* Special thanks to Julie Oh for her beautiful voice!
Online book store in Korea is as prosperous as in any other countries in the world. It has about 36% of entire book market share in Korea, and this number is consitently growing every year. YES24 is the leading online book store in Korea, occupying about 44% of online book market. However, YES24's book recommender system is not so good that it often recommends totally irrelavant books, or even a goods that is not a book. YES24 recently opened a competition where data scientists suggest a solution for accurate book recommender, releasing the purchase history of 19,000 users within 2014. This motivated us to build a book recommeder algorithm, using the technique we've learned throughout the semester in CS109.
We've tried three different algorithms: one is the simplest algorithm that YES24 supposedly uses on their current website, and the others are based on k-nearest neighbor (kNN) with user similarity and book similarity. As a result, we found that kNN with user similarity has the best recommendation accuracy, which we expect will be better than the current system by 2~7%p.
The data given by YES24 contains the information of 511,742 transactions of about 19,000 users' purchase history, involving about 19,000 books. Among them, we focused on data in five categories: foreign literature, Korean literature, self-development, humanities, and religion. They are five biggest categories except study materials and magazines.
One problem of the given data is that it is the record of what people bought only; we may obtain information about which books each person likes, but it is impossible to know which books each person dislike. Usual methods in machine learning are likely to classify items into different categories, thus we needed to modify these methods to circumvent this difficulty.
The simplest algorithm that commonly adopted in many online bookstores. His/her preferences will be determined from the previous similar purchase transactions. In other words, we recommend books that "Customers Who Bought This Item Also Bought."
Some books are written by the same author or the same publisher. Then wouldn't they be similar to one another? Also sometimes their titles are similar, in some of which cases they would contain similar contents. We use this information to recommend books to customers.
Similar to the first method but refined further. We carefully choose how many users whose transaction record is similar to me, how importantly we consider each similar user, and how we decide a score for each book from this. Popularity of each book in general is also considered.
We applied aforementioned three different methods to the test data. Since we supposed that the first method is likely to be used currently in YES24, which we call "the baseline," we hoped to implement a better algorithm than this one. It turned out that the performance of the third method, which we call "user kNN," is remarkable. It excels the baseline method in every category by at most 7%p. Roughly it means that if we recommend 100 books to customers, then "user kNN" method would predict 7 more books they are willing to buy than the baseline.
Please click the bar chart on the left to see more results.
One advantage of our method is that it can be applied to a single book instead of users. Please click each book here to see which other books are closely related to it according to our algorithm.
The GitHub repository of this project is where all IPython files for main codes and expository notes are stored.
Our video can be found here.
<EMAIL_ADDRESS><EMAIL_ADDRESS>tyyoo88@gmail.com


 What's that uncanny sound?
It's the sound of the cow-god's bog-side mooing
The sound of my and Gob's undoing.


Thank you for visiting my personal website. I am Alexander Andersson, currently an applicant for programming jobs in Norway. I received an MSc in Computer Science, with study specialisation 'software', from the Norwegian University of Science and Technology (NTNU) earlier in 2015. I graduated from Ålesund University College (HIALS) in 2012, where I finished my Bachelor of Engineering in Computer Science.
I created this site after having finished my Master's, both to get a personal introduction to development with Angular.js, and to create a showcase for some of my completed projects. More projects and other content will be added at a later date.
Full source code for this site can be found on GitHub. Please keep in mind that the site is still in development. Some issuses that are currently being worked on:


18-Jun-2017 | Milku
The proper one...no squirrels involved.
It's Day 18 of 30 Days Wild and I missed a day of blogging even if we did manage to tweet a couple of pictures to @30DaysWild. My humans came back with the pictures a bit too late for me to want to log on...I don't like blogging when they're around and watching me. So this update is all about what they did yesterday.
They hoped to visit the squirrels in the National Trust site at Formby. But so did the rest of the population. The queues were too long to get on site so they headed to Formby Point itself...just a little farther South.
There aren't so many trees near this part of Formby beach...actually, to the locals, the squirrels live in Freshfield, near to the big houses where lots of footballers reside. But if the National Trust want to refer to it as Formby then who am I to argue.
One of my big humans was telling me that she spent one summer surveying the dune vegetation at Formby, and checking what effects people and rabbits had on it. She thought it would be a great way to spend the holiday, lounging around the beach in the sun. There was just one problem, it was the most miserable summer weatherwise. Oh well, it was glorious sunshine yesterday and quite warm too.
Once again they hoped to spot prehistoric footprints or the tobacco cliffs, but were disappointed - again!
They enjoyed a picnic on the beach though and walked along the tide line to try to spot interesting shells. There were quite a few sea potatoes there.  But yesterday, they managed to find some that still had their spines attached - a bit unusual.
Then they ambled back through the dunes. They wanted to visit Grandma too. They knew she'd have lots of ice cream in her freezer, which was just the thing they needed in the heat.


The SectorFile class is a handler to a file in the Sector system.
There is no public member variables for this class.
| Method | Fuctionality |
| close | close this file handler |
| download | download the Sector file to local disk |
| eof | check if read has reached end of file |
| flush | send all unwritten data in local buffer to the physical files |
| open | open a Sector file |
| read | read a block of data from the opened file |
| seekg | set the read offset position |
| seekp | set the write offset position |
| tellg | query the read offset position |
| tellp | query the write offset position |
| upload | upload a local file to the Sector system |
| utime | update the time stamp of a file |
| write | write a block of data to the opened file |


Preparation time
less than 30 mins
Cooking time
10 to 30 mins
Serves
Makes 6
These sausage rolls are a good way to use up leftover Christmas stuffing in preparation for a New Year party.
For the tomato relish, grind the cumin seeds to a fine powder in a pestle and mortar. Transfer to a bowl and stir in the remaining tomato relish ingredients (except for the parsley), until well combined. Season, to taste, with salt and freshly ground black pepper. Chill in the fridge for at least 30 minutes, or until needed. Stir in the parsley just before serving.
For the sausage rolls, pre-heat the oven to 200C/180C Fan/Gas 6.
Roll out the pastry onto a lightly floured work surface to the thickness of pound coin. Make a long rectangle measuring at least 10-15cm/4-6in in width.
In a bowl, mix together the garlic, sage, leftover stuffing and sausage meat until well combined. Season with salt and freshly ground black pepper if necessary.
Roll the stuffing mixture into a sausage shape that’s a little shorter than the long side of the pastry.
Lay the stuffing mixture on top of the pastry rectangle, close to one long side of the rectangle. Brush the pastry all over with beaten egg. Roll the pastry over the stuffing mixture and press the edges to seal well.
Brush the top with the remaining egg and sprinkle with the sesame seeds. Cut into six equal-sized sausage rolls. Transfer to a baking tray. Bake for 25 minutes, or until the pastry has risen and is golden-brown and the filling is cooked through.
Allow the sausage rolls to cool slightly before serving. Serve with the tomato relish in dipping bowls alongside.


( #PCDATA | email | ext-link | uri | inline-supplementary-material | related-article | related-object | bold | fixed-case | italic | monospace | overline | roman | sans-serif | sc | strike | underline | ruby | alternatives | inline-graphic | inline-media | private-char | chem-struct | inline-formula | tex-math | mml:math | abbrev | milestone-end | milestone-start | named-content | styled-content | tp:taxon-name | tp:descriptive-statement | tp:material-citation | fn | target | xref | sub | sup )*
May Contain:


SnapPay
Simple URL Transaction sys
Home
Profile
Contact
Product Name :
Current Price :
profile
contact


Several flights delayed at Dane County Regional Airport
by Stephanie FryerMADISON, Wis. - There are several delayed flights in and out of the Dane County Regional Airport Monday morning.
Several flights heading to Chicago from Madison have been delayed for a couple of hours.
You can check the status of a departing flight by clicking on this link.
Several arriving flights have also been delayed. You can check the status of arriving flights by clicking on this link.


My Virtual Garage Sale
Home
Collectables/Hobbies/Sporting Goods
Household/Toys
About My Virtual Garage Sale


