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ActiveTcl User Guide
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Tcl_GetEncoding, Tcl_FreeEncoding, Tcl_ExternalToUtfDString, Tcl_ExternalToUtf, Tcl_UtfToExternalDString, Tcl_UtfToExternal, Tcl_WinTCharToUtf, Tcl_WinUtfToTChar, Tcl_GetEncodingName, Tcl_SetSystemEncoding, Tcl_GetEncodingNames, Tcl_CreateEncoding, Tcl_GetDefaultEncodingDir, Tcl_SetDefaultEncodingDir - procedures for creating and using encodings.
#include <tcl.h>
Tcl_Encoding
Tcl_GetEncoding(interp, name)
void
Tcl_FreeEncoding(encoding)
char *
Tcl_ExternalToUtfDString(encoding, src, srcLen,
dstPtr)
int
Tcl_ExternalToUtf(interp, encoding, src, srcLen, flags,
statePtr, dst, dstLen, srcReadPtr, dstWrotePtr,
dstCharsPtr)
char *
Tcl_UtfToExternalDString(encoding, src, srcLen,
dstPtr)
int
Tcl_UtfToExternal(interp, encoding, src, srcLen, flags,
statePtr, dst, dstLen, srcReadPtr, dstWrotePtr,
dstCharsPtr)
char *
Tcl_WinTCharToUtf(tsrc, srcLen, dstPtr)
TCHAR *
Tcl_WinUtfToTChar(src, srcLen, dstPtr)
CONST char *
Tcl_GetEncodingName(encoding)
int
Tcl_SetSystemEncoding(interp, name)
void
Tcl_GetEncodingNames(interp)
Tcl_Encoding
Tcl_CreateEncoding(typePtr)
CONST char *
Tcl_GetDefaultEncodingDir(void)
void
Tcl_SetDefaultEncodingDir(path)
These routines convert between Tcl's internal character representation, UTF-8, and character representations used by various operating systems or file systems, such as Unicode, ASCII, or Shift-JIS. When operating on strings, such as such as obtaining the names of files or displaying characters using international fonts, the strings must be translated into one or possibly multiple formats that the various system calls can use. For instance, on a Japanese Unix workstation, a user might obtain a filename represented in the EUC-JP file encoding and then translate the characters to the jisx0208 font encoding in order to display the filename in a Tk widget. The purpose of the encoding package is to help bridge the translation gap. UTF-8 provides an intermediate staging ground for all the various encodings. In the example above, text would be translated into UTF-8 from whatever file encoding the operating system is using. Then it would be translated from UTF-8 into whatever font encoding the display routines require.
Some basic encodings are compiled into Tcl. Others can be defined by the user or dynamically loaded from encoding files in a platform-independent manner.
Tcl_GetEncoding finds an encoding given its name. The name may refer to a builtin Tcl encoding, a user-defined encoding registered by calling Tcl_CreateEncoding, or a dynamically-loadable encoding file. The return value is a token that represents the encoding and can be used in subsequent calls to procedures such as Tcl_GetEncodingName, Tcl_FreeEncoding, and Tcl_UtfToExternal. If the name did not refer to any known or loadable encoding, NULL is returned and an error message is returned in interp.
The encoding package maintains a database of all encodings currently in use. The first time name is seen, Tcl_GetEncoding returns an encoding with a reference count of 1. If the same name is requested further times, then the reference count for that encoding is incremented without the overhead of allocating a new encoding and all its associated data structures.
When an encoding is no longer needed, Tcl_FreeEncoding should be called to release it. When an encoding is no longer in use anywhere (i.e., it has been freed as many times as it has been gotten) Tcl_FreeEncoding will release all storage the encoding was using and delete it from the database.
Tcl_ExternalToUtfDString converts a source buffer src from the specified encoding into UTF-8. The converted bytes are stored in dstPtr, which is then NULL terminated. The caller should eventually call Tcl_DStringFree to free any information stored in dstPtr. When converting, if any of the characters in the source buffer cannot be represented in the target encoding, a default fallback character will be used. The return value is a pointer to the value stored in the DString.
Tcl_ExternalToUtf converts a source buffer src from the specified encoding into UTF-8. Up to srcLen bytes are converted from the source buffer and up to dstLen converted bytes are stored in dst. In all cases, *srcReadPtr is filled with the number of bytes that were successfully converted from src and *dstWrotePtr is filled with the corresponding number of bytes that were stored in dst. The return value is one of the following:
Tcl_UtfToExternalDString converts a source buffer src from UTF-8 into the specified encoding. The converted bytes are stored in dstPtr, which is then terminated with the appropriate encoding-specific NULL. The caller should eventually call Tcl_DStringFree to free any information stored in dstPtr. When converting, if any of the characters in the source buffer cannot be represented in the target encoding, a default fallback character will be used. The return value is a pointer to the value stored in the DString.
Tcl_UtfToExternal converts a source buffer src from UTF-8 into the specified encoding. Up to srcLen bytes are converted from the source buffer and up to dstLen converted bytes are stored in dst. In all cases, *srcReadPtr is filled with the number of bytes that were successfully converted from src and *dstWrotePtr is filled with the corresponding number of bytes that were stored in dst. The return values are the same as the return values for Tcl_ExternalToUtf.
Tcl_WinUtfToTChar and Tcl_WinTCharToUtf are Windows-only convenience functions for converting between UTF-8 and Windows strings. On Windows 95 (as with the Macintosh and Unix operating systems), all strings exchanged between Tcl and the operating system are "char" based. On Windows NT, some strings exchanged between Tcl and the operating system are "char" oriented while others are in Unicode. By convention, in Windows a TCHAR is a character in the ANSI code page on Windows 95 and a Unicode character on Windows NT.
If you planned to use the same "char" based interfaces on both Windows 95 and Windows NT, you could use Tcl_UtfToExternal and Tcl_ExternalToUtf (or their Tcl_DString equivalents) with an encoding of NULL (the current system encoding). On the other hand, if you planned to use the Unicode interface when running on Windows NT and the "char" interfaces when running on Windows 95, you would have to perform the following type of test over and over in your program (as represented in pseudo-code):
if (running NT) { encoding <- Tcl_GetEncoding("unicode"); nativeBuffer <- Tcl_UtfToExternal(encoding, utfBuffer); Tcl_FreeEncoding(encoding); } else { nativeBuffer <- Tcl_UtfToExternal(NULL, utfBuffer);
Tcl_WinUtfToTChar and Tcl_WinTCharToUtf automatically handle this test and use the proper encoding based on the current operating system. Tcl_WinUtfToTChar returns a pointer to a TCHAR string, and Tcl_WinTCharToUtf expects a TCHAR string pointer as the src string. Otherwise, these functions behave identically to Tcl_UtfToExternalDString and Tcl_ExternalToUtfDString.
Tcl_GetEncodingName is roughly the inverse of Tcl_GetEncoding. Given an encoding, the return value is the name argument that was used to create the encoding. The string returned by Tcl_GetEncodingName is only guaranteed to persist until the encoding is deleted. The caller must not modify this string.
Tcl_SetSystemEncoding sets the default encoding that should be used whenever the user passes a NULL value for the encoding argument to any of the other encoding functions. If name is NULL, the system encoding is reset to the default system encoding, binary. If the name did not refer to any known or loadable encoding, TCL_ERROR is returned and an error message is left in interp. Otherwise, this procedure increments the reference count of the new system encoding, decrements the reference count of the old system encoding, and returns TCL_OK.
Tcl_GetEncodingNames sets the interp result to a list consisting of the names of all the encodings that are currently defined or can be dynamically loaded, searching the encoding path specified by Tcl_SetDefaultEncodingDir. This procedure does not ensure that the dynamically-loadable encoding files contain valid data, but merely that they exist.
Tcl_CreateEncoding defines a new encoding and registers the C procedures that are called back to convert between the encoding and UTF-8. Encodings created by Tcl_CreateEncoding are thereafter visible in the database used by Tcl_GetEncoding. Just as with the Tcl_GetEncoding procedure, the return value is a token that represents the encoding and can be used in subsequent calls to other encoding functions. Tcl_CreateEncoding returns an encoding with a reference count of 1. If an encoding with the specified name already exists, then its entry in the database is replaced with the new encoding; the token for the old encoding will remain valid and continue to behave as before, but users of the new token will now call the new encoding procedures.
The typePtr argument to Tcl_CreateEncoding contains information about the name of the encoding and the procedures that will be called to convert between this encoding and UTF-8. It is defined as follows:
typedef struct Tcl_EncodingType { CONST char *encodingName; Tcl_EncodingConvertProc *toUtfProc; Tcl_EncodingConvertProc *fromUtfProc; Tcl_EncodingFreeProc *freeProc; ClientData clientData; int nullSize; } Tcl_EncodingType;
The encodingName provides a string name for the encoding, by which it can be referred in other procedures such as Tcl_GetEncoding. The toUtfProc refers to a callback procedure to invoke to convert text from this encoding into UTF-8. The fromUtfProc refers to a callback procedure to invoke to convert text from UTF-8 into this encoding. The freeProc refers to a callback procedure to invoke when this encoding is deleted. The freeProc field may be NULL. The clientData contains an arbitrary one-word value passed to toUtfProc, fromUtfProc, and freeProc whenever they are called. Typically, this is a pointer to a data structure containing encoding-specific information that can be used by the callback procedures. For instance, two very similar encodings such as ascii and macRoman may use the same callback procedure, but use different values of clientData to control its behavior. The nullSize specifies the number of zero bytes that signify end-of-string in this encoding. It must be 1 (for single-byte or multi-byte encodings like ASCII or Shift-JIS) or 2 (for double-byte encodings like Unicode). Constant-sized encodings with 3 or more bytes per character (such as CNS11643) are not accepted.
The callback procedures toUtfProc and fromUtfProc should match the type Tcl_EncodingConvertProc:
typedef int Tcl_EncodingConvertProc( ClientData clientData, CONST char *src, int srcLen, int flags, Tcl_Encoding *statePtr, char *dst, int dstLen, int *srcReadPtr, int *dstWrotePtr, int *dstCharsPtr);
The toUtfProc and fromUtfProc procedures are called by the Tcl_ExternalToUtf or Tcl_UtfToExternal family of functions to perform the actual conversion. The clientData parameter to these procedures is the same as the clientData field specified to Tcl_CreateEncoding when the encoding was created. The remaining arguments to the callback procedures are the same as the arguments, documented at the top, to Tcl_ExternalToUtf or Tcl_UtfToExternal, with the following exceptions. If the srcLen argument to one of those high-level functions is negative, the value passed to the callback procedure will be the appropriate encoding-specific string length of src. If any of the srcReadPtr, dstWrotePtr, or dstCharsPtr arguments to one of the high-level functions is NULL, the corresponding value passed to the callback procedure will be a non-NULL location.
The callback procedure freeProc, if non-NULL, should match the type Tcl_EncodingFreeProc:
typedef void Tcl_EncodingFreeProc( ClientData clientData);
This freeProc function is called when the encoding is deleted. The clientData parameter is the same as the clientData field specified to Tcl_CreateEncoding when the encoding was created.
Tcl_GetDefaultEncodingDir and Tcl_SetDefaultEncodingDir access and set the directory to use when locating the default encoding files. If this value is not NULL, the TclpInitLibraryPath routine appends the path to the head of the search path, and uses this path as the first place to look into when trying to locate the encoding file.
Space would prohibit precompiling into Tcl every possible encoding algorithm, so many encodings are stored on disk as dynamically-loadable encoding files. This behavior also allows the user to create additional encoding files that can be loaded using the same mechanism. These encoding files contain information about the tables and/or escape sequences used to map between an external encoding and Unicode. The external encoding may consist of single-byte, multi-byte, or double-byte characters.
Each dynamically-loadable encoding is represented as a text file. The initial line of the file, beginning with a ``#'' symbol, is a comment that provides a human-readable description of the file. The next line identifies the type of encoding file. It can be one of the following letters:
The rest of the lines in the file depend on the type.
Cases [1], [2], and [3] are collectively referred to as table-based encoding files. The lines in a table-based encoding file are in the same format as this example taken from the shiftjis encoding (this is not the complete file):
# Encoding file: shiftjis, multi-byte M 003F 0 40 00<PHONE_NUMBER>020003000400050006000700080009000A000B000C000D000E000F<PHONE_NUMBER>120013001400150016001700180019001A001B001C001D001E001F<PHONE_NUMBER>220023002400250026002700280029002A002B002C002D002E002F<PHONE_NUMBER>320033003400350036003700380039003A003B003C003D003E003F<PHONE_NUMBER>420043004400450046004700480049004A004B004C004D004E004F<PHONE_NUMBER>520053005400550056005700580059005A005B005C005D005E005F<PHONE_NUMBER>620063006400650066006700680069006A006B006C006D006E006F<PHONE_NUMBER>720073007400750076007700780079007A007B007C007D203E007F<PHONE_NUMBER>000000000000000000000000000000000000000000000000000000<PHONE_NUMBER>000000000000000000000000000000000000000000000000000000 0000FF61FF62FF63FF64FF65FF66FF67FF68FF69FF6AFF6BFF6CFF6DFF6EFF6F FF70FF71FF72FF73FF74FF75FF76FF77FF78FF79FF7AFF7BFF7CFF7DFF7EFF7F FF80FF81FF82FF83FF84FF85FF86FF87FF88FF89FF8AFF8BFF8CFF8DFF8EFF8F FF90FF91FF92FF93FF94FF95FF96FF97FF98FF99FF9AFF9BFF9CFF9DFF9EFF9F<PHONE_NUMBER>000000000000000000000000000000000000000000000000000000<PHONE_NUMBER>000000000000000000000000000000000000000000000000000000 81<PHONE_NUMBER>000000000000000000000000000000000000000000000000000000<PHONE_NUMBER>000000000000000000000000000000000000000000000000000000<PHONE_NUMBER>000000000000000000000000000000000000000000000000000000<PHONE_NUMBER>000000000000000000000000000000000000000000000000000000<PHONE_NUMBER>02FF0CFF0E30FBFF1AFF1BFF1FFF01309B309C00B4FF4000A8FF3E FFE3FF3F30FD30FE309D309E30034EDD30053006300730FC20152010FF0F005C 301C2016FF5C2026202520182019201C201DFF08FF0930143015FF3BFF3DFF5B FF5D30083009300A300B300C300D300E300F30103011FF0B221200B100D70000 00F7FF1D2260FF1CFF1E22662267221E22342642264000B0203220332103FFE5 FF0400A200A3FF05FF03FF06FF0AFF2000A72606260525CB25CF25CE25C725C6 25A125A025B325B225BD25BC203B301221922190219121933013000000000000<PHONE_NUMBER>00000000000000000000002208220B2286228722822283222A2229<PHONE_NUMBER>00000000000000000000002227222800AC21D221D4220022030000<PHONE_NUMBER>000000000000000000000000000000222022A52312220222072261 2252226A226B221A223D221D2235222B222C0000000000000000000000000000 212B2030266F266D266A2020202100B6000000000000000025EF000000000000
The third line of the file is three numbers. The first number is the fallback character (in base 16) to use when converting from UTF-8 to this encoding. The second number is a 1 if this file represents the encoding for a symbol font, or 0 otherwise. The last number (in base 10) is how many pages of data follow.
Subsequent lines in the example above are pages that describe how to map from the encoding into 2-byte Unicode. The first line in a page identifies the page number. Following it are 256 double-byte numbers, arranged as 16 rows of 16 numbers. Given a character in the encoding, the high byte of that character is used to select which page, and the low byte of that character is used as an index to select one of the double-byte numbers in that page - the value obtained being the corresponding Unicode character. By examination of the example above, one can see that the characters 0x7E and 0x8163 in shiftjis map to 203E and 2026 in Unicode, respectively.
Following the first page will be all the other pages, each in the same format as the first: one number identifying the page followed by 256 double-byte Unicode characters. If a character in the encoding maps to the Unicode character 0000, it means that the character doesn't actually exist. If all characters on a page would map to 0000, that page can be omitted.
Case [4] is the escape-sequence encoding file. The lines in an this type of file are in the same format as this example taken from the iso2022-jp encoding:
# Encoding file: iso2022-jp, escape-driven E init {} final {} iso8859-1 \x1b(B jis0201 \x1b(J jis0208 \x1b$@ jis0208 \x1b$B jis0212 \x1b$(D gb2312 \x1b$A ksc5601 \x1b$(C
In the file, the first column represents an option and the second column is the associated value. init is a string to emit or expect before the first character is converted, while final is a string to emit or expect after the last character. All other options are names of table-based encodings; the associated value is the escape-sequence that marks that encoding. Tcl syntax is used for the values; in the above example, for instance, ``{}'' represents the empty string and ``\x1b'' represents character 27.
When Tcl_GetEncoding encounters an encoding name that has not been loaded, it attempts to load an encoding file called name.enc from the encoding subdirectory of each directory specified in the library path $tcl_libPath. If the encoding file exists, but is malformed, an error message will be left in interp.
Copyright © 1997-1998 Sun Microsystems, Inc. Copyright © 1995-1997 Roger E. Critchlow Jr.


