IIDadata
This package provides access to Dadata address suggestions and reverse geocoding APIs.
Basic usage.
try! DadataSuggestions
.shared(
apiKey: "<# Dadata API token #>"
).suggestAddress(
"Пенза"
completion: { r in
switch r {
case .success(let v):
print(v)
case .failure(let e):
print(e)
}
}
)
There are a bunch of additional init options
Ranging from init with explicit API token.
let dadata = DadataSuggestions(apiKey: "<# Dadata API token #>")
Through init with an API token from Info.plist. But may throw if it’s missing.
let dadata = try? DadataSuggestions()
Even to init with check on connectivity. However this init should not be called on main thread as it may take up long time as it makes request to server in a blocking manner. Throws if connection is impossible or request is timed out.
DispatchQueue.global(qos: .background).async {
let dadata = try? DadataSuggestions(apiKey: "<# Dadata API token #>", checkWithTimeout: 15)
}
Regardless of the way you init theris more to do with this library
Basic address suggestions request to only search in FIAS database: less matches, state provided address data only.
dadata?.suggestAddressFromFIAS("Тверская обл, Пеновский р-н, деревня Москва"){ print( try? $0.get().suggestions ) }
Basic address suggestions request takes KLADR or FIAS ID as a query parameter to lookup additional data.
dadata?.suggestByKLADRFIAS("9120b43f-2fae-4838-a144-85e43c2bfb29"){ print( try? $0.get().suggestions ) }
However more elaborate queries could be made by providing constraints and/or setting filtering.
var constraint = AddressQueryConstraint()
constraint.region = "Приморский"
constraint.city = "Владивосток"
constraint.country_iso_code = "RU"
constraint.region_iso_code = "RU-PRI"
dadata?.suggestAddress(
"Gogolya 9",
resultsCount: 5,
language: .en,
constraints: [constraint],
regionPriority: nil,
upperScaleLimit: .street,
lowerScaleLimit: .house,
trimRegionResult: false,
completion: completion
)
Or building AddressSuggestionQuery
manually. Note in this example it is a query made with FIAS ID instead of free-form text.
let q = AddressSuggestionQuery("9120b43f-2fae-4838-a144-85e43c2bfb29", ofType: .findByID)
q.resultsCount = 1
q.language = .en
dadata?.suggestAddress(q){ try? $0.get().suggestions?.forEach{ print($0) } }
Also reverse geocoding is available.
try? dadata?.reverseGeocode(query: "52.2620898,<PHONE_NUMBER>",
delimeter: ",",
resultsCount: 1,
language:"ru",
searchRadius: 100){ r in
let v = try? r.get()
if let s = v?.suggestions, s.count > 0{
print("\(s[0].value!): LAT#\(s[0].data!.geoLat!) @ LON#\(s[0].data!.geoLon!)")
}
}
Documentation
Project documentation is available here.
Example
To run the example project, clone the repo, and run pod install
from the Example directory first.
Installation
IIDadata is available through CocoaPods. To install it, simply add the following line to your Podfile:
pod 'IIDadata'
Or use Swift PM. Add the following line to your Package.swift file in the dependencies section:
.package(url: "https://github.com/illabo/IIDadata.git", from: "0.2.0")
For contributors
The most convenient way to edit the project is to open Example/IIDadata.xcworkspace
in Xcode. It is the workspace of a pod in Cocoapods’ terms. It includes not only the IIDadata pod itself, but also an example target with tests.
Alternatively you may want to edit IIDadata as Swift PM package. To do so just open Package.swift
. Please be aware that the layout in Project Navigator pane would look not the same as if you’d open the xcworkspace
.
To run XCTestCase
you have to create a struct in Tests
directory containint your Dadata API token according to example below. The token
field would be called during the tests.
struct DadataAPIConstants {
static let token = "<# Dadata API token #>"
}
Misc
- Pre- and post-commit hooks to autogenerate docs and create tag from Podspec version label when committing on release branch
- Android library port written in Kotlin
License
IIDadata is available under the MIT license. See the LICENSE file for more info.