The lutout record may selectively send values to the output fields by using the SELB field. This field is a bit mask for the enabled output fields. If the bit mask is 1, then only the VALA field will be written, if it is 3, then both VALA and VALB will be written. A value of 15 will write to all four output fields. The number of fields successfully written will be placed in the NVAL field. This value is the intersection of the bits set in SELB and the number of values in a tag's lookup table entry. The SEVR and STAT alarm fields are set to INVALID and SOFT if an input configuration string is not recognized
The lookup table can be reread from the file by writing a one to the LOAD field.
A lutout record can reference another lutout or lutin record's lookup table by making a connection between its LLNK field and the other record's LTBL field. The record can now find a tag in either its lookup table or the table from the other record. This feature can only work within an IOC; it will not work across channel access. [This feature is not yet implemented].
More information and examples can be found in the lutout manual[3].
|
Field
|
Type
|
Initial
|
Access
|
Modify
|
Monitor
|
PP
|
|---|---|---|---|---|---|---|
|
VAL
|
STRING
|
Null
|
Yes
|
Yes
|
Yes
|
Yes
|
|
OVAL
|
STRING
|
Null
|
Yes
|
No
|
No
|
No
|
|
FDIR
|
STRING
|
Null
|
Yes
|
Yes
|
No
|
No
|
|
FNAM
|
STRING
|
Null
|
Yes
|
Yes
|
No
|
No
|
|
NVAL
|
LONG
|
0
|
Yes
|
No
|
Yes
|
No
|
|
ONVL
|
LONG
|
0
|
Yes
|
No
|
No
|
No
|
|
SELB
|
LONG
|
15
|
Yes
|
Yes
|
No
|
No
|
|
LOAD
|
LONG
|
0
|
Yes
|
Yes
|
No
|
Special
|
|
LTBL
|
NOACCESS
|
0
|
No
|
No
|
No
|
No
|
|
LLNK
|
INLINK
|
0
|
No
|
No
|
No
|
No
|
|
PREC
|
LONG
|
2
|
Yes
|
Yes
|
No
|
No
|
|
VALA
|
NOACCESS
|
0
|
Yes
|
No
|
Yes
|
No
|
|
VALB
|
NOACCESS
|
0
|
Yes
|
No
|
Yes
|
No
|
|
VALC
|
NOACCESS
|
0
|
Yes
|
No
|
Yes
|
No
|
|
VALD
|
NOACCESS
|
0
|
Yes
|
No
|
Yes
|
No
|
|
OLDA
|
NOACCESS
|
0
|
No
|
No
|
No
|
No
|
|
OLDB
|
NOACCESS
|
0
|
No
|
No
|
No
|
No
|
|
OLDC
|
NOACCESS
|
0
|
No
|
No
|
No
|
No
|
|
OLDD
|
NOACCESS
|
0
|
No
|
No
|
No
|
No
|
|
OUTA
|
OUTLINK
|
0
|
No
|
No
|
No
|
No
|
|
OUTB
|
OUTLINK
|
0
|
No
|
No
|
No
|
No
|
|
OUTC
|
OUTLINK
|
0
|
No
|
No
|
No
|
No
|
|
OUTD
|
OUTLINK
|
0
|
No
|
No
|
No
|
No
|
|
FTVA
|
GBLCHOICE
|
STRING
|
Yes
|
No
|
No
|
No
|
|
FTVB
|
GBLCHOICE
|
STRING
|
Yes
|
No
|
No
|
No
|
|
FTVC
|
GBLCHOICE
|
STRING
|
Yes
|
No
|
No
|
No
|
|
FTVD
|
GBLCHOICE
|
STRING
|
Yes
|
No
|
No
|
No
|
|
Name
|
Summary
|
Description
|
|---|---|---|
|
VAL
|
Input string
|
An ASCII string which corresponds to a tag entry
in the lookup table.
|
|
OVAL
|
Old tag
|
The previous value.
|
|
FDIR
|
Initialization file directory
|
The name of the directory of the lookup table.
|
|
FNAM
|
Initialization file name
|
The name of the file for the lookup table.
|
|
NVAL
|
Number of outputs
|
This is the number of values found in the lookup
table for the appropriate input tag. It is between 0 and 4.
|
|
ONVL
|
Old number
|
The previous value of NVAL. Used for triggering monitors.
|
|
SELB
|
Selection Bits
|
This is a bit mask for the values which are to be
converted. If SELB is 1, only VALA will be written; if 3, VALA and VALB
will be written. A value of 15 will write all values.
|
|
LOAD
|
Reload configuration file
|
Any nonzero value written to this field will force
the reloading of the lookup table from the configuration file defined by
FDIR and FNAM.
|
|
LTBL
|
Lookup Table
|
This is the location where the conversion table is
stored in memory.
|
|
LLNK
|
Lookup Table Link
|
The link to another record's lookup table (LTBL).
This link only works within an IOC.
|
|
PREC
|
Precision
|
This is the level of precision given for double-precision
conversion.
|
|
VALA
|
Output value
|
The lookup table values are put on this port. A monitor
event is sent if the value changed.
|
|
VALB
|
Output value
|
The lookup table values are put on this port. A monitor
event is sent if the value changed.
|
|
VALC
|
Output value
|
The lookup table values are put on this port. A monitor
event is sent if the value changed.
|
|
VALD
|
Output value
|
The lookup table values are put on this port. A monitor
event is sent if the value changed.
|
|
OLDA
|
Old value
|
The old value. Used to trigger monitors.
|
|
OLDB
|
Old value
|
The old value. Used to trigger monitors.
|
|
OLDC
|
Old value
|
The old value. Used to trigger monitors.
|
|
OLDD
|
Old value
|
The old value. Used to trigger monitors.
|
|
OUTA
|
Output link
|
The lookup table values are sent out these links.
|
|
OUTB
|
Output link
|
The lookup table values are sent out these links.
|
|
OUTC
|
Output link
|
The lookup table values are sent out these links.
|
|
OUTD
|
Output link
|
The lookup table values are sent out these links.
|
|
FTVA
|
Output value type
|
May be one of STRING, DOUBLE, or LONG. This field
forces the conversion of the appropriate table value to the correct type.
|
|
FTVB
|
Output value type
|
May be one of STRING, DOUBLE, or LONG. This field
forces the conversion of the appropriate table value to the correct type.
|
|
FTVC
|
Output value type
|
May be one of STRING, DOUBLE, or LONG. This field
forces the conversion of the appropriate table value to the correct type.
|
|
FTVD
|
Output value type
|
May be one of STRING, DOUBLE, or LONG. This field
forces the conversion of the appropriate table value to the correct type.
|
There are two CapFast symbols for the lutout record: elutouts.sym
and elutout.sym. These symbol are included in the epics3.12.2Gem.4 and
later distributions.
FIGURE 6.1 CapFast elutouts and elutout symbols


You can add or remove your function of the avengers key. Make your functions in the below section and press apply button after done.
Since the program uses Microsoft .Net Framework, install and restart stream deck if the plugin does not work.
If any helps, please visit web-site below and make an issue or send an e-mail.


The Star object¶
-
class
photometry.
star
(kic, ffi_dir=None)[source]¶ The main interface to the f3 photometry package
Parameters: - kic – The Kepler Input Catalog identifier for the target for which you wish to do photometry
- ffi_dir – The directory relative to your current working directory where your
full frame images are stored (default:
ffidata/
)
-
adjust_aperture
(image_region=15, ignore_bright=0)[source]¶ Develop a panel showing the current aperture and the light curve as judged from that aperture. Clicking on individual pixels on the aperture will toggle those pixels on or off into the aperture (which will be updated after closing the plot). Clicking on the 0th row or column will turn off all pixels in that column or row, respectively. Will iterate continuously until the figure is closed without updating any pixels.
Parameters: - image_region – The size of the region around the target star to be plotted. Images will be a square
with side length
image_region
(default:15
) - ignore_bright – The number of brightest stars to be ignored in the determination of the flux from
reference stars. If there is reason to believe (for example) that saturated stars may behave
differently than the target star, they can be avoided with this flag (default:
0
)
- image_region – The size of the region around the target star to be plotted. Images will be a square
with side length
-
calc_centroids
()[source]¶ Identify the centroid positions for the target star at all epochs. Useful for verifying that there is no correlation between flux and position, as might be expected for high proper motion stars.
-
calc_fluxes
(min_flux=5000, outlier_iterations=5, max_outlier_obs=4, outlier_limit=1.7)[source]¶ Determine the suitable reference stars, and then the total flux in those stars and in the target star in each epoch
Parameters: - min_flux – The size of the region around the target star to be plotted. Images will be a square
with side length
image_region
(default:5000
) - outlier_iterations – The number of iterations to remove outliers from the reference star sample
(stars at epochs with more than
max_outlier_obs
observations more thanoutlier_limit
standard deviations from the median value for all stars after normalization) (default:5
) - max_outlier_obs – The maximum number of epochs at which a star is allowed to be more than
outlier_limit
standard deviations from the median value for all stars before it is removed as a suitable reference star (default:4
) - outlier_limit – The level of deviation (measured in standard deviations) which a target is allowed
to be discrepant from the median. If it is this discrepant at more than
max_outlier_obs
epochs, it is removed from consideration (default:1.7
)
- min_flux – The size of the region around the target star to be plotted. Images will be a square
with side length
-
data_for_target
(do_roll=True, ignore_bright=0)[source]¶ Determine the normalized photometry, accounting for effects shared by reference stars. Does not provide the opportunity to adjust the aperture
Parameters: - image_region – If
True
allow the aperture to be shifted up to one pixel in both the x and y directions to account for differential velocity aberration (default:True
) - ignore_bright – The number of brightest stars to be ignored in the determination of the flux from
reference stars. If there is reason to believe (for example) that saturated stars may behave
differently than the target star, they can be avoided with this flag (default:
0
)
- image_region – If
-
define_spotsignal
()[source]¶ Identify the “expected” flux value at the time of each observation based on the Kepler long-cadence data, to ensure variations observed are not the effects of a single large starspot. Only works if the target star was targeted for long or short cadence observations during the primary mission.
-
do_photometry
()[source]¶ Does photometry and estimates uncertainties by calculating the scatter around a linear fit to the data in each orientation. This function is called by other functions and generally the user will not need to interact with it directly.
-
do_rolltest
(g, wh)[source]¶ Test for shifts in the local positions of stars in each epoch due to differential velocity aberration. This is called by other functions in the development of light curves and shouldn’t ever need to be called by the user.
Returns: An array of the best pixel shifts in x and y to account for differential velocity aberration. Return type: ndarray
-
find_other_sources
(edge_lim=0.015, min_val=5000, ntargets=250, extend_region_size=3, remove_excess=4, plot_flag=False, plot_window=15)[source]¶ Identify apertures for all sources on the postcard, both for the target and potential reference stars
Parameters: - edge_lim – The initial limit for the creation of apertures. The aperture will be a region of
contiguous pixels with flux values larger than the product of
edge_lim
and the brightest pixel value for this star, as long as that product is larger thanmin_val
(default:0.015
) - min_val – Threshold for the minimum flux value in the
integrated_postcard
for a pixel to be included in the default apertures (default:5000
) - ntargets – The maximum number of potential reference stars to be included in the analysis (default:
250
) - extend_region_size – After the initial apertures are generated, they will be optionally extended an
additional number of pixels following this flag. Safe practice for reasonable apertures is to
leave
min_val
at a value well above the noise and then extend apertures via this flag until they are of suitable size (default:3
) - remove_excess – Stars with apertures that touch will be combined into a single aperture.
This is done by iterating through the starlist; this flag represents the number of times the
list will be iterated through to delete redundant apertures (default:
4
) - plot_flag – If true, a series of diagnostic plots will appear while this function runs to observe
apertures for the target star and other stars.
(default:
False
) - plot_window – If
plot_flag
isTrue
, the size of the region to be plotted around the target star to show the drawn aperture for visualization purposes only (default:15
)
- edge_lim – The initial limit for the creation of apertures. The aperture will be a region of
contiguous pixels with flux values larger than the product of
-
generate_panel
(img)[source]¶ Creates the figure shown in
adjust_aperture
for visualization purposes. Called by other functions and generally not called by the user directly.Parameters: img – The data frame to be passed through to be plotted. A cutout of the integrated_postcard
-
make_postcard
(npix=300, shape=(1070, 1132), buffer_size=15)[source]¶ Develop a “postcard” region around the target star. Other stars in this postcard will be used as possible reference stars.
Parameters: - npix – The size of the postcard region. The region will be a square with sides npix pixels
(default:
300
) - shape – The size of each individual image. For Kepler/K2 FFIs this should never need to be
changed from the default, but will be different for e.g. TESS FFIs (default:
(1070, 1132)
) - buffer_size – The number of pixels at the edge of the detector to avoid (default:
15
)
- npix – The size of the postcard region. The region will be a square with sides npix pixels
(default:


Personal Data Protection Policy
For us the protection and the security of our customers and users and the observation of the legal frames constitute a substantial part of the principles for protection of your personal data.
The personal data collected at the use of this site serve solely for the improvement of the users’ experience, for statistics and for feedback. All the technologies and instruments included in this Web Site are enumerated herein below.
The agreement for use of Cookies on the part of the User shall be provided through clicking on button “ОК“ of the appearing banner in the site particularizing their use and indicating a link to this site for personal data policy.
We use the information received during the use by you of our Internet site only for statistical purposes and for protection from illegal access to the offered by us in Internet. This helps us to take into consideration and optimize our Internet site in conformity with your needs. We do not create personal profiles of the individual users of the site.
Personal data
No personal profiles are created in this site and no information is collected about each user personally. No data are provided about third parties.
The page "contacts" provides a form to send an e-mail notification. At this point we are using a third-party service (formspree.io). Please note that the information you enter (including your name, e-mail address and message) will be transfered via the servers of formspree.io. To be able to provide this service formspree.io stores the messages for a specific time period. Please visit formspree.io for more information.
If you do not want to use this third-party service please simply use email<EMAIL_ADDRESS>COLLECTED INFORMATION
In event that you have chosen to make use of the functionalities of our Web Site and to use the online services provided through it, you shall be required to present some personal data, as, for instance, name(s), telephone number, e-mail in conformity with the specifics of the service or your request. The collected information shall be processed by "Slavov detailing-auto" Sole-owned Limited Liability Company only aimed at the provision of services requested by you, enquiries submitted by you and the establishment of a connection with you as our customers.
You are not obligated and we do not require from you to provide personally recognizable (personal) information to view our Web Site or to realize access to its contents. You may find more information about the conditions for use of the Internet sites of "Slavov detailing-auto" Sole-owned Limited Liability Company in the General Conditions.
RIGHTS OF THE USERS
– right of access to your personal data, processed by "Slavov detailing-auto" Sole-owned Limited Liability Company right to request making appropriate correction, deletion or blockage of your personal data and the right to object at any time against the processing of your personal data when there are legal grounds for the purpose;
– right to refuse the processing of your personal data for the purposes of the direct marketing.
If you want to exercise your right of access to your personal data or to correct them, you may contact us through the enquiry form.
The manners for collection and exchange of personal information we use are:
– Enquiry form
– Name
The e-mail provided by you is used for the following purposes:
– For identification of your requests submitted through the contact form
Processing personal data of the Users with cooperation of competent state and/or municipal authorities at making verifications by them
– At the provision of public electronic communication services "Slavov detailing-auto" Sole-owned Limited Liability Company is the target of control on the part of various state and municipal authorities – for instance, the Commission for Consumer Protection (CCP), the Commission for Personal Data Protection (CPDP), the National Revenue Agency (NRA) and others. In the course of exercise of this control these authorities have the power to make verifications, as well as require from "Slavov detailing-auto" Sole-owned Limited Liability Company to provide information it has. It is possible that the required documents and information should contain personal data of the Users.
– Examples:
– With a received signal or a complaint of a User the CCP and the CPDP shall have the power to require from "Slavov detailing-auto" Sole-owned Limited Liability Company to present relevant for the case documents and information which may contain the following data: main data, data about the contracts, data about the obligations, data about the payments as well as data about communication with the relevant Users;
– At the conduct of a tax audit, the authorities of the NRA shall have the power to require from "Slavov detailing-auto" Sole-owned Limited Liability Company to present accounting documents which may also contain personal data about certain Users.
PROCESSING PERSONAL DATA IN CONNECTION WITH THE TAX AND THE ACCOUNTING LEGISLATION
– The tax and the accounting legislation in the Republic of Bulgaria requires "Slavov detailing-auto" Sole-owned Limited Liability Company to draw up certain accounting and commercial information, inclusive of storing this information for a certain defined term, as well as any other information and documents of significance for taxation.
– At the fulfillment of this obligation the relevant information and documents which also contain personal data of the Users shall be stored by "Slavov detailing-auto" Sole-owned Limited Liability Company for terms anticipated in the relevant laws. These terms are with big duration (for instance the invoices, which are documents for tax-security control, should be stored for a term of eleven years).
Cookies
Cookies are a package of information sent from a web server to Internet browser and after that returned from the browser each time when it receives access to this server. There are various kinds of cookies. They are with different validity and the minimal one is only up to the end of the session and the maximal one shall be within a term of 3 years, and their management is made through the settings of the browser of the User.
This website uses Google Analytics, a web analytics service provided by Google, Inc. (“Google”). Google Analytics uses “cookies”, which are text files placed on your computer to help the website analyse how visitors use the site. The information generated by the cookie about your use of the website (including your IP address) will be transmitted to and stored by Google on servers in the United States. Google will use this information for the purpose of evaluating your use of the website, compiling reports on website activity for website operators and providing other services relating to website activity and internet usage. Google may also transfer this information to third parties where required to do so by law, or where such third parties process the information on Google’s behalf. Google will not associate your IP address with any other data held by Google. You may refuse the use of cookies by selecting the appropriate settings on your browser, however please note that if you do this you may not be able to use the full functionality of this website. By using this website, you consent to the processing of data about you by Google in the manner and for the purposes set out above.
Please note that this website initializes Google Analytics with the setting anonymizeIp. This guarantees anonymized data collection by masking the last part of your IP address.
You can prevent Google’s collection and use of data (cookies and IP address) by downloading and installing the browser plug-in available under https://tools.google.com/dlpage/gaoptout?hl=en.
More information about Google Analytics’ terms and conditions of use and data privacy.
You may find more information about cookies and their management on the following link:
Information about cookies – https://www.aboutcookies.org/
We should warn you that the refusal from cookies may result in reduction of the functionalities of the Web Site as well as in deterioration of the quality of the service we render through it.
Protection
Encryption – To protect your personal data from misuse by third parties, the information provided by you is in an encrypted form through SSL (Secure Socket Layer) protocol. You may get assured of it from the availability of green with a padlock in the progress bar on your browser and from the fact that the URL address starts with “https”. For any questions about the use of personal data and their protection or for the withdrawal of the consent for their processing, contact us on the following e-mail: interiorauto@abv.bg


Disclaimer: All pizza is good!
Click to go to Results Page
Hi Im Krusty!!
Welcome to the Pizza Tracker, Choose wisely....
What is your name?
Login


India consolidate position at the top
India have consolidated their position at the top of the ICC World Test Championship, reaching 360 points after completing a 2-0 series victory over Bangladesh.
India have yet to drop a point in the nine-team championship. They won 2-0 in the West Indies and beat South Africa 3-0 in a home series before completing their third series win in the day-night Kolkata Test.
Each series is worth 120 points with the points distributed evenly over the number of matches in a series.
The points range from 60 points for each match of a two-Test series to 24 for each match of a five-Test series.
Australia are on 116 points after winning the first match of their ongoing Test series against Pakistan. Australia and England had earlier settled for 56 points each from their five-match Ashes series, which ended in a 2-2 draw.
Sri Lanka and New Zealand are on 60 points each after drawing their two-match series 1-1. Pakistan are playing their first WTC series Down Under, while Bangladesh, West Indies and South Africa failed to get any points in their opening series.
The top two teams at the end of the league will play the final in the UK in June 2021 with the winners crowned the World Test Champions.
More on the WTC is available here. An FAQs document on the ICC World Test Championship is available here.


{% extends "users/layout.html" %} {% set active_page = 'players' %} {%block maincontent%}
| Player ID | Player Name | Create Date | Num Logons | Logon Date | Status |
|---|---|---|---|---|---|
| {{player.player_id}} | {{player.player_name}} | {{player.create_date | dt}} | {{player.num_logons}} | {{player.logon_date | dt}} | {{player.status}} |