Middleware
@available(*, deprecated, message: "Use `MiddlewareProtocol` instead of `Middleware`. This protocol will be removed on 1.0.")
public protocol Middleware : MiddlewareProtocol
⛓ Middleware
is a plugin, or a composition of several plugins, that are assigned to the ReduxStoreProtocol
pipeline in order to handle each
action received (InputActionType
), to execute side-effects in response, and eventually dispatch more actions (OutputActionType
) in the process.
This happens before the Reducer
to do its job.
We can think of a Middleware as an object that transforms actions into sync or async tasks and create more actions as these side-effects complete, also being able to check the current state at any point.
An action is a lightweight structure, typically an enum, that is dispatched into the ActionHandler
(usually a StoreProtocol
).
A Store like ReduxStoreProtocol
enqueues a new action that arrives and submits it to a pipeline of middlewares. So, in other words, a Middleware
is class that handles actions, and has the power to dispatch more actions to the ActionHandler
chain. The Middleware
can also simply ignore the
action, or it can execute side-effects in response, such as logging into file or over the network, or execute http requests, for example. In case of
those async tasks, when they complete the middleware can dispatch new actions containing a payload with the response (a JSON file, an array of
movies, credentials, etc). Other middlewares will handle that, or maybe even the same middleware in a future RunLoop, or perhaps some Reducer
, as
reducers pipeline is at the end of every middleware pipeline.
Middlewares can schedule a callback to be executed after the reducer pipeline is done mutating the global state. At that point, the middleware will have access to the new state, and in case it cached the old state it can compare them, log, audit, perform analytics tracking, telemetry or state sync with external devices, such as Apple Watches. Remote Debugging over the network is also a great use of a Middleware.
Every action dispatched also comes with its action source, which is the primary dispatcher of that action. Middlewares can access the file, line, function and additional information about the entity responsible for creating and dispatching that action, which is a very powerful debugging information that can help developers to trace how the information flows through the app.
Because the Middleware
receive all actions and accesses the state of the app at any point, anything can be done from these small and reusable
boxes. For example, the same CoreLocation
middleware could be used from an iOS app, its extensions, the Apple Watch extension or even different
apps, as long as they share some sub-state struct.
Some suggestions of middlewares:
- Run Timers, pooling some external resource or updating some local state at a constant time
- Subscribe for
CoreData
,Realm
,Firebase Realtime Database
or equivalent database changes - Be a
CoreLocation
delegate, checking for significant location changes or beacon ranges and triggering actions to update the state - Be a
HealthKit
delegate to track activities, or even combining that withCoreLocation
observation in order to track the activity route - Logger, Telemetry, Auditing, Analytics tracker, Crash report breadcrumbs
- Monitoring or debugging tools, like external apps to monitor the state and actions remotely from a different device
WatchConnectivity
sync, keep iOS and watchOS state in sync- API calls and other “cold observables”
- Network Reachability
- Navigation through the app (Redux Coordinator pattern)
CoreBluetooth
central or peripheral managerCoreNFC
manager and delegateNotificationCenter
and other delegates- WebSocket, TCP Socket, Multipeer and many other connectivity protocols
RxSwift
observables,ReactiveSwift
signal producers,Combine
publishers- Observation of traits changes, device rotation, language/locale, dark mode, dynamic fonts, background/foreground state
- Any side-effect, I/O, networking, sensors, third-party libraries that you want to abstract
┌─────┐ ┌─────┐
│ │ handle ┌──────────┐ request ┌ ─ ─ ─ ─ response ┌──────────┐ dispatch │ │
│ │ ┌─────────▶│Middleware├─────────────▶ External│─────────────▶│Middleware│───────────▶│Store│─ ─ ▶ ...
│ │ │ Action │ Pipeline │ side-effects │ World side-effects │ callback │ New Action │ │
│ │ │ └──────────┘ ─ ─ ─ ─ ┘ └──────────┘ └─────┘
┌──────┐ dispatch │ │ │ ▲
│Button│─────────▶│Store│──▶│ └───afterReducer─────┐ ┌────────┐
└──────┘ Action │ │ │ │ ┌─▶│ View 1 │
│ │ │ ┌─────┐ │ └────────┘
│ │ │ reduce ┌──────────┐ │ │ onNext │ ┌────────┐
│ │ └─────────▶│ Reducer ├───────────▶│Store│────────────▶├─▶│ View 2 │
│ │ Action │ Pipeline │ New state │ │ New state │ └────────┘
└─────┘ + └──────────┘ └─────┘ │ ┌────────┐
State └─▶│ View 3 │
└────────┘
Middleware protocol is generic over 3 associated types:
InputActionType:
The Action type that this Middleware
knows how to handle, so the store will forward actions of this type to this middleware.
Thanks to optics, this action can be a sub-action lifted to a global action type in order to compose with other middlewares acting on the global action of an app. Please check lift(inputActionMap:outputActionMap:stateMap:)
for more details.
OutputActionType:
The Action type that this Middleware
will eventually trigger back to the store in response of side-effects. This can be the same as InputActionType
or different, in case you want to separate your enum in requests and responses.
Thanks to optics, this action can be a sub-action lifted to a global action type in order to compose with other middlewares acting on the global action of an app. Please check lift(inputActionMap:outputActionMap:stateMap:)
for more details.
StateType:
The State part that this Middleware
needs to read in order to make decisions. This middleware will be able to read the most up-to-date StateType
from the store at any point in time, but it can never write or make changes to it. In some cases, middleware don’t need reading the whole global state, so we can decide to allow only a sub-state, or maybe this middleware doesn’t need to read any state, so the StateType
can safely be set to Void
.
Thanks to lenses, this state can be a sub-state lifted to a global state in order to compose with other middlewares acting on the global state of an app. Please check lift(inputActionMap:outputActionMap:stateMap:)
for more details.
When implementing your Middleware, all you have to do is to handle the incoming actions:
When implementing your Middleware, all you have to do is to handle the incoming actions:
class LoggerMiddleware: Middleware {
typealias InputActionType = AppGlobalAction // It wants to receive all possible app actions
typealias OutputActionType = Never // No action is generated from this Middleware
typealias StateType = AppGlobalState // It wants to read the whole app state
var getState: GetState<AppGlobalState>!
func receiveContext(getState: @escaping GetState<AppGlobalState>, output: AnyActionHandler<Never>) {
self.getState = getState
}
func handle(action: AppGlobalAction, from dispatcher: ActionSource, afterReducer: inout AfterReducer) {
let stateBefore: AppGlobalState = getState()
let dateBefore = Date()
afterReducer = .do {
let stateAfter = self.getState()
let dateAfter = Date()
let source = "\(dispatcher.file):\(dispatcher.line) - \(dispatcher.function) | \(dispatcher.info ?? "")"
Logger.log(action: action, from: source, before: stateBefore, after: stateAfter, dateBefore: dateBefore, dateAfter: dateAfter)
}
}
}
class FavoritesAPIMiddleware: Middleware {
typealias InputActionType = FavoritesAction // It wants to receive only actions related to Favorites
typealias OutputActionType = FavoritesAction // It wants to also dispatch actions related to Favorites
typealias StateType = FavoritesModel // It wants to read the app state that manages favorites
var getState: GetState<FavoritesModel>!
var output: AnyActionHandler<FavoritesAction>!
func receiveContext(getState: @escaping GetState<FavoritesModel>, output: AnyActionHandler<FavoritesAction>) {
self.getState = getState
self.output = output
}
func handle(action: FavoritesAction, from dispatcher: ActionSource, afterReducer: inout AfterReducer) {
guard let .toggleFavorite(movieId) = action else { return }
let favoritesList = getState()
let makeFavorite = !favoritesList.contains(where: { $0.id == movieId })
API.changeFavorite(id: movieId, makeFavorite: makeFavorite) (completion: { result in
switch result {
case let .success(value):
self.output.dispatch(.changedFavorite(movieId, isFavorite: true), info: "API.changeFavorite callback")
case let .failure(error):
self.output.dispatch(.changedFavoriteHasFailed(movieId, isFavorite: false, error: error), info: "API.changeFavorite callback")
}
})
}
}
-
Handles the incoming actions and may or not start async tasks, check the latest state at any point or dispatch additional actions. This is also a good place for analytics, tracking, logging and telemetry. You can schedule tasks to run after the reducer changed the global state if you want, and/or execute things before the reducer. This function is only called by the store after the
receiveContext(getState:output:)
was called, so if you saved the received context from there you can safely use it here to get the state or dispatch new actions. Setting theafterReducer
in/out parameter is optional, if you don’t set it, it defaults to.doNothing()
.Declaration
Swift
func handle(action: InputActionType, from dispatcher: ActionSource, afterReducer: inout AfterReducer)
Parameters
action
the action to be handled
dispatcher
information about the action source, representing the entity that created and dispatched the action
afterReducer
it can be set to perform any operation after the reducer has changed the global state. If the function ends before you set this in/out parameter,
afterReducer
will default to.doNothing()
. -
handle(action:
Extension methodfrom: state: ) Declaration
Swift
public func handle(action: InputActionType, from dispatcher: ActionSource, state: @escaping GetState<StateType>) -> IO<OutputActionType>


