String Manipulation

Some of the older elements of GMA (which used to be entirely written in the Tcl language, after it was ported from the even older C++ code) use Tcl list objects as their data representation. Notably the biggest example is the mapper(6) tool (which is still written in Tcl itself), whose map file format and TCP/IP communications protocl include mar‐ shalled data structures represented as Tcl lists. While this is obviously convenient for Tcl programs in that they can take such strings and natively use them as lists of values, it is also useful generally in that it is a simple string representation of a sim‐ ple data structure. The actual definition of this string format is included below. The tcllist Go package provides an easy interface to manipulate Tcl lists as Go types. As of yet, this only converts to and from slices of strings. We will extend this to manage mixed-types and nested lists if necessary, but that might not be needed for this application. We'll see. In a nutshell, a Tcl list (as a string representation) is a space- delimited list of values. Any value which includes spaces is enclosed in curly braces. An empty string (empty list) as an element in a list is represented as “{}”. (E.g., “1 {} 2” is a list of three elements, the middle of which is an empty string.) An entirely empty Tcl list is represented as an empty string “”. A list value must have balanced braces. A balanced pair of braces that happen to be inside a larger string value may be left as-is, since a string that happens to contain spaces or braces is only distinguished from a deeply-nested list value when you attempt to interpret it as one or another in the code. Thus, the list has three elements: “a”, “b”, and “this {is a} string”. Otherwise, a lone brace that's part of a string value should be escaped with a back‐ slash: Literal backslashes may be escaped with a backslash as well. While extra spaces are ignored when parsing lists into elements, a properly formed string representation of a list will have the miminum number of spaces and braces needed to describe the list structure.

Package linq provides methods for querying and manipulating slices, arrays, maps, strings, channels and collections. Authors: Alexander Kalankhodzhaev (kalan), Ahmet Alp Balkan, Cleiton Marques Souza.

Package morestrings implements additional functions to manipulate UTF-8 encoded strings, beyond what is provided in the standard "strings" package.

Package database provides a block and metadata storage database. This package provides a database layer to store and retrieve block data and arbitrary metadata in a simple and efficient manner. The default backend, ffldb, has a strong focus on speed, efficiency, and robustness. It makes use leveldb for the metadata, flat files for block storage, and strict checksums in key areas to ensure data integrity. A quick overview of the features database provides are as follows: The main entry point is the DB interface. It exposes functionality for transactional-based access and storage of metadata and block data. It is obtained via the Create and Open functions which take a database type string that identifies the specific database driver (backend) to use as well as arguments specific to the specified driver. The Namespace interface is an abstraction that provides facilities for obtaining transactions (the Tx interface) that are the basis of all database reads and writes. Unlike some database interfaces that support reading and writing without transactions, this interface requires transactions even when only reading or writing a single key. The Begin function provides an unmanaged transaction while the View and Update functions provide a managed transaction. These are described in more detail below. The Tx interface provides facilities for rolling back or committing changes that took place while the transaction was active. It also provides the root metadata bucket under which all keys, values, and nested buckets are stored. A transaction can either be read-only or read-write and managed or unmanaged. A managed transaction is one where the caller provides a function to execute within the context of the transaction and the commit or rollback is handled automatically depending on whether or not the provided function returns an error. Attempting to manually call Rollback or Commit on the managed transaction will result in a panic. An unmanaged transaction, on the other hand, requires the caller to manually call Commit or Rollback when they are finished with it. Leaving transactions open for long periods of time can have several adverse effects, so it is recommended that managed transactions are used instead. The Bucket interface provides the ability to manipulate key/value pairs and nested buckets as well as iterate through them. The Get, Put, and Delete functions work with key/value pairs, while the Bucket, CreateBucket, CreateBucketIfNotExists, and DeleteBucket functions work with buckets. The ForEach function allows the caller to provide a function to be called with each key/value pair and nested bucket in the current bucket. As discussed above, all of the functions which are used to manipulate key/value pairs and nested buckets exist on the Bucket interface. The root metadata bucket is the upper-most bucket in which data is stored and is created at the same time as the database. Use the Metadata function on the Tx interface to retrieve it. The CreateBucket and CreateBucketIfNotExists functions on the Bucket interface provide the ability to create an arbitrary number of nested buckets. It is a good idea to avoid a lot of buckets with little data in them as it could lead to poor page utilization depending on the specific driver in use. This example demonstrates creating a new database and using a managed read-write transaction to store and retrieve metadata. This example demonstrates creating a new database, using a managed read-write transaction to store a block, and using a managed read-only transaction to fetch the block.

