within the UK, therefore any donation is welcome. For more information see the next section! We also offer:
Medium-small to very small birds
Known simply as Robin or Robin redbreast
True finches are small to medium-sized
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About
My name is Josh Rickard and I am a creator and automator of things. I’m an experienced IT & DFIR (Digital Forensics & Incident Response) professional that loves to automate and release open-source tools to help the Information Security community.
Experience
Senior Detection Validation Engineer
Red Canary / Colorado / October 2022 to January 2023
Due to a reduction in force my position was let go. I was part of Red Canary’s Detection Enablement division focusing on proving detection capabilities at scale.
- Assisted with development of a rails web application to streamline testing of attacker techniques and tools.
- Assisted with development of infrastructure using terraform and ansible to build, deploy and execute several attack testing frameworks across multiple operating systems, EDR products and more
Senior Security Solutions Architect
Swimlane / Colorado / Dec 2018 to October 2022
I am part of the Swimlane research team which focuses on innovative security automation, building content and giving back to the security community.
- Automated complex and unique processes used by some of the largest private, public and governmental organizations in the world
- Implemented integrations with many critical security operations products
- Released many open-source tools like pyattck, atomic-operator, soc-faker and more
- Contributed by writing several blogs, presenting on webinars and at conferences
- Ideation to implementation for several internal tools and frameworks, including content migration and generation
Manager, Reporter Solutions Engineering
Cofense / Virginia / Dec 2015 to Nov 2018
Managed, designed and implemented features for all Cofense Reporter products which grew the product from 2 million to 15 million installs globally.
- Designed and managed day-to-day operations of new innovative products utilizing internal and external developers, from conception to market release
- Introduced automation tools for generation, verification and support of Cofense Reporter products, reducing support costs and reducing development time by 300%
- Technical Product Owner for 3 scrum teams (9 engineers & 6 quality assurance engineers)
Security Analyst - Specialist
University of Missouri / May 2012 to Dec 2015
I held several roles but I was a security analyst part of the university’s digital forensics & incident response team. I was also an IT systems analysts and a system administrator during my time at the University. Some focus areas in which I was worked on during my time are:
- Managed Vulnerability Management enterprise wide
- Managed A/V for thousands of endpoints
- Secure Group Policy creation and application across the enterprise
- Operating system deployment automation services
- Tool developer, including some open-source software
- Managed servers across multiple departments
- And more!
Open-Source Projects
You can see a full list of all my open-source projects on my GitHub. Here are a few highlights.
- pyattck - A Python Package to interact with the Mitre ATT&CK Framework
- atomic-operator - A Python package is used to execute Atomic Red Team tests (Atomics) across multiple operating system environments
- soc-faker - A python package for use in generating fake data for SOC and security automation
✍ Blog & Writing
I have written for many websites, but you can find most of my writing on my blog at letsautomate.it. You can find additional links to blogs, articles and more in which I was interviewed for, wrote myself, or was mentioned in here
Recognitions
- Past President & Board Member of the Central Missouri InfraGard chapter (January 2015 - December 2018)
- SC Media (SC Magazine) Reboot Leadership Awards awarded me in the Influencers category in 2019.
- An official maintainer of the Atomic Red Team project (January 2023)
Past Presentations
You can view my past presentations and some recordings here.


Factbox: U.S. vaping-related deaths rise to 47
(Reuters) - The Centers for Disease Control and Prevention (CDC) on Thursday confirmed 47 deaths and 2,290 confirmed and probable illnesses associated with vaping in the United States.
As of Nov. 20, deaths have been reported from 25 states and among ages 17-75 years, according to CDC data.
The CDC has identified vitamin E acetate as a “chemical of concern” among people with the vaping-associated lung injury known as EVALI.
The agency has urged people not to use e-cigarettes with marijuana ingredient tetrahydrocannabinol, saying the high-inducing component may have a role in causing the illness.
Here’s what we know about the vaping-related deaths so far:
** States that have reported deaths, according to the CDC: Alabama, California (4), Connecticut, Delaware, District of Columbia, Florida, Georgia (3), Illinois (5), Indiana (4), Kansas (2), Louisiana, Massachusetts (3), Michigan, Minnesota (3), Mississippi, Missouri (2), Montana, Nebraska, New Jersey, New York (2), Oregon (2), Pennsylvania, Tennessee (2), Texas, Utah, and Virginia.
** 68% of the 1,905 patients on whom data is available, are male, with 77% under 35 years (age data available for 1,906 patients), according to the CDC.
** Data shows all reported patients have a history of e-cigarette use or vaping.
** The CDC said new analysis of fluid samples collected from the lungs of patients with EVALI identified vitamin E acetate — an additive in some THC-containing e-cigarette, or vaping, products.
** Vitamin E acetate was found in all CDC lab tests of fluid samples from 29 patients from 10 states.
** On Nov. 20, a White House spokesman said U.S. President Donald Trump will host a meeting on vaping on Friday with groups, including industry and public health representatives, as his administration considers calls to tighten e-cigarette regulations.
** Patients have reported symptoms such as cough, shortness of breath or chest pain, nausea or diarrhea, according to the CDC.
** Kroger Co, Walgreens Boots Alliance Inc and Walmart Inc have said they would stop selling e-cigarettes at their stores.
** Chinese e-commerce firm Alibaba Group Holding Ltd said it will stop selling e-cigarette components in the United States.