Like many recommender
systems, we have the products, users, and rates that expose users (explicitly
or implicitly) products. Our task to predict the evaluation of products, which
have not yet assessed the user and thus to predict the products that can be highly
appreciated by the users, or products that may be of interest to users. (What
is the function of recommender systems - find products which may be of
potential interest to the user.)
It was necessary to develop
a recommender system that would:
As in any classic
recommender systems we have: 1) products, 2) users and 3) users ratings of
products.
For each product and user,
we define the vector in the N-dimensional space. Those. each product and each
user is represented by a point in our N-dimensional space. We are using two
spaces. One users space, a second - for products. (Vectors users IDs and
vectors products IDs).
We also use the data about
the user, the product evaluation in the construction of the model and in
obtaining results for the users of products ratings.
For example, for MovieLens
1M data set we use:
(See the source code.) It
should also be borne in mind that also the vectors used for users IDs and
products (size N).
Such data heuristically allow you to make more accurate rate of the users for the products. This data is converted into a vector:
For N-dimensional vectors
for each product / user, we use the following scheme using autoencoder-s.
Let me remind you that
autoencoder trained to compress data filed on its inputs and to provide input
data in a compressed form.
We use two autoencoders.
The input (and the target value), we provide the list in M (number equal to
5-7) entries, each of which is:
Thus, we get into the
process of learning (learning at each step) autoencoders at the inputs (and
target values), a list of estimates of M:
We also get, the first
autoencoder vector encodes a product ID, and the second vector encodes the user
ID.
In the minimum case, we can set (for the first autoencoder) vector only user IDs and evaluation. And for the second autoencoder -- only vector product identifiers and evaluation. Those, we not use the user data products and assessments. As shown in Fig. 1.
Fig. 1. Driving training
autoensoders when using the minimum data for training (only vector of user IDs,
product IDs of the vector and evaluation). Also scheme for vectors encoding
identifiers when autoencode.
They are obtained as
follows.
After several cycles of
training of autoencoders (about 100..1000), we put to the second autoencoder
value of a single user products ratings (for each user putting K different
options (24..64), or the values of users ratings for a single product for the
first autroencoder.
For example, for a single
user, we putted K options (random) product rates (second autoencoder), ie K
formed of different inputs for autoencoder. At the same time we got the K
different values autoencoder-compressed and received at work.(That is, we have
K vectors of partial user IDs.) (It is clear that we must build a autoencoder,
which would have a middle layer consisting of N elements, that would be equal
to the size of the vector user/product IDs.) We find the average of these K
values. This will be the new value of the user ID vector, to which we will move
from the current value of the user ID vector. So we are doing for a number of (L1)
users and obtain averages.
Similarly, we obtain the
average L2 values of autoencoder-compressed values, trained on users opinions
(or encoding product identifiers).
If initially we use a
random value vector IDs of users and products, we can move from our original
values to the received L1 and L2 average compressed (average compressed will be
the new target vectors identifiers).
We use heuristics to smooth
the movement of the target values of IDs. We are gradually changing the vector
of users and products IDs to the target values of the vectors obtained users
and products IDs.
In order to obtain
satisfactory values for the vectors of users and the products IDs we must
consider another aspect of autoencoders - is the "breath" or coded
values or swimming group of values within certain limits. At the
"breath" of encoded values autoencoders all received values move to a
some bias. As a result, if we will use the encoded values without any
correction, the vectors will be difficult to converge identifiers. This problem
is solved quite easily. As this is done, I will not describe in detail. This
point is resolved by finding new secondary displacement vectors obtained of
users/products IDs relative to the previous value of the vector users/products
IDs. And correction of previous vector values IDs further carried out without
taking into account the average displacement. (See source code for more
information.)
When we have IDs, they are
ordered in the N-dimensional space of the users or the products. Related
products/users (based on user ratings) are at a short distance of (Euclidean
metric). Next, we can use a neural network for the prediction function on: 1)
the vector product ID; 2) data on the product; 3) ratings data (not the rates
itself, but, for example, day of week / time when the user wants to see / have
watched the film); 4) vector user ID; 5) user data. Using these data, we train
a neural network to predict the rating(s), which can give the user to the
product under given conditions.
We reiterate our training
of autoencoders and neural network to approximate the function by the user
evaluation of the product. There are some nuances of cold start training of
autoencoders of random initial values. The proposed heuristics for the solution
of these problems can be found in the proposed source code for this article.
After the training, we have
a model consisting of usera and products IDs, of neural networks - two
autoencoders and neural network for prediction of ratings.
After learning system, we
can predict the ratings for products that are not rated by users.
But it is also an important
point is the possibility that we can:
To calculate the vectors of
the new identity we use autoencoders of the resulting model. In this case, we
use the same process as the process of obtaining identifiers of the vectors in
the training model, except that we do not teach autoencoders on the new data,
but only calculates the identifiers.
The process of calculating
the identifiers can be used and when new estimates. In this case, we can adjust
identifiers. In the framework of the already trained model, ie, again not
retrain / train no further autoencoders.
When calculating/correcting
identifiers, we, of course, in order to adjust the processing speed, we do not
correct the part of the model given by neural networks. But the new data may
change/extend the model, so that such a change/extension can not be expressed
only in the calculation of the vectors of users and products IDs, so a good
heuristic can be additional training model through a certain period of time
(once a day / week / month / quarter ). This additional training can be done in
parallel within the prediction system rates, while adding of new products,
users, new rates.
In addition to solving
problems, putting in the problem, as this approach makes it possible to enter
into the machine learning system memory. Here, the memory can be immediately
understood the calculated identifiers. The model can represent the objects of
the external world, bearing in itself a description of the external world from
the point of view of the system (some systems rates of data objects). This IDs
can be used to describe system objects.
In addition, this approach
makes it possible to set a large number of parameters that define the vectors
of users and products IDs, as well as ratings parameters.


WISP
Legend
Tea
Coffee
Pizza
Meat
Beef
Thai
Chinese
WISP
version: 0.0.8-beta
©Jimut Bahan Pal
Author : jimutbahanpal@yahoo.com


I am 17 years old and have been using drugs for a couple years now: marijuana, acid, mushrooms, MDMA, LSA, cocaine, codiene, DXM, salvia, various prescription drugs etc.
I smoke pot more than anything else. I was recently diagnosed as 'Depressed' and I have found my over all mood to be better during weeks that I smoke more pot, this is including things like my grades being better during months of heavy use. I have stopped most drug use except for the occasional trip or special party. (I do not consider marijuana to be a drug in the causual sense)
My psychiatrist perscribed me Remeron 3 weeks ago. I take 50 mg every night, which is a mid level dose for treating depression. A strange side effect of Remeron is that it causes increase in apetite, which is helpful for me because i was losing weight due to low grade nausea that was never explained by my doctors. It was dismissed as chemical imbalance, somthing to do with my neuron receptors.
I find that the medication causes very vivid dreams every night resulting (at least for me) in a very relaxed deep sleep. I wake up much more energized, at least after the groggyness fades with a warm shower.
The interaction of Remeron with marijuana is an interesting one. My high tends to be much trippier in the visual sense and tends to last longer than a normal high. When ever i smoke high quality bud or hash, i tend to get beautiful closed eye visuals and some mild open eye hallucinations. The only down side is that I usually fall asleep within 30 min.
My mood is at an all time high. The medication seems to affect ones contentment with everything in general as well. It is easy now for me to turn down a drug or even some delicious dessert, I feel more in tune with my body than ever before.
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.


'Brooklyn Nine-Nine's' Melissa Fumero expecting second child
by Wade SheridanNov. 18 (UPI) -- Brooklyn Nine-Nine star Melissa Fumero has announced on Instagram that she is expecting her second child with husband David Fumero of Power fame.
"Oh yeah, I'm hella pregnant. To be honest, I haven't felt like posting about it because this pregnancy has been way harder and... I don't feel that cute?" the actress said on Sunday alongside a photo of herself displaying her baby bump.
"But yesterday I got a really intense massage, an awesome chiropractic adjustment, and my hair feels thicker... so I feel a little bit cute today. #herewegoagain #babyboynumerodos," she continued.
Melissa Fumero and David Fumero are already parents to 3-year-old son Enzo who arrived in March 2016.
The couple met on the set of One Life to Live and were married in 2007.
Melissa Fumero portrays Amy Santiago on Brooklyn Nine-Nine with NBC recently renewing the comedy series for an eighth season.
(0) Leave a comment
upi.com/6960070
Latest Headlines
Music // 45 minutes ago
Kanye West announces opera show, 'Nebuchadnezzar'
Nov. 18 (UPI) -- Kanye West is set to hold his first opera show titled "Nebuchadnezzar" at the Hollywood Bowl in Los Angeles on Sunday.
Music // 1 hour ago
Chris Brown, Lizzo win big at 2019 BET Soul Train Awards
Nov. 18 (UPI) -- Chris Brown and Lizzo won big at 2019 BET Soul Train Awards, dominating the event's major categories.
Entertainment News // 1 hour ago
Street Fighter V: Champion Edition' announced with new character Gill
Nov. 18 (UPI) -- Developer and publisher Capcom is set to release a new version of "Street Fighter V" titled Champion Edition and a new character for the fighting game, Gill.
Entertainment News // 6 hours ago
Famous birthdays for Nov. 18: Margaret Atwood,
Nov. 18 (UPI) -- Author Margaret Atwood turns 80 and actor Chloe Sevigny turns 44, among the famous birthdays for Nov. 18.
Entertainment News // 6 hours ago
Hulu: What's coming and going in December 2019
Nov. 18 (UPI) -- "How to Train Your Dragon: Homecoming" and new seasons of "Younger," "Marvel's Runaways" and "Killing Eve" are headed to Hulu.
Music // 18 hours ago
Donny and Marie Osmond perform final show of 11-year Las Vegas residency
Nov. 17 (UPI) -- Brother-sister entertainers Donny and Marie Osmond ended their 11-year residency in Las Vegas this weekend.
TV // 18 hours ago
'General Hospital' stars to attend Graceland fan convention in January
Nov. 17 (UPI) -- Stars of the ABC soap opera "General Hospital" are confirmed to take part in a 2nd annual fan celebration at the late Elvis Presley's estate in Memphis this winter.
TV // 19 hours ago
'Fuller House' stars celebrate series wrap with karaoke
Nov. 17 (UPI) -- Production on the fifth and final season of the sitcom "Fuller House" is now complete.
Movies // 20 hours ago
'Ford v Ferrari' tops the North American box office with $31M
Nov. 17 (UPI) -- The Christian Bale-Matt Damon racing drama "Ford v Ferrari" is the No. 1 movie in North America, earning $31 million in receipts this weekend, BoxOfficeMojo.com announced Sunday.
TV // 20 hours ago
Harry Styles plays dog who becomes human on 'SNL'
Nov. 17 (UPI) -- British pop star Harry Styles sang and performed in comedy sketches as the guest host of this weekend's edition of "Saturday Night Live. "


Weightlifting Journal is an app that allows you to keep track of your workouts. Information such as sets, reps, exercise, and body region can all be saved, reviewed, updated, and deleted. So what are you waiting for? Sign up today! It’s FREE!


<EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS>An error has occurred when calculating your pay
An Error Has Occurred
{{ @SESSION.results->getTotal() }}


--- author: Nathaniel categories: - Links - Not data date: "2014-10-09T01:10:15Z" meta: _edit_last: "1" pe_theme_meta: O:8:"stdClass":2:{s:7:"gallery";O:8:"stdClass":3:{s:2:"id";s:2:"89";s:5:"width";s:0:"";s:6:"height";s:0:"";}s:5:"video";O:8:"stdClass":1:{s:2:"id";s:3:"262";}} published: true status: publish tags: - articles - links title: On developmentalism, planning, & early big data in Allende's Chile. type: post ---
"In Allende’s Chile, a futuristic op room was to bring socialism into the computer age."
``The consultant, Stafford Beer, had been brought in by Chile’s top planners to help guide the country down what Salvador Allende, its democratically elected Marxist leader, was calling `the Chilean road to socialism.' Beer was a leading theorist of cybernetics—a discipline born of midcentury efforts to understand the role of communication in controlling social, biological, and technical systems. Chile’s government had a lot to control: Allende, who took office in November of 1970, had swiftly nationalized the country’s key industries, and he promised “worker participation” in the planning process. Beer’s mission was to deliver a hypermodern information system that would make this possible, and so bring socialism into the computer age. The system he devised had a gleaming, sci-fi name: Project Cybersyn.''


Jewellery store ring display has people in stitches as it looks rather x-rated
Typically engagement rings are associated with romance and elegance, but one jewellery store has left people red-faced after one of it's ring displays ended up looking rather rude
by Courtney Pochin, https://www.facebook.com/courtneypochinmirror/?modal=admin_todo_tourThese days people on the internet love to spend time shaming just about anything.
Most common are perhaps wedding shaming and ring shaming, but in an interesting twist, members of a ring shaming group on Facebook have been mocking something other than a piece of jewellery.
In a post on the group, That's It, I'm Ring Shaming, someone shared an image of a diamond engagement ring and wedding band on a grey stand that looked rather x-rated, reports The Sun.
They said: "I don't like the ring, but I hate the presentation."
People were quick to suggest that the ring holder resembled a "penis".
One person joked: "It's a grower, not a shower."
Someone else wrote: "I've heard of a c*** ring but..."
A third person added: "Is that ring happy to see me or is it just my imagination?"
A different user quipped: "Takes 'if you like it then you should have put a ring on it' to a new level!"
"It's trying it's best," replied another.
And in other weird news, a man recently hit the headlines for turning his nail clippings into an engagement ring.
Yes, really.
The man, who creates videos on YouTube under the name Kiwami Japan, saved his nail clippings for an entire year to create the one-of-a-kind piece of jewellery.
The whole process was shared on Twitter in a disturbing viral video by SCMP News.
Once he had collected a sufficient amount of clippings, the man started by putting them into a blender.
However, this didn't give the desired consistency, so he then ground them into a very fine powder, before mixing with water in a pan.
The fourth step saw him compress the nail powder and water mixture and put it into an oven for 90 minutes.
What came out of the oven can only be described as looking like a lump of dark clay.
The man took the mixture and put it into a diamond-shaped mould before inserting it into a silver ring - which he also made himself.
When all was done, the finished product was a ring with a dull black stone, which thankfully looked nothing like fingernails.


Subject: ${subject}
|
||||||||||||||||||||||||||||||||||||||
| Adobe, the Adobe logo, Adobe Experience Cloud, and the Adobe Experience Cloud logo are either registered trademarks of Adobe in the United States and/or other countries. 2017 Adobe systems Incorporated. All rights reserved. |


View 1
View 2
View 3
Carousel slide view
A slider showing a slider with existing views
The element below defines a carousel
https://materializecss.com/carousel.html
https://materializecss.com/getting-started.html
https://materializecss.com
W


Start-ups in L.A. and Orange counties
Data from
L.A. Times
- News Story:
Hollywood is giving tech start-ups the star treatment
.


For ideal MHD perturbation, the perturbed magnetic field is written as
Using Eq. (142), the vector potential of magnetic perturbation is
written as
|
(144) |
Using Eq. (143), the parallel component of the magnetic perturbation
is written as
Here I have some important remarks about tensor identities (I had not known
these identities before CaiHuiShan told me). First we note the associate law
applies in this case (Important!), thus
|
(146) |
Second we have the tensor identity (Important!, CaiHuiShan let me know this
identity),
|
(147) |
Using this, the second term of Eq. (146) is written as
where
. The last
term of Eq. (146) is written as
We note that
(CaiHuiShan let me
know this), since the tensor identity in Eq. (147) indicates
|
(150) |
(It is interesting to note that
while the above result proves that
.) Thus Eq. (149) becomes
Using the above results, the parallel component of the perturbed magnetic
field Eq. (146) becomes
|
(152) |
The perturbed Lagrangian, Eq. (133), is
|
(153) |
Using Eq. (144) in Eq. (153) yields
|
(154) |
Using Eq. (78) for
, Eq. (154)
is written as
Equation (155) agrees with Eq. (55) in Porcelli's
paper[1]. The perturbed electrical field is
|
(156) |
On the other hand,
can be expressed as
Comparing Eqs. (156) and (157), we obtain
|
(158) |
which indicates the perturbed scalar potential is a constant. We can choose
. We consider the case that there is no electrical field in
the equilibrium, i.e.,
. Using
and
, the Lagrangian in Eq. (155) is written as
|
(159) |
Substituting the expression of
in Eq. (152)
into the above equation, we obtain
We note an important fact that magnetic curvature
is
perpendicular to
. This is because that
. The last equality is due to the vector identity
=
. Using this fact, Eq. (160) can also be written as
|
(161) |
Eq. (161) agrees with Eq. (58) in Porcelli's
paper[1].
YouJun Hu
2014-05-19


A competent professional with 3 years experience in Machine Learning. Fluent in Python
This is purely educational data mining project, the problems of dropout and school violence remain persistent challenges within high school education.In this paper, we present a case study on automatically detecting these indicators of student at-risk status in one diverse school district in Texas.Predict these constructs from data on students’ discipline, attendance, course taking, and grades, using a logistic regression framework. Implemented data analysis and machine learning to predict student performance and created model to analysis for future outcomes on student’s results
The aim of the project is to build a Data lake, which will be the single source of information for all
functional areas. It will help to provide 360 view of a customer and provide personalized, real-time
advertisements across all the channels. Project will reduce the marketing budget and improve the sales
exponentially.
Created static website using flask and performed some of constituency pre-election analysis using
social communication data
Created an web application using python in flask framework, this application is used for ticketing tool
SGPA: 6.5
SGPA: 7.56
Apart from being a Data Analyst, I enjoy most of my time being outdoors.
Other hobbies are Endurance Sports,Creative Hobbies,Team Sports,Strategic Games, Creative Writing,Reading, Museums, Libraries,Community Group Involvement


I’m Rae Moord, a happy human focused on web design, front-end development & print media. I'm passionate about utilizing a user-centric approach to build intuitive & straightforward websites. I have an eye for detail and use it to create clean & artful designs. My clients are my partners. Together, we collaborate to create beautifully designed websites and stunning print media. My goal is to create designs and websites you love!
When I’m not online, you can find me dreaming about all the places I want to travel, reading, binge watching old episodes of Fringe, and drinking cup after cup of coffee. Check out my portfolio to see my projects. Thanks for stopping by!