objx - Go package for dealing with maps, slices, JSON and other data. Objx provides the `objx.Map` type, which is a `map[string]interface{}` that exposes a powerful `Get` method (among others) that allows you to easily and quickly get access to data within the map, without having to worry too much about type assertions, missing data, default values etc. Objx uses a preditable pattern to make access data from within `map[string]interface{}'s easy. Call one of the `objx.` functions to create your `objx.Map` to get going: NOTE: Any methods or functions with the `Must` prefix will panic if something goes wrong, the rest will be optimistic and try to figure things out without panicking. Use `Get` to access the value you're interested in. You can use dot and array notation too: Once you have saught the `Value` you're interested in, you can use the `Is*` methods to determine its type. Or you can just assume the type, and use one of the strong type methods to extract the real value: If there's no value there (or if it's the wrong type) then a default value will be returned, or you can be explicit about the default value. If you're dealing with a slice of data as a value, Objx provides many useful methods for iterating, manipulating and selecting that data. You can find out more by exploring the index below. A simple example of how to use Objx: Since `objx.Map` is a `map[string]interface{}` you can treat it as such. For example, to `range` the data, do what you would expect:

Package btcutil provides bitcoin-specific convenience functions and types. A Block defines a bitcoin block that provides easier and more efficient manipulation of raw wire protocol blocks. It also memoizes hashes for the block and its transactions on their first access so subsequent accesses don't have to repeat the relatively expensive hashing operations. A Tx defines a bitcoin transaction that provides more efficient manipulation of raw wire protocol transactions. It memoizes the hash for the transaction on its first access so subsequent accesses don't have to repeat the relatively expensive hashing operations. To decode a base58 string: Similarly, to encode the same data:

Radix package provide radix algorithm. https://en.wikipedia.org/wiki/Radix_tree • This implementation allow indexing key with a bit precision. The wikipedia reference show a radix tree with a byte precision. It seems natural with string. This radix tree is designed to manipulate networks. • Each tree could accept ~2x10^12 nodes. • Keys are 16bit encoded, so could have 64k bytes of length. • Like most tree algothm, keys are stored sorted, accessing the little or greater value is very fast. • Lookup algortithm complexity is O(log(n)), tree depth is log(n). • The package provide facility to use string, uint64 and network as key. It is written to be fast and save memory. Below basic benchmark using CPU "Intel(R) Core(TM) i7-1068NG7 CPU @ 2.30GHz". Using IPv4 networks as key. The benchmark code is provided in radix_test.go file with a reference dataset. • Index 2 649 172 entries in 1.22s, so 2.17M insert/s • Lookup 1 000 000 random data in 0.78s with 146 190 hit, 853 810 miss, so 1.28M lookup/s • Browse 2 649 172 entries in 0.47s, so 5.64M read/s • Delete 2 649 172 sequential data in 0.74s, so 3.58M delete/s Nothing about memory consumation in this test beacause it hard to measure relevant data, because the garbage collector. The tree use two kind of nodes. Internal node `type node struct` were are not exported and leaf node `type Node struct`. These name are ambiguous, this is due to a necessary compatibility with existing programs. Node are just an interface{} associated with a `node struct`. Because this king of tree could contains millions of entries, it is important to use the mimnimum of memory. Member structs are obviously sorted in order to respect alignment packing data without hole. In other way, I used three means to compact memory: 1. Saving memory : use string in place of []byte The most simpler is storing []byte with string type. The string uses 16 byte, the []byte uses 24 bytes. 2. Saving memory : use 32bit reference in place of 64bit pointers More tricky, how use 32bit reference in place of 64bit pointers for chaining nodes. I use memory pool and 64k array of 64k array of nodes. The following explanation is not complete, but the code comment contains more information. There just an introduction. Usage of memory pool implies while the radix tree is in use, allocated node are not garbage colected. memory_pool growth by block of 64k nodes. Each time there are no free node, memory pool has one more slot of 64k node. memory_backref is dichotomic sorted list of pointer start and stop which reference the memory_pool index which contains pointer. ptr_start = &[0]node, ptr_stop = &[65535]node. memory_free is the list of avalaible nodes. node pointer from reference = &memory_pool[x][y], where x and y and 16bit values node reference from pointer: • x = dichotomic search of memory_pool_index in memory_backref array using &node pointer reference • y = (&node - ptr_start) / node_size In reality, there are two distinct pool per tree using this concept. The pool of node and the pool of leaf. the memory_backref contains also a boolean value to distinct these two kind of pool. In reality x is not used until 64k but limited to 32k and the msb is used to differenciate the two pools. 3. Saving memory : split node types according with their kind to avoid interface{} pointer Some node are used for internal chainaing, other nodes are used to display data. data is stored in an interface which uses 16bytes. It is garbage to let these 16bytes for each nodes. there the approximatively the same numbers of internal nodes than exposed nodes, so for 1M data indexed, 1M of internal nodes. I use a property which is &Node adress = &Node.node adress. I manipulate only node to chain each data. If I need to insert a leaf, I use Node.node. When I browse the tree I need to kwnown if I encounter leaf or node. I just chack the msb of the reference.

Package linq provides methods for querying and manipulating slices, arrays, maps, strings, channels and collections. Authors: Alexander Kalankhodzhaev (kalan), Ahmet Alp Balkan, Cleiton Marques Souza.