Put existing data or create new X.509 certificate and private key
Hashing algorithm: SHA-1 SHA-256 SHA-384 SHA-512
Signature algorithm: RSASSA-PKCS1-v1_5 RSA-PSS ECDSA
Create
Work with S/MIME Encryption
Content encryption algorithm: AES-CBC AES-GCM
Content encryption algorithm length: 128 256
RSA-OAEP Hashing Algorithm: SHA-1 SHA-256 SHA-384 SHA-512
Encrypt
Decrypt


Shielding Simulation:This java simulation illustrates the
electric field due to a free charge near an isolated conducting spherical shell with zero charge. The free
charge can be inside or outside the shell. We show the charges induced on the surfaces of the shell that
keep the electric field in the conductor zero. We also give the user a choice between showing the total field
(that is the field due to the free charge and the induced charges), or the field due to the free charge alone, or the
charge due to the induced charges alone.
|


Skins
Effect
Easing
Responsive Mode
Show On
Columns, rows, images, icons, maps, forms & more.
With a full grid system built in and individual layout controls for each menu item, it's easy to build gorgeous mega menu layouts.
Catch your customers' attention. Provide visual references to help your customers quickly navigate your site.
Maps, contact forms & more.
SmartMenu lets you add any HTML, forms, Google Maps or widget you like to the menu.


{{#with TemplateVar.get 'state'}}
{{#if isPosting}}
Your comment is being processed... This may take a minute.
{{/if}}
{{#if isPosted}}
Your comment has been processed!
{{/if}}
{{#if isError}}
There was an error processing your comment.
The error was: {{error}}
{{/if}}
{{/with}}


Why Javascript?
So you want to learn JavaScript? Excellent choice. There is much to love about the language and it will be a worthy addition to your development arsenal. Here's why!
- Popular and versatile. It is everywhere and is known as the programming language of the web.
- Every browser supports Javascript on the client side, but you can also use it to run server side code
- Runs fast and on the client side, which puts less strain on the server.
- Can be used within Java and C++
- Known to be relatively easy to learn
- Very large community willing to help
- Plenty of libraries and frameworks - No need to reinvent the wheel. There are plenty of ways designed to make what you are trying to do easier.


Moving by symbols
The ctrl-] key (in normal mode), jumps to the symbol under the caret.
If you have a tags file, Vico will try to
lookup the current word as a tag. The tags
file should be placed in
the windows current directory, ie the top-most directory displayed by
the explorer.
If no tag was found, Vico tries to match the current word with a symbol. If more than one match is found, you are presented with a menu.
If a tag or symbol is found, the current location is pushed on the tag stack, and the caret is jumped to the new location. Press ctrl-t to go back.
You can also use the ⇧⌘T key to search the symbol list.


Elasticsearch Tableau Web Data Connector
Connection Name
Use HTTP Basic Authentication?
Username
Password
Elasticsearch URL
Index Name
Type
Use custom query?
Query
Batch size of per request to Elasticsearch
Total limit on number of rows to sync
Submit
To add more rows of data you will need to:
Select Tableau's data menu
Select your data source name
Then select incremental refresh from extract menu.
Querying data...


