Definition for loading an existing order
| Field | Type | Label | Description |
| data | ExistingOrder.Data |
|
| Field | Validations |
| data |
|
| Field | Type | Label | Description |
| type | string | Resource name, by default should be order |
|
| attributes | ExistingOrderAttributes |
|
Defines attributes for loading an existing order
| Field | Type | Label | Description |
| created_at | google.protobuf.Timestamp | Time order was created |
|
| updated_at | google.protobuf.Timestamp | Time order was updated |
|
| purchaser | string | Person who is ordering (logged in user) |
|
| items | string | repeated | List of items in the order, in this case it will be mostly biological stocks such as plasmids and strains |
| Field | Validations |
| created_at |
|
| updated_at |
|
| purchaser |
|
| items |
|
ListParameters defines fields for manipulating output of Order collection
| Field | Type | Label | Description |
| cursor | int64 | A unique pointer to the next set of result in the list |
|
| limit | int64 | Maximum number of records that can be fetch per request |
|
| filter | string | The `filter` field restricts the data return by the collection. To use it, supply one or multiple allowed fields to filter followed by a filter expression. It uses the following syntax... field_name operator expression The following fields of `OrderAttributes` definition are allowed to be used for filtering * item - Items that are part of order (string). * courier - The courier used for delivery (string) * payment - Type of payment being used (string) * status - The status of the order (string) * created_at - Date the items are ordered (number), can be in the following formats: YYYY-MM-DD, YYYY-MM, YYYY field_name - Any one of the allowed field_name of the `OrderAttributes` definition. operator - Defines the type of filter match to use. It could be any of the following four and all of them should be URL-encoded for http request. Operators for strings =~ Contains substring !~ Not contains substring === Equals !== Not equals Operators for number == Equals > Greater than < Less than <= Less than equal to >= Greater than equal to Operators for dates $== Equals $> Greater than $< Less than $<= Less than equal to $>= Greater than equal to expression - The value that will be included or excluded from the result. URL-reserved characters must be URL-encoded for http request. filter: "status===Shipped" filter: "courier===FedEx" Filter can be combined using OR or AND boolean logic. * The OR is represented using a comma(,). * The AND is represented using a semi-colon(;). * AND and OR operators can be combined and AND takes precedence over OR. filter: "courier===FedEx;payment===Credit" filter: "created_at$>=20181201" The sort field allow to sort the data return by the collection based on fields of `OrderAttributes. To use it, supply a comma separated one or more allowed field from the definition of `OrderAttributes`. |
Metadata definition for traversing the collection
| Field | Type | Label | Description |
| next_cursor | int64 | A unique pointer to the next set of result in the collection. Set the cursor value parameter to the value of next_cursor to retrieve the next set of collection using the same method |
|
| limit | int64 | Maximum number of records that can be fetch per request |
|
| total | int64 | Total number of records in the collection. |
Definition for creating a new order
| Field | Type | Label | Description |
| data | NewOrder.Data |
|
| Field | Validations |
| data |
|
| Field | Type | Label | Description |
| type | string | Resource name, by default should be order |
|
| attributes | NewOrderAttributes |
|
Defines attributes for creating a new order
| Field | Type | Label | Description |
| courier | string | Name of courier for delivery |
|
| courier_account | string | Account identification used for courier service |
|
| comments | string | Any comments about the order |
|
| payment | string | Type of payment being used |
|
| purchase_order_num | string | Order number for purchase |
|
| status | OrderStatus | Status of order |
|
| consumer | string | Person (user) who is receiving the stocks in mail |
|
| payer | string | Person (user) who is paying for the stocks |
|
| purchaser | string | Person who is ordering (logged in user) |
|
| items | string | repeated | List of items in the order, in this case it will be mostly biological stocks such as plasmids and strains |
| Field | Validations |
| courier |
|
| courier_account |
|
| payment |
|
| purchase_order_num |
|
| status |
|
| consumer |
|
| payer |
|
| purchaser |
|
| items |
|
Definition of an individual order
| Field | Type | Label | Description |
| data | Order.Data |
|
| Field | Validations |
| data |
|
| Field | Type | Label | Description |
| type | string | Resource name, by default should be order |
|
| id | string | Unique identifier for the order |
|
| attributes | OrderAttributes |
|
Definition of various order attributes
| Field | Type | Label | Description |
| created_at | google.protobuf.Timestamp | Timestamp for creation |
|
| updated_at | google.protobuf.Timestamp | Timestamp for update |
|
| courier | string | Name of courier for delivery |
|
| courier_account | string | Account identification used for courier service |
|
| comments | string | Any comments about the order |
|
| payment | string | Type of payment being used |
|
| purchase_order_num | string | Order number for purchase |
|
| status | OrderStatus | Status of order |
|
| consumer | string | Person (user) who is receiving the stocks in mail |
|
| payer | string | Person (user) who is paying for the stocks |
|
| purchaser | string | Person who is ordering (logged in user) |
|
| items | string | repeated | List of items in the order, in this case it will be mostly biological stocks such as plasmids and strains |
| Field | Validations |
| created_at |
|
| updated_at |
|
List of orders
| Field | Type | Label | Description |
| data | OrderCollection.Data | repeated |
|
| meta | Meta |
|
| Field | Validations |
| data |
|
| meta |
|
| Field | Type | Label | Description |
| type | string | Resource name, by default should be order |
|
| id | string | Unique identifier for the order |
|
| attributes | OrderAttributes |
|
| Field | Type | Label | Description |
| id | string | Unique identifier for the order |
| Field | Validations |
| id |
|
Definition for updating an existing order
| Field | Type | Label | Description |
| data | OrderUpdate.Data |
|
| Field | Validations |
| data |
|
| Field | Type | Label | Description |
| type | string | Resource name, by default should be order |
|
| id | string | Unique identifier for the order |
|
| attributes | OrderUpdateAttributes |
|
| Field | Validations |
| id |
|
Defines attributes for updating an existing order
| Field | Type | Label | Description |
| courier | string | Name of courier for delivery |
|
| courier_account | string | Account identification used for courier service |
|
| comments | string | Any comments about the order |
|
| payment | string | Type of payment being used |
|
| purchase_order_num | string | Order number for purchase |
|
| status | OrderStatus | Status of order |
|
| items | string | repeated | List of items in the order, in this case it will be mostly biological stocks such as plasmids and strains |
The pre-defined labels for order status
| Name | Number | Description |
| In_preparation | 0 | |
| Growing | 1 | |
| Cancelled | 2 | |
| Shipped | 3 |
The order service specification
| Method Name | Request Type | Response Type | Description |
| GetOrder | OrderId | Order | Retrieves order by ID |
| CreateOrder | NewOrder | Order | Create a new order |
| UpdateOrder | OrderUpdate | Order | Update an existing order |
| ListOrders | ListParameters | OrderCollection | List orders using pagination, ten entries are retrieved by default |
| LoadOrder | ExistingOrder | Order | Load existing order |
| PrepareForOrder | .google.protobuf.Empty | .google.protobuf.Empty | Clear database before loading existing orders |
| .proto Type | Notes | C++ Type | Java Type | Python Type |
| double | double | double | float | |
| float | float | float | float | |
| int32 | Uses variable-length encoding. Inefficient for encoding negative numbers – if your field is likely to have negative values, use sint32 instead. | int32 | int | int |
| int64 | Uses variable-length encoding. Inefficient for encoding negative numbers – if your field is likely to have negative values, use sint64 instead. | int64 | long | int/long |
| uint32 | Uses variable-length encoding. | uint32 | int | int/long |
| uint64 | Uses variable-length encoding. | uint64 | long | int/long |
| sint32 | Uses variable-length encoding. Signed int value. These more efficiently encode negative numbers than regular int32s. | int32 | int | int |
| sint64 | Uses variable-length encoding. Signed int value. These more efficiently encode negative numbers than regular int64s. | int64 | long | int/long |
| fixed32 | Always four bytes. More efficient than uint32 if values are often greater than 2^28. | uint32 | int | int |
| fixed64 | Always eight bytes. More efficient than uint64 if values are often greater than 2^56. | uint64 | long | int/long |
| sfixed32 | Always four bytes. | int32 | int | int |
| sfixed64 | Always eight bytes. | int64 | long | int/long |
| bool | bool | boolean | boolean | |
| string | A string must always contain UTF-8 encoded or 7-bit ASCII text. | string | String | str/unicode |
| bytes | May contain any arbitrary sequence of bytes. | string | ByteString | str |


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---
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images:
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---
{% raw %}18{% endraw %}
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{% raw %}to help myself when I wanted. The next{% endraw %}
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{% raw %}was passing. I arose from the table and{% endraw %}
{% raw %}took the gun." Then follows, as seen{% endraw %}
{% raw %}from the records of the court, a full and{% endraw %}
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{% raw %}the .murder was committed, and the sub¬{% endraw %}
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{% raw %}prisoners. He was closely examined{% endraw %}
{% raw %}several times, and uniformly told a{% endraw %}
{% raw %}rational and consistent story. At one{% endraw %}


The Catavolt SDK entry point, an instance of the sdk {AppContext} which is always available to components.
A singleton instance is used by the underlying components to interact with the sdk.
cellValueDef
cellValueDef:CellValueDef
Optional classSelector
classSelector:function
Type declaration
(propDef: PropDef, defaultClass?: string): string
Parameters
propDef: PropDef
Optional defaultClass: string
Returns string
Optional detailsCallback
detailsCallback:CvDetailsPaneCallback
Optional detailsContext
detailsContext:EditorContext
Optional eventRegistry
eventRegistry:CvEventRegistry
The {@link CvEventRegistry} handles decoupled communication between components. Any component may subscribe to and publish
{@link CvEvent}s. See also {@link CvListener} and {@link CvEventType}
Allows for a component's rendering logic to be overridden and completely customized.
The first argument, the {@link CvContext}, exposes the {@link CvScopeContext} which provides the relevant SDK object
for use by the renderer. {@link CvScopeContext.scopeObj} will always be an SDK object exposing the data related to
the current component.
The Catavolt SDK entry point, an instance of the sdk {AppContext} which is always available to components. A singleton instance is used by the underlying components to interact with the sdk.