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--- layout: post date: 2012-05-06 time: "09:00:00" authors: ["Mike Hansen"] title: An Exercise With Functions and Plotting tags: ["Content"] ---
Let's say you have a text file called workout.csv that contains information about your workouts for the month of March:
# date, kind of workout, distance (miles), time (min) "2012, Mar-01", run, 2, 25 "2012, Mar-03", bike, 10, 55 "2012, Mar-06", bike, 5, 20 "2012, Mar-09", run, 3, 42 "2012, Mar-10", skateboarding, 2, 10 # Broke my leg :( "2012, Mar-11", Wii, 0, 60 "2012, Mar-12", Wii, 0, 60 "2012, Mar-13", Wii, 0, 60 "2012, Mar-14", Wii, 0, 60
It's a common-separated value (CSV) file, but contains comments and blank lines. The first line (a comment) describes the fields in this file, which are (from left to right) the date of your workout, the kind of workout, how many miles you traveled, and how many minutes you spent.
Our goal will be to read this data into Python and plot a graph with the day of the month on the x-axis and the time worked out on the y-axis. Let's get started.
1. Reading
To begin, let's read in the data file with Python's csv module. The code is fairly straightforward:
import csv # Read in all rows from the csv file reader = file("workout.csv", "r") csv_reader = csv.reader(reader) # Print out rows for row in csv_reader: print row
Saving this code to a file called plot_workouts.py and running python plot_workouts.py on the command-line produces the following output:
['# date', ' kind of workout', ' distance (miles)', ' time (min)'] ['2012, Mar-01', ' run', ' 2', ' 25'] ['2012, Mar-03', ' bike', ' 10', ' 55'] ['2012, Mar-06', ' bike', ' 5', ' 20'] ['2012, Mar-09', ' run', ' 3', ' 42'] ['2012, Mar-10', ' skateboarding', ' 2', ' 10'] [] ['# Broke my leg :('] [] ['2012, Mar-11', ' Wii', ' 0', ' 60'] ['2012, Mar-12', ' Wii', ' 0', ' 60'] ['2012, Mar-13', ' Wii', ' 0', ' 60'] ['2012, Mar-14', ' Wii', ' 0', ' 60']
Unfortunately, as we can see, Python's CSV reader doesn't filter out comments or blank lines. We'll need to do it manually. However, this is a common task that we might want to do again and again across programs. Let's write a function named filter_lines that will filter the lines in a file before the CSV reader does its thing.
def filter_lines(reader) lines = [] for line in reader: if len(line.strip()) > 0 or not line.startswith("#"): lines.append(line) return lines
This function will take a file reader and return a list of lines (excluding blank lines and comments). Let's make filter_lines a bit more readable by introducing a second function called keep_line:
def keep_line(line): return len(line.strip()) > 0 or not line.startswith("#"): def filter_lines(reader) lines = [] for line in reader: if keep_line(line): lines.append(line) return lines
This new code is easier to read. We can see that keep_line takes in a line and will return True when the line is not blank and not a comment. Here's the complete code so far:
import csv #------------------------------------------------------------ def keep_line(line): return len(line.strip()) > 0 and not line.startswith("#") #------------------------------------------------------------ def filter_lines(reader): lines = [] for line in reader: if keep_line(line): lines.append(line) return lines #------------------------------------------------------------ reader = file("workout.csv", "r") lines = filter_lines(reader) csv_reader = csv.reader(lines) for row in csv_reader: print row
Running this now produces the following output:
['2012, Mar-01', ' run', ' 2', ' 25'] ['2012, Mar-03', ' bike', ' 10', ' 55'] ['2012, Mar-06', ' bike', ' 5', ' 20'] ['2012, Mar-09', ' run', ' 3', ' 42'] ['2012, Mar-10', ' skateboarding', ' 2', ' 10'] ['2012, Mar-11', ' Wii', ' 0', ' 60'] ['2012, Mar-12', ' Wii', ' 0', ' 60'] ['2012, Mar-13', ' Wii', ' 0', ' 60'] ['2012, Mar-14', ' Wii', ' 0', ' 60']
Hooray! Our blank lines and comments are gone. Before moving on to parsing the data (converting it from text to dates, integers, etc.), let's take a moment to think about how Python is actually using our filter_lines and keep_line functions. For that, we need to understand the call stack
2. The Call Stack
Python tracks which functions are currently being executed with a data structure named the call stack. When Python encounters a function call, like lines = filter_lines(reader), it "pushes" information about where to come back to and then jumps to the function's code. When a return statement is found (or when the function ends), Python "pops" information off call stack to remember where it was.
This can be difficult to visualize. Below is a diagram of our program before and after the call to filter_lines.
Python starts out in the "global" function whose code is just the main body of your program. When we call filter_lines with reader as a parameter, Python copies a reference to workout.csv into a new variable reader, makes a note that it should return to the global function, and jumps to the code for filter_lines. Each time we call keep_line inside filter_lines, Python saves its place on the call stack, copies a reference to line, jumps to keep_line, and jumps back to filter_lines when it's done.
It's important to remember that the reader in the global function and the reader in filter_lines are two different variables. However, they point to the same file in memory, so reading from the file inside of filter_lines changes the file position of reader in the global function.
Python copies things by reference instead of by value, which is very fast (it only needs to point the new variable at the right thing in memory). It can lead to confusion, however, if you don't expect a function to make changes to a parameter (e.g., trying to read data from reader after calling filter_lines produces nothing since we're at the end of the file). If you really need to, making copies is easy. A list named my_list, for example, can be copied simply by slicing the whole thing my_list[:].
With a picture of the call stack in our heads, let's move on to parsing our workout data.
3. Parsing
Our workout data is stored as text. In order to process and plot it, we need to convert each field to its appropriate type (e.g., a date, an integer, etc.). Converting from text to integers or floating point numbers is easy; we can just call the int() or float() function. Our first field is a date, however, which requires a bit more work.
Parsing dates can get hairy very quickly. Luckily, the hard work has already been done for us! Python includes module called datetime that handles parsing for dates and times (go figure ;)).
3.1 The datetime module
The datetime module contains a class also called datetime. This class has a lot of useful functions for date manipulation as well as a function called strptime for parsing (think "string parse time" for strptime).
datetime.strptime takes two parameters: (1) a date string like "2012, Mar-01", and (2) a format string that describes how to parse the date string.
We make a format string by replacing the pieces of our date string with special format codes (which start with a '%'). For example, %Y stands for the "year with century as a decimal number", so we need to replace the year in our date string (2012) with %Y as such: "%Y, Mar-01". Next, we use the %b (abbreviated month name) and %d (day of the month) format codes to replace the remaining pieces ("Mar" and "01", respectively). Our final format string is "%Y, %b-%d". Note that we include the comma, space, and dash.
Let's write a function called parse_workouts that will take in a list of CSV rows and produce a list of workouts (one for each row). Each workout will itself be a list with the parsed date, workout kind, distance, and time. The complete code is below.
import csv from datetime import datetime #------------------------------------------------------------ def keep_line(line): return len(line.strip()) > 0 and not line.startswith("#") #------------------------------------------------------------ def filter_lines(reader): lines = [] for line in reader: if keep_line(line): lines.append(line) return lines #------------------------------------------------------------ def parse_workouts(rows): workouts = [] for row in rows: date = datetime.strptime(row[0], "%Y, %b-%d") kind = row[1].strip() distance = int(row[2]) time = int(row[3]) workouts.append([date, kind, distance, time]) return workouts #------------------------------------------------------------ reader = file("workout.csv", "r") lines = filter_lines(reader) csv_reader = csv.reader(lines) workouts = parse_workouts(csv_reader) for w in workouts: print w
At the top, we import the datetime class from the datetime module using Python's from module import class import form. Our parse_workouts function loops over each CSV row, parses the individual fields, and packages them up as a single workout list. At the end, we print out our workouts.
Running this code produces the following output:
[datetime.datetime(2012, 3, 1, 0, 0), 'run', 2, 25] [datetime.datetime(2012, 3, 3, 0, 0), 'bike', 10, 55] [datetime.datetime(2012, 3, 6, 0, 0), 'bike', 5, 20] [datetime.datetime(2012, 3, 9, 0, 0), 'run', 3, 42] [datetime.datetime(2012, 3, 10, 0, 0), 'skateboarding', 2, 10] [datetime.datetime(2012, 3, 11, 0, 0), 'Wii', 0, 60] [datetime.datetime(2012, 3, 12, 0, 0), 'Wii', 0, 60] [datetime.datetime(2012, 3, 13, 0, 0), 'Wii', 0, 60] [datetime.datetime(2012, 3, 14, 0, 0), 'Wii', 0, 60]
Each workout is a list whose first element is a datetime.datetime object. Python prints datetime objects as datetime.datetime(year, month, day, hour, second). The second element is the kind of workout (a string). The third and fourth elements are the workout distance and time, respectively (both integers).
Everything is looking good, so let's prepare for plotting. We want to plot the day of the month on the x-axis and the time we worked out on the y-axis. We'll write two functions, one to extract the day of the month from each workout, and another to extract the time from each workout.
import csv from datetime import datetime #------------------------------------------------------------ def keep_line(line): return len(line.strip()) > 0 and not line.startswith("#") #------------------------------------------------------------ def filter_lines(reader): lines = [] for line in reader: if keep_line(line): lines.append(line) return lines #------------------------------------------------------------ def parse_workouts(rows): workouts = [] for row in rows: date = datetime.strptime(row[0], "%Y, %b-%d") kind = row[1].strip() distance = int(row[2]) time = int(row[3]) workouts.append([date, kind, distance, time]) return workouts #------------------------------------------------------------ def extract_days(workouts): days = [] for w in workouts: date = w[0] days.append(date.day) return days #------------------------------------------------------------ def extract_times(workouts): times = [] for w in workouts: times.append(w[3]) return times #------------------------------------------------------------ reader = file("workout.csv", "r") lines = filter_lines(reader) csv_reader = csv.reader(lines) workouts = parse_workouts(csv_reader) days = extract_days(workouts) times = extract_times(workouts) print "Days:", days print "Times:", times
In the extract_days function, we loop through each workout and append the day field of each datetime object onto a list. See the datetime documentation for a complete list of fields. extract_times is similar to extract_days, but grabs the fourth element of each workout list (the workout time) instead.
Running the new code produces a list of days and workout times:
Days: [1, 3, 6, 9, 10, 11, 12, 13, 14] Times: [25, 55, 20, 42, 10, 60, 60, 60, 60]
We're now ready to start plotting.
4. Plotting
There are many plotting libraries available for Python. For this tutorial, we'll stick with one of the most popular libraries based on MATLAB: matplotlib
4.1 Installing matplotlib
matplotlib does not come with the standard Python installation. In addition, it depends on another library called numpy; which is also not included. The installing matplotlib page provides detailed instructions for installing matplotlib on Windows, Mac OS X, and Linux. Don't forget to download and install numpy as well.
In order to choose the correct downloads, you need to know which version of Python you're running. At the command-line, run python --version (mine says Python 2.7.2+). The first two numbers (2.7 for me) will give you an idea of which matplotlib file to choose. On Windows, I downloaded the file named "matplotlib-1.1.0.win32-py2.7.exe" because I have Python 2.7 and a 32-bit installation of Python. The numpy downloads are named similarly; I downloaded "numpy-1.6.1-win32-superpack-python2.7.exe".
Once everything is installed, you can check that it's working by running python and typing in the following code:
from matplotlib import pyplot
If no errors are printed, then you should be set.
4.2 Using matplotlib
There are many, many functions in matplotlib. Our program will use the pyplot.plot function, which makes line and scatter plots. This function takes a list of x values, a list of y values, and some options like the line thickness and color. For now, we'll create a function called plot that will create a new figure, plot workout days vs. times, and then save the figure to a file.
import csv from datetime import datetime from matplotlib import pyplot #------------------------------------------------------------ def keep_line(line): return len(line.strip()) > 0 and not line.startswith("#") #------------------------------------------------------------ def filter_lines(reader): lines = [] for line in reader: if keep_line(line): lines.append(line) return lines #------------------------------------------------------------ def parse_workouts(rows): workouts = [] for row in rows: date = datetime.strptime(row[0], "%Y, %b-%d") kind = row[1].strip() distance = int(row[2]) time = int(row[3]) workouts.append([date, kind, distance, time]) return workouts #------------------------------------------------------------ def extract_days(workouts): days = [] for w in workouts: date = w[0] days.append(date.day) return days #------------------------------------------------------------ def extract_times(workouts): times = [] for w in workouts: times.append(w[3]) return times #------------------------------------------------------------ def plot(days, times, filename): fig = pyplot.figure() pyplot.plot(days, times) pyplot.savefig(filename) #------------------------------------------------------------ reader = file("workout.csv", "r") lines = filter_lines(reader) csv_reader = csv.reader(lines) workouts = parse_workouts(csv_reader) days = extract_days(workouts) times = extract_times(workouts) plot(days, times, "workout_times.png")
Running this code will create a new file named workout_times.png that looks like this:
As you can see, matplotlib takes a "no frills" approach by default. We can spruce up our figure by adding a title, axes labels, a grid, and a "tick" on the x-axis for each day (instead of every other day).
def plot(days, times, filename): fig = pyplot.figure() pyplot.title("Times I worked out in March") pyplot.xlabel("Day") pyplot.ylabel("Time (min)") pyplot.xticks(range(1, max(days)+1)) pyplot.grid() pyplot.plot(days, times, color="red", linewidth=2) pyplot.savefig(filename)
A complete description of these pyplot functions is beyond the scope of this tutorial. A future tutorial will explore them in detail. For now, we suggest using the matplotlib gallery to get an idea of what each function does.
With the changes above, workout_times.png is looking a lot nicer:
That's all, folks! The complete code looks like this:
import csv from datetime import datetime from matplotlib import pyplot #------------------------------------------------------------ def keep_line(line): return len(line.strip()) > 0 and not line.startswith("#") #------------------------------------------------------------ def filter_lines(reader): lines = [] for line in reader: if keep_line(line): lines.append(line) return lines #------------------------------------------------------------ def parse_workouts(rows): workouts = [] for row in rows: date = datetime.strptime(row[0], "%Y, %b-%d") kind = row[1].strip() distance = int(row[2]) time = int(row[3]) workouts.append([date, kind, distance, time]) return workouts #------------------------------------------------------------ def extract_days(workouts): days = [] for w in workouts: date = w[0] days.append(date.day) return days #------------------------------------------------------------ def extract_times(workouts): times = [] for w in workouts: times.append(w[3]) return times #------------------------------------------------------------ def plot(days, times, filename): fig = pyplot.figure() pyplot.title("Times I worked out in March") pyplot.xlabel("Day") pyplot.ylabel("Time (min)") pyplot.xticks(range(1, max(days)+1)) pyplot.grid() pyplot.plot(days, times, color="red", linewidth=2) pyplot.savefig(filename) #------------------------------------------------------------ reader = file("workout.csv", "r") lines = filter_lines(reader) csv_reader = csv.reader(lines) workouts = parse_workouts(csv_reader) days = extract_days(workouts) times = extract_times(workouts) plot(days, times, "workout_times.png")


About me, the author.
My name is Roscoe P***l.
I'm currently enrolled at the University of Central Florida as a full time Information Technologies undergraduate student. I'm also enrolled in the university's Secure Computing and Networking minor. I'll be graduating in a year (Fall 2011), and as such, I have to make a few websites for my CIS 4004 Web Based IT class.
I have a few IT classes at the moment - Web Based IT would have to be one of my favorites... writing up pages is halfway between writing code and writing a paper. the hardest thing I find about web development is making up all of the stuff that goes in the content part of the pages. Prototyping the headers is a bit hard, but once you've got it down on paper it's pretty easy to implement.
I'm currently employed at the university mail center, but I am looking for an actual IT job (at least part time). It could also count for a few credits that I need in order to graduate.
I'm currently enrolled at the University of Central Florida as a full time Information Technologies undergraduate student. I'm also enrolled in the university's Secure Computing and Networking minor. I'll be graduating in a year (Fall 2011), and as such, I have to make a few websites for my CIS 4004 Web Based IT class.
I have a few IT classes at the moment - Web Based IT would have to be one of my favorites... writing up pages is halfway between writing code and writing a paper. the hardest thing I find about web development is making up all of the stuff that goes in the content part of the pages. Prototyping the headers is a bit hard, but once you've got it down on paper it's pretty easy to implement.
I'm currently employed at the university mail center, but I am looking for an actual IT job (at least part time). It could also count for a few credits that I need in order to graduate.