|
|||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | ||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Object com.googlecode.batchfb.FacebookBatcher
public class FacebookBatcher
Primary implementation of the Batcher interface.
| Field Summary | |
|---|---|
static java.lang.String |
GRAPH_ENDPOINT
Base URL for the graph api |
| Constructor Summary | |
|---|---|
FacebookBatcher(java.lang.String accessToken)
Construct a batcher with the specified facebook access token. |
| Method Summary | ||
|---|---|---|
Later<java.lang.Boolean> |
delete(java.lang.String object)
Enqueue a delete call to the Graph API. |
|
void |
execute()
Executes all existing batches and removes them from consideration for further batching. |
|
static java.lang.String |
getAccessToken(java.lang.String clientId,
java.lang.String clientSecret,
java.lang.String code,
java.lang.String redirectUri)
Get a user access token from Facebook. |
|
static java.lang.String |
getAppAccessToken(java.lang.String clientId,
java.lang.String clientSecret)
Get the app access token from Facebook. |
|
org.codehaus.jackson.map.ObjectMapper |
getMapper()
Get the Jackson mapper which will be used to transform all JSON responses into objects. |
|
int |
getRetries()
Gets the number of retries to execute when a timeout occurs. |
|
int |
getTimeout()
Gets the connection/read timeout in milliseconds, or 0 for "no timeout". |
|
|
graph(java.lang.String object,
java.lang.Class<T> type,
Param... params)
Enqueue a Graph API call. |
|
GraphRequest<org.codehaus.jackson.JsonNode> |
graph(java.lang.String object,
Param... params)
Enqueue a Graph API call. |
|
|
graph(java.lang.String object,
org.codehaus.jackson.type.TypeReference<T> type,
Param... params)
Enqueue a Graph API call. |
|
|
paged(java.lang.String object,
java.lang.Class<T> type,
Param... params)
Enqueue a Graph API call to an endpoint that results in paginated data. |
|
|
post(java.lang.String object,
java.lang.Class<T> type,
Param... params)
Enqueue a post (publish) call to the Graph API. |
|
Later<java.lang.String> |
post(java.lang.String object,
Param... params)
Enqueue a post (publish) call to the Graph API. |
|
QueryRequest<org.codehaus.jackson.node.ArrayNode> |
query(java.lang.String fql)
Enqueue a FQL call. |
|
|
query(java.lang.String fql,
java.lang.Class<T> type)
Enqueue a FQL call. |
|
Later<org.codehaus.jackson.JsonNode> |
queryFirst(java.lang.String fql)
Just like query(), but retrieves the first value from the result set. |
|
|
queryFirst(java.lang.String fql,
java.lang.Class<T> type)
Just like query(), but retrieves the first value from the result set. |
|
void |
setMaxBatchSize(int max)
Maximum number of graph requests to put in a single batch. |
|
void |
setRetries(int count)
Sets the number of retries to execute when a timeout occurs. |
|
void |
setTimeout(int millis)
Sets the connection timeout in milliseconds. |
| Methods inherited from class java.lang.Object |
|---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Field Detail |
|---|
public static final java.lang.String GRAPH_ENDPOINT
| Constructor Detail |
|---|
public FacebookBatcher(java.lang.String accessToken)
accessToken
- is required; you cannot make unauthenticated batch FB requests| Method Detail |
|---|
public static java.lang.String getAppAccessToken(java.lang.String clientId, java.lang.String clientSecret)
https://developers.facebook.com/docs/authentication/
public static java.lang.String getAccessToken(java.lang.String clientId, java.lang.String clientSecret, java.lang.String code, java.lang.String redirectUri)
https://developers.facebook.com/docs/authentication/
public org.codehaus.jackson.map.ObjectMapper getMapper()
public void setTimeout(int millis)
public int getTimeout()
public void setRetries(int count)
public int getRetries()
public void setMaxBatchSize(int max)
Maximum number of graph requests to put in a single batch. As you add more things to a single batch, the time FB takes to return it gets longer. You must balance this with timeout and retries to obtain optimum performance and reliability.
Default value is the Facebook max, 20.
Note that you can have virtually unlimited FQL calls.
public <T> GraphRequest<T> graph(java.lang.String object, java.lang.Class<T> type, Param... params)
Batcher
graph
in interface Batcher
object
- is the object to request, eg "me" or "1234". Doesn't need to start with "/".type
- is the type to map the result toparams
- are optional parameters to pass to the method.public <T> GraphRequest<T> graph(java.lang.String object, org.codehaus.jackson.type.TypeReference<T> type, Param... params)
Batcher
graph
in interface Batcher
object
- is the object to request, eg "me" or "1234". Doesn't need to start with "/".type
- is the Jackson type reference to map the result to (see the BatchFB UserGuide).params
- are optional parameters to pass to the method.public GraphRequest<org.codehaus.jackson.JsonNode> graph(java.lang.String object, Param... params)
Batcher
graph
in interface Batcher
object
- is the object to request, ie "me" or "1234". Doesn't need to start with "/".params
- are optional parameters to pass to the method.public <T> PagedLater<T> paged(java.lang.String object, java.lang.Class<T> type, Param... params)
Batcher
Enqueue a Graph API call to an endpoint that results in paginated data. Any of the Facebook "connections" fit this pattern; the results look like:
{ data:[{...},{...}], paging:{previous:"http://blahblah", next:"http://blahblah"} }
The PagedLater> returned from this method can be used to navigate forwards and
backwards in the pagination. For example, you could have a PagedLater
paged
in interface Batcher
object
- is the connection object to request, eg "me/friends" or "1234/feed". Doesn't need to start with "/".type
- is the type of the element that will be paged acrossparams
- are optional parameters to pass to the method.public <T> QueryRequest<java.util.List<T>> query(java.lang.String fql, java.lang.Class<T> type)
Batcher
query
in interface Batcher
fql
- is the query to run, which can include previously named query resultstype
- is what the contents of the resulting list will be mapped topublic QueryRequest<org.codehaus.jackson.node.ArrayNode> query(java.lang.String fql)
Batcher
query
in interface Batcher
fql
- is the query to run, which can include previously named query resultspublic <T> Later<T> queryFirst(java.lang.String fql, java.lang.Class<T> type)
Batcher
queryFirst
in interface Batcher
public Later<org.codehaus.jackson.JsonNode> queryFirst(java.lang.String fql)
Batcher
queryFirst
in interface Batcher
public Later<java.lang.Boolean> delete(java.lang.String object)
Batcher
delete
in interface Batcher
public Later<java.lang.String> post(java.lang.String object, Param... params)
Batcher
post
in interface Batcher
params
- can include a BinaryParam to post binary objects.public <T> Later<T> post(java.lang.String object, java.lang.Class<T> type, Param... params)
Batcher
post
in interface Batcher
type
- defines the expected return type from the call.params
- can include a BinaryParam to post binary objects.public void execute()
execute
in interface Batcher
|
|||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | ||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |


{{ site.user_description }}
My Master's dissertation research focused on consumer conceptions of authenticity in entertainment, tourism, and educational environments. This work, alongside my ethnographic study of workplace culture on river barges has equipped me with a holistic methodological approach to business-centered research objectives.
I am experienced in research design, data analysis, grant applications, and academic/educational writing. During my time conducting field studies I have also learned about and applied various interviewing and data collection techniques.
I have experience with many data analysis and transformation tools including SPSS, Python, UCINet, Excel. My experiences using cutting-edge tools have taught me to work with data efficiently and effectively.


Chinese Literature in English
September 18th
Questions from last time?
Li Sao 離騷
On Encountering Sorrow
Chu ci 楚辭
Songs of the South
From Hawkes, "Songs of the South" p. 1
Qu Yuan 屈原
The Style
xi 兮
Text of the Lisao
Point of View
Interpretation
Reflection of Chu Culture
The Poem
Open Discussion


Sandusky expected in court for new sentencing in abuse case
BELLEFONTE, Pa. (AP) — Former Penn State assistant football coach Jerry Sandusky is expected in a Pennsylvania courtroom to be resentenced after an appeals court said mandatory minimum sentences had been improperly applied against him.
The 75-year-old Sandusky will be resentenced Friday by Judge Maureen Skerda at the county courthouse in Bellefonte.
State Superior Court in February rejected many of Sandusky’s arguments but determined the sentencing was flawed.
Sandusky was convicted of 45 counts of child sexual abuse in 2012 and sentenced to 30 to 60 years. It’s unclear whether Skerda will issue a significantly different sentence.
Court filings in recent week indicate that there may also be argument about Sandusky’s designation as a sexually violent predator.


John Doe
4242 Ghila Road
Tucson, AZ 85701
Profile
Desires a resident position in the Bastyr University Acupuncture and Oriental
Medicine Residency Program. Able to be effective in a practice of any size.
Draw on experience with a range of patient issues, including additional work
in women and children’s care. Interested in health education for homeless.
Strong desire to contribute to the success of a program through an ability to
initiate and maintain relationships. Creative developer and presenter of
educational information.
Education
Masters of Acupuncture and Oriental Medicine,
Graduating June 2003
Bastyr University, Kenmore, WA 1999
-
Completing an accredited program of coursework and supervised
practice
in Acupuncture and Oriental Medicine. Extensive exposure to issues
involving
women and children.
Research Project
-
Assisted the primary investigator in a double blind, randomized
controlled
trail conducted at the Bastyr Center for Natural Health that evaluated
the
effectiveness of Chinese herbs towards the control of Diabetes
Mellitus in
post-menopausal women. Co-authored the research report that has
been
submitted for publication to the Journal of Traditional Chinese
Medicine.
Bachelor of Science, Zoology
Miami University, Oxford, OH 1991 - 1995
-
Participated in a community service project to increase citizen
participation
in a clean up campaign.
-
Served as project leader in a fund raising project sponsored by the
University
Student Council towards helping homeless youthsâ€™ return back to
school.
Related Experience
Bastyr University, Kenmore, WA 1999-present
Teaching Assistant
-
Assists professor in the Anatomy & Physiology class.
-
Answers questions and demonstrate as needed.
Kenmore Youth Ministry, Kenmore, WA 2000-2001
Camp Group Leader
-
Participated in community youth group activities.
-
Developed activity programs now utilized by the youth ministry in
helping
children improve reading skills.
Franciscan Care Center Nursing Home,
Seattle, WA 1999 - 2000
Volunteer Recreation Worker
-
Provided social support to patients by reading to them, writing letters,
and visiting with them.
-
Formed friendships which enriched lives of patients


Home
Bowls & Trays
Click on an image to add the item to your wishlist
Asian Dream Open Vegetable Bowl
Medusa Prisma Clear Ashtray


--- layout: homesimple title: 404 Not Found sitemap: false ---
The requested URL was not found.
Return Home


Departments of Centre College
Come and see the adventure that awaits you at Centre College.
Studio Art
Economics
Politics
Computer Science
Mathematics


Help & Support
New Quiz
/ Enter basic informations about new quiz.
0/100
*Quiz Name:
You need to enter title
Quiz Image:
Upload Icon
Drop Image to Upload
or
click here
0/100
*Quiz Title:
You need to enter title
0/500
*Quiz Description:
You need to enter description
*Call to Action:
Start My Quiz
View My Quiz
Show My Quiz
Google Analytics ID:
Segment:
Do not use integration
Do not use integration
Do not use integration
Social Sharing:
Enabled
Disabled
Start Page:
Enabled
Disabled
Go Back
Live Preview
How Effective Is Your Weight Loss Program?
Take The Weight Loss Quiz And Determine How Much Weight You Can Lose.


sbigtopgm(1) sbigtopgm(1) NAME sbigtopgm - convert an SBIG CCDOPS file into a portable graymap SYNOPSIS sbigtopgm [sbigfile] DESCRIPTION Reads an an image file in the native format used by the Santa Barbara Instrument Group (SBIG) astronomical CCD cameras, and produces a portable graymap as output. Additional information on SBIG cameras and documenta‐ tion of the file format is available at the Web site: http://www.sbig.com/ SEE ALSO pgm(5) AUTHOR John Walker (http://www.fourmilab.ch/), January 1998. This program is in the public domain. 23 January 98 sbigtopgm(1)


Name: Date of Bookings: Movie: K.G.F Kabir Singh Sultan Show Timings: 12 A.M 4 A.M 8 A.M 12 P.M Select Class: Platinum Gold Exclusive Price: No. of Tickets: Total Price: Submit Reset