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It all started way back when I decided to go to Canada. During my training Hyatt Regency Ahmedabad, I had it in my mind that I'm going to open my small outlet no matter the cost! I had an amazing journey at Hyatt Regency because of this one
chef who taught me the basics of kitchen as well as the Indian cuisine ! He very well taught me about the curries and the different spices used in Indian cooking. From that I came up with the idea of my little outlet which I was gonna
open and that is "SEVEN SPICES". All because I use secret seven spices in my curries. Also during my training I found out that hygiene is the most important factor while cooking food so it always stays on top of my list! Moreover my plans
got changed due to this deadly corona virus and again the safety of the people whom I feed is really important, so I came up with an idea to cook delicious food, served with utmost hygiene practices!


NHW 2016 Cluster Cleaning
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Special thanks to the Yeatman Lab for the viewer code!!
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CoffeeScript and Java Class Documentation
Documentation for Tapestry's client-side CoffeeScript modules.
Documentation for Tapestry's server-side Java classes.
Quick links:
See also:


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{% set page = { title: 'index', dev: true, secondary: true, html_classes: ['page-class'] } %} {% extends page.layout | d(prototype.current.layout) %} {% block primary %}
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| #docs in the search result set which contain the term |
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| N10 |
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Vighnesh Reddy Konda --- Naman Jain --- Vamsi Krishna Reddy Satti


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x1, y1 to x2, y2
set line


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Provide the application with a message data object.
More...
Detailed Description
- Outline
-
-
- Purpose:
- Provide the application with a message data object.
-
- Classes:
-
- See also:
- bmqa::MessageEvent : Mechanism for data event notification. bmqa::MessageEventBuilder: Builder for
bmqa::MessageEvent
-
- Description:
- A
bmqa::Message
represents the data message to put on a queue, or retrieved from a queue. It is composed of the following fields:
-
A message GUID, which is a printable string generated by the broker to uniquely identify this message.
-
A correlation Id, which is a user-provided identifier for the message.
-
A queue Id, to map with the queue this message is associated with.
-
The payload, which is opaque to the framework. At some point, framework may provide utilities to encode and decode schema messages using various CODECs. For example, a JavaScript publisher may publish a message into a queue using a JSON object as payload, and the consumer may be receiving that payload as a BER-encoded schema object.
-
At some point, system properties such as version, encoding, timestamp, priority, message group and "reply-to" will be supported. System properties will be used by the broker; for example to deliver high-priority messages first or to filter based on a minimum version.
-
At some point, application-defined message properties will also be supported, where properties are a list of name-value pairs.
- A
bmqa::MessageConfirmationCookie
is a small object which allows to confirm a bmqa::Message
asynchronously without having to hold on to the entire message. This can be useful when, for example, the message is decoded in the event handler, and the resulting object is enqueued for asynchronous processing, along with that small cookie object for confirming the message once successfully processed.


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Weekly Nerd – articles & sketchnotes
During the minor program Everything Web I followed for the past six months, guest speakers orated at us every week for our benefit.
During the minor program Everything Web I followed for the past six months, guest speakers orated at us every week for our benefit.


--- layout: archive title: Zulip Chat Archive permalink: /stream/113489-new-members/topic/constants.20and.20variables.html ---
Is scoping the only difference between constants and variables in Lean?
constants are axioms while variables is just a shorthand to insert "forall" in the following theorems
so for example classical.choice
is a constant
"forall" as an assumed hypothesis in all the following theorems?
I guess I'm not certain how that differs from an axiom.
I have struggled explaining it before, but I guess I'll still try
constant
never goes out of scope, it's as permanent as a def
def f : nat -> nat := fun x, x+1
is the same as:
variable (n : nat) def f : nat := n + 1
but if you do:
constant n : nat def g : nat := n + 1
then you're declaring a constant n
and g
is now a natural number, not a function
f 3
evaluates to 4
while g 3
is a type mismatch because the type of g
is nat
f (f n)
works but g (g n)
doesn't make sense
g n
doesn't make sense to start with?
My point being that there is no analog of f (f n)
for g
you can't substitute for a constant
So it is like constants and variables in C? I.e. const float pi = 3.14, versus int x = 0. pi can never take a different value, but x can?
well Lean is a functional programming language like Haskell, unlike the more conventional programming languages (C, Java, Python) which are imperative languages
but Lean constant
would be C const
with a "secret" value
where variable
is just the input to functions
I think I kind of see. I started reading a tutorial on Haskell earlier this week. Does it have something similar that I will run across?
I don't know Haskell but I don't think so
Is a variable the same as a variable in the lambda calculus?
yes
Ah. I have not gotten to the typed lambda calculus yet. Will I see constants there?
Constants are like Haskell compiler intrinsic functions
they are functions, you can see that they have been declared as such, but you can't see the definition
Haskell doesn't really have an equivalent to the variables
command. Scopes are handled differently in Haskell - you can think of the whole program as being in a single shared scopes where all your definitions are like let
bindings. Lean is not like that - there are no variable scopes that span multiple definitions
I guess I haven't gotten that far yet.
Are constants the same as the "term constants" mentioned here: https://en.wikipedia.org/wiki/Simply_typed_lambda_calculus
yes
Thank you
One other difference is that users are hugely discouraged from ever using constants ever. I'm not sure there's a single one in mathlib. But there are variables everywhere
{% endraw %}Last updated: Apr 24 2020 at 19:02 UTC


Adult Further Education Statistics
Email<EMAIL_ADDRESS>Telephone: Steve Aherne 020 7215 6075
Official Statistics
Experimental statistics on employment and continued education of adults finishing funded further education training between 2011 and 2014.
PDF , 1.46MB , 29 pages
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Experimental outcome-based measures covering the destinations (into employment and learning) and the progression of post-19 learners. It covers learners completing funded further education training in academic years:
It builds on previous experimental data for learners completing training in 2010 to 2013 .
The data uses the longitudinal education outcomes ( LEO ) study, which looks at how learners move through education and into the labour market by bringing together:
The ‘outcome-based success measures’ documents show data for all traineeships from academic year 2013 to 2014 - the most recent year for which measures are available. The tables give additional context on destination rates at provider level.
Email<EMAIL_ADDRESS>Telephone: Steve Aherne 020 7215 6075
Published: 27 October 2016
Updated: 20 December 2016
From: Department for Education
Part of: Further education and training


Updated 27/02/2006
Since creating this page I have been told about rzip, so this idea isn't new after all.
This program attempts to detect and exploit duplication in streams which normal compression programs such as gzip and bzip2 fail to. The program uses a rolling checksum inspired by rsync to efficiently detect large blocks of data repeated arbitrarily far apart, distances much further than bzip2 notices. Imagine a tar / pax file of an application directory. The same dll may appear more than once in the file structure or the same library may have been statically linked to different executables. These duplicated blocks may be arbitrarily far apart in the archive.
I will not attempt to explain in detail how the algorithm works here but feel free to download the source or email me. I will probably write up a description once the source has settled down.
A file of any size containing no repeated blocks large enough for LRC to detect will result in LRC adding 4 bytes to the length of the file. Here random1 is a file generated from /dev/urandom.
| File | Size (in bytes) |
|---|---|
| random1 | 7,654,321 |
| random1.bz2 | 7,688,794 |
| random1.lrc | 7,654,325 |
| random1.lrc.bz2 | 7,687,749 |
A large block of random data several megabytes in size repeating itself is ideal for LRC. The algorithm will spot the duplication of the entire block and squash out all of the repetition. Here random2 is the above random1 file repeated twice.
| File | Size (in bytes) |
|---|---|
| random2 | 15,308,642 |
| random2.bz2 | 15,376,676 |
| random2.lrc | 7,774,358 |
| random2.lrc.bz2 | 7,722,119 |
LRC will demonstrate the same behaviour if the block is repeated many more times, ie only one copy of the block will be kept. This is true even if the copies of the block are spread throughout the input at large distances.
Here some real filesystem trees have been tested. The LRC program does not attempt to duplicate what bzip2 and others already do for local compression. For that reason LRC output still benefits from being compressed itself with bzip2.
| File or directory | Original (.pax or .tar) | .bz2 | .lrc | .lrc.bz2 | Comments |
|---|---|---|---|---|---|
| /etc (approx 3100+ files) | 23,265,280 | 2,985,250 | 22,129,132 | 2,961,793 | As expected not much saving here as /etc doesn't contain large portions of repeated data. |
| /usr/X11R6 (approx 3400+ files) | 148,746,240 | 43,125,635 | 86,368,716 | 35,845,001 | Better compression here as presumably chunks of libraries / binaries duplicate compiled object code. |
| linux-<IP_ADDRESS>.tar (<IP_ADDRESS> kernel source) | 224,102,400 | 39,194,997 | 214,558,252 | 38,552,800 | Not very great compression here, again the files are mostly text and not binary. |
| linux-<IP_ADDRESS>-<IP_ADDRESS>.tar (<IP_ADDRESS> and <IP_ADDRESS> kernel source tar files concatenated) | 452,270,080 | 79,018,004 | 253,090,140 | 44,601,962 | Here LRC is doing an excellent job of spotting the similarities between the two archives despite the repetitions being over 200 megabytes apart in the stream. This is a good example of how LRC works well when used with bzip2. |
In terms of speed the current algorithm takes time O( N log( N ) ) where N is the length of the input stream. This should be easy to improve to O( N ) by replacing some tree maps with hash maps.
In terms of memory used during compression LRC currently uses O( N ). This looks bad but in reality the memory used is really a small fraction of the input stream size. The above 400 megabyte files required only 40 megs of memory during compression. The constant fraction can no doubt be improved but the O( N ) is unavoidable.
This is easy but requires seeking around in the output file as it is reconstructed.
The current implementation is not optimized or very well tested. Some of the tunable parameters have not been tested across different settings.
This is very much work in progress, use at your own risk. The file format is likely to change in the near future so do not archive anything important.
Subversion: svn://pauldoo.dyndns.org/home/svn/Programs/LRC