Created by Saksham Agarwal / Piyush Bhopalka
TextView tv = (TextView)findViewById(R.id.my_text_view);
tv.setText("Hello text view");
EditText editText = (EditText)findViewById(R.id.my_edit_text);
String s = editText.getText().toString();
Button b = (Button)findViewById(R.id.my_button);
b.setOnClickListener(new View.OnClickListener() {
@Override
public void onClick(View v) {
/* Whatever you may want to do on Click */
}
});
Two EditTexts For input
Four buttons, one each for basic arithmetic operations
After completion, check to see if you have done the same as here
The same code can be written efficiently like this
Choose Empty Activity, not Blank Activity
Intent i = new Intent(MainActivity.this, Activity2.class);
startActivity(i);
Intent i = new Intent(MainActivity.this, Activity2.class);
i.putExtra("my_key", "The text to be passed");
startActivity(i);
Intent i = getIntent();
String s = i.getStringExtra("my_key");
Explicit Intents - Intents within an app
Implicit Intents - Intents sent to another app on your device
String url = "http://www.facebook.com/groups/nitcdroid";
Intent i = new Intent(Intent.ACTION_VIEW, Uri.parse(url));
startActivity(i);
String url = "http://www.facebook.com/groups/nitcdroid";
Intent i = new Intent(Intent.ACTION_VIEW, Uri.parse(url));
startActivity(Intent.createChooser(i, "Visit NITC-Droid using"));
Create a Contacts app which displays several contacts each having:
Optional: Clicking on the contact should open dialer with that number
Next slide contains a demo of how the app should look likeYour app should look something like this:
- That's it for Week 1
- We just barely scratched through the tip of a few things. Self study is going to be the key.
- For deeper understanding, go through the Udacity Course or the Android Developer Website.
- Next week we will dive a little deeper into Views


Lorry driver Mo Robinson pleads guilty to plotting to assist illegal immigration in Essex lorry deaths' case
Lorry driver Maurice Robinson (25) who is accused over the deaths of 39 migrants, has pleaded guilty to plotting to assist illegal immigration.
Maurice Robinson, known as Mo Robinson, who was allegedly part of a global smuggling ring, is charged with the manslaughter of a group of men, women and children found dead in a refrigerated trailer.
The bodies of eight females and 31 males were discovered in the trailer attached to his Scania cab in an industrial park in Grays, Essex, on October 23.
The victims were later identified as coming from various provinces of Vietnam, with the youngest being two boys aged 15.
Robinson appeared at the Old Bailey via video link from Belmarsh prison for a plea hearing this morning.
Wearing a light blue sweater and tan trousers, he spoke to confirm his identity and British nationality.
During the hearing before Mr Justice Edis, he admitted conspiracy to assist unlawful immigration between May 1 2018 and October 24 2019.
The charge states that he plotted with others to do "an act or series of acts which facilitated the commission of a breach of immigration law by various persons".
He also admitted acquiring criminal property - namely cash - on the same dates.
The defendant, of Laurel Drive in Craigavon, was not asked to enter pleas to other charges, including 39 counts of manslaughter.
He is charged with conspiracy to commit human trafficking offences between May 1 2018 and October 24 2019.
The details of that charge state that he "arranged or facilitated the travel of other persons into the UK with a view to their being exploited".
He is also charged with transferring criminal property.
The defendant was remanded into custody until a further hearing on December 13.
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simpleCount
1.0
Getting Started
Choice Of Components
Design Choices
Conception
simpleCount
Docs
»
SimpleCount Project for Epitech
View page source
SimpleCount Project for Epitech
¶
Features
¶
RPN (Reverse Polish Notation)
Google calculator design (nearly!)
Reflexivity + generic listener
MVC pattern / observer pattern
100% Carottes
Documentation
¶
Getting Started
Build / Execute simpleCount
Execute jar file
Execute exe file
Use an IDE to run the solution
About the project itself
Choice Of Components
JDK version used
Libraries used
AWT Library
Swing Library
Math Library
Util Library
Design Choices
Design components
JFrame
JPanel
JButton
Conception
Reverse Polish Notation
Model Pattern View Controller (MVC)
Observer / Observable Pattern
Generic Listener