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Glitch me wild:


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Some quick example text to build on the card title and make up the bulk of the card's content.
Some quick example text to build on the card title and make up the bulk of the card's content.
Some quick example text to build on the card title and make up the bulk of the card's content.
Some quick example text to build on the card title and make up the bulk of the card's content.
Some quick example text to build on the card title and make up the bulk of the card's content.
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Alternatively, for H1 and H2, an underline-ish style:
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Emphasis, aka italics, with asterisks or underscores.
Strong emphasis, aka bold, with asterisks or underscores.
Combined emphasis with asterisks and underscores.
Strikethrough uses two tildes. Scratch this.
I'm an inline-style link with title
I'm a relative reference to a repository file
You can use numbers for reference-style link definitions
Or leave it empty and use the link text itself.
URLs and URLs in angle brackets will automatically get turned into links.
http://www.example.com or http://www.example.com and sometimes
example.com (but not on Github, for example).
Some text to show that the reference links can follow later.
Here's our logo (hover to see the title text):
Inline-style:
Reference-style:
Inline code
has back-ticks around
it.
var s = "JavaScript syntax highlighting";
alert(s);
s = "Python syntax highlighting"
print s
No language indicated, so no syntax highlighting.
But let's throw in a <b>tag</b>.
Colons can be used to align columns.
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| col 3 is | right-aligned | $1600 |
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There must be at least 3 dashes separating each header cell.
The outer pipes (|) are optional, and you don't need to make the
raw Markdown line up prettily. You can also use inline Markdown.
| Markdown | Less | Pretty |
|---|---|---|
| Still | renders |
nicely |
| 1 | 2 | 3 |
| Test | Test2 | test3 |
|---|
still
Blockquotes are very handy in email to emulate reply text.
This line is part of the same quote.
Quote break.
This is a very long line that will still be quoted properly when it wraps. Oh boy let's keep writing to make sure this is long enough to actually wrap for everyone. Oh, you can put Markdown into a blockquote.
Three or more...
Hyphens
Asterisks
Underscores
Here's a line for us to start with.
This line is separated from the one above by two newlines, so it will be a separate paragraph.
This line is also a separate paragraph, but...
This line is only separated by a single newline, so it's a separate line in the same paragraph.


--- layout: post title: ! 'Handy Hack: Connect Linux to a MAC OS X Tiger (10.4) attached printer' tags: - Linux status: publish type: post published: true meta: _edit_last: '451289' --- Tiger comes with CUPS installed so:
lpq localhost
which will list the name of your CUPS printer queueshttp://<Mac_IP_Address>:631/printers/<cupsQueueName>
, e.g. http://<IP_ADDRESS>:631/printers/DESKJET_640C


I'm a 17 year-old male in the UK with experiences of stimulants, narcotics and psychedelics.
On to my experience...
I measured out approximately 200mg of mephedrone by splitting a 1g packet into 5 equal lumps. The mephedrone was an off-white powder with a strong fishy smell. The 200mg was dissolved into a cup of water and drunk quickly. Despite experience with many other substances, I have no desire to ever insufflate anything, hence the oral dose.
As I had recently come back from work, I grabbed myself a sandwich and crisps whilst waiting for the mephedrone to take affect. After about 20 minutes, I could feel more than anticipation. The chemical was starting to come up.
Bang! The mephedrone hit with surprising force. An overwhelming sense of speed enveloped my body; I could only describe what I could feel as my pupils dilating quickly, close objects becoming larger when focussed on, and distant objects becoming smaller. There was a sense of disconnection from the room. Music playing sounded slightly distant and tinny, albeit much, much faster.
Moving around seemed very, very fast and I felt the need to pace a bit. At one point, I lay down for a couple of seconds as the rush became too intense. I didn't record my heart rate accurately, but estimated it at 150bpm + at this point.
Oddly lacking from this crazy speed was a sense of euphoria. This is where the mephedrone for me became disappointing. As the speedy rush weakened (after only 5 - 10 minutes), I was expecting euphoria to wash over me. No such luck. The speed diminished into a caffeine-like residual stimulation. A side effect present however was strong leg shaking and jaw-clenching.
This residual stimulation lasted for about two hours after the short, 10 minute rush diminished. Despite this, I had no problem sleeping, and awoke early the next morning refreshed.
In conclusion, mephedrone really disappointed me. The initial come-up rush led me on to thinking I had stumbled upon something very special - then it dropped off. Whether this is due to the method of ingestion, the fact that I ate after dosing, or my own brain chemistry is unknown.
It seems that few reports from Erowid and afar have mentioned a lack of euphoria, so it just goes to show that chemicals affect people uniquely. Being a school night, and driving the next day, I didn't intend to redose; this may have brought on the desired euphoria, and I may try this at another point. At no point was I compelled to take more mephedrone, despite its reputation of being moreish.
In the future, I will try accurately measuring 200mg into a gelcap, and try the substance in a more fitting situation - a rave or party. However, based on my first experience, it proved disappointing and not worthwhile considering little is known about harmful effects.
Cheers,
-- Sparky
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.


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Hello, I'm Cristina Maze
I am a senior at The Ohio State University, pursuing a B.A in Public Affairs with a certificate in full-stack coding development from the College of Engineering and a double-minor in political science and economics. My expected graduation date is Fall 2021, after which I will be pursuing a graduate degree in Public Affairs with a focus on nonprofit studies from the John Glenn College. I have a background in data entry through Mac Tools, a subsidiary of Stanley Black and Decker, and management through USPS Freight.
I have experience as a sales and out-of-state event representative, and a passion for jobs that are challenging. In my free time, I am an avid reader of American history and fan of foreign films. I also enjoy playing guitar and hiking.


{% extends "layout.html" %} {% block content %}
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class Minitest::Reporters::JUnitReporter
A reporter for writing JUnit test reports Intended for easy integration with CI servers - tested on JetBrains TeamCity
Inspired by ci_reporter (see github.com/nicksieger/ci_reporter) Also inspired by Marc Seeger's attempt at producing a JUnitReporter (see github.com/rb2k/minitest-reporters/commit/e13d95b5f884453a9c77f62bc5cba3fa1df30ef5) Also inspired by minitest-ci (see github.com/bhenderson/minitest-ci)
Public Class Methods
new(reports_dir = "test/reports", empty = true, options = {})
click to toggle source
Calls superclass method
Minitest::Reporters::BaseReporter.new
# File lib/minitest/reporters/junit_reporter.rb, line 12 def initialize(reports_dir = "test/reports", empty = true, options = {}) super({}) @reports_path = File.absolute_path(reports_dir) @single_file = options[:single_file] if empty puts "Emptying #{@reports_path}" FileUtils.mkdir_p(@reports_path) File.delete(*Dir.glob("#{@reports_path}/TEST-*.xml")) end end
Public Instance Methods
report()
click to toggle source
Calls superclass method
Minitest::Reporters::BaseReporter#report
# File lib/minitest/reporters/junit_reporter.rb, line 24 def report super puts "Writing XML reports to #{@reports_path}" suites = tests.group_by(&:class) if @single_file write_xml_file_for("minitest", tests.group_by(&:class).values.flatten) else suites.each do |suite, tests| write_xml_file_for(suite, tests) end end end
Private Instance Methods
analyze_suite(tests)
click to toggle source
# File lib/minitest/reporters/junit_reporter.rb, line 108 def analyze_suite(tests) result = Hash.new(0) tests.each do |test| result[:"#{result(test)}_count"] += 1 result[:assertion_count] += test.assertions result[:test_count] += 1 result[:time] += test.time end result end
filename_for(suite)
click to toggle source
# File lib/minitest/reporters/junit_reporter.rb, line 119 def filename_for(suite) file_counter = 0 suite_name = suite.to_s[0..240].gsub(/[^a-zA-Z0-9]+/, '-') # restrict max filename length, to be kind to filesystems filename = "TEST-#{suite_name}.xml" while File.exist?(File.join(@reports_path, filename)) # restrict number of tries, to avoid infinite loops file_counter += 1 filename = "TEST-#{suite_name}-#{file_counter}.xml" puts "Too many duplicate files, overwriting earlier report #{filename}" and break if file_counter >= 99 end File.join(@reports_path, filename) end
location(exception)
click to toggle source
# File lib/minitest/reporters/junit_reporter.rb, line 99 def location(exception) last_before_assertion = '' exception.backtrace.reverse_each do |s| break if s =~ /in .(assert|refute|flunk|pass|fail|raise|must|wont)/ last_before_assertion = s end last_before_assertion.sub(/:in .*$/, '') end
message_for(test)
click to toggle source
# File lib/minitest/reporters/junit_reporter.rb, line 83 def message_for(test) suite = test.class name = test.name e = test.failure if test.passed? nil elsif test.skipped? "Skipped:\n#{name}(#{suite}) [#{location(e)}]:\n#{e.message}\n" elsif test.failure "Failure:\n#{name}(#{suite}) [#{location(e)}]:\n#{e.message}\n" elsif test.error? "Error:\n#{name}(#{suite}):\n#{e.message}" end end
write_xml_file_for(suite, tests)
click to toggle source
# File lib/minitest/reporters/junit_reporter.rb, line 42 def write_xml_file_for(suite, tests) suite_result = analyze_suite(tests) xml = Builder::XmlMarkup.new(:indent => 2) xml.instruct! xml.testsuite(:name => suite, :skipped => suite_result[:skip_count], :failures => suite_result[:fail_count], :errors => suite_result[:error_count], :tests => suite_result[:test_count], :assertions => suite_result[:assertion_count], :time => suite_result[:time]) do tests.each do |test| xml.testcase(:name => test.name, :classname => suite, :assertions => test.assertions, :time => test.time) do xml << xml_message_for(test) unless test.passed? end end end File.open(filename_for(suite), "w") { |file| file << xml.target! } end
xml_message_for(test)
click to toggle source
# File lib/minitest/reporters/junit_reporter.rb, line 60 def xml_message_for(test) # This is a trick lifted from ci_reporter xml = Builder::XmlMarkup.new(:indent => 2, :margin => 2) def xml.trunc!(txt) txt.sub(/\n.*/m, '...') end e = test.failure if test.skipped? xml.skipped(:type => test.name) elsif test.error? xml.error(:type => test.name, :message => xml.trunc!(e.message)) do xml.text!(message_for(test)) end elsif test.failure xml.failure(:type => test.name, :message => xml.trunc!(e.message)) do xml.text!(message_for(test)) end end end