Package dom provides GopherJS bindings for the JavaScript DOM APIs. This package is an in progress effort of providing idiomatic Go bindings for the DOM, wrapping the JavaScript DOM APIs. The API is neither complete nor frozen yet, but a great amount of the DOM is already useable. While the package tries to be idiomatic Go, it also tries to stick closely to the JavaScript APIs, so that one does not need to learn a new set of APIs if one is already familiar with it. One decision that hasn't been made yet is what parts exactly should be part of this package. It is, for example, possible that the canvas APIs will live in a separate package. On the other hand, types such as StorageEvent (the event that gets fired when the HTML5 storage area changes) will be part of this package, simply due to how the DOM is structured – even if the actual storage APIs might live in a separate package. This might require special care to avoid circular dependencies. The documentation for some of the identifiers is based on the MDN Web Docs by Mozilla Contributors (https://developer.mozilla.org/en-US/docs/Web/API), licensed under CC-BY-SA 2.5 (https://creativecommons.org/licenses/by-sa/2.5/). The usual entry point of using the dom package is by using the GetWindow() function which will return a Window, from which you can get things such as the current Document. The DOM has a big amount of different element and event types, but they all follow three interfaces. All functions that work on or return generic elements/events will return one of the three interfaces Element, HTMLElement or Event. In these interface values there will be concrete implementations, such as HTMLParagraphElement or FocusEvent. It's also not unusual that values of type Element also implement HTMLElement. In all cases, type assertions can be used. Example: Several functions in the JavaScript DOM return "live" collections of elements, that is collections that will be automatically updated when elements get removed or added to the DOM. Our bindings, however, return static slices of elements that, once created, will not automatically reflect updates to the DOM. This is primarily done so that slices can actually be used, as opposed to a form of iterator, but also because we think that magically changing data isn't Go's nature and that snapshots of state are a lot easier to reason about. This does not, however, mean that all objects are snapshots. Elements, events and generally objects that aren't slices or maps are simple wrappers around JavaScript objects, and as such attributes as well as method calls will always return the most current data. To reflect this behaviour, these bindings use pointers to make the semantics clear. Consider the following example: The above example will print `true`. Some objects in the JS API have two versions of attributes, one that returns a string and one that returns a DOMTokenList to ease manipulation of string-delimited lists. Some other objects only provide DOMTokenList, sometimes DOMSettableTokenList. To simplify these bindings, only the DOMTokenList variant will be made available, by the type TokenList. In cases where the string attribute was the only way to completely replace the value, our TokenList will provide Set([]string) and SetString(string) methods, which will be able to accomplish the same. Additionally, our TokenList will provide methods to convert it to strings and slices. This package has a relatively stable API. However, there will be backwards incompatible changes from time to time. This is because the package isn't complete yet, as well as because the DOM is a moving target, and APIs do change sometimes. While an attempt is made to reduce changing function signatures to a minimum, it can't always be guaranteed. Sometimes mistakes in the bindings are found that require changing arguments or return values. Interfaces defined in this package may also change on a semi-regular basis, as new methods are added to them. This happens because the bindings aren't complete and can never really be, as new features are added to the DOM.

Package linq provides methods for querying and manipulating slices, arrays, maps, strings, channels and collections. Authors: Alexander Kalankhodzhaev (kalan), Ahmet Alp Balkan, Cleiton Marques Souza.

Package Filenamer provides a set of methods for filename manipulation. It's a very simple API for adding custom prefixes and suffixes to your base filename such as timestamps, random strings etc. Very useful when working with file uploads and you need to genereate unique filenames for your uploads. Basic usage example This example shows basic usage when given file name is just cleaned up from characters that should not be used in general This example shows how to add prefix to a file name This example shows how to hash file name This example shows how to hash file name and add suffix to it

Package database provides a block and metadata storage database. This package provides a database layer to store and retrieve block data and arbitrary metadata in a simple and efficient manner. The default backend, ffldb, has a strong focus on speed, efficiency, and robustness. It makes use leveldb for the metadata, flat files for block storage, and strict checksums in key areas to ensure data integrity. A quick overview of the features database provides are as follows: The main entry point is the DB interface. It exposes functionality for transactional-based access and storage of metadata and block data. It is obtained via the Create and Open functions which take a database type string that identifies the specific database driver (backend) to use as well as arguments specific to the specified driver. The Namespace interface is an abstraction that provides facilities for obtaining transactions (the Tx interface) that are the basis of all database reads and writes. Unlike some database interfaces that support reading and writing without transactions, this interface requires transactions even when only reading or writing a single key. The Begin function provides an unmanaged transaction while the View and Update functions provide a managed transaction. These are described in more detail below. The Tx interface provides facilities for rolling back or committing changes that took place while the transaction was active. It also provides the root metadata bucket under which all keys, values, and nested buckets are stored. A transaction can either be read-only or read-write and managed or unmanaged. A managed transaction is one where the caller provides a function to execute within the context of the transaction and the commit or rollback is handled automatically depending on whether or not the provided function returns an error. Attempting to manually call Rollback or Commit on the managed transaction will result in a panic. An unmanaged transaction, on the other hand, requires the caller to manually call Commit or Rollback when they are finished with it. Leaving transactions open for long periods of time can have several adverse effects, so it is recommended that managed transactions are used instead. The Bucket interface provides the ability to manipulate key/value pairs and nested buckets as well as iterate through them. The Get, Put, and Delete functions work with key/value pairs, while the Bucket, CreateBucket, CreateBucketIfNotExists, and DeleteBucket functions work with buckets. The ForEach function allows the caller to provide a function to be called with each key/value pair and nested bucket in the current bucket. As discussed above, all of the functions which are used to manipulate key/value pairs and nested buckets exist on the Bucket interface. The root metadata bucket is the upper-most bucket in which data is stored and is created at the same time as the database. Use the Metadata function on the Tx interface to retrieve it. The CreateBucket and CreateBucketIfNotExists functions on the Bucket interface provide the ability to create an arbitrary number of nested buckets. It is a good idea to avoid a lot of buckets with little data in them as it could lead to poor page utilization depending on the specific driver in use. This example demonstrates creating a new database and using a managed read-write transaction to store and retrieve metadata. This example demonstrates creating a new database, using a managed read-write transaction to store a block, and using a managed read-only transaction to fetch the block.