Across: 5. In rehearsal, Ivan wants to spit! (6) 8. Getting wagon to hospital takes time in old city (8) 9. Ring copper and get roll for doctor (7) 10. A strip might be an excitin’ fing! (5) 11. Handed over document about organ (9) 13. Second bowler for Major Tom (or Tim!) (8) 14. Terrible dearth of string! (6) 17. Member returns to Unite (3) 19. I said “Yes!” (3) 20. Tune puts worker on edge! (6) 23. Likely to be in favour of British adept (8) 26. Suggest to evil louts: “Split head!” (9) 28. Blooming fiddle! (5) 29. Tears by and turns in (7) 30. Chastises salesmen about to wander (8) 31. Alters figures to get more off! (6) Down: 1. In seconds, wristband makes marks (6) 2. Craftsman gets a bad strain (7) 3. Problem finding £2 with Elizabeth, in coins (9) 4. List of information held by Mrs Larkins (6) 5. Cry, as it’s difficult to find room in church (8) 6. Sick in the French city (5) 7. Gutsy return in Slavic conflict (8) 12. Last journalist to go around the north (3) 15. We heard the woman earlier than the vegetarian (9) 16. Fashionable sound may be rude! (8) 18. Boss gets me back to trick Queen (8) 21. Meet leaders of all-party talks (3) 22. Find innocent sailors have a problem with love (7) 24. Counted stags coming back—about fifty-one (6) 25. Please pass (6) 27. Lawrence is not in lottery around Innsbruck area (5)


Blindness detection and classification system
Eye-Net is a Artificial Intelligence based startup company, working in healthcare. Millions of peoples around the globe are suffering from different kind of disease whose detection sometimes become headache for doctors whereas machines can detect it. Our aim is to help doctors by providing them custom models based upon Artificial intelligence and revolutionalized the health industry of Pakistan. Our services and products will not only be accessible through Pakistan but around the globe as well.
We at a Eyenet till now provide a services:
The price of our products:
You're interested to test our product you can contact us at following


{% extends "places/base.html" %} {% load molly_maps %}{% load molly_utils %}{% load i18n %} {% block title %} {% blocktrans with entity.title as title %}Update {{ title }}{% endblocktrans %} {% endblock %} {% block extrahead %}{{ block.super }} {% endblock %} {% block content %}
{% blocktrans %}Thank you for wanting to improve the data provided by {{ site_name }}. However, before you submit any changes, you should be aware of the following terms.{% endblocktrans %}
{% blocktrans %}Your contribution will be released into the Public Domain, and then submitted to OpenStreetMap by {{ site_name }}.{% endblocktrans %}
{% blocktrans %}Your changes will be checked by a member of the {{ site_name }} team before being uploaded. {{ site_name }} may tidy or normalise the data you provide before they are uploaded using the {{ site_name }} OSM account.{% endblocktrans %}
{% blocktrans %}If you would like to be named as the original author of the changes, please provide your name and tick the attribution box. Your e-mail address will never be submitted to OSM, but may be used by us to clarify any changes you provide.{% endblocktrans %}
{% url places:static-openstreetmap as osm_url %} {% blocktrans %}You may be interested to read further information about OpenStreetMap and other ways in which one may contribute.{% endblocktrans %}


COVID-19 Patients directory for Rourkela
We are going to use different material components to create nice looking angular app.
We will consume our .NET Core application. Basically, we will create complete CRUD client app.
By using material components, we are going to create fully responsive navigation menu, with its side-bar as well.


game
scalePlafield
gridresolution
debugVideo
showGame
showDebug
showGrid
showHelp
showTransform
showMapping
brightness
contrast
saturation
threshold
lasercolor
lasercolor2
topleftx
toplefty
slope topleftx
slope toplefty
toprightx
toprighty
slope toprightx
slope toprighty
bottomleftx
bottomlefty
slope bottomleftx
slope bottomlefty
bottomrightx
bottomrighty
slope bottomrightx
slope bottomrighty
screenshots


Kerala tourisum department
DISTRICTS
Thiruvananthapuram
Kollam
Alappuzha
Pathanamthitta
Kottayam
Idukki
Ernakulam
Thrissur
Palakkad
Malappuram
Kozhikode
Wayanad
Kannur
Kasaragod


--- layout: default date: 13/10/2020 ---
Covers races from 21st August, 2020 — 9th October, 2020.
Last updated: {{ page.date | date: "%A, %B %e" }}
{% include standings.html riders=site.data.2020.series_5.ages teams=site.data.2020.series_5.agesteam %} {% include datetime.html %}