above |
K'an The Abysmal, Water |
|
below |
K'un The Receptive, Earth |
Holding Together brings good fortune.
Inquire of the oracle once again
Whether you possess sublimity, constancy, and perseverance;
Then there is no blame.
Those who are uncertain gradually join.
Whoever comes too late
Meets with misfortune.
On the earth is water:
The image of Holding Together.
Thus the kings of antiquity
Bestowed the different states as fiefs
And cultivated friendly relations
With the feudal lords.
Six at the beginning means:
Hold to him in truth and loyalty;
This is without blame.
Truth, like a full earthen bowl:
Thus in the end
Good fortune comes from without.
Six in the second place means:
Hold to him inwardly.
Perseverance brings good fortune.
Six in the third place means:
You hold together with the wrong people.
Six in the fourth place means:
Hold to him outwardly also.
Perseverance brings good fortune.
Nine in the fifth place means:
Manifestation of holding together.
In the hunt the king uses beaters on three sides only
And foregoes game that runs off in front.
The citizens need no warning.
Good fortune.
Six at the top means:
He finds no head for holding together.
Misfortune.


This Titanium module wraps the oficial Testflight SDK, available at https://testflightapp.com/sdk/.
It allows you to write Titanium apps and still benefict from using the Testflight SDK.
To access this module from JavaScript, you would do the following:
var testflight = require("com.0x82.testflight");
The testflight variable is a reference to the Module object.
This should be the first function you should call to initialize the module. It starts a TestFlight session, setups the crash handler, and sends pending notifications to the server.
It accepts a single argument teamToken, with your TestFlight team token. You can obtain that token at https://testflightapp.com/dashboard/team/edit
Track when a user has passed a checkppint after the flight has taken off. Eg. passed level 1, posted hight score, etc.
It accepts a single argument checkPointName with the String name of the checkpoint.
Opens a feedback window that is not attached to a checkpoint. You should just call it with no arguments. The windows open modally.
Add custom environment information. If you want to track a user name from your application you can add it here.
It accepts a single hash/dictionary argument hashOptions, with key/value pairs of options you want to set on your environment.
Please check the examples/app.js for the full API demonstration.
Ruben Fonseca<EMAIL_ADDRESS>This module is licensed under the MIT License. Please see the LICENSE file for details.


Python and MongoDB¶
This primarily refers to usage of the pymongo
package, however, the
concepts apply to using MongoDB from Python in general. Interacting with
MongoDB from Python has a couple of easy traps to fall into, and this looks
at one in particular and how to avoid the pitfall via proper usage of indexes
and careful construction of queries.
When querying MongoDB in general, it will attempt to use indexes based on the components of your query, in the order you specify them. That is, if you construct a query that looks as follows:
docs = db.collection.find({"stuff": 1, "things": 0})
If you use that as the filter for a .find()
call, MongoDB will look for a
compound index where the fields are specified in the order (stuff, things)
.
If a compound index exists with both fields but the ordering is instead
(things, stuff)
, then the index may not be used! I have experienced a
number of situations where the query planner will select the correct index
despite providing the query fields in a different order, however, that behavior
should not be relied upon.
NOTE 1: make sure that you create compound indexes on your MongoDB collections with the fields specified in the order which you want to query them in and that you construct query filters using the same ordering as your indexes!
Great, so we understand that ordering is important on the MongoDB side of the
equation, but there’s just one little problem. Almost all examples of using
a library like pymongo
to interact with MongoDB from Python use plain old
dict
objects to construct query filters; the thing is, Python dict
objects are inherently an unordered data structure and thus provide no
guarantee of maintaining any specific ordering. While that is not entirely true
for Python 3.6+ (but that is a whole different topic) I would still argue that
using the approach explained below conforms better to best practice and more
explicitly communicates the intent of what the code is doing.
If the filter only contains
a single field, then there won’t be any issues because there aren’t multiple
fields. However, as soon as you introduce multiple fields into a filter using
a normal dict
, the order in which they might be presented to MongoDB
becomes non-deterministic. This means that our example query might actually
be serialized at runtime to:
{"things": 0, "stuff": 1}
Which could prevent MongoDB from utilizing a compound index on
(stuff, things)
. That might not be an issue on very small
collections, but try doing that on hundreds of thousands or millions of
documents and the queries will start taking orders of magnitude longer.
There are certain edge-cases with some versions of Python where depending on
whether hash randomization is enabled or not the ordering of dict``s may be
preserved (or at least deterministic), however, the point here is that things
like this **should not** ever be relied upon for ordering since the ``dict
as a data structure provides no guarantees or ordering.
It is unfortunate that the pymongo documentation is not clearer on this point;
though it does mention it, you essentially have to read a section about a
method which takes a filter (like the collection
find
method), and notice that the filter
argument says:
filter (optional): a SON object specifying elements which must be present for a document to be included in the result set
Well it says nothing about dict
… so what is a SON object? The quoted
description above provides no clickable link in the documentation, but if you
dig around a little more you can come across the
Tools for working with SON an ordered mapping
page about the bson.son
module which defines SON
objects, and says
(emphasis added by me):
Regular dictionaries can be used instead of SON objects, but not when the order of keys is important. A SON object can be used just like a normal Python dictionary.
NOTE 2: now we see that filters are expected to be SON objects, or speaking
more broadly, dict
objects can be used in specific cases, but as a
general rule filters are expected to be an ordered mapping.
Right, so pymongo
actually expects an ordered mapping, which makes sense
based on the importance of ordering on the MongoDB side. How then do we ensure
that ordering is preserved for queries? There are effectively two options;
personally I’ve not found any compelling reasons to use bson.son.SON
and
prefer to use the already-familiar option that is built right into Python,
collections.OrderedDict
. OrderedDict
acts almost exactly like a normal
dict
object, however, it also preserves the order in which keys were
inserted. Using this approach, our example query filter could instead be
constructed with:
from collections import OrderedDict
query_filter = OrderedDict()
query_filter['stuff'] = 1
query_filter['things'] = 0
docs = db.collection.find(query_filter)
It can also be built directly by utilizing the constructor but you have to
keep in mind that initializing data by passing keyword arguments or another
dict object will not preserve ordering. This is because OrderedDict
can
only preserve what ordering it has access to, and neither kwargs nor a dict
provide an order. Instead, you will need to pass it an iterable of some sort
(such as a list, tuple, or generator) of key-value pairs. Constructing the
example filter in this manner would look like:
from collections import OrderedDict
query_filter = OrderedDict([('stuff', 1), ('things', 0)])
docs = db.collection.find(query_filter)
NOTE 3: initializing it may not look as clean or pretty as a dict
, but you
should almost always use OrderedDict
for performing MongoDB queries in
Python; you can initialize an OrderedDict
properly by passing an iterable
of key-value pairs to the constructor. This will ensure that ordering is
preserved and ensure compound indexes with the same order will be utilized.