Package dom provides GopherJS bindings for the JavaScript DOM APIs. This package is an in progress effort of providing idiomatic Go bindings for the DOM, wrapping the JavaScript DOM APIs. The API is neither complete nor frozen yet, but a great amount of the DOM is already useable. While the package tries to be idiomatic Go, it also tries to stick closely to the JavaScript APIs, so that one does not need to learn a new set of APIs if one is already familiar with it. One decision that hasn't been made yet is what parts exactly should be part of this package. It is, for example, possible that the canvas APIs will live in a separate package. On the other hand, types such as StorageEvent (the event that gets fired when the HTML5 storage area changes) will be part of this package, simply due to how the DOM is structured – even if the actual storage APIs might live in a separate package. This might require special care to avoid circular dependencies. The documentation for some of the identifiers is based on the MDN Web Docs by Mozilla Contributors (https://developer.mozilla.org/en-US/docs/Web/API), licensed under CC-BY-SA 2.5 (https://creativecommons.org/licenses/by-sa/2.5/). The usual entry point of using the dom package is by using the GetWindow() function which will return a Window, from which you can get things such as the current Document. The DOM has a big amount of different element and event types, but they all follow three interfaces. All functions that work on or return generic elements/events will return one of the three interfaces Element, HTMLElement or Event. In these interface values there will be concrete implementations, such as HTMLParagraphElement or FocusEvent. It's also not unusual that values of type Element also implement HTMLElement. In all cases, type assertions can be used. Example: Several functions in the JavaScript DOM return "live" collections of elements, that is collections that will be automatically updated when elements get removed or added to the DOM. Our bindings, however, return static slices of elements that, once created, will not automatically reflect updates to the DOM. This is primarily done so that slices can actually be used, as opposed to a form of iterator, but also because we think that magically changing data isn't Go's nature and that snapshots of state are a lot easier to reason about. This does not, however, mean that all objects are snapshots. Elements, events and generally objects that aren't slices or maps are simple wrappers around JavaScript objects, and as such attributes as well as method calls will always return the most current data. To reflect this behaviour, these bindings use pointers to make the semantics clear. Consider the following example: The above example will print `true`. Some objects in the JS API have two versions of attributes, one that returns a string and one that returns a DOMTokenList to ease manipulation of string-delimited lists. Some other objects only provide DOMTokenList, sometimes DOMSettableTokenList. To simplify these bindings, only the DOMTokenList variant will be made available, by the type TokenList. In cases where the string attribute was the only way to completely replace the value, our TokenList will provide Set([]string) and SetString(string) methods, which will be able to accomplish the same. Additionally, our TokenList will provide methods to convert it to strings and slices. This package has a relatively stable API. However, there will be backwards incompatible changes from time to time. This is because the package isn't complete yet, as well as because the DOM is a moving target, and APIs do change sometimes. While an attempt is made to reduce changing function signatures to a minimum, it can't always be guaranteed. Sometimes mistakes in the bindings are found that require changing arguments or return values. Interfaces defined in this package may also change on a semi-regular basis, as new methods are added to them. This happens because the bindings aren't complete and can never really be, as new features are added to the DOM. If you depend on none of the APIs changing unexpectedly, you're advised to vendor this package.

Package xlsxtra provides extra utilities for the xlsx package (https://github.com/tealeg/xlsx) to manipulate excel files: - Sort(), SortByHeaders: multi-column (reverse) sort of selected rows. (Note that columns are one based, not zero based to make reverse sort possible.) - AddBool(), AddInt(), AddFloat(), ...: shortcut to add a cell to a row with the right type. - NewStyle(): create a style and set the ApplyFill, ApplyFont, ApplyBorder and ApplyAlignment automatically. - NewStyles(): create a slice of styles based on a color palette - Sheets: access sheets by name instead of by index - Col: access cell values of a row by column header title - SetRowStyle: set style of all cells in a row - ToString: convert a xlsx.Row to a slice of strings See Col(umn) and Sort example for a quick introduction.

Package morestrings implements additional functions to manipulate UTF-8 encoded strings, beyond what is provided in the standard "strings" package.