This section applies to disk stores that hold the latest copy of your data for at least one region.
Show Missing Disk Stores
Using gfsh
, the show missing-disk-stores
command lists all disk stores with most recent data that are being waited on by other members.
For replicated regions, this command only lists missing members that are preventing other members from starting up. For partitioned regions, this command also lists any offline data stores, even when other data stores for the region are online, because their offline status may be causing PartitionOfflineExceptions
in cache operations or preventing the system from satisfying redundancy.
Example:
gfsh>show missing-disk-stores
Disk Store ID | Host | Directory
------------------------------------ | --------- | -------------------------------------
60399215-532b-406f-b81f-9b5bd8d1b55a | excalibur | /usr/local/gemfire/deploy/disk_store1
Note:
You need to be connected to JMX Manager in gfsh
to run this command.
Note: The disk store directories listed for missing disk stores may not be the directories you have currently configured for the member. The list is retrieved from the other running members—the ones who are reporting the missing member. They have information from the last time the missing disk store was online. If you move your files and change the member’s configuration, these directory locations will be stale.
Disk stores usually go missing because their member fails to start. The member can fail to start for a number of reasons, including:
- Disk store file corruption. You can check on this by validating the disk store.
- Incorrect distributed system configuration for the member
- Network partitioning
- Drive failure
Revoke Missing Disk Stores
This section applies to disk stores for which both of the following are true:
- Disk stores that have the most recent copy of data for one or more regions or region buckets.
- Disk stores that are unrecoverable, such as when you have deleted them, or their files are corrupted or on a disk that has had a catastrophic failure.
When you cannot bring the latest persisted copy online, use the revoke command to tell the other members to stop waiting for it. Once the store is revoked, the system finds the remaining most recent copy of data and uses that.
Note: Once revoked, a disk store cannot be reintroduced into the system.
Use gfsh show missing-disk-stores to properly identify the disk store you need to revoke. The revoke command takes the disk store ID as input, as listed by that command.
Example:
gfsh>revoke missing-disk-store --id=60399215-532b-406f-b81f-9b5bd8d1b55a
Missing disk store successfully revoked


--- layout: post title: What He Said... date: 2014-11-09 21:20:49.000000000 -06:00 type: post published: true status: publish categories: [feed] tags: dev meta: _edit_last: '8005175' _publicize_pending: '1' geo_public: '0' author: login: dvollrath email<EMAIL_ADDRESS>display_name: dvollrath first_name: '' last_name: '' ---
When I grow up, I want to be Lant Pritchett. He gives an excellent summary of issues that I've tried to get my head around before.
Lant's big question is "Are interventions being evaluated important for development?". I think the answer is no. The interventions - bed nets, micro-credit, deworming - are crucially important for poverty alleviation. But that does necessarily have anything to do with economic development.


Coding Quiz Challenge
Try to answer the following code-related questions within the limit.
Keep in mind that incorrect answers will penalize your score
time
by 10 seconds!
All Done!
Try to answer the following code-related questions within the limit.
Keep in mind that incorrect answers will penalize your score
time
by 10 seconds!


Country
Canada
France
Japan
United Kingdom
United States
Zimbabwe
Address 1
Address 2
City
State
ZIP code


Login Form
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Invalid username and password..
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22 Dec 2014
I'm an Double bass player. Now I remembered that I couldn't decide on which instrument to practice the exercises. He says that they should be on your live own instrument but on the other hand that people with no musical experience can both learn perfect pitch. I'm a python
programming hobbyist and I will try to write all the practices.
Keywords
Relative and perfect pitch are both important.
Relative pitch help us to say that the chord is dominant:9 and perfect pitch is helping us to hear that it is on tone d.
Absolute means non changing. A has always the same sound. It is absolute.
Different levels:
- color awareness
- color discrimination (12 chromatic pitch colors) - quality of sound
Exercise
Go to your own instrument and have a listen, here for yourself that this color sounds do exist.
21 Dec 2014
Perfect pitch sounds so long good until you take your pace to practice it. It's always hard to learn something new. It takes time and energy.
I didn't buy the program. I found it on GrooveShark website. Here is a little of the supercourse.
Keywords
Performer can only preform as well as he can here.
A composer can only compose what he can think up.
And you can only think up what your ear can comprehend, what your ear can grasp.
You can only appreciate and enjoy whatever your own perception and awareness allows you to enjoy.
It is all dependent on your own musical awareness.
Perfect pitch is the color in music (black and white TV example.
Its a delicate perception which opens up the ear in all area of music.
Its something which is already in our ear.
21 Dec 2014
This is a third time that I'll try to develop perfect pitch. My first approach was at the freshmen year at the university at Zagreb. I did David Lucas Burge program and I did develop until then but didn't develop perfect pitch as it was proposed. Now I will try to find time to really practice the program and in detail to document what I am going through. I remember that the practice lessons where really hard and I needed more time than it was suggested in the program.
20 Dec 2014
This is proof of concept blog is working and i'm glad that i did it.
02 Jan 1996
Jekyll is a static site generator, an open-source tool for creating simple yet powerful websites of all shapes and sizes. From the project's readme:
Jekyll is a simple, blog aware, static site generator. It takes a template directory [...] and spits out a complete, static website suitable for serving with Apache or your favorite web server. This is also the engine behind GitHub Pages, which you can use to host your project’s page or blog right here from GitHub.
It's an immensely useful tool and one we encourage you to use here with Hyde.
Find out more by visiting the project on GitHub.