INDIANA JONES AND THE TEMPLE OF DOOM Review By David Wilcock (C)1998
Running Time: 118 minutes (1 hour 58 minutes) Starring Harrison Ford, Kate Capshaw and Ke Huy Quan Directed By Steven Spielberg OSCAR(R) Nominations: Best Music, Visual Effects (Won)
Steven Spielbergs headache inducing, if not pariculary exciting, second Indiana Jones adventure. A prequel to Raiders of the Lost Ark (1981), this film sees intrepid archaeologist/adventurer Indiana Jones (Ford) plunged into a dark world of child slaves, thugees and dark rituals. It's up to Jones, and his child friend Short Round (Quan) and singer Willie Scott (Capshaw), to save the kids, and stop the thugees from finding two diamonds that could give them a lot of power.
Temple of Doom starts well enough with a well directed performance of 'Anything Goes', performed by Willie. We then have one of the greatest opening sequences ever when Jones bargains with two Chinese over a diamond. Naturally, the bargaining goes wrong, and the sequence turns into a slapstick routine with Jones trying to find the diamond which is being kicked all around a restaurant. It's a very well directed scene, and features even more chaos than Speilbergs own 1941 (1979) jitterbug scene. After this, there's an exciting plane crash. But after the plane crash, the film starts to go downhill when Indy is set on his quest.
The main problem with the film is that it tries to out do Raiders of the Lost Ark on every level. The film features more 'gross out' gags, more stunts, more explosions and more gory deaths, but strangely it all seems 'dead.' It all seems to be in there just for the hell of it. Unlike Raiders, where all the big chases and stunts were exciting, Temple of Doom piles on so many deaths, explosions etc. it just cancels itself out. The film is trying so hard to make the audience excited, it just falls flat on it's face.
 She just shouts and screams, and points out the obvious. She seems to just ask 'What is it?' questions, so Indy can explain to her, but mainly to the audience, what is going on in the film. From the start, Capshaw is terrible, just shouting and screaming and being really annoying. If I were Indy, I would of tried to dump her as quickly as possible. Had the screenwriters wrote her part better, her whining and screaming could of been funny. However, like everything else in this film, she is hugely exgrarated, and almost seems pointless in this film.  He has some good lines, and even gets the chance to kick some thugee butt. Ford, as usual, is fun, although he was better in Raiders, and even Indiana Jones and the Last Crusade (1989).
Spielberg's direction, however, is too frantic. The film belts along, and never lets the audience catch up. He never gives the audience a chance to enjoy a stunt, because the picture moves along too fast to let the audience enjoy it. It's a shame, because there are some good stunt scenes in there, including a amazing mine cart sequence. It's just on the first viewing, the audience will never catch up on them. Also, the script is weak. It's mainly just references to the first film (even though this is a prequel) and the dialogue between Indy and Willie is dud. The script only really works with scenes between Indy and Shorty, but they work more on the strength of the actors than the script. Also, the film is a bit too violent for young kids, the target audience. If your child can stand watching hearts ripped out and men crushed by rock crushers, they may enjoy this film.
It's not all that bad, though. Some of the action scenes are good, and the film has a great sense of humor. Some of the scenes made me laugh out loud. But, overall, it just isn't much fun. It's too dark, too eager to excite us, and Indy has hardly any character in this film. Temple of Doom, then, is disappointing, and the weakest of the Indiana Jones trilogy.
OVERALL RATING=3Dout of REVIEW BY DAVID WILCOCK
DAVID WILCOCK<EMAIL_ADDRESS>Visit the Wilcock Movie Page! http://wilcockmovie.home.ml.org -OR- http://www.geocities.com/Hollywood/9061
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


Comments
-
Greg Hurrell
Thanks for the request. There's no easy way of doing this, but it should be possible to implement. The basic problem is that the UNIX underpinnings of Mac OS X make it impossible for one user to control the processes of another user. Only the "superuser" (root) can do this.
It's not appropriate for Synergy itself to run as root, but it should be possible to write a background daemon process that runs as root and starts at boot time. Synergy would issue instructions to the daemon and the daemon would then perform the necessary operations to effect changes in the processes of the other user.
This is probably going to be fairly complicated, so it's unlikely to get implemented in the near future. Other, more oft-requested stuff will probably make it in first. But at least the request is in the database now so it won't be forgotten.
-
Greg Hurrell
Changing assignment to reflect my new email address.
https://wincent.com/a/news/archives/2006/05/change_of_email.php
Add a comment
Comments are now closed for this issue.


{% extends "base.html" %} {% block title %}Edit Researcher {{ admin._id }}{% endblock %} {% block content %}
This researcher is not authorized on any studies.


W00t?
This repository contains description of the first Cloudopoly challenge. Cloudopoly is a set of challenges targeted towards raising awareness of AWS stack. Winners will get prizes from AWS! The first Cloudopoly will have 3 challenges, one per month. By getting 3 times in top 3 you will win a special prize from LatCraft.
Problem definition
Publish a simple web service that accepts 3 keywords as a search criteria.
Web service must respond with the most popular book (with the highest average rating) for each keyword on the following Amazon websites:
- amazon.co.uk
- amazon.fr
- amazon.de
Expected input:
http://<ip address>/search?query=Linux+Ubuntu+MacOs
Expected JSON response:
[
"Practical Vim",
"Linux",
"Mac OS X Snow Leopard"
]
Average book rating calculation
Book rating should be calculated using the following formula:
R = (Rafr * Nafr + Rade * Nade + Rauk * Nauk) / (Nafr + Nade + Nauk)
- Rafr - average rating on amazon.fr
- Nafr - number of ratings on amazon.fr
- Rade - average rating on amazon.de
- Nade - number of ratings on amazon.de
- Rauk - average rating on amazon.co.uk
- Nauk - number of ratings on amazon.co.uk
NOTE: Only books with at least 15 reviews should be considered for result.
NOTE: For book title matching on different web sites, consider the following rule: remove everything that is after colon or semicolon (if any), and anything that is in the brackets (if any). If titles have the same rating, then return the one with the biggest number of reviews. If titles have the same rating and the same number in reviews, then return the one that goes first in alphabetical order.
Example searches
The following list shows example URLs that return book query results for a given KEYWORD on the web:
-
amazon.co.uk:
http://www.amazon.co.uk/s/ref=nb_sb_noss_1?
url=search-alias%3Dstripbooks&
field-keywords=[KEYWORD]&
sort=review-rank
-
amazon.de:
http://www.amazon.de/s/ref=nb_sb_noss_2?
url=search-alias%3Dstripbooks&
field-keywords=[KEYWORD]&
sort=review-rank
-
amazon.fr:
http://www.amazon.fr/s/ref=nb_sb_noss_2?
url=search-alias%3Denglish-books&
field-keywords=[KEYWORD]&
sort=review-rank
Requirements
- Any programming language, any operating system
- Deploy your service to AWS EC2 (free tier)
- Use smallest instance type (
t2.micro
) - Send IP address of your service before
06.01.2015 16:00
to<EMAIL_ADDRESS>- At
17:00
we start the test!
Winner election
Web services, which return the expected result faster, will win. Test data set consists of 3 queries, each query contains 3 keywords. Each query will be sent 3 times to the web service published at your IP address.


Hello, from an entrepreneurial background, I am an individual with the mindset of combining
holistic and pragmatic approach to problem solving. I see this skill being very useful in
building humanized, eco-friendly applications and softwares that actually solves existing
problems without creating another. Why I transitioned into Tech. world during the first covid-19
pandemic by taking a full stack developement course. I come from a fitness, health, wellness and
digital content creating background with an international and remote working experience.
My journey into Tech. hasn't been easy but I keep working to improve my newly gained technical
skills. As a practical person, I will improve immersely being surrounded by like-minded
individuals and team.
I am hungry to offer my skills, to learn,
advance and impact.
I have gained knowledge and experience building projects in JavaScript, HTML, CSS and very little with Java as programing languages. Frameworks and library like React.js, react router, Node.js, Express, MySQL and SQL database. With these knowledge and proven records with few projects, I can occupy any relatable with higher interest in learning and improving on my skills. I back my technical skills with useful skills application of agile methodology in team organization and project managment and more.
I have a great interest in data building and manipulation. I gained knowledge in both SQL and MySQL with my first project as a backend developer, I had the opportunity to build a database.With continue studies and interest, I desire to take this role at entry level and further knowledge and skills. Ready to learn new languages and frameworks to become a valuable data analyst
From a entrepreneurial background, I have had the experience of working in a well organized structure to be able to reach the targets with product orientation, estimated time and team members welfare as a priority. I believe in the usage of communication, technical knowledge, team building and agile methodology, I will shine at this role.
Graphic designing using canva, videography, photography and editing and sharing the contents on digital medial platforms to market my products and skills. I am continuely learning each day to improve my skills and champion my craft.
In this project, I worked 360 all round as UX designer, project manager, both backend and frontend web development.
My very first MVP which I'm yet to build the frontend. It is a charity web app aimed at building a direct link between philanthropists and homeless people.
An informative massage multiple page website with featured API to external websites for booking and contacting. This website was built whiles self teaching HTML and CSS.
I am curently working as a volunteer on a mobile app project of 10 team members. It is a start-app project but with very well structured professional approach. I form part of the engineering team working on both backend and frontend. The tech stacks for this project are totally new to me and that is what is existing. We are focusing on using GraphQL, Postgre, Phoenix, ReactNative
An intensive 550 hrs full stack development bootcamp focused on fundamentals of JavaScript, Advanced Functions & Data Structures, Frontend Frameworks & Servers & Databases. By completion, knowledge is gain in the application & usage of Vue.js, React.js, Node.js/Express, MySQL, RESTful API, Docker, Mongo DB, Git, GitHub & TDD working on various projects with the implementation of above Tech. stacks
As an aspiring motivational speaker in the diaspora, I reach audience on social media platforms by creating professional contents on immigration, visa and residence, motivational mentorship on entrepreneurship,youth empowerment and personal growth not leaving out fitness.I also focus social media presence and reaching out to clients for my past business pages.
As an entrepreneur, I have ventured into various sector including culinary, health, wellbeing and fitness. As an individual who uses pagmatic and holistic approach into solving problems, I help individuals become the best versions of themselves by combining and offering the servicest as a personal trainer, massage therapist, curlinary coach focusing pn method of cooking and ingredients used as well as motivastional speaking. I have over the years worked as employee, employer, freelance, collaboration with other profesionals, contracted by other companies under these fields internationally.