0
157
10:00
12
0
157
10:00
12
5
Settings
Pause
Double
Roll
Pass
Take
Pass
Done
Undo
Opening Roll
You WIN and the MATCH
Get
2
pt
7
-
5
(
9
pt)
Next
OK


|
|||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | ||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Object befungeinterpreter.BefungeProgram
public class BefungeProgram
This class represents a Befungeprogram and is able to execute it step by step.
There are some minor differences to the original Language Specifications:
| Field Summary | |
|---|---|
static int |
CODE_CHANGED
|
static int |
COLS
The number of columns and rows a Befunge Program has. |
static int |
NEW_OUTPUTS
|
static int |
PROGRAM_ENDS
|
static int |
PROGRAM_OK
|
static int |
ROWS
The number of columns and rows a Befunge Program has. |
static int |
WAITS_FOR_INPUT
|
| Constructor Summary | |
|---|---|
BefungeProgram(java.io.OutputStream out,
java.io.InputStream in)
Creates a new instance of BefungeProgram. |
| Method Summary | |
|---|---|
boolean |
changedSinceLastSave()
Returns wether setCellAt() ha been called after the last call of saveFile(). |
void |
clear()
Clears the program, i.e. sets every cell to ' '. |
BefungeStack |
getBefungeStack()
|
long |
getCellAt(int col,
int row)
Returns the character or the command in the given column and row. 0, 0 refers to the upper-left command. |
PC |
getPC()
Returns the Program Counter. |
void |
loadFile(java.lang.String file)
Loads a Befungefile from a textfile. |
int |
nextStep()
Does the next step in interpreting the Befunge program. |
void |
reset()
Restarts the program, i.e. puts the Program Counter (PC) into the upper-left corner, pointing to the right and clears the stack. |
void |
restoreProgram()
Restores the program to the state it was at the last call of saveProgram. |
void |
saveFile(java.lang.String file)
Saves a Befunge Program on the hard drive. |
void |
saveProgram()
Creates a copy of the current Program. |
void |
setCellAt(byte c,
int col,
int row)
Changes the character or the command in the given column and row. 0, 0 refers to the upper-left command. |
| Methods inherited from class java.lang.Object |
|---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Field Detail |
|---|
public static final int COLS
public static final int ROWS
public static final int CODE_CHANGED
public static final int NEW_OUTPUTS
public static final int WAITS_FOR_INPUT
public static final int PROGRAM_ENDS
public static final int PROGRAM_OK
| Constructor Detail |
|---|
public BefungeProgram(java.io.OutputStream out, java.io.InputStream in)
out
- The Writer where the output is written into.| Method Detail |
|---|
public long getCellAt(int col, int row)
public void setCellAt(byte c, int col, int row)
public int nextStep() throws befungeinterpreter.SyntaxErrorException, befungeinterpreter.ProgramExecutionException, java.io.IOException
befungeinterpreter.SyntaxErrorException
befungeinterpreter.ProgramExecutionException
java.io.IOException
public void reset()
public void clear()
public void loadFile(java.lang.String file) throws java.io.IOException
java.io.IOException
public void saveFile(java.lang.String file) throws java.io.IOException
java.io.IOException
public boolean changedSinceLastSave()
public void saveProgram()
public void restoreProgram()
public PC getPC()
public BefungeStack getBefungeStack()
|
|||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | ||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |


Alan has been making pixel art for almost ten years and is the chief concept artist, background artist, UI/UX designer and sprite artist for SpellCasters. The look and feel of the game and site are his creation. He also handled devops and server architecture.
Bryan worked for a small web development company for a year while completing his last year of college. Afterwards, he headed out to Hawaii to grow as a Full Stack Developer. He is a recent graduate of Devleague.
In the SpellCasters application, Bryan created and implemented the Postgres database, user login, and user registration. He also created the user profile and the D3 graphs for percent and total words completed.
Marta has been designing applications and architecture in the private sector as a professional project manager for more than a decade. Marta focused on Spellcasters' back-end functionality, including database design, user interface, and validations. She also implemented the bubble chart on the user profile. She is a recent graduate of Devleague cohort 13.
Renee began coding in college and recently began pursuing her career aspiration of becoming a Full-Stack Web Developer. She is also a graduate of Devleague's cohort 13.
For SpellCasters, Renee created the soundtrack, integrated music and sound effects, and assisted with game logic. She also created the APIs for spells, individual user statistics, and leaderboard statistics. Additionally, she created the scoring algorithm.
Megan is a professional animator who provided additional concept art as well as roughs for the motion design of SpellCasters' character animations.


Police nab seven suspects after scam delivers safe with fake cash
by Nicole McCainKwaZulu-Natal police have arrested seven men after a woman was handed a safe full of fake money in an apparent scam.
In March a woman was allegedly convinced by the suspects to resign from her job and hand over her savings, which the suspects would then invest on her behalf for "massive returns", explains provincial police spokesperson Colonel Thembeka Mbele.
When the woman was handed a safe, expecting to receive the return on her investment, she instead found it to contain counterfeit money and papers, Mbele says.
Following the incident, a case of theft was opened at Ladysmith Police Station for investigation.
READ MORE: Quick-thinking cops save Eastern Cape man from alleged scam
On Wednesday, police officers from Uthukela Cluster and Vryheid made the arrest of seven suspects, who are being charged with being in the possession of suspected stolen property. Police confiscated an undisclosed amount of cash, counterfeit money, 15 cellphones, a laptop, different bank cards and two brand new vehicles.
KwaZulu-Natal Provincial Commissioner, Lieutenant General Khombinkosi Jula, has applauded the investigators for arresting the suspects.
“We receive these kinds of complaints and we always caution people to refrain from trusting strangers with their hard-earned money.”


Elixir v1.3.4 OptionParser
This module contains functions to parse command line options.
Summary
Functions
Low-level function that parses one option
Parses argv
into a keywords list
The same as parse/2
but raises an OptionParser.ParseError
exception if any invalid options are given
Similar to parse/2
but only parses the head of argv
;
as soon as it finds a non-switch, it stops parsing
The same as parse_head/2
but raises an OptionParser.ParseError
exception if any invalid options are given
Splits a string into argv chunks
Receives a key-value enumerable and converts it to argv
Types
Functions
Low-level function that parses one option.
It accepts the same options as parse/2
and parse_head/2
as both functions are built on top of this function. This function
may return:
{:ok, key, value, rest}
- the optionkey
withvalue
was successfully parsed{:invalid, key, value, rest}
- the optionkey
is invalid withvalue
(returned when the value cannot be parsed according to the switch type){:undefined, key, value, rest}
- the optionkey
is undefined (returned in strict mode when the switch is unknown){:error, rest}
- there are no switches at the head of the givenargv
Parses argv
into a keywords list.
It returns a three-element tuple with the form {parsed, args, invalid}
, where:
parsed
is a keyword list of parsed switches with{switch_name, value}
tuples in it;switch_name
is the atom representing the switch name whilevalue
is the value for that switch parsed according toopts
(see the “Examples” section for more information)args
is a list of the remaining arguments inargv
as stringsinvalid
is a list of invalid options as{option_name, value}
whereoption_name
is the raw option andvalue
isnil
if the option wasn’t expected or the string value if the value didn’t have the expected type for the corresponding option
Elixir converts switches to underscored atoms, so --source-path
becomes
:source_path
. This is done to better suit Elixir conventions. However, this
means that switches can’t contain underscores and switches that do contain
underscores are always returned in the list of invalid options.
Without any options, this function will try to parse all switches in the argv
.
iex> OptionParser.parse(["--debug"])
{[debug: true], [], []}
iex> OptionParser.parse(["--source", "lib"])
{[source: "lib"], [], []}
iex> OptionParser.parse(["--source-path", "lib", "test/enum_test.exs", "--verbose"])
{[source_path: "lib", verbose: true], ["test/enum_test.exs"], []}
Switches followed by a value will be assigned the value, as a string.
Switches without an argument, like --debug
in the examples above, will
automatically be set to true
.
Options
The following options are supported:
:switches
or:strict
- see the “Switch definitions” section below:aliases
- see the “Aliases” section below
Switch definitions
Often it is better to explicitly list the known switches and their formats. The switches can be specified via one of two options:
:switches
- defines some switches and their types. This function still attempts to parse switches that are not in this list.:strict
- defines strict switches. Any switch inargv
that is not specified in the list is returned in the invalid options list.
Both these options accept a keyword list of {name, type}
tuples where name
is an atom defining the name of the switch and type
is an atom that
specifies the type for the value of this switch (see the “Types” section below
for the possible types and more information about type casting).
Note that you should only supply the :switches
or :strict
option.
If you supply both, an ArgumentError
exception will be raised.
Types
Switches parsed by OptionParser
may take zero or one arguments.
The following switches types take no arguments:
:boolean
- sets the value totrue
when given (see also the “Negation switches” section below):count
- counts the number of times the switch is given
The following switches take one argument:
:integer
- parses the value as an integer:float
- parses the value as a float:string
- parses the value as a string
If a switch can’t be parsed according to the given type, it is returned in the invalid options list.
Modifiers
Switches can be specified with modifiers, which change how they behave. The following modifiers are supported:
:keep
- keeps duplicated items instead of overriding them; works with all types except:count
. Specifyingswitch_name: :keep
assumes the type of:switch_name
will be:string
.
Note that if you want to use :keep
with a type other than :string
, use a list
as the type for the switch. For example: [foo: [:integer, :keep]]
.
Negation switches
In case a switch SWITCH
is specified to have type :boolean
, it may be
passed as --no-SWITCH
as well which will set the option to false
:
iex> OptionParser.parse(["--no-op", "path/to/file"], switches: [op: :boolean])
{[op: false], ["path/to/file"], []}
Aliases
A set of aliases can be specified in the :aliases
option:
iex> OptionParser.parse(["-d"], aliases: [d: :debug])
{[debug: true], [], []}
Examples
Here are some examples of working with different types and modifiers:
iex> OptionParser.parse(["--unlock", "path/to/file"], strict: [unlock: :boolean])
{[unlock: true], ["path/to/file"], []}
iex> OptionParser.parse(["--unlock", "--limit", "0", "path/to/file"],
...> strict: [unlock: :boolean, limit: :integer])
{[unlock: true, limit: 0], ["path/to/file"], []}
iex> OptionParser.parse(["--limit", "3"], strict: [limit: :integer])
{[limit: 3], [], []}
iex> OptionParser.parse(["--limit", "xyz"], strict: [limit: :integer])
{[], [], [{"--limit", "xyz"}]}
iex> OptionParser.parse(["--verbose"], switches: [verbose: :count])
{[verbose: 1], [], []}
iex> OptionParser.parse(["-v", "-v"], aliases: [v: :verbose], strict: [verbose: :count])
{[verbose: 2], [], []}
iex> OptionParser.parse(["--unknown", "xyz"], strict: [])
{[], ["xyz"], [{"--unknown", nil}]}
iex> OptionParser.parse(["--limit", "3", "--unknown", "xyz"],
...> switches: [limit: :integer])
{[limit: 3, unknown: "xyz"], [], []}
iex> OptionParser.parse(["--unlock", "path/to/file", "--unlock", "path/to/another/file"], strict: [unlock: :keep])
{[unlock: "path/to/file", unlock: "path/to/another/file"], [], []}
The same as parse/2
but raises an OptionParser.ParseError
exception if any invalid options are given.
If there are no errors, returns a {parsed, rest}
tuple where:
parsed
is the list of parsed switches (same as inparse/2
rest
is the list of arguments (same as inparse/2
Examples
iex> OptionParser.parse!(["--debug", "path/to/file"], strict: [debug: :boolean])
{[debug: true], ["path/to/file"]}
iex> OptionParser.parse!(["--limit", "xyz"], strict: [limit: :integer])
** (OptionParser.ParseError) 1 error found!
--limit : Expected type integer, got "xyz"
iex> OptionParser.parse!(["--unknown", "xyz"], strict: [])
** (OptionParser.ParseError) 1 error found!
--unknown : Unknown option
iex> OptionParser.parse!(["-l", "xyz", "-f", "bar"],
...> switches: [limit: :integer, foo: :integer], aliases: [l: :limit, f: :foo])
** (OptionParser.ParseError) 2 errors found!
-l : Expected type integer, got "xyz"
-f : Expected type integer, got "bar"
Similar to parse/2
but only parses the head of argv
;
as soon as it finds a non-switch, it stops parsing.
See parse/2
for more information.
Example
iex> OptionParser.parse_head(["--source", "lib", "test/enum_test.exs", "--verbose"])
{[source: "lib"], ["test/enum_test.exs", "--verbose"], []}
iex> OptionParser.parse_head(["--verbose", "--source", "lib", "test/enum_test.exs", "--unlock"])
{[verbose: true, source: "lib"], ["test/enum_test.exs", "--unlock"], []}
The same as parse_head/2
but raises an OptionParser.ParseError
exception if any invalid options are given.
If there are no errors, returns a {parsed, rest}
tuple where:
parsed
is the list of parsed switches (same as inparse_head/2
rest
is the list of arguments (same as inparse_head/2
Examples
iex> OptionParser.parse_head!(["--source", "lib", "path/to/file", "--verbose"])
{[source: "lib"], ["path/to/file", "--verbose"]}
iex> OptionParser.parse_head!(["--number", "lib", "test/enum_test.exs", "--verbose"], strict: [number: :integer])
** (OptionParser.ParseError) 1 error found!
--number : Expected type integer, got "lib"
iex> OptionParser.parse_head!(["--verbose", "--source", "lib", "test/enum_test.exs", "--unlock"],
...> strict: [verbose: :integer, source: :integer])
** (OptionParser.ParseError) 2 errors found!
--verbose : Missing argument of type integer
--source : Expected type integer, got "lib"
Splits a string into argv chunks.
This function splits the given string
into a list of strings in a similar
way to many shells.
Examples
iex> OptionParser.split("foo bar")
["foo", "bar"]
iex> OptionParser.split("foo \"bar baz\"")
["foo", "bar baz"]
Receives a key-value enumerable and converts it to argv.
Keys must be atoms. Keys with nil
value are discarded,
boolean values are converted to --key
or --no-key
(if the value is true
or false
, respectively),
and all other values are converted using to_string/1
.
Examples
iex> OptionParser.to_argv([foo_bar: "baz"])
["--foo-bar", "baz"]
iex> OptionParser.to_argv([bool: true, bool: false, discarded: nil])
["--bool", "--no-bool"]