Note: Roam tabs must be refreshed after settings changes.
Navigation mode is initiated by pressing Alt+g, or just g when not editing text. Then just type the visual hints to navigate!
To open links in the sidebar, hold Shift while typing the last letter of the visual navigation key.
The key for toggling the sidebar is a backtick (`).
Roam Navigator's icon was made by Pixel perfect from www.flaticon.com.


Default implementation of the Rand class for integral data types.This default implementation of the Rand class creates random, integral numbers in the range , where max is the maximal value of the given data type T. More...
#include <Random.h>
Public Member Functions | |
Generate functions | |
| T | generate () const |
| Generation of a random value in the range . More... | |
| T | generate (T min, T max) const |
| Generation of a random value in the range . More... | |
Randomize functions | |
| void | randomize (T &value) const |
| Randomization of the given variable with a new value in the range . More... | |
| void | randomize (T &value, T min, T max) const |
| Randomization of the given variable with a new value in the range . More... | |
Default implementation of the Rand class for integral data types.
This default implementation of the Rand class creates random, integral numbers in the range , where max is the maximal value of the given data type T.
|
inline |
Generation of a random value in the range .
This generate function creates a random number in the range , where max is the maximal value of the given data type T.
|
inline |
Generation of a random value in the range .
| min | The smallest possible random value. |
| max | The largest possible random value. |
This generate function creates a random number in the range , where min must be smaller or equal to max. Note that this requirement is only checked in debug mode. In release mode, no check is performed to enforce the validity of the values. Therefore the returned value is undefined if min is larger than max.
|
inline |
Randomization of the given variable with a new value in the range .
| value | The variable to be randomized. |
This function randomizes the given variable to a new value in the range , where max is the maximal value of the given data type T.
|
inline |
Randomization of the given variable with a new value in the range .
| value | The variable to be randomized. |
| min | The smallest possible random value. |
| max | The largest possible random value. |
This function randomizes the given variable to a new value in the range , where min must be smaller or equal to max. Note that this requirement is only checked in debug mode. In release mode, no check is performed to enforce the validity of the values. Therefore the returned value is undefined if min is larger than max.