FOR several moments after Mr. Kampura’s shocking announcement about Mrs. Rossmeyer,
there was silence. Nancy and her father looked at each other, then at the Mises.
Finally Mr. Drew asked, “Are you sure of your information? We heard nothing about this in
our country.”
Mr. Kampura rose from his chair and said, “I have no details. Her death was discussed at a
jeweler’s conference. As you know, she was a lover of gems and, therefore, was well known
to the trade.”
“In a company as large and successful as yours,” Mr. Drew said, “I suppose you have a good
deal of thievery.”
“Oh, no, not at all,” Mr. Kampura replied. “We have very tight security and little loss.”
Impatiently, he stepped from behind his desk and went toward the door. The Drews and the
Mises realized that he did not wish to prolong the meeting, and they followed him.
“I’m from a rather small town in the United States,” Mr. Drew said. “However, a Japanese
man lives there who is an expert on gems. His name is Moto. Do you know him?”
26
“No,” Mr. Kampura replied, “I have never heard of him.”
He opened the door, and the visitors thanked him, said good-by, and left. No remarks were
exchanged as they went down in the elevator and out the building.
When they were seated once more in the Mises car, Mrs. Mise spoke up. “Nancy, I am sure
that Mr. Kampura did not discover your disguise. I am very glad.”
“So am I,” Nancy remarked. “I have a hunch that Mr. Kampura was not telling the truth
about either Mrs. Rossmeyer or Mr. Moto. Let’s try to find out about Mrs. Rossmeyer
through other sources.”
Mr. Mise directed them to a Tokyo newspaper office that published an English edition. They
looked through file copies for any notices of the socialite’s death. There was nothing, and
the group drove home.
Mr. Drew made various overseas telephone calls but could not verify the report that Mr.
Kampura had given them. Finally Nancy had an idea.
“Dad, you remember Renee Marcel who attended school with me? She was from Paris and
now is a society reporter for a paper there. Why don’t I get in touch with her? Surely if Mrs.
Rossmeyer died, Renee would know about it.”
“Good thinking. Phone Renee and see what she can find out.”
Nancy put in the call and surprised her friend. The two girls chatted about personal matters
for a few moments, then Nancy asked about Mrs. Rossmeyer.
“Hold the line,” Renee answered. “I will make a quick search.” She was gone no more than
two minutes. “Nancy,” she said upon her return, “this story is not true. Night before last,
Mrs. Rossmeyer gave a large dinner party in Paris. I’ll try to get in touch with her and let you
know more details if I can.”
Nancy gave Renee the Mises’ telephone number and waited for an answer. It came after
lunch.
“I learned that Mrs. Rossmeyer is in good health,” Renee reported. “She told a friend that
for personal reasons she was going into hiding for a short time.”
“Have you any idea where?” Nancy asked.
Renee said that one source had mentioned Japan, another the United States. Later that day,
the girl phoned again. She had spoken to the porter in Mrs. Rossmeyer’s hotel. He had
heard her say the previous day that she was heading for the airport to fly to Japan to the
Mikomoto Pearl Farm. It was her expectation to make some large purchases.
27
Nancy was elated about the news. “Could we go there soon and verify the report?” she
asked Mr. Mise.
“It is a long way from here,” he said. “But a friend of mine runs a seaplane that he charters
to groups. Let me call him and see when the next flight is.”
After a short phone conversation, their host hung up with a smile. “The plane is leaving for
the pearl farm early tomorrow morning.”
“Wonderful!” Nancy exclaimed. “We’re in luck!”
Conversation now turned from Mrs. Rossmeyer to Mr. Kampura. Had he lied intentionally to
throw the Drews off the scent? Was Mrs. Rossmeyer in some way connected with World
Wide Gems? Was he trying to protect her? And why had he denied knowing Mr. Moto? Had
they not been his tire tracks that showed the Rising Sun insignia in the rear of the jewelry
shop?
Nancy mentioned that she felt it was probably wise to contact the police at this point. “They
may have records on World Wide Gems, Mr. Kampura, and Mrs. Rossmeyer.”
Mr. Mise said he would take Nancy to headquarters but suggested that perhaps she would
like to remove her Japanese disguise.
“I’ll be happy to,” Nancy said.
It took her nearly half an hour to restore her skin to the American look, to lighten the
blackened eyebrows, and to change into her own clothes. Then she and Mr. Mise set off. He
knew the chief of police personally and explained their case, translating for Nancy what he
learned.
“It is not generally known, but World Wide Gems is under surveillance in several countries,”
the chief told them. “As you heard in the United States, the organization as a whole is not
suspected of any wrongdoing, but certain members are thought to have connections with
underworld characters. The police are watching carefully.”
“Is Mr. Kampura under suspicion?” Nancy asked.
“Not so far. Why?”
“Because we think that he visited Mr. Moto’s jewelry shop in River Heights just before the
jeweler disappeared without a trace. But Mr. Kampura denied knowing Mr. Moto. He also
told us Mrs. Rossmeyer had a fatal accident, which does not seem to be true.”
The chief nodded thoughtfully. “We will try to find out more about Mr. Kampura.”
Nancy asked the chief about Mr. Moto, but as far as he knew, the man had not come to
Japan.
28
“I’m afraid he was kidnapped,” Nancy said. “It seems strange that Mr. Kikichi, whom he left
in charge of his shop, had not heard anything from his friend after he left.”
“It is possible,” the officer said, “that Mr. Moto, for some reason of his own, disappeared in
a hurry, and therefore left his room in a shambles. Has anyone investigated the possibility
that he might have gone into hiding?”
Nancy admitted that they had not thought of this. “But why should he?” she asked. “He has
had the shop in River Heights for many years and is highly respected.”
“Even the finest people can have enemies,” the officer said with a smile. “They might be
connected with business, or family, or even friends.”
“But Mr. Moto is such a nice man. I can’t imagine his having any personal enemies. I’m sure
that if something happened to him, it was because of the thievery going on in his business.”
The chief promised to let her know if any leads to Mr. Moto’s disappearance turned up, and
Nancy and Mr. Mise thanked him, then left.
After their visit to police headquarters, there was still enough time for the Drews to do
some shopping and to go to Mr. Tetsuo Moto’s former residence to see if they could learn a
clue from the neighbors.
Mr. Mise picked up Mr. Drew, who had visited a business associate during his daughter’s
trip to police headquarters, then he drove the Drews to the Ginza, Tokyo’s main shopping
street. Nancy’s first purchase was a lovely pearl necklace for Hannah Gruen. The salesman
showed them matching earrings and suggested that the lucky receiver of the necklace could
surely use earrings to go with it.
Mr. Drew smiled. “All right, we’ll take them for Hannah, too.”
Pretty pins of pearls intertwined with enameled leaves were selected for Bess and George.
Nancy’s gift to Ned Nickerson was a pearl stick pin, and she bought cufflinks for Burt and
Dave with money the girls had given her. The Drews concluded their shopping with a lovely
pearl and silver bracelet for Mr. Drew’s sister, Eloise.
While they were waiting for the articles to be gift-wrapped, Nancy wandered around the
store looking at pictures on the walls.  She was wearing a necklace with a huge pinkish pearl in the middle and smaller-sized
white ones on both sides of it.
“I wonder if this is like Mrs. Rossmeyer’s,” Nancy thought and looked at the date of the
picture. It was a hundred years old.
“This type of necklace must have been popular with royalty in those days,” the girl mused.
29
Just then Mr. Mise said he would bring the car to the door. After he left, the Drews
examined various art objects that were displayed throughout the shop. They saw a vase that
was very similar to the one belonging to Professor Mise and his wife in River Heights, which
Togo had inadvertently broken.
“Let’s buy it and have it sent to them!” Nancy urged her father. He agreed. When the
transaction was taken care of, they walked out of the shop and climbed into Mr. Mise’s car.
He drove them to the street where Mr. Moto’s brother had lived. They found the small
apartment building facing one of the many streams that crisscrossed the city.
“Suppose we question the neighbors first,” Nancy suggested. “I’ll go with Mrs. Mise and Dad
with Mr. Mise, so we each have a translator.”
“Good idea,” Mr. Drew agreed. “We’ll meet out here when we’re finished.”
It was more than an hour before the four assembled in the street again. Their search had
been unsuccessful. A number of people had known Tetsuo Moto, but could tell the Drews
no more than that he had moved to the country. Next, the group went to all neighborhood
stores and questioned the owners, but again in vain. There was no trace of the jeweler’s
brother!
“We’ll just have to rely on the police to track him down,” Mr. Drew said to Nancy, who was
very disappointed. “I’ll call them again tonight.”
She nodded. “Even though I believe Mr. Moto was kidnapped, I was still hoping to pick up
some information from his brother, Tetsuo. Well—” she sighed, “maybe we’ll find a clue
elsewhere.”
Early the following morning the Mises and the Drews set out for a visit to a pearl farm. They
drove to the dock where the seaplane was anchored and joined a group of people for the
take-off. The journey was pleasant and the scenery interesting, with woods and mountains
in the background.
“Tell me something about pearl farms,” Nancy begged Mr. Mise.
“I will be glad to,” he said. “You see, there are two kinds of beds, those in which the oysters
are raised until they are large enough to be used in pearl culture, and those in which they
are kept after insertion of the nucleus.”
“Today we’ll see one of the latter kind, won’t we?” Nancy asked.
“That is right. They must be in an area where nutritious plankton is plentiful and where the
currents can flow freely around the oyster,” Mr. Mise went on, “but they shouldn’t be near
mouths of rivers that pump pollution into the sea.”
“Should the water be a certain temperature?”
30
“Oh, yes. The oysters tolerate a range between fifty and seventy-seven degrees Fahrenheit.
Since the farm waters reach temperatures below fifty degrees in the winter, the rafts and
baskets must be moved farther south. To people in the culture region, these caravans that
are pulled by boats are a familiar sight.”
Nancy laughed. “I wonder if the oysters enjoy the trip.”
“I suppose we will never know,” Mr. Mise said with a chuckle.
“How about depth?” Nancy asked. “Does that influence the production of nacre?”
“Definitely. In shallow water, more layers develop, but they tend to be of inferior quality.”
“What is considered shallow?”
“About seven to ten feet. You see, when water temperatures are between fifty-nine and
seventy-seven degrees in the summer, increased nacre production is encouraged. But in the
winter, the oysters are lowered to a depth of about seventeen to twenty feet. This insures a
lovely pink color and better quality.”
“How old are the oysters when they are injected with the nucleus?” Nancy inquired.
“About two years.”
After a long flight, the pilot’s voice sounded over the intercom. He announced that they
would be landing soon. He spoke first in English, then in Japanese.
Suddenly the seaplane began to lurch.
“What’s happening?” Nancy asked apprehensively, looking at her father.
“I don’t know,” Mr. Drew replied. “I can’t imagine—”
The craft lurched again, and the smooth hum of the engines seemed to change. The
passengers were tossed about, and a woman screamed. An engine conked out, then the
other. Nancy and her father grabbed each other’s hands. Were they about to crash?