Objx - Go package for dealing with maps, slices, JSON and other data. Objx provides the `objx.Map` type, which is a `map[string]interface{}` that exposes a powerful `Get` method (among others) that allows you to easily and quickly get access to data within the map, without having to worry too much about type assertions, missing data, default values etc. Objx uses a preditable pattern to make access data from within `map[string]interface{}` easy. Call one of the `objx.` functions to create your `objx.Map` to get going: NOTE: Any methods or functions with the `Must` prefix will panic if something goes wrong, the rest will be optimistic and try to figure things out without panicking. Use `Get` to access the value you're interested in. You can use dot and array notation too: Once you have sought the `Value` you're interested in, you can use the `Is*` methods to determine its type. Or you can just assume the type, and use one of the strong type methods to extract the real value: If there's no value there (or if it's the wrong type) then a default value will be returned, or you can be explicit about the default value. If you're dealing with a slice of data as a value, Objx provides many useful methods for iterating, manipulating and selecting that data. You can find out more by exploring the index below. A simple example of how to use Objx: Since `objx.Map` is a `map[string]interface{}` you can treat it as such. For example, to `range` the data, do what you would expect:

Package seshcookie enables you to associate session-state with HTTP requests while keeping your server stateless. Because session-state is transferred as part of the HTTP request (in a cookie), state can be seamlessly maintained between server restarts or load balancing. It's inspired by Beaker (http://pypi.python.org/pypi/Beaker), which provides a similar service for Python webapps. The cookies are authenticated and encrypted (using AES-GCM) with a key derived from a string provided to the NewHandler function. This makes seshcookie reliable and secure: session contents are opaque to users and not able to be manipulated or forged by third parties. Storing session-state in a cookie makes building some apps trivial, like this example that tells a user how many times they have visited the site:

Package stringutil contains small utility functions for string manipulation and parsing.

Package cfw contains ports of a few selected CFWheels helpers that are used for string manipulation and have no Go equivalent. © Ben Garrett https://github.com/bengarrett/cfw

Package dom provides GopherJS bindings for the JavaScript DOM APIs. This package is an in progress effort of providing idiomatic Go bindings for the DOM, wrapping the JavaScript DOM APIs. The API is neither complete nor frozen yet, but a great amount of the DOM is already useable. While the package tries to be idiomatic Go, it also tries to stick closely to the JavaScript APIs, so that one does not need to learn a new set of APIs if one is already familiar with it. One decision that hasn't been made yet is what parts exactly should be part of this package. It is, for example, possible that the canvas APIs will live in a separate package. On the other hand, types such as StorageEvent (the event that gets fired when the HTML5 storage area changes) will be part of this package, simply due to how the DOM is structured – even if the actual storage APIs might live in a separate package. This might require special care to avoid circular dependencies. The documentation for some of the identifiers is based on the MDN Web Docs by Mozilla Contributors (https://developer.mozilla.org/en-US/docs/Web/API), licensed under CC-BY-SA 2.5 (https://creativecommons.org/licenses/by-sa/2.5/). The usual entry point of using the dom package is by using the GetWindow() function which will return a Window, from which you can get things such as the current Document. The DOM has a big amount of different element and event types, but they all follow three interfaces. All functions that work on or return generic elements/events will return one of the three interfaces Element, HTMLElement or Event. In these interface values there will be concrete implementations, such as HTMLParagraphElement or FocusEvent. It's also not unusual that values of type Element also implement HTMLElement. In all cases, type assertions can be used. Example: Several functions in the JavaScript DOM return "live" collections of elements, that is collections that will be automatically updated when elements get removed or added to the DOM. Our bindings, however, return static slices of elements that, once created, will not automatically reflect updates to the DOM. This is primarily done so that slices can actually be used, as opposed to a form of iterator, but also because we think that magically changing data isn't Go's nature and that snapshots of state are a lot easier to reason about. This does not, however, mean that all objects are snapshots. Elements, events and generally objects that aren't slices or maps are simple wrappers around JavaScript objects, and as such attributes as well as method calls will always return the most current data. To reflect this behaviour, these bindings use pointers to make the semantics clear. Consider the following example: The above example will print `true`. Some objects in the JS API have two versions of attributes, one that returns a string and one that returns a DOMTokenList to ease manipulation of string-delimited lists. Some other objects only provide DOMTokenList, sometimes DOMSettableTokenList. To simplify these bindings, only the DOMTokenList variant will be made available, by the type TokenList. In cases where the string attribute was the only way to completely replace the value, our TokenList will provide Set([]string) and SetString(string) methods, which will be able to accomplish the same. Additionally, our TokenList will provide methods to convert it to strings and slices. This package has a relatively stable API. However, there will be backwards incompatible changes from time to time. This is because the package isn't complete yet, as well as because the DOM is a moving target, and APIs do change sometimes. While an attempt is made to reduce changing function signatures to a minimum, it can't always be guaranteed. Sometimes mistakes in the bindings are found that require changing arguments or return values. Interfaces defined in this package may also change on a semi-regular basis, as new methods are added to them. This happens because the bindings aren't complete and can never really be, as new features are added to the DOM. If you depend on none of the APIs changing unexpectedly, you're advised to vendor this package.

for any misc discord functions random functions that are useful For all functions that manipulate strings

Package linq provides methods for querying and manipulating slices, arrays, maps, strings, channels and collections. Authors: Alexander Kalankhodzhaev (kalan), Ahmet Alp Balkan, Cleiton Marques Souza.