Books
Title
Author
Publisher
Year
ISBN
Genre
Condition
Available?
Add a book
Title
Author
Publisher
Year
ISBN
Genre
Condition
Available?


Galleria Picasa Plugin Demo
Demonstrating a basic gallery example with photos from a Picasa album.
Made by
Galleria
.


Monday, 26 January 2015
This is something anyone can learn...
I love the new HTML. HTML5, that is. Even a 40 year-old like me can learn it.
Why should you learn it?
 If you learn just one HTML tag, you will know how to use the rest of them. All HTML tags follow simple rules that work for any tag – but before we get into using HTML, let’s go over what an HTML tag is.
As a child, these colourful superheroes that could fly, or were horrifying like Ghost Rider and the Hulk, with this tremendous rage or these supernatural powers, provided an escape for me from my mundane existence, from my lack of friends or my inability to communicate well with people. They liberated me.
- Nicolas Cage
Here are some great reasons to learn HTML5.
- You can expand your business.
- You can learn how to code.
- You can have loads of fun!
 And go learn it!
Comments Form
"Nic Cage is a dick."
"Nic Cage has a big one!"


EPR spectra do not consist of a discrete set of infinitely sharp lines. Lines are broadened by dynamic effects (relaxation, tumbling, chemical exchange) or static effects (orientational disorder, unresolved hyperfine splittings, distributions in magnetic properties such as g, A, and D values).
EasySpin takes orientational disorder into account explicitly for solid-state spectra. It allows you to include some forms of additional broadening in most spectral simulations (solid-state cw EPR with pepper, liquid EPR with garlic, ENDOR with salt). In addition, any static broadening model can be implemented using explicit averaging.
The two types of broadening models built into EasySpin are:
The broadenings are given in fields of the spin system structure, which contains the spin system and all associated spin Hamiltonian parameters. Not all types of broadenings are supported by all simulation functions.
Broadenings are treated differently in the simulation of slow-motion cw EPR spectra using chili
. See the documentation of chili.
All broadenings are understood to be FWHM (full width at half height) or PP (peak-to-peak), independent of the simulation function, the line shape or the detection harmonic. For the conversion to and from peak-to-peak line widths, see the reference page on line shapes.
Use only broadenings of one type at a time.
This type of broadening is applied by convolving a stick spectrum with a single lineshape. Therefore, it applies the same line width and line shape to each transition and orientation.
Isotropic convolutional broadening should only be used for S=1/2 systems with very small g anisotropy, and for S>1/2 systems with small zero-field splittings. For systems with substantial g anisotropy, or higher electron spin with substantial zero-field splitting, it will lead to incorrect results. The reason is that in those cases, distributions in g and D are almost always dominant, and a simple comvolutional broadening is inappropriate.
The following fields in the spin system structure specify convolutional broadenings.
lwpp
For field-swept spectra, the unit of lwpp
is mT. For frequency-swept spectra, the unit is MHz.
Gaussian
[Gaussian Lorentzian]
Sys.lwpp = 10; % Gaussian broadening Sys.lwpp = [0 12]; % Lorentzian broadening Sys.lwpp = [10 12]; % Voigtian broadening (Gaussian + Lorentzian)
For conversion between FWHM and PP line widths, see the reference page on line shapes.
lw
lwpp
, except that the numbers are assumed to indicate the full width at half maximum (FWHM) instead of the peak-to-peak (PP) width. For conversion between FWHM and PP line widths, see the reference page on line shapes.
lwEndor
lw
. For lwEndor
, no peak-to-peak analogue is available. See the page on line shapes for conversion formulas.
To model anisotropic broadenings in solid-state cw EPR spectra, use fields depending on the physical origin of the broadening:
HStrain
.
gStrain
, AStrain
and/or DStrain
.
More than one of these broadenings can be specified simultaneously. The total broadening for a given orientation is the combination of all individual broadenings.
The broadenings resulting from the various strains are computed in an approximate way. For example, for gStrain
, the derivative with respect to g of the resonance field of a given transition is computed, and then the magnitude of this derivative is multiplied by the value from gStrain
to give the actual line width. A Gaussian with this line width is then added to the spectrum. A similar procedure is used for all other strains.
This approximation, which corresponds to the first term in a Taylor expansion or to first-order perturbation theory, is valid only as long as the strain distribution width is much smaller than the parameter itself, e.g. a gStrain
of 0.02 for a g
of 2. If the distributions is wider, an explicit loop (see below) should be used, see below.
HStrain
[FWHM_x FWHM_y FWHM_z]
Sys.HStrain = [10 10 10]; % 10 MHz Gaussian FWHM broadening in all directions Sys.HStrain = [10 10 50]; % broadening along the molecular z axis larger than along x and y
The line width for a given orientation
of the static
magnetic field is given by
where , and
are the three elements of HStrain
.
If the spin system contains only one electron spin, it is possible to specify combined g and A strain or D strain.
gStrain
[FWHM_gx FWHM_gy FWHM_gz]
If the spin system contains more than one electron spin, gStrain
should contain one row for each electron spin.
AStrain
[FWHM_Ax FWHM_Ay FWHM_Az]
, in MHz
A
(Ax, Ay, Az) of the first nucleus in the spin system. The distributions are completely uncorrelated. AStrain is not supported for systems with more than one electron spin, and it is only available for the first nucleus.
To set the correlation between gStrain
and AStrain
, use the field gAStrainCorr
.
gAStrainCorr
+1
(default) or -1
gStrain
and AStrain
. +1
indicates that positive change in gx is correlated with a positive change in Ax etc, whereas -1
indicates anticorrelation.
DStrain
FWHM_D
or [FWHM_D FWHM_E]
FWHM_E
is omitted, it defaults to zero.
The distributions in D and in E are treated as uncorrelated, unless DStrainCorr
is provided.
If the spin system contains more than one electron spin, DStrain
should contain one row for each electron spin.
Examples:
DStrain = [10, 5]
specifies a Gaussian distribution of D with a FWHM of 10 MHz and a Gaussian distribution of E with a FWHM of 5 MHz. DStrain = [100 33]
specifies a Gaussian distribution of D with a FWHM of 100 MHz and a Gaussian distribution of E with a FWHM of 33 MHz. For two electron spins, DStrain = [10 5; 100 20]
specifies [10 5]
for the first electron spin and [100 20]
for the second.
DStrainCorr
+1
(default) or -1
D
and E
, which can be between -1 and +1. +1
indicates that positive change in D is correlated with a positive change in E, whereas -1
indicates anticorrelation. Any value between -1 and +1 is possible. If not given, it defaults to 0, and the distributions in D and E are uncorrelated.
If the spin system has more than one electron spin, give one correlation coefficient per electron spin.
You can model any arbitrary form of inhomogeneous broadening. For this, run explicit loops over distributions of spin Hamiltonian parameters, simulate the associated spectra and sum them up (including weights of the distribution function) to obtain an broadened spectrum.
This approach is necessary if the distributions are so broad as to render the built-in perturbational treatment invalid, or if you want to average over non-Gaussian distributions, or correlated distributions, or distributions over parameters other than g, A, and D.
Here is a basic example for a broad Gaussian distribution of D:
% Set up distribution of D D0 = 1000; % center of distribution, MHz Dfwhm = 500; % FWHM of distribution, MHz D = linspace(0,2*D0,401); % range of D values, MHz weights = gaussian(D,D0,Dfwhm); % associated weights % Spin system Sys.S = 1; Sys.lwpp = 1; % mT % Experiment Exp.mwFreq = 9.5; % GHz Exp.Range = 330+ [-1 1]*100; % mT % Explicit averaging loop over D distribution spec = 0; for iD = 1:numel(D) Sys.D = D(iD); [B,spec_] = pepper(Sys,Exp); spec = spec + weights(iD)*spec_; end % Plotting subplot(2,1,1); plot(D,weights); axis tight subplot(2,1,2); plot(B,spec); axis tight
If more than one parameter is distributed, then nested loops over a multi-dimensional distribution are needed.