Trading_GetSellerListRequestType Class Reference
| Inherits from | Trading_AbstractRequestType : NSObject |
| Declared in | Trading_GetSellerListRequestType.h Trading_GetSellerListRequestType.m |
Overview
Returns a list of the items posted by the authenticated user, including
the related item data.
@ingroup EBayAPIInterface
Tasks
-
userID
Specifies the seller whose items will be returned. UserID is an optional
input. If not specified, retrieves listings for the user identified by the
authentication token passed in the request. Note that since user
information is anonymous to everyone except the bidder and the seller
(during an active auction), only sellers looking for information about
their own listings and bidders who know the user IDs of their sellers will
be able to make this API call successfully. See <a href=
“http://developer.ebay.com/DevZone/XML/docs/WebHelp/index.htm?context=eBay_XML_API&topic=AnonymousUserInfo”
propertyWorking with Anonymous User Informationin the eBay Web
Services Guide for more information. -
motorsDealerUsers
Specifies the list of Motors Dealer sellers for which a special set of
property
metrics can be requested. Applies to eBay Motors Pro applications only. -
endTimeFrom
Specifies the earliest (oldest) date to use in a date range filter based on
property
item end time. Specify either an end-time range or a start-time range
filter in every call request. Each of the time ranges must be a value less than
120 days. -
endTimeTo
Specifies the latest (most recent) date to use in a date range filter based
property
on item end time. Must be specified if EndTimeFrom is specified. -
sort
Specifies the order in which returned items are sorted (based on the end
property
dates of the item listings). Valid values:
0 = No sorting
1 = Sort in descending order
2 = Sort in ascending order -
startTimeFrom
Specifies the earliest (oldest) date to use in a date range filter based on
property
item start time. Each of the time ranges must be a value less than
120 days. In all calls, at least one date-range filter must be specified
(i.e., you must specify either the end time range or start time range
in every request). -
startTimeTo
Specifies the latest (most recent) date to use in a date range filter based
property
on item start time. Must be specified if StartTimeFrom is specified. -
pagination
Contains the data controlling the pagination of the returned values.
property
If you set a DetailLevel in this call, you must set pagination values.
The Pagination field contains
the number of items to be returned per page of data (per call),
and the page number to return with the current call. -
granularityLevel
Specifies the subset of item and user fields to return. See GetSellerList
property
in the eBay Web Services guide for a list of the fields that are returned
for each granularity level. For GetSellerList, use DetailLevel or
GranularityLevel in a request, but not both. For GetSellerList, if
GranularityLevel is specified, DetailLevel is ignored. -
skuArray
Container for a set of SKUs.
property
Filters (reduces) the response to only include active listings
that the seller listed with any of the specified SKUs.
If multiple listings include the same SKU, they are
all returned (assuming they also match the other criteria
in the GetSellerList request).
SKUArray can be used to retrieve items listed by the user
identified in AuthToken or in UserID.
Note:
Listings with matching SKUs are returned regardless of their
Item.InventoryTrackingMethod settings.
-
includeWatchCount
Specifies whether to include WatchCount in Item nodes returned.
property
WatchCount is only returned with DetailLevel ReturnAll. -
adminEndedItemsOnly
Specifies whether to return only items that were administratively ended
property
based on a policy violation. -
categoryID
The category ID for the items retrieved.
property
If you specify CategoryID in a GetSellerList call,
the response contains only items in the category you specify. -
includeVariations
If true, the Variations node is returned for all multi-variation
property
listings in the response.
Please note that if the seller includes a large number of
variations in many listings, using this flag may degrade the
call’s performance. Therefore, when you use this flag, you
may need to reduce the total number of items you’re requesting
at once.
For example, you may need to use shorter time ranges in the
EndTime or StartTime filters, fewer entries per page in
Pagination, and/or SKUArray.
Properties
adminEndedItemsOnly
Specifies whether to return only items that were administratively ended
based on a policy violation.
@property (nonatomic, retain) NSNumber *adminEndedItemsOnly
Discussion
Specifies whether to return only items that were administratively ended
based on a policy violation.
type : NSNumber, wrapper for primitive bool
Declared In
Trading_GetSellerListRequestType.h
categoryID
The category ID for the items retrieved.
If you specify CategoryID in a GetSellerList call,
the response contains only items in the category you specify.
@property (nonatomic, retain) NSNumber *categoryID
Discussion
The category ID for the items retrieved.
If you specify CategoryID in a GetSellerList call,
the response contains only items in the category you specify.
type : NSNumber, wrapper for primitive int
Declared In
Trading_GetSellerListRequestType.h
endTimeFrom
Specifies the earliest (oldest) date to use in a date range filter based on
item end time. Specify either an end-time range or a start-time range
filter in every call request. Each of the time ranges must be a value less than
120 days.
@property (nonatomic, retain) NSDate *endTimeFrom
Discussion
Specifies the earliest (oldest) date to use in a date range filter based on
item end time. Specify either an end-time range or a start-time range
filter in every call request. Each of the time ranges must be a value less than
120 days.
type : NSDate, wrapper for primitive date
Declared In
Trading_GetSellerListRequestType.h
endTimeTo
Specifies the latest (most recent) date to use in a date range filter based
on item end time. Must be specified if EndTimeFrom is specified.
@property (nonatomic, retain) NSDate *endTimeTo
Discussion
Specifies the latest (most recent) date to use in a date range filter based
on item end time. Must be specified if EndTimeFrom is specified.
type : NSDate, wrapper for primitive date
Declared In
Trading_GetSellerListRequestType.h
granularityLevel
Specifies the subset of item and user fields to return. See GetSellerList
in the eBay Web Services guide for a list of the fields that are returned
for each granularity level. For GetSellerList, use DetailLevel or
GranularityLevel in a request, but not both. For GetSellerList, if
GranularityLevel is specified, DetailLevel is ignored.
@property (nonatomic, retain) NSString *granularityLevel
Discussion
Specifies the subset of item and user fields to return. See GetSellerList
in the eBay Web Services guide for a list of the fields that are returned
for each granularity level. For GetSellerList, use DetailLevel or
GranularityLevel in a request, but not both. For GetSellerList, if
GranularityLevel is specified, DetailLevel is ignored.
type: string constant in Trading_GranularityLevelCodeType.h
Declared In