Package strutil gets your string manipulation covered! Features include escaping reserved words, wildcard compare, and pattern extraction.

Package luar provides a convenient interface between Lua and Go. It uses Alessandro Arzilli's golua (https://github.com/nwidger/golua). Most Go values can be passed to Lua: basic types, strings, complex numbers, user-defined types, pointers, composite types, functions, channels, etc. Conversely, most Lua values can be converted to Go values. Composite types are processed recursively. Methods can be called on user-defined types. These methods will be callable using _dot-notation_ rather than colon notation. Arrays, slices, maps and structs can be copied as tables, or alternatively passed over as Lua proxy objects which can be naturally indexed. In the case of structs and string maps, fields have priority over methods. Use 'luar.method(<value>, <method>)(<params>...)' to call shadowed methods. Unexported struct fields are ignored. The "lua" tag is used to match fields in struct conversion. You may pass a Lua table to an imported Go function; if the table is 'array-like' then it is converted to a Go slice; if it is 'map-like' then it is converted to a Go map. Pointer values encode as the value pointed to when unproxified. Usual operators (arithmetic, string concatenation, pairs/ipairs, etc.) work on proxies too. The type of the result depends on the type of the operands. The rules are as follows: - If the operands are of the same type, use this type. - If one type is a Lua number, use the other, user-defined type. - If the types are different and not Lua numbers, convert to a complex proxy, a Lua number, or a Lua string according to the result kind. Channel proxies can be manipulated with the following methods: - close(): Close the channel. - recv() value: Fetch and return a value from the channel. - send(x value): Send a value in the channel. Complex proxies can be manipulated with the following attributes: - real: The real part. - imag: The imaginary part. Slice proxies can be manipulated with the following methods/attributes: - append(x ...value) sliceProxy: Append the elements and return the new slice. The elements must be convertible to the slice element type. - cap: The capacity of the slice. - slice(i, j integer) sliceProxy: Return the sub-slice that ranges from 'i' to 'j' excluded, starting from 1. String proxies can be browsed rune by rune with the pairs/ipairs functions. These runes are encoded as strings in Lua. Indexing a string proxy (starting from 1) will return the corresponding byte as a Lua string. String proxies can be manipulated with the following method: - slice(i, j integer) sliceProxy: Return the sub-string that ranges from 'i' to 'j' excluded, starting from 1. Pointers to structs and structs within pointers are automatically dereferenced. Slices must be looped over with 'ipairs'.

Package luar provides a convenient interface between Lua and Go. It uses Alessandro Arzilli's golua (https://github.com/aarzilli/golua). Most Go values can be passed to Lua: basic types, strings, complex numbers, user-defined types, pointers, composite types, functions, channels, etc. Conversely, most Lua values can be converted to Go values. Composite types are processed recursively. Methods can be called on user-defined types. These methods will be callable using _dot-notation_ rather than colon notation. Arrays, slices, maps and structs can be copied as tables, or alternatively passed over as Lua proxy objects which can be naturally indexed. In the case of structs and string maps, fields have priority over methods. Use 'luar.method(<value>, <method>)(<params>...)' to call shadowed methods. Unexported struct fields are ignored. The "lua" tag is used to match fields in struct conversion. You may pass a Lua table to an imported Go function; if the table is 'array-like' then it is converted to a Go slice; if it is 'map-like' then it is converted to a Go map. Pointer values encode as the value pointed to when unproxified. Usual operators (arithmetic, string concatenation, pairs/ipairs, etc.) work on proxies too. The type of the result depends on the type of the operands. The rules are as follows: - If the operands are of the same type, use this type. - If one type is a Lua number, use the other, user-defined type. - If the types are different and not Lua numbers, convert to a complex proxy, a Lua number, or a Lua string according to the result kind. Channel proxies can be manipulated with the following methods: - close(): Close the channel. - recv() value: Fetch and return a value from the channel. - send(x value): Send a value in the channel. Complex proxies can be manipulated with the following attributes: - real: The real part. - imag: The imaginary part. Slice proxies can be manipulated with the following methods/attributes: - append(x ...value) sliceProxy: Append the elements and return the new slice. The elements must be convertible to the slice element type. - cap: The capacity of the slice. - slice(i, j integer) sliceProxy: Return the sub-slice that ranges from 'i' to 'j' excluded, starting from 1. String proxies can be browsed rune by rune with the pairs/ipairs functions. These runes are encoded as strings in Lua. Indexing a string proxy (starting from 1) will return the corresponding byte as a Lua string. String proxies can be manipulated with the following method: - slice(i, j integer) sliceProxy: Return the sub-string that ranges from 'i' to 'j' excluded, starting from 1. Pointers to structs and structs within pointers are automatically dereferenced. Slices must be looped over with 'ipairs'.