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I didn't get a chance to try the insights and techniques this week, but will definitely try the SIY version of the Metta Bhavana practice in stealth mode next time I have a conflict with someone. I've recently moved in with my parents again after living independently for 7 years plus. I have a feeling this will come in very handy with the current situation. I also like the idea of asking people who I've just met or currently know how they want to save the world, so that I can create a positive association for that person everytime I see them.
have scheduled a time slot to complete this with a friend this evening. watch this space!
I found that after the excercise during my 1 minute of resting the mind I was a lot calmer, and i was a lot easier to rest the mind and hold attention then when I did my 2 minute resting the mind before the exercise. I like the traditional practice structure too. I think I will try a few minutes of this practice in the morning, this week.
A Scenario of a conflict... and accounts on each person's point of view where they are both 100% correct and 100% reasonable.


The following pages encapsulate the various functions available in the File and Edit menus from the top menu bar, as well as documented possible errors.


vignettes/sql-translation.Rmd
There are two components to dplyr’s SQL translation system:
translation of vector expressions like x * y + 10
translation of whole verbs like mutate()
or summarise()
To explore them, you’ll need to load both dbplyr and dplyr:
Most filtering, mutating or summarising operations only perform simple mathematical operations. These operations are very similar between R and SQL, so they’re easy to translate. To see what’s happening yourself, you can use translate_sql()
. The basic techniques that underlie the implementation of translate_sql()
are described in “Advanced R”. translate_sql()
is built on top of R’s parsing engine and has been carefully designed to generate correct SQL. It also protects you against SQL injection attacks by correctly escaping the strings and variable names needed by the database that you’re connecting to.
The following examples work through some of the basic differences between R and SQL.
"
and '
mean different things
Many functions have slightly different names
And some functions have different argument orders:
R and SQL have different defaults for integers and reals. In R, 1 is a real, and 1L is an integer. In SQL, 1 is an integer, and 1.0 is a real
If statements are translated into a case statement:
dplyr knows how to convert the following R functions to SQL:
+
, -
, *
, /
, %%
, ^
abs
, acos
, acosh
, asin
, asinh
, atan
, atan2
, atanh
, ceiling
, cos
, cosh
, cot
, coth
, exp
, floor
, log
, log10
, round
, sign
, sin
, sinh
, sqrt
, tan
, tanh
<
, <=
, !=
, >=
, >
, ==
, %in%
&
, &&
, |
, ||
, !
, xor
mean
, sum
, min
, max
, sd
, var
tolower
, toupper
, trimws
, nchar
, substr
as.numeric
, as.integer
, as.character
Perfect translation is not possible because databases don’t have all the functions that R does. The goal of dplyr is to provide a semantic rather than a literal translation: what you mean rather than what is done. In fact, even for functions that exist both in databases and R, you shouldn’t expect results to be identical; database programmers have different priorities than R core programmers. For example, in R in order to get a higher level of numerical accuracy, mean()
loops through the data twice. R’s mean()
also provides a trim
option for computing trimmed means; this is something that databases do not provide. Databases automatically drop NULLs (their equivalent of missing values) whereas in R you have to ask nicely. This means the essence of simple calls like mean(x)
will be translated accurately, but more complicated calls like mean(x, trim = 0.5, na.rm = TRUE)
will raise an error:
translate_sql(mean(x, na.rm = TRUE))
#> <SQL> avg("x") OVER ()
translate_sql(mean(x, trim = 0.1))
#> Error in mean(x, trim = 0.1): unused argument (trim = 0.1)
translate_sql()
takes an optional con
parameter. If not supplied, this causes dplyr to generate (approximately) SQL-92 compliant SQL. If supplied, dplyr uses sql_translate_env()
to look up a custom environment which makes it possible for different databases to generate slightly different SQL: see vignette("new-backend")
for more details.
Any function that dplyr doesn’t know how to convert is left as is. This means that database functions that are not covered by dplyr can be used directly via translate_sql()
. Here a couple of examples that will work with SQLite:
Things get a little trickier with window functions, because SQL’s window functions are considerably more expressive than the specific variants provided by base R or dplyr. They have the form [expression] OVER ([partition clause] [order clause] [frame_clause])
:
The expression is a combination of variable names and window functions. Support for window functions varies from database to database, but most support the ranking functions, lead
, lag
, nth
, first
, last
, count
, min
, max
, sum
, avg
and stddev
.
The partition clause specifies how the window function is broken down over groups. It plays an analogous role to GROUP BY
for aggregate functions, and group_by()
in dplyr. It is possible for different window functions to be partitioned into different groups, but not all databases support it, and neither does dplyr.
The order clause controls the ordering (when it makes a difference). This is important for the ranking functions since it specifies which variables to rank by, but it’s also needed for cumulative functions and lead. Whenever you’re thinking about before and after in SQL, you must always tell it which variable defines the order. If the order clause is missing when needed, some databases fail with an error message while others return non-deterministic results.
The frame clause defines which rows, or frame, that are passed to the window function, describing which rows (relative to the current row) should be included. The frame clause provides two offsets which determine the start and end of frame. There are three special values: -Inf means to include all preceeding rows (in SQL, “unbounded preceding”), 0 means the current row (“current row”), and Inf means all following rows (“unbounded following)”. The complete set of options is comprehensive, but fairly confusing, and is summarised visually below.
Of the many possible specifications, there are only three that commonly used. They select between aggregation variants:
Recycled: BETWEEN UNBOUND PRECEEDING AND UNBOUND FOLLOWING
Cumulative: BETWEEN UNBOUND PRECEEDING AND CURRENT ROW
Rolling: BETWEEN 2 PRECEEDING AND 2 FOLLOWING
dplyr generates the frame clause based on whether your using a recycled aggregate or a cumulative aggregate.
To see how individual window functions are translated to SQL, we can again use translate_sql()
:
translate_sql(mean(G))
#> Warning: Missing values are always removed in SQL.
#> Use `avg(x, na.rm = TRUE)` to silence this warning
#> <SQL> avg("G") OVER ()
translate_sql(rank(G))
#> <SQL> rank() OVER (ORDER BY "G")
translate_sql(ntile(G, 2))
#> <SQL> NTILE(2) OVER (ORDER BY "G")
translate_sql(lag(G))
#> <SQL> LAG("G", 1, NULL) OVER ()
If the tbl has been grouped or arranged previously in the pipeline, then dplyr will use that information to set the “partition by” and “order by” clauses. For interactive exploration, you can achieve the same effect by setting the vars_group
and vars_order
arguments to translate_sql()
translate_sql(cummean(G), vars_order = "year")
#> <SQL> mean("G") OVER (ORDER BY "year" ROWS UNBOUNDED PRECEDING)
translate_sql(rank(), vars_group = "ID")
#> <SQL> rank() OVER (PARTITION BY "ID")
There are some challenges when translating window functions between R and SQL, because dplyr tries to keep the window functions as similar as possible to both the existing R analogues and to the SQL functions. This means that there are three ways to control the order clause depending on which window function you’re using:
For ranking functions, the ordering variable is the first argument: rank(x)
, ntile(y, 2)
. If omitted or NULL
, will use the default ordering associated with the tbl (as set by arrange()
).
Accumulating aggregates only take a single argument (the vector to aggregate). To control ordering, use order_by()
.
Aggregates implemented in dplyr (lead
, lag
, nth_value
, first_value
, last_value
) have an order_by
argument. Supply it to override the default ordering.
The three options are illustrated in the snippet below:
Currently there is no way to order by multiple variables, except by setting the default ordering with arrange()
. This will be added in a future release.
All dplyr verbs generate a SELECT
statement. To demonstrate we’ll make a temporary database with a couple of tables
con <- DBI::dbConnect(RSQLite::SQLite(), ":memory:")
flights <- copy_to(con, nycflights13::flights)
airports <- copy_to(con, nycflights13::airports)
select()
and mutate()
modify the SELECT
clause:
flights %>%
select(contains("delay")) %>%
show_query()
#> <SQL>
#> SELECT `dep_delay`, `arr_delay`
#> FROM `nycflights13::flights`
flights %>%
select(distance, air_time) %>%
mutate(speed = distance / (air_time / 60)) %>%
show_query()
#> <SQL>
#> SELECT `distance`, `air_time`, `distance` / (`air_time` / 60.0) AS `speed`
#> FROM (SELECT `distance`, `air_time`
#> FROM `nycflights13::flights`)
(As you can see here, the generated SQL isn’t always as minimal as you might generate by hand.)
filter()
generates a WHERE
clause:
arrange()
generates an ORDER BY
clause:
summarise()
and group_by()
work together to generate a GROUP BY
clause:
flights %>%
group_by(month, day) %>%
summarise(delay = mean(dep_delay)) %>%
show_query()
#> Warning: Missing values are always removed in SQL.
#> Use `AVG(x, na.rm = TRUE)` to silence this warning
#> <SQL>
#> SELECT `month`, `day`, AVG(`dep_delay`) AS `delay`
#> FROM `nycflights13::flights`
#> GROUP BY `month`, `day`
| R | SQL |
|---|---|
inner_join() |
SELECT * FROM x JOIN y ON x.a = y.a |
left_join() |
SELECT * FROM x LEFT JOIN y ON x.a = y.a |
right_join() |
SELECT * FROM x RIGHT JOIN y ON x.a = y.a |
full_join() |
SELECT * FROM x FULL JOIN y ON x.a = y.a |
semi_join() |
SELECT * FROM x WHERE EXISTS (SELECT 1 FROM y WHERE x.a = y.a) |
anti_join() |
SELECT * FROM x WHERE NOT EXISTS (SELECT 1 FROM y WHERE x.a = y.a) |
intersect(x, y) |
SELECT * FROM x INTERSECT SELECT * FROM y |
union(x, y) |
SELECT * FROM x UNION SELECT * FROM y |
setdiff(x, y) |
SELECT * FROM x EXCEPT SELECT * FROM y |
x
and y
don’t have to be tables in the same database. If you specify copy = TRUE
, dplyr will copy the y
table into the same location as the x
variable. This is useful if you’ve downloaded a summarised dataset and determined a subset of interest that you now want the full data for. You can use semi_join(x, y, copy = TRUE)
to upload the indices of interest to a temporary table in the same database as x
, and then perform a efficient semi join in the database.
If you’re working with large data, it maybe also be helpful to set auto_index = TRUE
. That will automatically add an index on the join variables to the temporary table.
The verb level SQL translation is implemented on top of tbl_lazy
, which basically tracks the operations you perform in a pipeline (see lazy-ops.R
). Turning that into a SQL query takes place in three steps:
sql_build()
recurses over the lazy op data structure building up query objects (select_query()
, join_query()
, set_op_query()
etc) that represent the different subtypes of SELECT
queries that we might generate.
sql_optimise()
takes a pass over these SQL objects, looking for potential optimisations. Currently this only involves removing subqueries where possible.
sql_render()
calls an SQL generation function (sql_select()
, sql_join()
, sql_subquery()
, sql_semijoin()
etc) to produce the actual SQL. Each of these functions is a generic, taking the connection as an argument, so that the details can be customised for different databases.