Shaked Walker
1.0
Loading...
Searching...
No Matches
Public Attributes
|
List of all members
GeomAssimpMesh Struct Reference
Public Attributes
GLuint
aVao
GLuint
aVbo
GLuint
aIbo
GLuint
aTexture0
int
aVerticeCount
int
aIndiceCount
int
aFaceCount
char *
aName
MainVertexPTN
*
aVtx
unsigned int *
aIndices
The documentation for this struct was generated from the following file:
C:/Users/Admin/Documents/GitHub/shaked_walker/Walking_Humanoid_Shaked/System/
GeomGL.h
Generated by
1.9.6


Welcome to Super Simple Backbone Starter Kit
This is your home page. To edit it, just modify the
index.html
file.
Learn more.


Introduction
Summary
This week we will review the basics of HTML, CSS, and JS and create a personal website. We will reflect on our relationship with technology and learning. And think about the "big ideas" we want to explore this semester.
Readings
Read at least one of the following articles
- "Computer as Material: Messing about Time" by Seymour Papert (1988)
- "Papert's Big Idea" by Seymour Papert (2000)
- "Ghost in the Machine: Seymour Papert on How Computers Fundamentally Change the Way Kids Learn" Interview of Seymour Papert by Dan Schwartz (1999)
- "Mindstorms: Children, Computers, and Powerful Ideas", Chapter 2 Mathphobia: The Fear of Learning, Seymour Papert (1980)
Deliverables
- Sign-up for a GitHub Account
- Share your GitHub user-name with your professor immediately so they can add you to the class repository.
- Once you have access to the class github repository, you will find a folder with your name in the 'students' folder.
-
Start your personal website. Follow these instuctions:
- Use the template website as a starting point
- Create a table of contents in 'index.html'. It will contain a link to a page for each of the 15 weeks of the coure.
- Make sure to create a seperate webpage for each week. For example, week 1 would be saved in 'week_01.html'.
- Use at least 25 different HTML tags
- Use use at least 50 different CSS tags
- Push to github when completed. Feel free to update as many times as you like.
- Reflection Assignment, Week 1 Write 300-400 words reflecting on your relationship with technology. What are your goals for the course? Is there a "big idea" you hope to explore? Is there a topic you have encountered at DIDI or another school you want to learn better? What is your biggest fear with this course? Cite the readings and/or an inspiring person, project, or problem to help formulate a response. Include any sketches or images to help you explain your answer.


I'm sorry to say, but your browser does not seem supported. You might want to try another (more modern?) browser. As far as we know this site works on most modern browsers, such as Mozilla Firefox and Google Chrome.
In case you're interested: This has to do with the FileReader
API only being available in modern webbrowser. We use this API to make it possible for you to upload and run your own combats.


?Plantas
de
la
Repblica
Dominicana
New
York
Botanical
Garden
Ib245b3
BOTANICAL
OARDE^.
t
Eustoma
exaltatum
Det.
by:
M.
Alford,
viii/2000
(L.)
Griseb.
COttlttlOh
names
Gentianaceae
Collector:
Mac
Alford
MA
2768
7/30/2000
Description:
Succulent
herbs;
leaves
glaucous;
petals
purplish;
stigma
large
and
bifid.
Locality:
Prov.
LA
ALTAGRACIA:
road
along
Juamillo
south
of
Punta
Cana,
5-15
km.
Chemical
analyses:
EX
HERBARIUM
BAILEY
HORTORIUM
(BH),
CORNELL
UNIVERSITY,
ITHACA.
NEW
YORK
Cornell
University
Biodiversity
Laboratory
at
Punta
Cana
1624563
Legend -
Level of confidence that token is an accurately-transcribed word
extremely low
very low
low
undetermined
medium
high
very high


About Me
I am an electrical engineer looking to change careers to become a software engineer. In addition to some device and test rig programming experience, primarily in Python and C, I have experience consulting in the defense, consumer device, and medical device industry.
Currently I am attending the Epicodus Javascript/C#/React coding bootcamp, and look forward to learning the tools and habits to become a better programmer!
Things I'm looking for in my next company:
- Mentorship and growth opportunities
- Work flexibility
- Meaningful diversity initiatives
- Time set aside for employees to volunteer
- Company hackathons
Education:
Epicodus - Seattle, WA (remote)
Javascript, C#, React Sept 2021
Georgia Institute of Technology - Atlanta, GA
M.S. Electrical and Computer Engineering May 2018
B.S. Electrical Engineering Dec 2015
Skills:
HTML, CSS, Javascript, React, Python, C, Java, Flask, Express, AWS (Lambda, DynamoDB, SMS,
API Gateway, Amplify, Cognito, RDS), C++, MATLAB, LabVIEW
Experience:
Freelancing for Bill Johnson - Upwork Aug 2020
- Migrated an existing Express backend API to a Javascript AWS Lambda and API Gateway, associated to the React frontend and RDS MySQL database using Amplify with API restriction to a Cognito user pool.
Cambridge Consultants - Boston, MA
Electrical Engineer - MedTech Aug 2018 - Feb 2021
Electrical Engineering Co-OpJan 2018 - Aug 2018
- Created a React web app, with a Flask API back end and instrument drivers in Python, to automate radiation pattern testing and control equipment for an anechoic chamber.
- Created instrument drivers and test cases in Python and assembled a test bed for simulating
hardware faults on a consumer device to aid in automated testing of firmware error detection and
handling.
- Programmed a microcontroller in C for prototyping and determining the performance of a linear
magnetic actuator.
- Created batch files in order to automate the configuration of laptops and acquire test data for WiFi
latency in hospitals and clinical test facilities.
- Designed and laid out rigid and flex printed circuit boards (PCBs) for communication coil/sensor
interfaces for medical devices and user study devices, and for programming/testing consumer
devices.
- Created power budget and predicted size models for sensor systems in medical device feasibility and
usage studies.
Georgia Tech Research Institute - Sensors and Electromagnetic Applications Lab - Smyrna, GA
Electrical Engineering Associate (Kelly Services Contractor) Feb - Jul 2016
Electrical Engineering Co-OpJan 2014 - Aug 2015
- Programmed microcontrollers in C to control modules in a radio frequency (RF) system and interface
with a computer through Ethernet and USB.
- Created programs in LabVIEW to control instruments and automate report generation in the testing
of incoming batches of RF boards.
- Utilized various lab equipment to evaluate during testing and debug digital, power, and mixed signal
RF PCBs.
- Augmented the layout for and produced PCBs for signal drivers, destructive test, and multi-channel
RF boards with microcontrollers and logic array devices.
- Designed and laid out power conversion and distribution boards with microcontrollers, breakout
boards for testing differential signals, and signal driver boards for LEDs and digital modules.
Hobbies:
- Combat Archery League at Archery Games Boston
- Boardgames - some favorites:
- Hiking/Backpacking
- Aspirations to complete the NH48!