Objx - Go package for dealing with maps, slices, JSON and other data. Objx provides the `objx.Map` type, which is a `map[string]interface{}` that exposes a powerful `Get` method (among others) that allows you to easily and quickly get access to data within the map, without having to worry too much about type assertions, missing data, default values etc. Objx uses a predictable pattern to make access data from within `map[string]interface{}` easy. Call one of the `objx.` functions to create your `objx.Map` to get going: NOTE: Any methods or functions with the `Must` prefix will panic if something goes wrong, the rest will be optimistic and try to figure things out without panicking. Use `Get` to access the value you're interested in. You can use dot and array notation too: Once you have sought the `Value` you're interested in, you can use the `Is*` methods to determine its type. Or you can just assume the type, and use one of the strong type methods to extract the real value: If there's no value there (or if it's the wrong type) then a default value will be returned, or you can be explicit about the default value. If you're dealing with a slice of data as a value, Objx provides many useful methods for iterating, manipulating and selecting that data. You can find out more by exploring the index below. A simple example of how to use Objx: Since `objx.Map` is a `map[string]interface{}` you can treat it as such. For example, to `range` the data, do what you would expect:

Package strmangle is a collection of string manipulation functions. Primarily used by boil and templates for code generation. Because it is focused on pipelining inside templates you will see some odd parameter ordering.

Package dom provides GopherJS and Go bindings for the JavaScript DOM APIs. This package is an in progress effort of providing idiomatic Go bindings for the DOM, wrapping the JavaScript DOM APIs. The API is neither complete nor frozen yet, but a great amount of the DOM is already useable. While the package tries to be idiomatic Go, it also tries to stick closely to the JavaScript APIs, so that one does not need to learn a new set of APIs if one is already familiar with it. One decision that hasn't been made yet is what parts exactly should be part of this package. It is, for example, possible that the canvas APIs will live in a separate package. On the other hand, types such as StorageEvent (the event that gets fired when the HTML5 storage area changes) will be part of this package, simply due to how the DOM is structured – even if the actual storage APIs might live in a separate package. This might require special care to avoid circular dependencies. The documentation for some of the identifiers is based on the MDN Web Docs by Mozilla Contributors (https://developer.mozilla.org/en-US/docs/Web/API), licensed under CC-BY-SA 2.5 (https://creativecommons.org/licenses/by-sa/2.5/). The usual entry point of using the dom package is by using the GetWindow() function which will return a Window, from which you can get things such as the current Document. The DOM has a big amount of different element and event types, but they all follow three interfaces. All functions that work on or return generic elements/events will return one of the three interfaces Element, HTMLElement or Event. In these interface values there will be concrete implementations, such as HTMLParagraphElement or FocusEvent. It's also not unusual that values of type Element also implement HTMLElement. In all cases, type assertions can be used. Example: Several functions in the JavaScript DOM return "live" collections of elements, that is collections that will be automatically updated when elements get removed or added to the DOM. Our bindings, however, return static slices of elements that, once created, will not automatically reflect updates to the DOM. This is primarily done so that slices can actually be used, as opposed to a form of iterator, but also because we think that magically changing data isn't Go's nature and that snapshots of state are a lot easier to reason about. This does not, however, mean that all objects are snapshots. Elements, events and generally objects that aren't slices or maps are simple wrappers around JavaScript objects, and as such attributes as well as method calls will always return the most current data. To reflect this behaviour, these bindings use pointers to make the semantics clear. Consider the following example: The above example will print `true`. Some objects in the JS API have two versions of attributes, one that returns a string and one that returns a DOMTokenList to ease manipulation of string-delimited lists. Some other objects only provide DOMTokenList, sometimes DOMSettableTokenList. To simplify these bindings, only the DOMTokenList variant will be made available, by the type TokenList. In cases where the string attribute was the only way to completely replace the value, our TokenList will provide Set([]string) and SetString(string) methods, which will be able to accomplish the same. Additionally, our TokenList will provide methods to convert it to strings and slices. This package has a relatively stable API. However, there will be backwards incompatible changes from time to time. This is because the package isn't complete yet, as well as because the DOM is a moving target, and APIs do change sometimes. While an attempt is made to reduce changing function signatures to a minimum, it can't always be guaranteed. Sometimes mistakes in the bindings are found that require changing arguments or return values. Interfaces defined in this package may also change on a semi-regular basis, as new methods are added to them. This happens because the bindings aren't complete and can never really be, as new features are added to the DOM. If you depend on none of the APIs changing unexpectedly, you're advised to vendor this package.