Trading_GetSellerListRequestType.h
includeVariations
If true, the Variations node is returned for all multi-variation
listings in the response.
Please note that if the seller includes a large number of
variations in many listings, using this flag may degrade the
call’s performance. Therefore, when you use this flag, you
may need to reduce the total number of items you’re requesting
at once.
For example, you may need to use shorter time ranges in the
EndTime or StartTime filters, fewer entries per page in
Pagination, and/or SKUArray.
@property (nonatomic, retain) NSNumber *includeVariations
Discussion
If true, the Variations node is returned for all multi-variation
listings in the response.
Please note that if the seller includes a large number of
variations in many listings, using this flag may degrade the
call’s performance. Therefore, when you use this flag, you
may need to reduce the total number of items you’re requesting
at once.
For example, you may need to use shorter time ranges in the
EndTime or StartTime filters, fewer entries per page in
Pagination, and/or SKUArray.
type : NSNumber, wrapper for primitive bool
Declared In
Trading_GetSellerListRequestType.h
includeWatchCount
Specifies whether to include WatchCount in Item nodes returned.
WatchCount is only returned with DetailLevel ReturnAll.
@property (nonatomic, retain) NSNumber *includeWatchCount
Discussion
Specifies whether to include WatchCount in Item nodes returned.
WatchCount is only returned with DetailLevel ReturnAll.
type : NSNumber, wrapper for primitive bool
Declared In
Trading_GetSellerListRequestType.h
motorsDealerUsers
Specifies the list of Motors Dealer sellers for which a special set of
metrics can be requested. Applies to eBay Motors Pro applications only.
@property (nonatomic, retain) Trading_UserIDArrayType *motorsDealerUsers
Discussion
Specifies the list of Motors Dealer sellers for which a special set of
metrics can be requested. Applies to eBay Motors Pro applications only.
type : class Trading_UserIDArrayType
Declared In
Trading_GetSellerListRequestType.h
pagination
Contains the data controlling the pagination of the returned values.
If you set a DetailLevel in this call, you must set pagination values.
The Pagination field contains
the number of items to be returned per page of data (per call),
and the page number to return with the current call.
@property (nonatomic, retain) Trading_PaginationType *pagination
Discussion
Contains the data controlling the pagination of the returned values.
If you set a DetailLevel in this call, you must set pagination values.
The Pagination field contains
the number of items to be returned per page of data (per call),
and the page number to return with the current call.
type : class Trading_PaginationType
Declared In
Trading_GetSellerListRequestType.h
skuArray
Container for a set of SKUs.
Filters (reduces) the response to only include active listings
that the seller listed with any of the specified SKUs.
If multiple listings include the same SKU, they are
all returned (assuming they also match the other criteria
in the GetSellerList request).
SKUArray can be used to retrieve items listed by the user
identified in AuthToken or in UserID.
Note:
Listings with matching SKUs are returned regardless of their
Item.InventoryTrackingMethod settings.
@property (nonatomic, retain) Trading_SKUArrayType *skuArray
Discussion
Container for a set of SKUs.
Filters (reduces) the response to only include active listings
that the seller listed with any of the specified SKUs.
If multiple listings include the same SKU, they are
all returned (assuming they also match the other criteria
in the GetSellerList request).
SKUArray can be used to retrieve items listed by the user
identified in AuthToken or in UserID.
Note:
Listings with matching SKUs are returned regardless of their
Item.InventoryTrackingMethod settings.
type : class Trading_SKUArrayType
Declared In
Trading_GetSellerListRequestType.h
sort
Specifies the order in which returned items are sorted (based on the end
dates of the item listings). Valid values:
0 = No sorting
1 = Sort in descending order
2 = Sort in ascending order
@property (nonatomic, retain) NSNumber *sort
Discussion
Specifies the order in which returned items are sorted (based on the end
dates of the item listings). Valid values:
0 = No sorting
1 = Sort in descending order
2 = Sort in ascending order
type : NSNumber, wrapper for primitive int
Declared In
Trading_GetSellerListRequestType.h
startTimeFrom
Specifies the earliest (oldest) date to use in a date range filter based on
item start time. Each of the time ranges must be a value less than
120 days. In all calls, at least one date-range filter must be specified
(i.e., you must specify either the end time range or start time range
in every request).
@property (nonatomic, retain) NSDate *startTimeFrom
Discussion
Specifies the earliest (oldest) date to use in a date range filter based on
item start time. Each of the time ranges must be a value less than
120 days. In all calls, at least one date-range filter must be specified
(i.e., you must specify either the end time range or start time range
in every request).
type : NSDate, wrapper for primitive date
Declared In
Trading_GetSellerListRequestType.h
startTimeTo
Specifies the latest (most recent) date to use in a date range filter based
on item start time. Must be specified if StartTimeFrom is specified.
@property (nonatomic, retain) NSDate *startTimeTo
Discussion
Specifies the latest (most recent) date to use in a date range filter based
on item start time. Must be specified if StartTimeFrom is specified.
type : NSDate, wrapper for primitive date
Declared In
Trading_GetSellerListRequestType.h
userID
Specifies the seller whose items will be returned. UserID is an optional
input. If not specified, retrieves listings for the user identified by the
authentication token passed in the request. Note that since user
information is anonymous to everyone except the bidder and the seller
(during an active auction), only sellers looking for information about
their own listings and bidders who know the user IDs of their sellers will
be able to make this API call successfully. See <a href=
“http://developer.ebay.com/DevZone/XML/docs/WebHelp/index.htm?context=eBay_XML_API&topic=AnonymousUserInfo”
Working with Anonymous User Informationin the eBay Web
Services Guide for more information.
@property (nonatomic, retain) NSString *userID
Discussion
Specifies the seller whose items will be returned. UserID is an optional
input. If not specified, retrieves listings for the user identified by the
authentication token passed in the request. Note that since user
information is anonymous to everyone except the bidder and the seller
(during an active auction), only sellers looking for information about
their own listings and bidders who know the user IDs of their sellers will
be able to make this API call successfully. See <a href=
“http://developer.ebay.com/DevZone/XML/docs/WebHelp/index.htm?context=eBay_XML_API&topic=AnonymousUserInfo”
Working with Anonymous User Informationin the eBay Web
Services Guide for more information.
type : NSString, wrapper for primitive string
Declared In
Trading_GetSellerListRequestType.h