{{ metadata.get('title') }}
Chapter 5: Third Parties
Introduction
The open web is vast, linkable, and interoperable by design. The ability
to grab someone else’s complex library and use it on your site with a
single <link>
or <script>
element
has supercharged developers’ productivity and enabled awesome new web
experiences. On the flip side, the immense popularity of a select few
third-party providers raises important performance and privacy concerns.
This chapter examines the prevalence and impact of third-party code on
the web in 2019, the web usage patterns that lead to the popularity of
third-party solutions, and potential repercussions for the future of web
performance and privacy.
Definitions
“Third Party”
A third party is an entity outside the primary site-user relationship, i.e. the aspects of the site not directly within the control of the site owner but present with their approval. For example, the Google Analytics script is an example of a common third-party resource.
Third-party resources are…
- Hosted on a shared and public origin
- Widely used by a variety of sites
- Uninfluenced by an individual site owner
To match these goals as closely as possible, the formal definition used throughout this chapter of a third-party resource is a resource that originates from a domain whose resources can be found on at least 50 unique pages in the HTTPArchive dataset.
Provider Categories
This chapter divides third-party providers into one of these broad categories. A brief description is included below and the mapping of domain to category can be found in the third-party-web repository.
- Ad - display and measurement of advertisements
- Analytics - tracking site visitor behavior
- CDN - providers that host public shared utilities or private content of their users
- Content - providers that facilitate publishers and host syndicated content
- Customer Success - support and customer relationship management functionality
- Hosting - providers that host the arbitrary content of their users
- Marketing - sales, lead generation, and email marketing functionality
- Social - social networks and their affiliated integrations
- Tag Manager - provider whose sole role is to manage the inclusion of other third parties
- Utility - code that aids the development objectives of the site owner
- Video - providers that host the arbitrary video content of their users
- Other - uncategorized or non-conforming activity
Data
Third-party code is everywhere. 93% of pages include at least one third-party resource, 76% of pages issue a request to an analytics domain, the median page requests content from at least 9 unique third-party domains that represent 35% of their total network activity, and the most active 10% of pages issue a whopping 175 third-party requests or more. It’s not a stretch to say that third parties are an integral part of the web.
<insert stylized value of metric 05_01>
<insert stylized value of metric 05_02>
Categories
If the ubiquity of third-party content is unsurprising, perhaps more interesting is the breakdown of third-party content by provider type.
While advertising might be the most user-visible example of third-party presence on the web, analytics providers are the most common third-party category with 76% of sites including at least one analytics request. CDNs at 63%, ads at 57%, and developer utilities like Sentry, Stripe, and Google Maps SDK at 56% follow up as a close second, third, and fourth for appearing on the most web properties. The popularity of these categories forms the foundation of our web usage patterns identified later in the chapter.
<insert graphic of metric 05_11>
Providers
A relatively small set of providers dominate the third-party landscape, the top 100 domains account for 30% of network requests across the web. Powerhouses like Google, Facebook, and YouTube make the headlines here with full percentage points of share each, but smaller entities like Wix and Shopify command a substantial portion of third-party popularity as well.
While much could be said about every individual provider’s popularity and performance impact, this more opinionated analysis is left as an exercise for the reader and other purpose-built tools such as third-party-web.
<insert table of metric 05_06>
<insert table of metric 05_09>
Resource Types
The resource type breakdown of third-party content also lends insight into how third-party code is used across the web. While first-party requests are 56% images, 23% script, 14% CSS, and only 4% HTML, third-party requests skew more heavily toward script and HTML at 32% script, 34% images, 12% HTML, and only 6% CSS. While this suggests that third-party code is less frequently used to aid the design and instead used more frequently to facilitate or observe interactions than first-party code, a breakdown of resource types by party status tells a more nuanced story. While CSS and images are dominantly first-party at 70% and 64% respectively, fonts are largely served by third-party providers with only 28% being served from first-party sources. This concept of usage patterns is explored in more depth later in this chapter.
<insert graphic of metric 05_03>
Several other amusing factoids jump out from this data. Tracking pixels (image requests to analytics domains) make up 1.6% of all network requests, six times as many video requests are to social networks like Facebook and Twitter than dedicated video providers like YouTube and Vimeo (presumably because the default YouTube embed consists of HTML and a preview thumbnail but not an autoplaying video), and there are still more requests for first-party images than all scripts combined.
Request Count
49% of all requests are third-party. At 51%, first-party can still narrowly hold on to the crown in 2019 of comprising the majority of the web resources. Given that just under half of all the requests are third-party yet a small set of pages do not include any at all, the most active third-party users must be doing quite a bit more than their fair share. Indeed, at the 75th, 90th, and 99th percentiles we see nearly all of the page being comprised of third-party content. In fact, for some sites heavily relying on distributed WYSIWYG platforms like Wix and SquareSpace, the root document might be the sole first-party request!
<insert graphic of metric 05_11>
The number of requests issued by each third-party provider also varies considerably by category. While analytics are the most widespread third-party category across websites, they account for only 7% of all third-party network requests. Ads, on the other hand, are found on nearly 20% fewer sites yet make up 25% of all third-party network requests. Their outsized resource impact compared to their popularity will be a theme we continue to uncover in the remaining data.
Byte Weight
While 49% of requests are third-party, their share of the web in terms of bytes is quite a bit lower at only 28%. The same goes for the breakdown by multiple resource types. Third-party fonts make up 72% of all fonts, but they’re only 53% of font bytes; 74% of HTML requests, but only 39% of HTML bytes; 68% of video requests, but only 31% of video bytes. All this seems to suggest third-party providers are responsible stewards who keep their response sizes low, and, for the most part, that is in fact the case until you look at scripts.
Despite serving 57% of scripts, third parties comprise 64% of script bytes. meaning their scripts are larger on average than first-party scripts. This is an early warning sign for their performance impact to come in the next few sections.
<insert graphic of metric 05_04>
<insert graphic of metric 05_12>
As for specific third-party providers, the same juggernauts topping the request count leaderboards make their appearance in byte weight as well. The only few notable movements are the large, media-heavy providers such as YouTube, Shopify, and Twitter which climb to the top of the byte impact charts.
<insert table of metric 05_07>
Script Execution
57% of script execution time is from third-party scripts, and the top 100 domains already account for 48% of all script execution time on the web. This underscores just how large an impact a select few entities really have on web performance. This topic is explored more in depth in the Repercussions > Performance section.
<insert graphic of metric 05_05>
<insert graphic of metric 05_13>
The category breakdowns among script execution largely follow that of resource counts. Here too advertising looms largest. Ad scripts comprise 25% of third-party script execution time with hosting and social providers in a distant tie for second at 12%.
<insert table of metric 05_08>
<insert table of metric 05_10>
While much could be said about every individual provider’s popularity and performance impact, this more opinionated analysis is left as an exercise for the reader and other purpose-built tools such as the previously mentioned third-party-web.
Analysis
Usage Patterns
Why do site owners use third-party code? How did third-party content grow to be nearly half of all network requests? What are all these requests doing? Answers to these questions lie in the three primary usage patterns of third-party resources. Broadly, site owners reach for third parties to generate and consume data from their users, monetize their site experiences, and simplify web development.
Generate and Consume Data
Analytics is the most popular third-party category found across the web and yet is minimally user-visible. Consider the volume of information at play in the lifetime of a web visit; there’s user context, device, browser, connection quality, location, page interactions, session length, return visitor status, and more being generated continuously. It’s difficult, cumbersome, and expensive to maintain tools that warehouse, normalize, and analyze time series data of this magnitude. While nothing categorically necessitates that analytics fall into the domain of third-party providers, the widespread attractiveness of understanding your users, deep complexity of the problem space, and increasing emphasis on managing data respectfully and responsibly naturally surfaces analytics as a popular third-party usage pattern.
There’s also a flip side to user data though: consumption. While analytics is about generating data from your site’s visitors, other third-party resources focus on consuming data about your visitors that is known only by others. Social providers fall squarely into this usage pattern. A site owner must use Facebook resources if they wish to integrate information from a visitor’s Facebook profile into their site. As long as site owners are interested in personalizing their experience with widgets from social networks and leveraging the social networks of their visitors to increase their reach, social integrations are likely to remain the domain of third-party entities for the foreseeable future.
Monetize Web Traffic
The open model of the web does not always serve the financial interests of content creators to their liking and many site owners resort to monetizing their sites with advertising. Because building direct relationships with advertisers and negotiating pricing contracts is a relatively difficult and time-consuming process, this concern is largely handled by third-party providers performing targeted advertising and real-time bidding. Widespread negative public opinion, the popularity of ad blocking technology, and regulatory action in major global markets such as Europe pose the largest threat to the continued use of third-party providers for monetization. While it’s unlikely that site owners suddenly strike their own advertising deals or build bespoke ad networks, alternative monetization models like paywalls and experiments like Brave’s Basic Attention Token have a real chance of shaking up the third-party ad landscape of the future.
Simplify Development
Above all, third-party resources are used to simplify the web development experience. Even previous usage patterns could arguably fall into this pattern as well. Whether analyzing user behavior, communicating with advertisers, or personalizing the user experience, third-party resources are used to make first-party development easier.
Hosting providers are the most extreme example of this pattern. Some of these providers even enable anyone on Earth to become a site owner with no technical expertise necessary. They provide hosting of assets, tools to build sites without coding experience, and domain registration services.
The remainder of third-party providers also tend to fall into this usage pattern. Whether it’s hosting of a utility library such as jQuery for usage by front-end developers cached on Cloudflare’s edge servers or a vast library of common fonts served from a popular Google CDN, third-party content is another way to give the site owner one fewer thing to worry about and, maybe, just maybe make the job of delivering a great experience a little bit easier.
Repercussions
Performance
The performance impact of third-party content is neither categorically good nor bad. There are good and bad actors across the spectrum and different category types have varying levels of influence.
The good: shared third-party font and stylesheet utilities are, on average, delivered more efficiently than their first-party counterparts.
Utilities, CDNs, and Content categories are the brightest spots on the third-party performance landscape. They offer optimized versions of the same sort of content that would otherwise be served from first-party sources. Google Fonts and Typekit serve optimized fonts that are smaller on average than first-party fonts, Cloudflare CDN serves a minified version of open source libraries that might be accidentally served in development mode by some site owners, Google Maps SDK efficiently delivers complex maps that might otherwise be naively shipped as large images.
The bad: a very small set of entities represent a very large chunk of JavaScript execution time carrying out narrow set of functionality on pages.
Ads, social, hosting, and certain analytics providers represent the largest negative impact on web performance. While hosting providers deliver a majority of a site’s content and will understandably have a larger performance impact than other third-party categories, they also serve almost entirely static sites that demand very little JavaScript in most cases that should not justify the volume of script execution time. The other categories hurting performance though have even less of an excuse. They fill very narrow roles on each page they appear on and yet quickly take over a majority of resources. For example, the Facebook "Like" button and associated social widgets take up extraordinarily little screen real estate and are a fraction of most web experiences, and yet the median impact on pages with social third parties is nearly 20% of their total JavaScript execution time. The situation is similar for analytics - tracking libraries do not directly contribute to the perceived user experience, and yet the 90th percentile impact on pages with analytics third parties is 44% of their total JavaScript execution time.
The silver lining of such a small number of entities enjoying such large market share is that a very limited and concentrated effort can have an enormous impact on the web as a whole. Performance improvements at just the top few hosting providers can improve 2-3% of all web requests.
Privacy
The abundance of analytics providers and top-heavy concentration of script execution raises two primary privacy concerns for site visitors: the largest use case of third-parties is for site owners to track their users and a handful of companies receive information on a large swath of web traffic.
The interest of site owners in understanding and analyzing user behavior is not malicious on its own, but the widespread and relatively behind-the-scenes nature of web analytics raises valid concerns, and users, companies, and lawmakers have taken notice in recent years with privacy regulation such as GDPR in Europe and the CCPA in California. Ensuring that developers handle user data responsibly, treat the user respectfully, and are transparent with what data is collected is key to keeping analytics the most popular third-party category and maintaining the symbiotic nature of analyzing user behavior to deliver future user value.
The top-heavy concentration of script execution is great for the potential impact of performance improvements, but less exciting for the privacy ramifications. 29% of all script execution time across the web is just from scripts on domains owned by Google or Facebook. That’s a very large percentage of CPU time that is controlled by just two entities. It’s critical to ensure that the same privacy protections held to analytics providers be applied in these other ad, social, and developer utility categories as well.
Caveats
- All data presented here is based on a non-interactive, cold load. These values could start to look quite different after user interaction.
- Third-party content served from a first-party domain is counted as first-party content. i.e. self-hosting Google Fonts or bootstrap.css will be considered first-party content.
- First-party content served from a third-party domain is counted as third-party content. i.e. first-party images served over a third-party CDN will be considered third-party content.
- Roughly 84% of all third-party domains by request volume have been identified and categorized. The remaining 16% fall into the “Other” category.