AMENDMENTS TO THE CONSTITUTION
For decisions applying to U.S. Constitution and Amendments to the Territory of Hawaii, see notes to Organic Act, §§5, 55, 86.


| I l@ve RuBoard |
2.24 The code ModuleThe code module provides a number of functions that can be used to emulate the behavior of the standard interpreter's interactive mode. The compile_command behaves like the built-in compile function, but does some additional tests to make sure you pass it a complete Python statement. In Example 2-47, we're compiling a program line by line, executing the resulting code objects as soon as we manage to compile. The program looks like this: a = ( 1, 2, 3 ) print a Note that the tuple assignment cannot be properly compiled until we've reached the second parenthesis. Example 2-47. Using the code Module to Compile StatementsFile: code-example-1.py import code import string # SCRIPT = [ "a = (", " 1,", " 2,", " 3 ", ")", "print a" ] script = "" for line in SCRIPT: script = script + line + "\n" co = code.compile_command(script, "<stdin>", "exec") if co: # got a complete statement. execute it! print "-"*40 print script, print "-"*40 exec co script = "" ---------------------------------------- a = ( 1, 2, 3 ) ---------------------------------------- ---------------------------------------- print a ---------------------------------------- (1, 2, 3) The InteractiveConsole class implements an interactive console, much like the one you get when you fire up the Python interpreter in interactive mode. The console can be either active (it calls a function to get the next line) or passive (you call the push method when you have new data). The default is to use the built-in raw_input function. Overload the method with the same name if you prefer to use another input function. Example 2-48 shows how to use the code module to emulate the interactive interpreter. Example 2-48. Using the code Module to Emulate the Interactive InterpreterFile: code-example-2.py import code console = code.InteractiveConsole() console.interact() Python 1.5.2 Copyright 1991-1995 Stichting Mathematisch Centrum, Amsterdam (InteractiveConsole) >>> a = ( ... 1, ... 2, ... 3 ... ) >>> print a (1, 2, 3) The script in Example 2-49 defines a function called keyboard. It allows you to hand control over to the interactive interpreter at any point in your program. Example 2-49. Using the code Module for Simple DebuggingFile: code-example-3.py def keyboard(banner=None): import code, sys # use exception trick to pick up the current frame try: raise None except: frame = sys.exc_info()[2].tb_frame.f_back # evaluate commands in current namespace namespace = frame.f_globals.copy() namespace.update(frame.f_locals) code.interact(banner=banner, local=namespace) def func(): print "START" a = 10 keyboard() print "END" func() START Python 1.5.2 Copyright 1991-1995 Stichting Mathematisch Centrum, Amsterdam (InteractiveConsole) >>> print a 10 >>> print keyboard <function keyboard at 9032c8> ^Z END |
| I l@ve RuBoard |


We redefine cats!
- extend back-end web services
- whiteboard B2B models
- leverage impactful paradigms
- incubate impactful supply-chains
- streamline magnetic ROI
- repurpose cross-platform eyeballs
- incentivize 24/365 methodologies
- envisioneer revolutionary markets
- transform vertical eyeballs
- extend holistic action-items
- synthesize magnetic e-tailers
- transition value-added e-tailers
- integrate collaborative relationships
- integrate robust infomediaries
- innovate e-business markets


Fighting the Imposter Syndrome
It’s funny. I’ve been a developer my whole life (since I was 18, professionally) and I’ve always thought of myself as a good one. I’ve never had any issues solving any challenges that my employers presented. Some were easy, others took a little bit more time, but they were never unsolved. I must say, though, that I had a lot of different jobs. Usually with the same title and responsibilities, but in many different companies. I have landed great jobs and participated in some life changing projects throughout my career. Things that I really should be proud of.
The thing is, in 2013 I had my first big failure as a developer. I was interviewed for a job opening in Facebook (dream job, right?). And I thought I had it. Yes, I was a silly goose but, what the hell, right? I had nailed every single interview I’ve ever been in. Technical and non-technical. Well, not that one. I failed that one HARD!  I didn’t take it easy.  Not to me, anyway.
Here is the deal: I started to think that I was an imposter, a phony, a person who was full of it. Everything that I’ve accomplished in my life was a lie. My jobs, promotions, compliments that I have received. I WAS A LIE! Even now, 3 years later, after receiving 3 incredible feedbacks from my managers and peers, I still think that I’m deceiving them, that I’m not good enough. That I’m lucky and I should tell them that.
I came upon this term, Imposter Syndrome, just a few weeks ago, in a youtube video from a channel I follow closely. It is Portuguese only(sorry). And it was eye opening to me. “I’m not alone”, I thought. And it was pretty clear to me that my lack of confidence in my skills brought me to that position. And this is something that needs fixing ASAP.
Million-dollar question: How to change that?
Well, you are going to find a lot of solutions online, that might be right or wrong, as I haven’t tried them. There is a great post by David Walsh that was very helpful and made me feel better about myself. He is clearly more successful than I am and he still suffers from this. I’m REALLY not alone on this one. I decided, though, to ask myself what brought me into this… The Facebook failure was not the starting point; it was the last drop. I was feeling like an imposter way before that, but it wasn’t bothering me, like it is now. So, I’ve decided to regroup.
I failed the Facebook interview for multiple reasons:
-
I forgot the basics. Peterson, Dijkstra and Knuth left my mind as soon as I graduated from college and started developing real software.
-
I lean to much on the intellisense feature that comes along with 99% of the IDEs.

For these issues, I came up with the following solutions:
- Get back to the basics: The first thing I did was to buy new technical books. Yes, books! Books related to algorithms, best practices and optimization.
- Instead of finding my solutions on Stackoverflow, the Apple documentation became my number one resource. That was a small but very significant change, mainly because things are not chewed and thrown into your IDE that easily. You have to read the docs, understand what going on and then apply the theory into your code. I know it sounds simple, but bad habits don’t break that easily.
- Optimize everything. Every single loop, array, dictionary, collection, whatever. There is always a way to make things faster and better if you look into the solution deep enough.
So, here I am. Trying to change my professional life, trying to get more confidence and, most importantly, trying to get cured from this “syndrome thing”.
By rerouting my focus to relearn what I forgot, I hope to become a better developer. Not for the organization that I’m currently working for, but for myself.