- Solid Work
- Rhino
- Autodesk Remake ( It now converting to ReCap Pro Not available for Mac)
- Fusion 360
Autodesk Remake
Step 1 Download ( Education Version) Link | 950 MB
Step 2 Setup
Autodesk Product require Login as this is Cloud based Product it store your photos to cloud and process them.
Select Photos and Upload.
this will upload photos to Autodesk Drive and Process
After Process it will show where to store output file.
Output extension is in Format
Step 5 Mesh Model
Project Done for 3D Printing
Problem Faced
-
Scanning from Phone ( object should be steady or Phone if few photos submitted wrong for remake it will spoil your other image ref. so check before uploading)


Game info
Type: FreeCell - Decks: 2 decks (104 cards)
- Redeals: None
- Game time: Medium
- Difficulty level: Medium
- Skill level: Mostly skill
- Chance of winning: High (about 1 in 3 games)
Object of the game: Move all the cards to the foundations.
Rules
Foundations (Eight piles; upper right side of screen)
- Build up in suit from Ace to King. For example, a 2
can be played on an Ace
.
Cells (or Reserve: eight cells, upper left)
- These are the "cells". The cells are storage (holding) locations for
cards being played to the foundations and the tableau.
- Cells can hold only one card at a time.
Tableau (Ten columns, below foundations and cells)
- Build down in alternating colors. For example, a 10
can be played on a Jack
.
- The top card of each column is available for play to the foundations, to
another tableau column or to the cells.
- Move groups of cards if they are in sequence, and if there are enough
free cells where the cards could be moved individually.
- Spaces may be filled with any card or card sequence.
Strategy
- Try to move cards from the reserve (free cells) to the tableau as soon
as possible.
- Use the reserve to temporarily hold cards that are blocking tableau
columns.
- When building on the tableau, always try to play cards to a column whose
top card is a King or has a very high rank.


ResultSet Provider - preudo component to push the current resultset into Java Sctipt and register on central plase (baseline for multip data source components)
Link to blog: Design Studio SDK: ResultSet Provider Component


Annotations can be used in classes to help generating the documentation. The Markups in the documentaion files are able to access all these annotations.
CodeDocs uses the Doctrine Annotations library. You can also use your own Annotations by extending \CodeDocs\Annotation.
Here's a list of all build-in annotations provided by CodeDocs:
| Name | Description |
|---|---|
| CodeDocs\Tag | Creates a tag that can be used to filter classes, methods, etc. |
| CodeDocs\Topic | Creates a topic that can be used by the topic() markup function. |


You ever heard of the Mandela Effect? It’s a really weird phenomena. I’ve been studying it heavily since July of 2015. The origin of the name stems from people who recall the same story in great detail about Nelson Mandela dying in prison, the riots that occured afterward, and how they had a ceremony in school or news played on the radio… except, it never happened. Nelson Mandela became President of South Africa and died years later (no longer in prison).
Many of these Mandela Effects are known. I have a quiz with around ~50k takers that show a strong bias towards something very bizarre. People with extremely accurate memories remember a different sequence of events… in some cases so does the vast majority of the population. Take these quizes to see which ones effect you. The shortest is the first one. The middle is a middle length one. The last one is a doozy.
https://goo.gl/EhPW8U
https://goo.gl/Q1KIRf
https://goo.gl/caHgbf
Here’s an image from Alice in Wonderland.
https://scontent.fbos1-1.fna.fbcdn.net/v/t1.0-9/18620331_1295571357158490_7947965661681254889_n.jpg?oh=8c0a045e4b07fd6a0c150206091ccad9&oe=59C08580
It freaks me out because I know they had little twirly beanies on their head. I remember owning a beanie with a twirly like the ones they had, but now they have flags… It’s not like the movie has been remastered… In this reality they have Flags.
How about this one of the old communist flag. Do you remember the star? The star I associate with China. This was never there for me.
https://scontent.fbos1-1.fna.fbcdn.net/v/t1.0-9/18619899_10158730255935029_5291643769552675397_n.jpg?oh=1ae1e5e774d179cc016eda5ece8588a1&oe=59A23FAE
What about the name of this dressing.
https://scontent.fbos1-1.fna.fbcdn.net/v/t1.0-9/18619957_10154925665928241_8771708522026493872_n.jpg?oh=994c72de575b1cc66e030b421a2ca08e&oe=59BF8BC1
VinAIgrette? it’s supposed to be an E not an AI. Totally weird.
I think we’re in a matrix. I think the matrix changes around us. I think the Mandela Effect is evidence of that. I just don’t know why it’s changing.
This page is synchronized from the post: ‘More Mandela Effects! Alice in Wonderland, Soviet flag, Wish Bone…’


This modal window content comes from dummy-data.component
You can specify a component or string content. Your choice!
You can do the following things with it:
- Read: modal windows will probably tell you something important so don't forget to read what they say.
- Look: a modal window enjoys a certain kind of attention; just look at it and appreciate its presence.
- Close: click on the button below to close the modal.


emini
echnologies
WASD to position "gemini" text
arrow keys to position "technologies" text
Foreground colour
Background colour
Font (from
Google Fonts
)
Font weight (multiple of 100 between 100-900; normal is 500)
300 is light, 400 is normal, 700 is bold. not all fonts have all font weights
Font size (px)
Output:


Ray
Protagonist, from Tatooine
Finn
Storm Trooper, befriends Ray
Kylo
Main villain, or is he?
Poe
Neutral pilot
Chewbacca
A great first mate
Yoda
Wise old Jedi master
Ray
Protagonist, from Tatooine
Finn
Storm Trooper, befriends Ray
Kylo
Main villain, or is he?
Poe
Neutral pilot
Chewbacca
A great first mate
Yoda
Wise old Jedi master


BPSU GAB
by Butch GunioBataan Peninsula State University president Dr. Greg Rodis, Bataan Gov. Abet Garcia, and keynote speaker DOST Usec. Renato Solidum share a laugh during the BPSU 2nd National Conference in Food, Environment, Engineering, and Technology in Balanga City.