Lesson 1 Tidy Spatial Analysis
1.1 Overview
Questions
- How to elegantly conduct complex spatial analysis by chaining operations?
- What is the percent area of water by region across the United States?
Objectives
- Use the
%>%
operator (aka “then” or “pipe”) to pass output from one function into input of the next. - Calculate metrics on spatial attributes.
- Aggregate spatial data with metrics.
- Display a map of results.
1.2 Prerequisites
R Skill Level: Intermediate - you’ve got basics of R down.
You will use the sf
package for vector data along with the dplyr
package for calculating and manipulating attribute data.
# load packages
library(tidyverse) # load dplyr, tidyr, ggplot2 packages
library(sf) # vector reading & analysis
# set working directory to data folder
# setwd("pathToDirHere")
1.3 States: read and plot
Similar to Lesson 9: Handling Spatial Projection & CRS in R, we’ll start by reading in a polygon shapefile using the sf
package. Then use the default plot()
function to see what it looks like.
# read in states
states <- read_sf("data/NEON-DS-Site-Layout-Files/US-Boundary-Layers/US-State-Boundaries-Census-2014.shp")
# plot the states
plot(states)
## Warning: plotting the first 9 out of 10 attributes; use max.plot = 10 to
## plot all
Notice the default plot on sf
objects outputs colorized values of the first 9 of 10 columns. Use the suggestion from the warning to plot the 10th column.
# plot 10th column
plot(states, max.plot = 10)
# show columns of the data frame
names(states)
## [1] "STATEFP" "STATENS" "AFFGEOID" "GEOID" "STUSPS" "NAME"
## [7] "LSAD" "ALAND" "AWATER" "region" "geometry"
# look at table
glimpse(states)
## Observations: 58
## Variables: 11
## $ STATEFP <chr> "06", "11", "12", "13", "16", "17", "19", "21", "22",...
## $ STATENS <chr> "01779778", "01702382", "00294478", "01705317", "0177...
## $ AFFGEOID <chr> "0400000US06", "0400000US11", "0400000US12", "0400000...
## $ GEOID <chr> "06", "11", "12", "13", "16", "17", "19", "21", "22",...
## $ STUSPS <chr> "CA", "DC", "FL", "GA", "ID", "IL", "IA", "KY", "LA",...
## $ NAME <chr> "California", "District of Columbia", "Florida", "Geo...
## $ LSAD <chr> "00", "00", "00", "00", "00", "00", "00", "00", "00",...
## $ ALAND <dbl><PHONE_NUMBER>81, 158350578,<PHONE_NUMBER>55,<PHONE_NUMBER>99, ...
## $ AWATER <dbl><PHONE_NUMBER>1, 18633500,<PHONE_NUMBER>1,<PHONE_NUMBER>, 23977...
## $ region <chr> "West", "Northeast", "Southeast", "Southeast", "West"...
## $ geometry <simple_feature> MULTIPOLYGONZ(((-118.593969..., MULTIPOLYG...
# convert to tibble for nicer printing
as_tibble(states)
## Simple feature collection with 58 features and 10 fields
## geometry type: MULTIPOLYGON
## dimension: XYZ
## bbox: xmin: -124.7258 ymin: 24.49813 xmax: -66.9499 ymax: 49.38436
## epsg (SRID): 4326
## proj4string: +proj=longlat +datum=WGS84 +no_defs
## # A tibble: 58 x 11
## STATEFP STATENS AFFGEOID GEOID STUSPS NAME LSAD
## <chr> <chr> <chr> <chr> <chr> <chr> <chr>
## 1 06 01779778 0400000US06 06 CA California 00
## 2 11 01702382 0400000US11 11 DC District of Columbia 00
## 3 12 00294478 0400000US12 12 FL Florida 00
## 4 13 01705317 0400000US13 13 GA Georgia 00
## 5 16 01779783 0400000US16 16 ID Idaho 00
## 6 17 01779784 0400000US17 17 IL Illinois 00
## 7 19 01779785 0400000US19 19 IA Iowa 00
## 8 21 01779786 0400000US21 21 KY Kentucky 00
## 9 22 01629543 0400000US22 22 LA Louisiana 00
## 10 24 01714934 0400000US24 24 MD Maryland 00
## # ... with 48 more rows, and 4 more variables: ALAND <dbl>, AWATER <dbl>,
## # region <chr>, geometry <simple_feature>
names(states)
## [1] "STATEFP" "STATENS" "AFFGEOID" "GEOID" "STUSPS" "NAME"
## [7] "LSAD" "ALAND" "AWATER" "region" "geometry"
# inspect the class(es) of the states object
class(states)
## [1] "sf" "tbl_df" "tbl" "data.frame"
The class of the states
object is both a simple feature (sf
) as well as a data frame, which means the many useful functions available to a data frame (or “tibble”) can be applied.
To plot the column of interest, feed the “slice” of that column to the plot()
function.
plot(states['region'])
Question: To motivate the spatial analysis for the rest of this lesson, you will answer this question: “What is the percent water by region?”
1.4 Challenge: analytical steps?
Outline a sequence of analytical steps needed to arrive at the answer.
1.4.1 Answers
- Sum the area of water (
AWATER
) and land (ALAND
) per region. - Divide the area of water (
AWATER
) by the area of land (ALAND
) per region to arrive at percent water. - Show table of regions sorted by percent water.
- Show map of regions by percent water with a color ramp and legend.
1.5 Regions: calculate % water
- Use the
%>%
operator (aka “then” or “pipe”) to pass output from one function into input of the next.- In RStudio, see menu Help > Keyboard Shortcuts Help for a shortcut to the “Insert Pipe Operator”.
- Calculate metrics on spatial attributes.
- In RStudio, see menu Help > Cheatsheets > Data Manipulation with dplyr, tidyr.
- Aggregate spatial data with metrics.
regions = states %>%
group_by(region) %>%
summarize(
water = sum(AWATER),
land = sum(ALAND)) %>%
mutate(
pct_water = water / land * 100 %>% round(2))
# object
regions
## Simple feature collection with 5 features and 4 fields
## geometry type: GEOMETRY
## dimension: XYZ
## bbox: xmin: -124.7258 ymin: 24.49813 xmax: -66.9499 ymax: 49.38436
## epsg (SRID): 4326
## proj4string: +proj=longlat +datum=WGS84 +no_defs
## # A tibble: 5 x 5
## region water land pct_water geometry
## <chr> <dbl> <dbl> <dbl> <simple_feature>
## 1 Midwest<PHONE_NUMBER>33 1.943869e+12 9.485380 <MULTIPOLYGON...>
## 2 Northeast<PHONE_NUMBER>45 8.690661e+11 12.533273 <MULTIPOLYGON...>
## 3 Southeast<PHONE_NUMBER>98 1.364632e+12 7.612063 <MULTIPOLYGON...>
## 4 Southwest<PHONE_NUMBER>8 1.462632e+12 1.655761 <POLYGONZ((-9...>
## 5 West<PHONE_NUMBER>9 2.432336e+12 2.366780 <MULTIPOLYGON...>
Notice the geometry in the column. To remove the geometry column pipe to st_set_geometry(NULL)
. To arrange in descending order use arrange(desc(pct_water))
.
# table
regions %>%
st_set_geometry(NULL) %>%
arrange(desc(pct_water))
## # A tibble: 5 x 4
## region water land pct_water
## <chr> <dbl> <dbl> <dbl>
## 1 Northeast<PHONE_NUMBER>45 8.690661e+11 12.533273
## 2 Midwest<PHONE_NUMBER>33 1.943869e+12 9.485380
## 3 Southeast<PHONE_NUMBER>98 1.364632e+12 7.612063
## 4 West<PHONE_NUMBER>9 2.432336e+12 2.366780
## 5 Southwest<PHONE_NUMBER>8 1.462632e+12 1.655761
1.6 Regions: plot
Now plot the regions.
# plot, default
plot(regions['pct_water'])
1.7 Regions: ggplot
The ggplot2
library can visualise sf objects.
- In RStudio, see menu Help > Cheatsheets > Data Visualization with ggplot2.
# plot, ggplot
ggplot(regions) +
geom_sf(aes(fill = pct_water)) +
scale_fill_distiller(
"pct_water", palette = "Spectral", direction=1,
guide = guide_legend(title = "% water", reverse=T)) +
theme_bw() +
ggtitle("% Water by US Region")
1.8 Regions: recalculate area
So far you’ve used the ALAND
column for area of the state. But what if you were not provided the area and needed to calculate it? Because the states
are in geographic coordinates, you’ll need to either transform to an equal area projection and calculate area, or use geodesic calculations. Thankfully, the sf
library provides area calculations with the st_area()
and uses the geosphere::distGeo()
to perform geodesic calculations (ie trigonometric calculation accounting for the spheroid nature of the earth). Since the states
data has the unusual aspect of a z dimension, you’ll need to first remove that with the st_zm()
function.
library(geosphere)
library(units)
regions = states %>%
mutate(
water_m2 = AWATER %>% set_units(m^2),
land_m2 = geometry %>% st_zm() %>% st_area()) %>%
group_by(region) %>%
summarize(
water_m2 = sum(water_m2),
land_m2 = sum(land_m2)) %>%
mutate(
pct_water = water_m2 / land_m2)
# table
regions %>%
st_set_geometry(NULL) %>%
arrange(desc(pct_water))
## # A tibble: 5 x 4
## region water_m2 land_m2 pct_water
## <chr> <units> <units> <units>
## 1 Northeast<PHONE_NUMBER>45 m^2 9.117041e+11 m^2 0.11947126 1
## 2 Midwest<PHONE_NUMBER>33 m^2 1.987268e+12 m^2 0.09278233 1
## 3 Southeast<PHONE_NUMBER>98 m^2 1.427079e+12 m^2 0.07278971 1
## 4 West<PHONE_NUMBER>9 m^2 2.467170e+12 m^2 0.02333363 1
## 5 Southwest<PHONE_NUMBER>8 m^2 1.483765e+12 m^2 0.01632178 1
# plot, ggplot
ggplot(regions) +
geom_sf(aes(fill = as.numeric(pct_water))) +
scale_fill_distiller(
"pct_water", palette = "Spectral", direction=1,
guide = guide_legend(title = "% water", reverse=T)) +
theme_bw() +
ggtitle("% Water by US Region")
1.9 Challenge: project & recalculate area
Use st_transform()
with a USA Contiguous Albers Equal Area Conic Projection that minimizes distoration, and then calculate area using the st_area()
function.
1.9.1 Answers
library(geosphere)
library(units)
# Proj4 of http://spatialreference.org/ref/esri/usa-contiguous-albers-equal-area-conic/
crs_usa = '+proj=aea +lat_1=29.5 +lat_2=45.5 +lat_0=37.5 +lon_0=-96 +x_0=0 +y_0=0 +ellps=GRS80 +datum=NAD83 +units=m +no_defs'
regions = states %>%
st_transform(crs_usa) %>%
mutate(
water_m2 = AWATER %>% set_units(m^2),
land_m2 = geometry %>% st_zm() %>% st_area()) %>%
group_by(region) %>%
summarize(
water_m2 = sum(water_m2),
land_m2 = sum(land_m2)) %>%
mutate(
pct_water = water_m2 / land_m2)
# table
regions %>%
st_set_geometry(NULL) %>%
arrange(desc(pct_water))
## # A tibble: 5 x 4
## region water_m2 land_m2 pct_water
## <chr> <units> <units> <units>
## 1 Northeast<PHONE_NUMBER>45 m^2 9.117031e+11 m^2 0.11947138 1
## 2 Midwest<PHONE_NUMBER>33 m^2 1.987266e+12 m^2 0.09278246 1
## 3 Southeast<PHONE_NUMBER>98 m^2 1.427078e+12 m^2 0.07278973 1
## 4 West<PHONE_NUMBER>9 m^2 2.467167e+12 m^2 0.02333367 1
## 5 Southwest<PHONE_NUMBER>8 m^2 1.483758e+12 m^2 0.01632185 1
# plot, ggplot
ggplot(regions) +
geom_sf(aes(fill = as.numeric(pct_water))) +
scale_fill_distiller("pct_water", palette = "Spectral") +
theme_bw() +
ggtitle("% Water (geodesic) by US Region")
1.10 Key Points
- The
sf
package can take advantage of chaining spatial operations using the%>%
operator. - Data manipulation functions in
dplyr
such asgroup_by()
,summarize()
andmutate()
work onsf
objects. - Area can be calculated a variety of ways. Geodesic is preferred if starting with geographic coordinates (vs projected).