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12. Emergence
Getting Clean via Emergent Design
"Many of us feel that Kent Beck's four rules of Simple Design are of significant help in creating well-designed software. According to Kent, a design is "simple" if it follows these rules:
Runs all the tests
Contains no duplication
Expresses the intent of the programmer
Minimizes the number of classes and methods
The rules are given in order of importance."
Simple Design Rule 1: Runs All the Tests
"A system might have a perfect design on paper, but if there is no simple way to verify that the system actually works as intended, then all the paper effort is questionable."
"Fortunately, making our systems testable pushes us toward a design where our classes are small and single purpose. It's just easier to test classes that conform to the SRP."
"Tight coupling makes it difficult to write tests. So, similarly, the more tests we write, the more we use principles like DIP and tools like dependency injection, interfaces, and abstraction to minimize coupling."
"Writing tests leads to better design."
Simple Design Rules 2-4: Refactoring
"Once we have tests, we are empowered to keep our code and classes clean. [...] The fact that we have these tests eliminates the fear that cleaning up the code will break it!"
"We can increase cohesion, decrease coupling, separate concerns, modularize system concerns, shrink our functions and classes, choose better names, and so on. This is also where we apply the final three rules of simple design: Eliminate duplication, ensure expressiveness, and minimize the number of classes and methods."
No Duplication
"Duplication is the primary enemy of a well-designed system. It represents additional work, additional risk, and additional unnecessary complexity. [...] Lines of code that look exactly alike are, of course, duplication."
"Creating a clean system requires the will to eliminate duplication, even in just a few lines of code."
"The TEMPLATE METHOD pattern is a common technique for removing higher-level duplication."
Expressive
"The majority of the cost of a software project is in long-term maintenance."
"Therefore, code should clearly express the intent of its author. The clearer the author can make the code, the less time others [including you after few weeks or months] will have to spend understanding it."
"You can express yourself by choosing good names."
"You can also express yourself by keeping your functions and classes small."
"You can also express yourself by using standard nomenclature. Design patterns, for example, are largely about communication and expressiveness."
"Well-written unit tests are also expressive. A primary goal of tests is to act as documentation by example."
"But the most important way to be expressive is to try."
"take care of what you've created. Care is a precious resource."
Minimal Classes and Methods
"High class and method counts are sometimes the result of pointless dogmatism."
"Remember, however, that this rule is the lowest priority of the four rules of Simple Design. So, although it's important to keep class and function count low, it's more important to have tests, eliminate duplication, and express yourself."


👯 Meet the Team
Jakub Fiala
CEO
A serial entrepreneur, cryptobaron and an all-round bro, Jakub built up to 7 startups - in elementary school. His ruthless commercial acumen was proven when he managed to monetise the concept of friendship in the mid-00's. Owns a collection of rare opinions about poor people.
Karin Valis
CTO
A mysterious AI prodigy emerging from the dark panelaky estates beyond the Iron Curtain. On her triple-encrypted hard drive, Karin has code which, if executed, would mangle the very fabric of the Western world. A hardened student of the Qabalah, she wrote a faster version of Tensorflow entirely without using the letter "e".