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{% extends "govuk_template.html" %} {% block head %} {% endblock %} {% block cookie_message %}
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Extracting Maximum from Heap
The following heap is constructed with the specified set of elements.
The size of this heap: 12
The maximum element of the above heap is 15. So, the HEAP-EXTRACT-MAX operation extracts and returns the element 15 from the heap. Then the MAX-HEAPIFY operation rearranges the elements to satisfy the max-heap property.
Steps Involved:
• Extract the maximum element 15 from the root
• Move the value 1, which is at the last node, to the root
• Swap 1 and 13
• Swap 1 and 12
• Swap 1 and 6
• Remove the last node
Therefore the new heap is as below.
Now,
The size of this heap: 11
The extracting elements (in extracting order): 15
The maximum element of the above heap is 13. So, the HEAP-EXTRACT-MAX operation extracts and returns the element 13 from the heap. Then the MAX-HEAPIFY operation rearranges the elements to satisfy the max-heap property.
Steps Involved:
• Extract the maximum element 13 from the root
• Move the value 2, which is at the last node, to the root
• Swap 2 and 12
• Swap 2 and 6
• Remove the last node
Therefore the new heap is as below.
Now,
The size of this heap: 10
The extracting elements (in extracting order): 15, 13
The maximum element of the above heap is 12. So, the HEAP-EXTRACT-MAX operation extracts and returns the element 12 from the heap. Then the MAX-HEAPIFY operation rearranges the elements to satisfy the max-heap property.
Steps Involved:
• Extract the maximum element 12 from the root
• Move the value 1, which is at the last node, to the root
• Swap 1 and 9
• Swap 1 and 8
• Remove the last node
Therefore the new heap is as below.
Now,
The size of this heap: 9
The extracting elements (in extracting order): 15, 13, 12
The maximum element of the above heap is 9. So, the HEAP-EXTRACT-MAX operation extracts and returns the element 9 from the heap. Then the MAX-HEAPIFY operation rearranges the elements to satisfy the max-heap property.
Steps Involved:
• Extract the maximum element 9 from the root
• Move the value 0, which is at the last node, to the root
• Swap 0 and 8
• Swap 0 and 7
• Remove the last node
Therefore the new heap is as below.
Now,
The size of this heap: 8 The extracting elements (in extracting order): 15, 13, 12, 9The maximum element of the above heap is 8. So, the HEAP-EXTRACT-MAX operation extracts and returns the element 8 from the heap. Then the MAX-HEAPIFY operation rearranges the elements to satisfy the max-heap property.
Steps Involved:
• Extract the maximum element 8 from the root
• Move the value 4, which is at the last node, to the root
• Swap 4 and 7
• Remove the last node
Therefore the new heap is as below.
Now,
The size of this heap: 7
The extracting elements (in extracting order): 15, 13, 12, 9, 8
The maximum element of the above heap is 7. So, the HEAP-EXTRACT-MAX operation extracts and returns the element 7 from the heap. Then the MAX-HEAPIFY operation rearranges the elements to satisfy the max-heap property.
Steps Involved:
• Extract the maximum element 7 from the root
• Move the value 0, which is at the last node, to the root
• Swap 0 and 6
• Swap 0 and 5
• Remove the last node
Therefore the new heap is as below.
Now,
The size of this heap: 6
The extracting elements (in extracting order): 15, 13, 12, 9, 8, 7
The maximum element of the above heap is 6. So, the HEAP-EXTRACT-MAX operation extracts and returns the element 6 from the heap. Then the MAX-HEAPIFY operation rearranges the elements to satisfy the max-heap property.
Steps Involved:
• Extract the maximum element 6 from the root
• Move the value 1, which is at the last node, to the root
• Swap 1 and 5
• Swap 1 and 2
• Remove the last node
Therefore the new heap is as below.
Now,
The size of this heap: 5
The extracting elements (in extracting order): 15, 13, 12, 9, 8, 7, 6
The maximum element of the above heap is 5. So, the HEAP-EXTRACT-MAX operation extracts and returns the element 5 from the heap. Then the MAX-HEAPIFY operation rearranges the elements to satisfy the max-heap property.
Steps Involved:
• Extract the maximum element 5 from the root
• Move the value 1, which is at the last node, to the root
• Swap 1 and 4
• Remove the last node
Therefore the new heap is as below.
Now,
The size of this heap: 4
The extracting elements (in extracting order): 15, 13, 12, 9, 8, 7, 6, 5
The maximum element of the above heap is 4. So, the HEAP-EXTRACT-MAX operation extracts and returns the element 4 from the heap. Then the MAX-HEAPIFY operation rearranges the elements to satisfy the max-heap property.
Steps Involved:
• Extract the maximum element 4 from the root
• Move the value 0, which is at the last node, to the root
• Swap 0 and 2
• Remove the last node
Therefore the new heap is as below.
Now,
The size of this heap: 3
The extracting elements (in extracting order): 15, 13, 12, 9, 8, 7, 6, 5, 4
The maximum element of the above heap is 2. So, the HEAP-EXTRACT-MAX operation extracts and returns the element 2 from the heap. Then the MAX-HEAPIFY operation rearranges the elements to satisfy the max-heap property.
Steps Involved:
• Extract the maximum element 2 from the root
• Move the value 1, which is at the last node, to the root
• Remove the last node
Therefore the new heap is as below.
Now,
The size of this heap: 2
The extracting elements (in extracting order): 15, 13, 12, 9, 8, 7, 6, 5, 4, 2The maximum element of the above heap is 1. So, the HEAP-EXTRACT-MAX operation extracts and returns the element 1 from the heap. Then the MAX-HEAPIFY operation rearranges the elements to satisfy the max-heap property.
Steps Involved:
• Extract the maximum element 1 from the root
• Move the value 0, which is at the last node, to the root
• Remove the last node
Therefore the new heap is as below.
Now,
The size of this heap: 1
The extracting elements (in extracting order): 15, 13, 12, 9, 8, 7, 6, 5, 4, 2, 1The maximum element of the above heap is 0. So, the HEAP-EXTRACT-MAX operation extracts and returns the element 0 from the heap. Then the MAX-HEAPIFY operation rearranges the elements to satisfy the max-heap property.
Steps Involved:
• Extract the maximum element 0 from the root
• Remove the last node
Therefore the new heap is empty.
The size of this heap: 0
The extracting elements (in extracting order): 15, 13, 12, 9, 8, 7, 6, 5, 4, 2, 1, 0
The following heap, is constructed with the specified set of elements
Insert 10 as the last node. After inserting, the tree is as follows:
As the parent of node 10, which is 8 is less than 10, exchange the nodes 8 and 10. After exchanging, the tree is as follows:
As the parent of node 10 which is 15 is greater 10, no exchange takes place.
Hence, the final heap is as shown below:
Consider the HEAP-INCREASE-KEY algorithm provided in the textbook which needs three assignments in its line number 5. These three assignments are reduced using the concept of inner loop of INSERTION-SORT.
In HEAP-INCREASE-KEY algorithm the exchange operation used in line number 5 requires three assignments.
• In first step assign the value of in a temporary variable named temp.
• In second step assign the value of to
• In third step assign the value of temp to.
Following three steps are used to swap the value:
These three assignments are necessary for the exchange of variables but they can be reduced to just one assignment by using the concept of the inner loop of insertion sort.
while loop is used in line no. 4 of algorithm will reduce the three assignments to one assignment as illustrated below:
HEAP-INCREASE-KEY (A, i, key)
//check the value of key
1. if
//display the error message.
2. error "new key is smaller than current key"
//assign the value of key in ith location of array A.
3.
//while loop is used to check the value of index i and compare the value of A[i] to its
//parent.
4. while
//sift the value of parent to its child
5.
//copy the parent node value into i.
6.
7.
Explanation of Algorithm:
• In line 5 of the above algorithm shift the value of the parent node to its child till the parent value is less than the child value.
• When while loop used in line no. 4 breaks, assign the key value to the parent.
• In this way reduce the 3 assignments of line no. 5 to just one assignment.
HEAP-DELETE can be implementead as HEAP-EXTRACT-MAX. First swap the last value in the array with the item in the node i. Then decrease the heap size by 1. Finally, to maintain max-heap property , call MAX-HEAPIFY.
Run time for HEAP-DELETE:
• All lines except the line 3 runs in constant time.
• In each call of MAX-HEAPIFY, it determines the largest between left and right of node i. Then swaps the largest value with item in node i. MAX-HEAPIFY called recursively until the max-heap property is achieved.
• Thus the MAX-HEAPIFY runs O(lg n) time.
Therefore, the HEAP-DELETE( A , i ) also runs in O (lg n ) time.
Consider the min-heap property of min-heap. According to this property, “every node except the root node consists its value minimum as much as that of its parent node”.
So, the minimum value in all the elements is acquired by the root node of the min-heap.
Now consider the following:
BUILD-MIN-HEAP:
It is used to create a min-heap using elements. It takes a time complexity of to build this min-heap.
HEAP-MINIMUM:
It is used to return the minimum of all the elements exists in the heap. It takes a time complexity of to return the minimum of all the elements.
MIN-HEAPIFY(root):
In MIN-HEAPIFY(root), it is assumed that the sub-trees, which are rooted at the child of the root, are min-heaps and it takes a time complexity of to heapifies the tree.
Now consider the following -time algorithm to merge sorted lists into one sorted list.
Algorithm:
1. Build a min-heap by choosing the first element from each of the sorted lists. The heap size is, so BUILD-MIN-HEAP will take time to build the min-heap. In this heap, list-id of the list (or from which list it has been taken) will also be stored along with the heap elements.
At this stage, the root contains the minimum of the min-heap.
2. Now, put the root into the final sorted list. Then, the root will be replaced with the next elements of the same list. It will take a time complexity of time.
At this stage, the min-heap property may be violated by the root.
3. Now, run the MIN-HEAPIFY(root). The time taken in this is.
4. When the list is empty then repeat step (2) for non-empty list.
Running time analysis of the above algorithm:
In the above algorithm, step (1) will take a time complexity of by the BUILD-MIN-HEAP.
The step (2) and step (3) will be repeated times. So, the total time complexity can be calculated by multiplying complexity of both steps by n.
Calculate the total running time as follows:
Hence, the running time of the algorithm is .