API
The suite currently consists of 13 IDL object classes and two helper programs. The main interface to the database is provided by the AmesPAHdbIDLSuite-object, which will parse the dowloaded XML-file utilizing IDL's AmesPAHXMLParser-object. The available PAH data is divided into four parts, each handled by its own object class and providing its own functionality.
- The Species-object, holds the PAH molecular properties,
- The Transitions-object, holds the fundamental vibrational transitions,
- The Laboratory_Spectrum-object holds the raw laboratory spectrum, and
- The Geometry-objects, holds the geometrical data.
The AmesPAHdbIDLSuite-object will return one of these object classes upon request. In addition, the AmesPAHdbIDLSuite_Transitions-object returns object classes upon convolving, co-adding and fitting spectra; an AmesPAHdbIDLSuite_Spectrum-, AmesPAHdbIDLSuite_Coadded_Spectrum- and AmesPAHdbIDLSuite_Fitted_Spectrum-object, respectively. The AmesPAHdbIDLSuite_Observation-object can handle some commonly used astronomical data formats. The AmesPAHdbIDLSuite_Browser-object is a graphical user interface to the database that can be used to browse its contents. Lastly, the IDL_Object-object is a class used to inherit from in IDL versions before 8.0, allowing operator overloaded classes to still compile on these earlier versions.
The application programming interface (API) and its use is described in turn.


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The evaluator is reminiscent of the symbolic differentiation program
discussed in section \ref{sec:symbolic-differentiation}. Both
programs operate on symbolic expressions. In both programs, the
result of operating on a compound expression is determined by
operating recursively on the pieces of the expression and combining
the results in a way that depends on the type of the expression. In
both programs we used
data abstraction to decouple the general rules
of operation from the details of how expressions are represented. In
the differentiation program this meant that the same differentiation
function
could deal with algebraic expressions in prefix form, in
infix form, or in some other form. For the evaluator, this means that
the syntax of the language being evaluated is determined solely by the
functions
that classify and extract pieces of expressions.
Here is the specification of the syntax of our language:
-
The self-evaluating items are numbers, strings and boolean values.
-
The function is_name tests
whether the given statement is a name
expression, and the function
name_of_name accesses
the JavaScript string that represents the name.
The function is_name
is defined in terms of the function
is_tagged_list,
which identifies lists beginning with a designated string that
we call tag:
-
Assignments have the form $\textit{name}$ = $\textit{value}$:
-
Declarations have the form
const $\textit{name}$ = $\textit{value}$;
or
let $\textit{name}$ = $\textit{value}$;
or
function $\textit{name}$($\textit{parameter}_{1}$, $\ldots$, $\textit{parameter}_{n}$) {
$\textit{body}$
}
Here, we treat the latter form (function
declarations) as syntactic sugar
for
const $\textit{name}$ = ($\textit{parameter}_{1}$, $\ldots$, $\textit{parameter}_{n}$) => { $\textit{body}$; };
The corresponding syntax functions are the following:
-
Function definitions are objects tagged with the
string function_definition:
-
return statements are objects
tagged with the string
"return_statement":
-
Conditional expressions are tagged with
"conditional_expression"
and have a predicate, a consequent, and an alternative.
-
A sequence is a list of statements.
-
A block contains its body statement.
-
A function application is an object tagged with
the string "application".
We provide access functions for the
operator, the
operands, and three
functions for iterating through the operand list:
\stepcounter{ExerciseDisplayNumber}
\begin{Exercise}
Rewrite
evaluate
so that the dispatch is done in data-directed
style. Compare this with the data-directed
differentiation
function
of
exercise \ref{ex:data-directed-differentiation}.
(You may use the head of a compound expression as the
type of the expression, as is appropriate for the syntax implemented
in this section.)
\end{Exercise}
\stepcounter{ExerciseDisplayNumber}
\begin{Exercise}
Recall the definitions of the special forms
&&
and
||
from chapter 1:
- $\textit{expression}_1$ && $\textit{expression}_2$: The expression $\textit{expression}_1$ is evaluated first. If it evaluates to
false, false
is returned; the expression $\textit{expression}_2$
is not evaluated. If it evaluates to true, the value
of $\textit{expression}_2$ is returned.
- $\textit{expression}_1$ || $\textit{expression}_2$: The expression $\textit{expression}_1$ is evaluated first. If it evaluates to true,
true is returned;
the expression $\textit{expression}_2$
is not evaluated. If it evaluates to
false, the value
of $\textit{expression}_2$ is returned.
Include
&& and ||
expressions
by defining appropriate syntax
functions
and evaluation functions
eval_and
and
eval_or
\end{Exercise}
4.1.2 Representing Statements and Expressions


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