--- title: 'California School Dashboards Part 1: Cleaning the Data' description: "Cleaning the California School Dashboard data to help your analysis" url: "post/analyzing-california-school-dashboards-part-1-cleaning/" author: Ryan Estrellado date: '2018-02-08' slug: analyzing-california-school-dashboards-part-1-cleaning categories: [] tags: [rstats, education] ---
This is part one of a three part series where I’ll be working with California School Dashboard data by cleaning, visualizaing, and exploring through modeling.
I’m writing this series for data scientists, public school educators, and data scientists who are also public school educators. Turns out, this is pretty hard to do. Most data scientists want to see reprodicible code because it explains the analysis explicitly. On the other hand, public educators may be less interested in the code and more interested in the process, questions, and answers.
So to keep things as interesting as I can for all parties, I broke up the post with descriptive headers so readers can skip sections or jump around to where their curiosity takes them. There’s code scattered throughout the post, but if that’s not interesting to you feel free to jump right over it and into the results. These usually appear right after the code. If code is your thing, you are always welcome to view all of it on my GitHub profile and to help me by making contributions and improvements.
The California School Dashboard website was built to show and analyze public school metrics such as English language arts test scores and graduation rates. The website delivers the information using icons that show scores and growth from the previous year. They also use a color coded grid so you can compare scores and growth across schools.
For a lot of folks the interface and visuals on the website will be enough to answer the questions they are asking about a school district. Others may find that the natural progression of curiosity leads to questions that require stepping outside of the California School Dashboard website to ask more specific questions and to compare across districts. If you want to start answering questions outside of what’s available in the dashboard website, you’ll need to get the data out of the website and work with it directly.
This series of posts will work through the analysis process, covering the main steps I take when exploring public education datasets:
We’ll cover the first step here and will do the rest in later posts.
I picked a school district and did some cleaning to hide the district and school names. Every California school district’s data is available on the California School Dashboard website. This demonstration will work on any of the dashboard math datasets.
The California Department of Education makes this data available on the five-by-five grid pages. First we’ll bring the data into R. Here’s how you get to the dataset:
Here’s what the math dataset looks like without any changes:
url <- "https://raw.githubusercontent.com/restrellado/data_for_blog/master/Somedistrictmath.txt"
# Show the whole CDS code instead of scientific format
math <- read_tsv(url, col_types = cols(cds = col_character()))
math
## # A tibble: 232 x 26
## cds rtype schoolname districtname countyname charter_flag coe_flag
## <chr> <chr> <chr> <chr> <chr> <lgl> <lgl>
## 1 14 D <NA> district_1 county_1 NA NA
## 2 14 D <NA> district_1 county_1 NA NA
## 3 14 D <NA> district_1 county_1 NA NA
## 4 14 D <NA> district_1 county_1 NA NA
## 5 14 D <NA> district_1 county_1 NA NA
## 6 14 D <NA> district_1 county_1 NA NA
## 7 14 D <NA> district_1 county_1 NA NA
## 8 14 D <NA> district_1 county_1 NA NA
## 9 14 D <NA> district_1 county_1 NA NA
## 10 14 D <NA> district_1 county_1 NA NA
## # … with 222 more rows, and 19 more variables: studentgroup <chr>,
## # currdenom <dbl>, currstatus <dbl>, priordenom <dbl>, priorstatus <dbl>,
## # change <dbl>, statuslevel <dbl>, changelevel <dbl>, color <dbl>, box <dbl>,
## # caa_denom <dbl>, caa_level1_num <dbl>, caa_level1_pct <dbl>,
## # caa_level2_num <dbl>, caa_level2_pct <dbl>, caa_level3_num <dbl>,
## # caa_level3_pct <dbl>, ReportingYear <chr>, X26 <lgl>
Notice that the column names aren’t immediately clear about what they’re describing. For example, the sizes of the student subgroups are kept in a column called currdenom
. The average distance from score level of three is currstatus
.
It’s super important to take the time to review the file layout, which provides definitions for every column name. It’s not the most fun reading, but you’ll find that you can help people answer questions better when you are confident you understand precisely what the numbers mean. Once you have a good understanding of what each column means, you can drop the column names you don’t need for your analysis and rename the ones that you keep. Let’s drop all columns except the school name, subgroup name, size of the subgroup, average distance from three, and the change from last year:
math <- math %>%
# Filter on just schools, not whole district counts
filter(rtype == "S") %>%
select(school = schoolname,
subgroup = studentgroup,
subgroup_size = currdenom,
avg_dfrom3 = currstatus,
change)
math
## # A tibble: 215 x 5
## school subgroup subgroup_size avg_dfrom3 change
## <chr> <chr> <dbl> <dbl> <dbl>
## 1 school_13 AA 2 NA NA
## 2 school_13 ALL 217 57.3 0.7
## 3 school_13 AS 45 73.8 2.4
## 4 school_13 EL 44 26.1 8.9
## 5 school_13 ELO 18 -8 14.5
## 6 school_13 EO 158 60.6 -3.7
## 7 school_13 FI 1 NA NA
## 8 school_13 HI 23 -22 -6.3
## 9 school_13 MR 31 62.5 -17.3
## 10 school_13 RFP 26 49.7 -2.6
## # … with 205 more rows
Much better! Now we have only the columns we want, renamed so they’re clearer:
school
: name of the schoolsubgroup
: name of the subgroupsubgroup_size
: number of students in the subgroupavg_dfrom3
: average distance from test score level three for each subgroupchange
: change in distance from three score compared to last yearThere’s one more thing I want to do here. It’s hard to see right away which subgroups I’m looking at because the dataset uses subgroup codes instead of actual names. We want to use our brain power more to ask and answer questions and less to remember what codes mean, so let’s change that. I built a handy tool in my spedtools R package that will quickly rename the codes to actual words.
(math <- math %>% mutate(subgroup = convert_subgroup(subgroup)))
## # A tibble: 215 x 5
## school subgroup subgroup_size avg_dfrom3 change
## <chr> <chr> <dbl> <dbl> <dbl>
## 1 school_13 Black/African American 2 NA NA
## 2 school_13 All Students 217 57.3 0.7
## 3 school_13 Asian 45 73.8 2.4
## 4 school_13 English Learner 44 26.1 8.9
## 5 school_13 English Learners Only 18 -8 14.5
## 6 school_13 English Only 158 60.6 -3.7
## 7 school_13 Filipino 1 NA NA
## 8 school_13 Hispanic 23 -22 -6.3
## 9 school_13 Multiple Races/Two or More 31 62.5 -17.3
## 10 school_13 RFEPs Only 26 49.7 -2.6
## # … with 205 more rows
Now that we have just the columns we want to explore and actual subgroup names instead of codes, we can start exploring the dataset faster with a series of quick exploratory questions. We just want to indulge a little curiosity and ask quick questions and answers to get the analytic juices going. My favorite way to do this is to encourage lots of questions and to provide rapid answers so the process feels casual and conversational, rather than writing up a list of questions and taking days to respond with the data. Having a clean dataset ready and being fast at the keyboard helps us do this. Here are some examples:
How different are the student subgroups in size?
Sometimes you want to get a sense of how big the student subgroups are, especially when dealing with metrics like “average distance of three”, the results of which are influenced in some part by how big the group is. Here are the top ten biggest subgroup student counts in this dataset, along with their school.
math %>%
select(-c(avg_dfrom3, change)) %>%
filter(subgroup != "All Students") %>%
filter(min_rank(desc(subgroup_size)) <= 10) %>%
arrange(desc(subgroup_size))
## # A tibble: 10 x 3
## school subgroup subgroup_size
## <chr> <chr> <dbl>
## 1 school_10 English Only 765
## 2 school_07 English Only 628
## 3 school_10 White 509
## 4 school_07 Asian 474
## 5 school_12 English Only 404
## 6 school_07 White 380
## 7 school_10 Asian 331
## 8 school_12 Asian 254
## 9 school_12 White 251
## 10 school_04 English Only 190
It’s important to note here that not all of these groups are mutually exclusive. For example, it’s possible for a student to be counted both in the White
category and in the English Only
category.
Where were the highest performing English Learner groups?
Two questions that seem to come up a lot when I work with school staff are
One way to answer the second question is to transform the data so it shows you the schools with the top ten average distance from 3 for the subgroup you’re interested in. Here’s that transformation for English learners:
math %>%
select(-c(subgroup_size, change)) %>%
filter(subgroup == "English Learner") %>%
filter(min_rank(desc(avg_dfrom3)) <= 10) %>%
arrange(desc(avg_dfrom3))
## # A tibble: 10 x 3
## school subgroup avg_dfrom3
## <chr> <chr> <dbl>
## 1 school_09 English Learner 90.5
## 2 school_07 English Learner 72.1
## 3 school_14 English Learner 61.2
## 4 school_04 English Learner 54
## 5 school_02 English Learner 50.7
## 6 school_15 English Learner 49.7
## 7 school_01 English Learner 48.9
## 8 school_03 English Learner 43.5
## 9 school_06 English Learner 37.6
## 10 school_05 English Learner 32.8
Now school staff can call colleagues at other schools to get a conversation going about what’s been working well.
Which schools had the highest increases from last year in each subgroup?
We can keep the conversation going by looking at the top two positive change scores for every subgroup. These are the schools that had the best increases in the distance from three score from last year. Now schools can get a sense of where to start calling if they want to hear about strategies, interventions, or initiatives that their colleagues are using to be successful.
math %>%
select(-subgroup_size) %>%
# Remove the All Students category so we're just looking at subgroups
filter(subgroup != "All Students", change > 0) %>%
group_by(subgroup) %>%
filter(min_rank(desc(change)) <= 2) %>%
select(subgroup, school, change) %>%
arrange(subgroup)
## # A tibble: 21 x 3
## # Groups: subgroup [11]
## subgroup school change
## <chr> <chr> <dbl>
## 1 Asian school_08 12.4
## 2 Asian school_12 11.6
## 3 Black/African American school_12 58.4
## 4 English Learner school_13 8.9
## 5 English Learner school_04 3.4
## 6 English Learners Only school_13 14.5
## 7 English Learners Only school_04 34.1
## 8 English Only school_09 9.1
## 9 English Only school_12 6.3
## 10 Hispanic school_09 13.1
## # … with 11 more rows
The California School Dashboard website makes much of its underlying data available for us to explore. It’s worthwhile to import and clean that data so when the exploration starts, school staff can rapidly ask questions and get answers in a way that organically moves the conversation towards the important questions. Next we’ll look at ways to explore the data further through data visualization.


|
Content Rating
Rate content based on objective content.
|
Functions | |
| def | perform_rating |
| def | rate |
| def | get_content_type (form) |
| def | get_rating_results_context |
| def | create_category_ratings_dict (category_ratings_queryset) |
| def | create_word_count_dict (word_count_queryset) |
| def | create_word_count_category_dict |
| def | get_rating |
This file contains helper functions for the ratings results view
| def capstoneproject.helpers.view_helpers.ratings_view_helper.create_category_ratings_dict | ( | category_ratings_queryset | ) |
This function creates a dictionary where the keys are category names and the values are category ratings from a given queryset. :param category_ratings_queryset: A CategoryRatingsQueryset which contains category names and their associated category rating. :return: A dictionary containing the data from the given queryset.
Definition at line 82 of file ratings_view_helper.py.
| def capstoneproject.helpers.view_helpers.ratings_view_helper.create_word_count_dict | ( | word_count_queryset | ) |
This function creates a dictionary where the keys are word names and the values are word counts from a given queryset. :param word_count_queryset: A WordCountQueryset containing word names and their associated word counts. :return: A dictionary containing the data from the given queryset.
Definition at line 96 of file ratings_view_helper.py.
| def capstoneproject.helpers.view_helpers.ratings_view_helper.get_content_type | ( | form | ) |
This function returns the content type of the content being rated. :param form: The form containing details about the rated content. :return: The content type as a string
Definition at line 47 of file ratings_view_helper.py.


The GUI presents instrument information to the operator.
The GUI driver is code that is part of the GUI. It's job is to present data from the instrument driver on the GUI.
Configuration files determine how the driver interacts with the instrument. They determine the communication transport, the parsers, the scripts which implement the standard features of the driver.
The GUI Data is a standardized dataset that is produced by the driver and consumed by the GUI.


Saving a vim session before quitting
When you working on a project, you often have a lot of files open in your vim. I use split and tab a lot to open all I need to work on a feature.
I leave my vim open as much as possible to avoid the pain of reopening them all everyday. Obviously, this isn't enough as sometime you don't have other choice than closing it (restarting your computer for example).
I started using the mksession command:
!mksession
(or without the ! if you don't want to override a previous session file).