WITNESS LIST Appropriations Committee September 16, 1998-1:00P Full committee meeting On: Shannon Porterfield (DIR)


PhoneGap/Cordova Reference
Version 1.7.0
File
Device
Accelerometer
Compass
Geo Location
Notification
Camera
Connection
Events
Media
Storage
Capture
Contacts
SOCIETIES


public interface IChange
IChange
describing the change.
Note 1: There are points of similarity between IChangeSet
/IChange
and
IUpdateReport
/IItemUpdateReport
. The former is used for long-term storage of
change information in a change history. The latter is used for describing the
outcome of an accept operation.
Note 2: It may be confusing that the states are also of type IVersionableHandle
.
The difference between a versionable and a versionable state is that a
versionable state references a particular state of the versionable and has a
state id.
IVersionable
| Modifier and Type | Field and Description |
|---|---|
static int |
ADD
Kind constant indicating the addition of a versionable item in the state
given by
afterState() . |
static java.lang.String |
AFTER_PROPERTY
The after state property.
|
static java.lang.String |
BEFORE_STATE_PROPERTY
The before state property.
|
static int |
DELETE
Kind constant indicating the deletion of a versionable item in the state
given by
beforeState() . |
static java.lang.String |
ITEM_PROPERTY
The item property.
|
static java.lang.String |
KIND_PROPERTY
The change kind property.
|
static java.lang.String |
MERGES_PROPERTY
The merge states property.
|
static int |
MODIFY
Kind constant indicating the modification of a versionable item from the
state given by
beforeState() to the state given by
afterState() . |
static int |
NONE
Kind constant indicating the change has equivalent "before" and "after" states.
|
static int |
RENAME
Kind constant indicating the modification of a versionable item from the
state given by
beforeState() to the state given by
afterState() , indicating that the item's name has changed in this
transition. |
static int |
REPARENT
Kind constant indicating the modification of a versionable item from the
state given by
beforeState() to the state given by
afterState() , indicating that the item's parent has changed in this
transition. |
| Modifier and Type | Method and Description |
|---|---|
IVersionableHandle |
afterState()
Returns the "after" state of the versionable item, or
null if the change is the deletion of a versionable item
from the configuration. |
IVersionableHandle |
beforeState()
Returns the "before" state of the versionable item, or
null if the change is the addition of a versionable item
to the configuration. |
int |
getMergeKind(IVersionableHandle mergeState)
Returns the change kind which describes the type of change between the supplied
merge state and the after state.
|
IVersionableHandle |
item()
Returns the handle of the versionable item.
|
int |
kind()
Returns the kind of change.
|
java.util.List |
mergeStates()
Returns the additional states of the versionable item that were merged
with the "before" state.
|
static final java.lang.String KIND_PROPERTY
kind()
static final java.lang.String ITEM_PROPERTY
item()
static final java.lang.String BEFORE_STATE_PROPERTY
beforeState()
static final java.lang.String MERGES_PROPERTY
mergeStates()
static final java.lang.String AFTER_PROPERTY
afterState()
static final int NONE
null
, or both non-null
with
equivalent item and state identifiers. This may occur when a user resolves a conflict with
"mine". The before state is the same as the after. The change is relevant because it represents
what happened during the merge but nothing really happened.kind()
,
Constant Field Valuesstatic final int ADD
afterState()
. For this kind of change, the
"after" state is never null
, and the
"before" state is always null
.kind()
,
Constant Field Valuesstatic final int MODIFY
beforeState()
to the state given by
afterState()
. Both "before" and "after"
states are for the same versionable item, and are both non-
null
and non-equal for this kind of change.kind()
,
Constant Field Valuesstatic final int RENAME
beforeState()
to the state given by
afterState()
, indicating that the item's name has changed in this
transition. Both "before" and "after"
states are for the same versionable item, and are both non-
null
and non-equal for this kind of change.kind()
,
Constant Field Valuesstatic final int REPARENT
beforeState()
to the state given by
afterState()
, indicating that the item's parent has changed in this
transition. Both "before" and "after"
states are for the same versionable item, and are both non-
null
and non-equal for this kind of change.kind()
,
Constant Field Valuesstatic final int DELETE
beforeState()
. For this kind of change, the "before"
state is never null
, and the "after" state is always
null
.kind()
,
Constant Field Valuesint kind()
NONE
, ADD
, DELETE
or a bitwise OR of
the following flags:
IVersionableHandle item()
null
IVersionableHandle beforeState()
null
if the change is the addition of a versionable item
to the configuration.
Always returns null
for an addition.
For a modification, returns non- null
.
null
if the change is an additionjava.util.List mergeStates()
null
, indicating the merging of a deletion of the
versionable item.
Even when the before state is null
(an addition), the list
of merge states may be non-empty indicating a merge with another history
in which the item was already present (evil-twin).
Consider this list to be the proposed versions that were merged with the
before state. The after state is the versionable after the merge has been
completed. The state of the user's version (mine) before the merge is not
recorded in this IChange
. It can be found in the IChange
of the previous IChangeSet
state.
If the after state is the same as the latest merge state, the conflict was resolved by accepting the proposed version instead of resolving with mine or merging.
IVersionableHandle
or null
)int getMergeKind(IVersionableHandle mergeState)
mergeState
- must be a valid merge state handle as produced from mergeStates; null
is allowed if there is a null
merge state handle.mergeStates()
IVersionableHandle afterState()
null
if the change is the deletion of a versionable item
from the configuration.
Always returns null
for a deletion.
For a modification or addition,
always returns non-null
.
null
if the change is a
deletion


Math
- Paul's Algebra/Trig review. Read, solve all examples.
- Paul's Algebra. Read, solve all examples.
- Paul's Linear Algebra. Read, solve all examples.
- Paul's Calculus I. Read, solve all examples.
- Paul's Calculus II. Read, solve all examples.
- Paul's Calculus III. Read, solve all examples.
- Paul's Differential Equations. Read, solve all examples.
Physics
- Walter Lewin - 8.01. Video playlist; 35 lectures. Watch.
- Walter Lewin - 8.02. Video playlist; 36 lectures. Watch.
Circuits
- Morris Mano - Digital Logic. Read first 7 chapters. Solve all exercises.
- Sedra/Smith - Microelectronic Circuits. Read Parts I & II.
- Vlach - Computer Methods. Read chapters 1, 2, 3, 4. Follow all examples.
C
- Nick Parlante - Essential C. Read.
- Nick Parlante - Pointers & Memory. Read.
- Nick Parlante - Linked List Basics. Read.
- Nick Parlante - Linked List Problems. Solve.
- K & R. Read.
Programming Languages
- SICP. Video playlist; 20 lectures. Watch.
- Learn you a Haskell. Read.
Algorithms
- CLRS. Read.
- Project Euler. Make an account and solve 50 problems of your choice.
Technical Management and Culture
- The Mythical Man-Month. Read.
- Peopleware. Read.
- How to ask smart questions. Read.
- How to become a hacker. Read.
Web Development
- HTMLDog. Read all HTML and CSS tutorials.
- Ruby on Rails Tutorial. Read all and follow through.
Software Architecture
- Gang of Four. Read.
- gitref. Read.
- Git Book. Read Chapters 1, 2, 3.
- LearnGitBranching. Follow through.
- Submit a pull request and have it merged on an open source project of your choice.
Others
- Real-time rendering. Read.
- Regular expressions tutorial. Read from Introduction to backreferences, part 2.
- db-class. Online class. Take.
- ml-class. Online class. Take.
- Andrew Tanenbaum - Computer Networks. Read.
- Alan Oppenheim - Systems and Signals. Video playlist; 26 lectures. Watch.


{% extends 'template-lab-1b.html' %} {% set mainClasses = 'nhsuk-u-padding-top-0' %} {% block pageTitle %} Symptoms - NHS {% endblock %} {% block beforeContent %}
Heart palpitations are heartbeats that suddenly become more noticeable.
Your heart may feel like it's pounding, fluttering or beating irregularly, often for just a few seconds or minutes. You may also feel these sensations in your throat or neck.
Palpitations may seem alarming, but in most cases they're harmless and are not a sign of a serious problem.
Sometimes you may feel an extra or missed beat. These are known as ectopic beats and are also usually nothing to worry about.
Causes of heart palpitations include:
Common triggers of heart palpitations include:
In these cases, the palpitations should go away on their own. Avoiding these triggers may help stop them from coming back.
Heart palpitations are also often caused by emotions or psychological issues, such as:
Doing breathing exercises and learning how to deal with a panic attack may help if you're feeling stressed, anxious or panicked.
Palpitations can occasionally be triggered by some medicines, including:
Speak to a GP if you think a medicine may be causing your heart palpitations. But do not stop taking a prescribed treatment without first getting medical advice.
Heart palpitations in women can sometimes be the result of hormonal changes that happen during:
In these cases, the palpitations are usually temporary and not a cause for concern.
Palpitations are sometimes caused by a problem with the heart rhythm (arrhythmia), such as:
Some palpitations may be associated with other types of heart conditions, such as:
Some of these conditions can be serious and often require treatment.
Other conditions that can cause heart palpitations include:
You do not usually need to see a GP if the palpitations pass quickly and only happen occasionally. They're unlikely to be caused by a serious problem and probably will not need treatment.
But it's a good idea to see a GP if:
To help find the cause, a GP may:
If you cannot have an ECG at the GP surgery or the GP wants to arrange heart monitoring over a longer time period, you may be referred for tests at a local hospital.
Call 999 for an ambulance or go to your nearest A&E if you have heart palpitations and any of the following symptoms:
These symptoms could indicate a serious or potentially life-threatening heart problem that should be checked by a doctor straight away.
Page last reviewed: 02 August 2019
Next review due: 02 August 2022


%+header%>
This product includes GeoLite2 data created by MaxMind, available from https://www.maxmind.com.
A collection of all country flags in SVG — plus the CSS for easier integration https://flagicons.lipis.dev


!! GUDDU JEWELLERS !!
!! Your Order Has Placed !!
!! We Will Delivered At Your Place In 3-4 Days !!
!! Inconvenience Will Be Regretted !!


% c++ #include "admmodels.h" %> <% skin sgskin %> <% view EconomicIndicatorManageView uses sg::web::adm::EconomicIndicatorManagementModel %> <% template render() %>
Name:
Description:
Table Name:
Publish Period: Daily Weekly Monthly Quarterly Annually
Copyright:
Source Link:
Download Link:
Release Day:
Category:
Is Displayed:
Is Seasonal:
Determiner: None Quantity Rate


Definition at line 42 of file emergency_stop.py.
| def airbus_cobot_gui.emergency.emergency_stop.EmergencyStopButton.__init__ |
( |
|
self | ) |
|
| def airbus_cobot_gui.emergency.emergency_stop.EmergencyStopButton._emergency_stop_publisher_loop |
( |
|
self | ) |
|
|
private |
| def airbus_cobot_gui.emergency.emergency_stop.EmergencyStopButton._trigger_button |
( |
|
self, |
|
|
|
checked |
|
) |
| |
|
private |
Called when user click on ermergency stop button.
@param checked: Button status (True/False).
@type checked: bool.
Definition at line 71 of file emergency_stop.py.
| def airbus_cobot_gui.emergency.emergency_stop.EmergencyStopButton.shutdown |
( |
|
self | ) |
|
| airbus_cobot_gui.emergency.emergency_stop.EmergencyStopButton._button_state |
|
private |
| airbus_cobot_gui.emergency.emergency_stop.EmergencyStopButton._estop_pub |
|
private |
| airbus_cobot_gui.emergency.emergency_stop.EmergencyStopButton._estop_pub_thread |
|
private |
| airbus_cobot_gui.emergency.emergency_stop.EmergencyStopButton._keep_running |
|
private |
| string airbus_cobot_gui.emergency.emergency_stop.EmergencyStopButton.EMERGENCY_STOP_TOPIC_NAME = '/emergency_stop/state' |
|
static |
| string airbus_cobot_gui.emergency.emergency_stop.EmergencyStopButton.EVENT_NAME = 'emergencyStopStatusChanged' |
|
static |
| airbus_cobot_gui.emergency.emergency_stop.EmergencyStopButton.ICON_PAUSE |
| airbus_cobot_gui.emergency.emergency_stop.EmergencyStopButton.ICON_PLAY |
The documentation for this class was generated from the following file:


I am seeking a position to build responsive, modern websites that solve business problems, communicate messages, and gather clean and reliable consumer / user data to enable business intelligence.
Currently Seeking a Web Developer Position - Seattle, WA, USA
November 2017 - Present
After moving across the country from Boston to Everett, WA, I am looking to buiild a network and start a new career here in the Seattle area. Please check out my work on Github here, or click on a project to view the project page.
Boston International Academy - Brighton, MA, USA
May 2016 - October 2017
Music & Arts - Newton, MA, USA
February 2016 - May 2016
Live Noodles, LLC - Boston, MA, USA
August 2015 - January 2016
International Pioneers Schools - Bangkok, Thailand
August 2014 - July 2015


I'LL BE HOME FOR CHRISTMAS A film review by Matt Williams
RATING: * out of * * * *
It must be the holiday season already. Stores are stocked with decorations galore, and the local theaters are stocked with "feel-good" holiday films, like I'll Be Home for Christmas. However, don't be fooled by its title...you aren't likely to build up much holiday cheer by forcing yourself to sit through this torturous ninety-minute debacle.
Jonathan Taylor Thomas stars as the annoying prep school kid, Jake. Jake is the type of smarmy kid who tries to talk his way out of everything, and mostly succeeds. His father (Gary Cole), believing the only way his son will return home for the holidays, resorts to bribery. If Jake can make it home by 6:00 Christmas Eve, he will get his dad's classic Porsche as a present. Jake would do anything for the car...but he runs into a little bit of trouble along the way...
A group of angry jocks, angry at Jake for a failed scheme of his, kidnaps him, glues him into a Santa suit, and strands him in the California desert. Penniless, Jake must make his cross-country trek in a few short days if he ever hopes to see that car...or his girlfriend.
You see, his charms have been wearing thin on his girlfriend, Allie (Jessica Biel). She's had one too many stories and lies, and when he fails to meet her for the Christmas return home, she decides to take a ride with Jake's rival, Eddie (Adam Lavorgna), instead.
All of this might be the slightest bit interesting if we cared one iota about Jake and/or his predicament. But we don't. From the get-go, his cocky attitude is extremely off-putting, and his "charms" never grow on us. Frankly, his dad might as well keep the car, and Allie would certainly be better off with the only slightly-less annoying Eddie.
Of course, we are treated to all sorts of wild adventures and wacky, "colorful" characters which Jake runs across in his cross-country trek. Anyone who's seen any sort of road-trip movie will be intimately familiar with the type. Most of these are not near as interesting, nor as entertaining, as they might have appeared on paper (though it's even doubtful that some of these appeared interesting there either).
I'll Be Home for Christmas is reminiscent of an annual present that you don't really want to get. It means well, but is best left alone and forgotten.
Copyright 1998 Matt Williams
- Matt Williams<EMAIL_ADDRESS>Reviewer for Cinematter: http://www.cinematter.com Home of over 650 reviews, and information on nearly 700 upcoming releases
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


{% extends "./dashboard_base.html" %} {% load static %} {% block styles %} {% endblock %} {% block content %}
| Add platform policy |
| Edit platform policy |
| Remove platform policy |
| Recover platform policy |
| Add constitution policy |
| Edit constitution policy |
| Remove constitution policy |
| Recover constitution policy |
| Propose {{action.readable_name|default:action.action_codename}} |
| Add document |
| Edit document |
| Remove document |
| Recover document |
| Add role |
| Edit role |
| Remove role |
| Grant role to user |
| Revoke role from user |


Couldn't find a sticky with rules etc. so hope this is OK.
Would be nice to have some more detailed information in the server browser from the live scoreboard. Battlelog+ has a particularly nice option where it displays the average rank / points of each team. Would be a nice addition if this and the current tickets could be displayed in the server browser.
Thanks for all the effort put into this.
BrainFooLong
Administrator
Current tickets are already available also in the server browser (when you click on a entry - right bellow the join button).
But to show tickets/more information for each entry in the server list results in a huge amount of requests which i do not want to inegrate.