I mapped to SQ
a command that create a vim session in the current directory so I just use SQ for quitting and I know that there will be a session file generated thanks to this command.
After that, I just added an «autoloading» configuration to load a session file in the current directory if any exist.
This is the stuff I added in my vimrc:
""" SESSION function! RestoreSession() if argc() == 0 "vim called without arguments let FILESESSION=expand("./session.vim") if filereadable(FILESESSION) execute 'source ./session.vim' endif end endfunction nmap SQ <ESC>:mksession! ./session.vim<CR>:wqa<CR> autocmd VimEnter * call RestoreSession()
Now, I just need to open vim from the root directory of the project and think about leaving using SQ to generate the session file. The next time, I just need to go to root directory of the project and open vim without argument and the session will be loaded.
/!\ If you open a file directly (by using vim ./path/to/file
), the session won't be open.
It makes sens for me to do this in the project root directory as I already have my ctags file there, as explain in this blog post.
As long as I open vim from the root directory of each project, my ctags and my session will be loaded :)
Isn't that beautiful ? :)


Ronaldinho
This is an image of world best footballer
He is great
played for brazil
Top skiller OAT
Passes like real legend
read more about ronaldinho


Haydy Abdalla
Mini Project 1
This project involves GitHub. I partnered with fellow classmates to gain experience with working on
projects with other people on GitHub and using controls such as "forking," "branching," "pull requests,"
"commits" and "push."
Mini Project 2
In this project I teamed up with a classmate to build a website together using GitHub and Webstorm. Throughout
this process, I have learned about how to work with other people, how to edit, and the steps needed to take so
that my partner can see the changes I've made.
Mini Project 3
This project involved me exercising the use of GitHub, Webstorm, Jekyll, and Bootstrap to create a wepage.
Paulina Ortiz
IS117 Mini Project 1
For Mini Project 1 I was in charge of part three of the project. I created a step by step tutorial that
explains how to set up Git and work with others.
I explained how to use branching and how to solve merge conflicts to ease the process of working with others.
For Mini Project 2 I worked with my classmate, Haydy Adballa, to create a website collaboratively. The skills I
learned in Mini Project 1 helped in working as a group and I gained new ones after this project.
For Mini Project 3 I worked with my classmate to create a website using Bootstrap and Jekyll pages.


| ▼NHelix | |
| ▼NSocket | |
| ▼NWebSocket | |
| CFrame | A WebSocket frame |
| CFrameHandler | Interprets parsed frames from the peer, and packs and writes frames |
| CFrameReader | Reads frames from the peer |
| CHandshake | Initial WebSocket connection handshake |
| CWebSocketClient | Wraps a WebSocket peer |
| CWebSocketError | A WebSocket error |
| CWebSocketServer | A WebSocket server |
| CAbstractClient | Abstract client socket |
| CAbstractServer | Abstract server socket |
| CAbstractSocket | Abstract parent to all sockets |
| CDatagramClient | Broadcasts datagrams |
| CDatagramServer | Receives datagrams |
| CReactiveInterface | The instance can be added to a reactor and notified of selection |
| CReactor | Selects and calls reactive sockets when they are readable |
| CSocketError | A socket error |
| CSocketInterface | Instance has an underlying socket resource |
| CStreamClient | Full duplex connection |
| CStreamServer | Server that accepts and wraps incoming connections as client instances |


PRISCILLA, QUEEN OF THE DESERT A film review by Max Hoffmann Copyright 1994 Max Hoffmann
World Premiere!!! Castro Theatre, SF Film Festival Sun May 8th
THE ADVENTURES OF PRISCILLA, QUEEN OF THE DESERT -- Australian 1994, 107 min Director & Screenplay: Stephan Elliot Producer: Al Clark, Michael Hamlyn Camera: Brian Breheny Editor: Sue Blainey Cast: Terence Stamp, Hugo Weaving, Guy Pearce, Bill Hunter, Sara Chadwick Print: Polygram International
Rating: Scale 1-10 (10 = highest) 11
A lengthy, standing ovation in SF's venerable Castro theatre ended the world premiere of what may prove to be the festival's runaway hit!  PRISCILLA is high camp comedy, with mainstream appeal that succeeds on nearly every level, a definite "cross over" candidate if it finds the right distribution. Imagine the funniest, most life-affirming moments from HAROLD AND MAUDE, LA CAGE AUX FOLLES, STRICTLY BALLROOM, and BAGDAD CAFE and you'll have some sense of what a jewel this film is.
It's worth the price of admission for the costumes and wigs alone! We haven't seen anything this outrageous since Von Sternberg took Marlena Dietrich's eyebrows to new heights. Although the premise for this film might scare away the less imaginative film goer, for the rest of us there's something supremely liberating about seeing a silver-lame coated drag queen, straddling the top of a speeding bus like a champion water skier, trailed by a 50-foot mylar scarf, lip-synching Opera! I don't know about you, but that's something I just can't see too often!
PRISCILLA is a far cry from PARIS IS BURNING, with its sad, clown-like drag queens vainly trying to latch on to someone else's faded glamour. These girls tear through the heartland of Australia's homophobia, like a sequined Conestoga wagon, blazing new trails into the frontiers of possiblity and self-discovery. Each encounter leaves the people they meet changed, mostly for the better. They're living proof that Goddess placed drag queens on the planet to bring life and color into our sad and dreary lives.
Hugo Weaving (of PROOF) as "Mitzi" gets an offer to do a four-week gig in Alice Springs. He's joined by Guy Pearce as "Felicia" and Terence Stamp as "Bernadette" to go westward-ho, scattering sequins and adventures along the way. Stephan Elliot's script has almost as many juicy one-liners as sequins and rivals THE WOMEN for deliciously bitchy humor. The screenplay often steers the audience's attention one way, and then pulls the punchline in another. Bernadette joins the trek because his twenty-five-year-old lover has just died. As the crane shot descends over the sequined crowd gathered around the grave site, everyone in the audience immediately draws the conclusion that the young man died of AIDS. Heading towards the limo, Berndatte steams, "cheeky little bugger, he was bleaching his hair in the bathroom, was overcome by the peroxide fumes, passed out and hit his head on the tiles! I told him to go to a salon."
Although there is one fag bashing, and several intense encounters with homophobia, neither the characters nor the film ever wallow in self pity, or take on the status of a victim. The three drag stars take life face on, on their own terms, often trading successfully on their underdog status (much the way the first ROCKY did).
Terence Stamp (FAR FROM THE MADDING CROWD, THE COLLECTOR) in his first comedic role, gives a touching and inspired performance as a tired but regal transsexual who's seen it all. Unlike other mainstream actor's, who go over the top doing drag, Stamp brings a quiet sense of dignity to his Tallulah-esque diva. If the film gets sufficient distribution, Stamp may have to make room on his mantle for a little gold statue next spring.
Stamp garnered some of the best on-liners in the film, and aims them with the accuracy of a heat-seeking missile. He's a scene stealer, equal to Eve Arden in STAGEDOOR.
Elliot's script fleshes out his characters quite nicely, belying most of the stereotypes usually related to drag. (It's revealed early on that one of the trio has been "batting for both sides" so to speak, giving rise to a brief, healthy dose of "heterophobia.") Speaking of fleshed out, Guy Pearce needs little help in that arena. His scantily clad form, often out of drag, is the stuff of a calendar publisher's dream! Pearce is the perfect foil for Stamp's world weary comic timing. Hugo Weaving's Mitzi, the more responsible member of the party, keeps one eye on the road and the uncertain future ahead, in a highly compelling performance (with considerable "sticking power" for a comedy).
Characters encountered along the way are as rich and endearing as any found in BAGDAD CAFE. Bill Hunter as the garage mechanic, who chucks his conventional lifestyle to join the merry trio, makes a strong mark on the film. As does Sara Chadwick as the kind of mother that is the stuff of Jesse Helm's worst nightmares. I'll avoid any more plot spoilers, but will say that the "ping pong" scene must be seen to be believed.
In the director's talk, Elliott revealed that the costumes by his friends Lizzy Gardener and Tim Chapell were done on a literal shoe string. My favorite was the 60's miniskirt outfit made of cheap plastic sandels! Elliott revealed that the natural "bounce" for Stamp's bosom was achieved by filling condoms with moisturizer. One scene with a heavy embrace had to be re-filmed when the condoms popped! Several of the costumes used during club performances make eye popping visual puns (including the Sydney Opera house).
Any budget restraints on the film were belied by the stunning camera work and keen sense of lighting. Frequent interior shots on the bus never approached claustrophobia due to the variety of imaginative camera angles.
Incidentally, director Elliot had originally planned to use real drag queens. But as he put it, when he ran an ad announcing the opportunity to trek across the outback in drag, covered in flies, he only had one applicant, so he used real actors. Stamp was chosen from a list of actors who were considered to be playing "against type." Elliot never imagined that Stamp would actually accept. If the film is seen by the right audience in LA, Stamp's the decision to play "Bernadette" may prove to be the shrewdest move of his career.
PRISCILLA doesn't have distribution yet, but it's under consideration by Polygram. FAX this review with your vote to see it to:
Polygram Film International 9348 Civic Center Drive, Sutie 300 Beverly Hills, CA 90210, USA FAX:<PHONE_NUMBER>
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