'Hello , welcome to my portfolio'
And I am a webdeveloper
Web development.
Android development.
software development.
webpage for kalos millers limited
A wild life conservation app
A dietary application
Systems for a gas station company
Modile games
Navigation app
Food delivery apps
Social media app
You can find me using the following methods


Majors:
- Corporate Finance
- Supply Chain and Operations Management
Minor:
- International Relations
Born in FL in 1984 Tim joined the Army after highschool and became an infantryman in the 82nd Airborne Division. After that he met his future wife in university and calmed down a (very) little bit. His career has been in the insurance industry and drifted more into the startup/tech world over the past few years.
Majors:
Minor:


Company One Liner:
{{company?.oneLiner}}
Plug and Play Office:
{{company?.pnpOffice}}
Account Manager:
{{company?.pnpContact}}
Verticals:
{{company.verticals}}
Tags:
{{company.tags}}
Competition:
{{company.competition}}
Advantage:
{{company.advantage}}
Founded:
{{company.founded}}
Investors:
{{company?.investors}}
How you initially heard about us:
{{company?.howDidYouHear}}
International office business opportunities:
{{company?.intlBusinessOpp}}
Partner Interests:
{{company.partnerInterests}}
Case Study:
{{company.caseStudy}}
Comments:
{{company.comments}}
Date of Investment:
{{company.dateOfInvestment}}
Materials:
Time Stamp:
{{company.timestamp}}
Database ID:
{{company.id}}
Last Updated:
{{company.updated}}


import { mergeOver, pushUnique, λnull, Ωempty } from '../core/utilities.js';
The asset factories - ImageAsset, SpriteAsset, and VideoAsset - are wrappers around images and videos which can either be pulled from the current document (DOM-based assets) or fetched from the server using an URL address.
Assets can be loaded into scrawl using dedicated import and create functions:
scrawl.importImage
scrawl.importDomImage
scrawl.importDomVideo
scrawl.importVideo
scrawl.importMediaStream
scrawl.importSprite
scrawl.createImageFromCell
scrawl.createImageFromGroup
scrawl.createImageFromEntity
Assets will also be created when Picture entitys or Pattern styles are defined using a ‘scrawl.make’ function (makePicture
, makePattern
), or updated with the set
function, where the imageSource, videoSource or spriteSource key in the argument object has been set to a valid URL path string.
Be aware that loading assets takes time!
import { mergeOver, pushUnique, λnull, Ωempty } from '../core/utilities.js';
export default function (P = Ωempty) {
const defaultAttributes = {
sourceLoaded - A flag to indicate that the source image or video has completed sufficient loading (or streaming) to be usefully consumed by Picture entitys and Pattern styles.
sourceLoaded: false,
source - A handle to the DOM element supplying the image - either an <img>, <video> or <canvas> element.
source: null,
subscribers - An Array containing the Picture entity and Pattern style Objects, who wish to use the asset as their source.
subscribers: null,
};
P.defs = mergeOver(P.defs, defaultAttributes);
Assets do not include their source images (or videos!) in their packet output. They do include the String name values of each of their subscribers.
P.packetExclusions = pushUnique(P.packetExclusions, ['sourceLoaded', 'source', 'subscribers']);
P.finalizePacketOut = function (copy) {
if (this.subscribers && this.subscribers.length) {
copy.subscribers = this.subscribers.map(sub => sub.name);
}
return copy;
};
P.kill = function (removeDomEntity = false) {
if (removeDomEntity && this.source) this.source.remove();
return this.deregister();
};
const S = P.setters;
source - imageAsset.js and videoAsset.js overwrite this function, thus only put here so cell.js also gains the function - which I don’t think it will ever need as cells ARE their own source.
S.source = function (item) {
if (item) {
No action required for Canvas objects as they don’t have a source; they ARE the source!
if (this.sourceLoaded) this.notifySubscribers();
}
};
subscribers - we disable the ability to set the subscribers Array directly. Picture entitys and Pattern styles will manage their subscription to the asset using their subscribe() and unsubscribe() functions.
S.subscribers = λnull;
assetConstructor
- Common actions required by imageAsset, spriteAsset, and videoAsset factories as part if their instance constructor work.
P.assetConstructor = function (items) {
this.makeName(items.name);
this.register();
this.subscribers = [];
this.set(this.defs);
this.set(items);
if (items.subscribe) this.subscribers.push(items.subscribe);
return this;
};
P.subscribe = function (sub) {
if (sub && sub.name) {
const name = sub.name;
if (this.subscribers.every(item => item.name !== name)) this.subscribeAction(sub);
}
};
subscribeAction
- separated out because cells handle things differently (they ARE the source)
P.subscribeAction = function (sub) {
if (sub) {
this.subscribers.push(sub);
sub.asset = this;
sub.source = this.source;
this.notifySubscriber(sub);
}
};
unsubscribe
P.unsubscribe = function (sub) {
if (sub && sub.name) {
const name = sub.name,
index = this.subscribers.findIndex(item => item.name == name);
if (index >= 0) {
sub.source = null;
sub.asset = null;
sub.sourceNaturalHeight = 0;
sub.sourceNaturalWidth = 0;
sub.sourceLoaded = false;
this.subscribers.splice(index, 1)
}
}
};
notifySubscribers
, notifySubscriber
- Subscriber notification in the asset factories will happen when something changes with the image. Changes vary across the different types of asset:
All notifications are push; the notification is achieved by setting various attributes and flags in each subscriber.
P.notifySubscribers = function () {
this.subscribers.forEach(sub => this.notifySubscriber(sub), this);
};
P.notifySubscriber = function (sub) {
sub.sourceNaturalWidth = this.sourceNaturalWidth;
sub.sourceNaturalHeight = this.sourceNaturalHeight;
sub.sourceLoaded = this.sourceLoaded;
sub.source = this.source;
sub.dirtyImage = true;
sub.dirtyCopyStart = true;
sub.dirtyCopyDimensions = true;
sub.dirtyImageSubscribers = true;
sub.dirtyFilterIdentifier = true;
};
}


1. Print all numbers between -10 and 19
2. Print all even numbers between 10 and 40
3. Print all odd numbers between 300 and 333
4. Print all numbers divisible by 5 and 3 between 5 and 50


Vue.js for interactive apps
Two-way data binding listens for changes and automatically updates.
Enter your name (2 to 40 characters):
Enter first number (1 to 100):
Enter second number (1 to 100):
{{result}}


This menu command will allow you to withdraw a CIX forum message or Usenet newsgroup article. A CIX Forums message will be withdrawn the next time that Ameol connects to CIX Forums. Withdrawing newsgroup articles is less straightforward because the message that Ameol sends to withdraw your article has to follow the article around the Internet. Note that the copy of the message within your database will not be deleted but will be marked with a `W'.


You can annotation anything on the page with a marker.
If you want, you can draw shapes.
Or highlight.
It even works on images:


PATCH ADAMS (1998) A Review by Amateur Film Critic Sharon Connolly
Cast: Robin Williams, Monica Potter, Bob Gunton, Daniel London, Philip Seymour Hoffman, Josef Sommer and Peter Coyote Directed by Tom Shadyac Written by Steve Oedekerk Released by Universal Pictures
This film is based on real-life doctor Patch Adams of Virginia who tried to reinvent the medical practice through humor and a free clinic. Patch has been described as an iconoclast, a pattern-breaker and professional clown, and who could play Patch any better than Robin Williams, who's proven to the world over and over again that he's a comedic genius! Williams also has that unique ability to make you laugh and cry almost within the same scene.
With a Christmas premiere, the timing is perfect because it's a "feel-good" film for the holidays. Now I ask you - what's wrong with that? Its clever script brings rich humor poking fun at the medical establishment and the myth of doctors as godlike creatures. And that's something nearly every one of us can relate to. Described as a drama/comedy, the script focuses on five years of the doctor's life. As an amateur film critic, I have to declare "Patch Adams" a definite winner DESPITE the influx of complaints from national critics who have referred to it as syrupy, beyond belief and toying with the emotions with a heavy hand, even going so far as to say that the soundtrack was also manipulative. Well, name one that isn't. At the sneak preview I attended, the audience responded with a round of applause, highly unusual. I think moviegoers have had their share this year of action and special-effects films, which demand total suspension of disbelief for a solid two hours! Therefore, "Patch Adams" has a refreshing appeal and can be embraced as a story of joy and hope in the face of illness and death, which we must all eventually succumb to.
Bob Gunton plays his villainous role with fervor as Dean Walcott (remember him as the prison warden in "Shawshank Redemption"?) while Monica Potter delightfully plays Patch's love interest despite her Julia Roberts' look-alike image. Kudos also goes to Daniel London as Patch's geeky pal as well as to Philip Seymour Hoffman as the earnest but pompous and humorless roommate. (A bit like some of these film critics, eh?) And, yes, the cantankerous, dying patient in Room 305 is indeed Peter Coyote, whose awesome voice can still be easily recognized.
As a final note, this film has received two Golden Globe nominations, one for Best Picture in the musical/comedy category and one for Williams as Best Actor. Guess there must be plenty of other folks out there who agree with me.
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Related links: index of all rec.arts.movies.reviews reviews


Utah Jazz arena evacuated minutes after game over suspicious shoebox
by Brie StimsonVivant Smart Home Arena in Salt Lake City was evacuated Friday night after a suspicious shoebox was found underneath a table in an arena restaurant, according to reports.
The discovery came just minutes after the Utah Jazz defeated the Golden State Warriors 113-109 in an NBA game.
Players still in uniform left the building with the crowd, without even going to their locker rooms. Most of the spectators had already exited before the evacuation started.
"We don’t know if it’s anything explosive. So far what we have is just a suspicious package,” Salt Lake City Police Department Lt. Carlos Valencia told reporters after the evacuation. "Public safety is paramount to us and we take these complaints very seriously."
CALIFORNIA HOMEOWNER FINDS DEAD WOMAN INSIDE HOUSE, BOMB THREAT WRITTEN ON WALL: POLICE
A police bomb squad was called in after a bomb-sniffing dog reacted to the shoebox, Valencia said.
Salt Lake City police said the package turned out to be a toolbox and the teams were allowed to return to the building about two hours later, the Jazz said.
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No injuries were reported.
Separately, about 25 minutes after the evacuation, three people were wounded in a drive-by shooting outside a concert venue called The Complex just two blocks away, The Salt Lake City Tribune reported. Valencia said one of the victims was shot in the chest but was expected to survive. No arrests were reported as of early Sunday.
The Associated Press contributed to this report.


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