Package nlp provides implementations of selected machine learning algorithms for natural language processing of text corpora. The primary focus is the statistical semantics of plain-text documents supporting semantic analysis and retrieval of semantically similar documents. The package makes use of the Gonum (http://http//www.gonum.org/) library for linear algebra and scientific computing with some inspiration taken from Python's scikit-learn (http://scikit-learn.org/stable/) and Gensim(https://radimrehurek.com/gensim/) The primary intended use case is to support document input as text strings encoded as a matrix of numerical feature vectors called a `term document matrix`. Each column in the matrix corresponds to a document in the corpus and each row corresponds to a unique term occurring in the corpus. The individual elements within the matrix contain the frequency with which each term occurs within each document (referred to as `term frequency`). Whilst textual data from document corpora are the primary intended use case, the algorithms can be used with other types of data from other sources once encoded (vectorised) into a suitable matrix e.g. image data, sound data, users/products, etc. These matrices can be processed and manipulated through the application of additional transformations for weighting features, identifying relationships or optimising the data for analysis, information retrieval and/or predictions. Typically the algorithms in this package implement one of three primary interfaces: One of the implementations of Vectoriser is Pipeline which can be used to wire together pipelines composed of a Vectoriser and one or more Transformers arranged in serial so that the output from each stage forms the input of the next. This can be used to construct a classic LSI (Latent Semantic Indexing) pipeline (vectoriser -> TF.IDF weighting -> Truncated SVD): Whilst they take different inputs, both Vectorisers and Transformers have 3 primary methods:

package skiprope provides rope-like data structure for efficient manipulation of large strings.

Package jin Copyright (c) 2020 eco. License that can be found in the LICENSE file. "your wish is my command" Jin is a comprehensive JSON manipulation tool bundle. All functions tested with random data with help of Node.js. All test-path and test-value creation automated with Node.js. Jin provides parse, interpret, build and format tools for JSON. Third-party packages only used for the benchmark. No dependency need for core functions. We make some benchmark with other packages like Jin. In Result, Jin is the fastest (op/ns) and more memory friendly then others (B/op). For more information please take a look at BENCHMARK section below. WHAT IS NEW? 7 new functions tested and added to package. - GetMap() get objects as map[string]string structure with key values pairs - GetAll() get only specific keys values - GetAllMap() get only specific keys with map[string]stringstructure - GetKeys() get objects keys as string array - GetValues() get objects values as string array - GetKeysValues() get objects keys and values with separate string arrays - Length() get length of JSON array. 06.04.2020 INSTALLATION And you are good to go. Import and start using. Major difference between parsing and interpreting is parser has to read all data before answer your needs. On the other hand interpreter reads up to find the data you need. With parser, once the parse is complete you can access any data with no time. But there is a time cost to parse all data and this cost can increase as data content grows. If you need to access all keys of a JSON then, we are simply recommend you to use Parser. But if you need to access some keys of a JSON then we strongly recommend you to use Interpreter, it will be much faster and much more memory-friendly than parser. Interpreter is core element of this package, no need to create an Interpreter type, just call which function you want. First let's look at general function parameters. We are gonna use Get() function to access the value of path has pointed. In this case 'jin'. Path value can consist hard coded values. Get() function return type is []byte but all other variations of return types are implemented with different functions. For example. If you need "value" as string use GetString(). Parser is another alternative for JSON manipulation. We recommend to use this structure when you need to access all or most of the keys in the JSON. Parser constructor need only one parameter. We can parse it with Parse() function. Let's look at Parser.Get() About path value look above. There is all return type variations of Parser.Get() function like Interpreter. For return string use Parser.GetString() like this, Other usefull functions of Jin. -Add(), AddKeyValue(), Set(), SetKey() Delete(), Insert(), IterateArray(), IterateKeyValue() Tree(). Let's look at IterateArray() function. There are two formatting functions. Flatten() and Indent(). Indent() is adds indentation to JSON for nicer visualization and Flatten() removes this indentation. Control functions are simple and easy way to check value types of any path. For example. IsArray(). Or you can use GetType(). There are lots of JSON build functions in this package and all of them has its own examples. We just want to mention a couple of them. Scheme is simple and powerful tool for create JSON schemes. Testing is very important thing for this type of packages and it shows how reliable it is. For that reasons we use Node.js for unit testing. Lets look at folder arrangement and working principle. - test/ folder: test-json.json, this is a temporary file for testing. all other test-cases copying here with this name so they can process by test-case-creator.js. test-case-creator.js is core path & value creation mechanism. When it executed with executeNode() function. It reads the test-json.json file and generates the paths and values from this files content. With command line arguments it can generate different paths and values. As a result, two files are created with this process. the first of these files is test-json-paths.json and the second is test-json-values.json test-json-paths.json has all the path values. test-json-values.json has all the values that corresponding to path values. - tests/ folder All files in this folder is a test-case. But it doesn't mean that you can't change anything, on the contrary, all test-cases are creating automatically based on this folder content. You can add or remove any .json file that you want. All GO side test-case automation functions are in core_test.go file. This package developed with Node.js v13.7.0. please make sure that your machine has a valid version of Node.js before testing. All functions and methods are tested with complicated randomly genereted .json files. Like this, Most of JSON packages not even run properly with this kind of JSON streams. We did't see such packages as competitors to ourselves. And that's because we didn't even bother to benchmark against them. Benchmark results. - Benchmark prefix removed from function names for make room to results. - Benchmark between 'buger/jsonparser' and 'ecoshub/jin' use the same payload (JSON test-cases) that 'buger/jsonparser' package use for benchmark it self. We are currently working on, - Marshal() and Unmarshal() functions. - http.Request parser/interpreter - Builder functions for http.ResponseWriter If you want to contribute this work feel free to fork it. We want to fill this section with contributors.

Package luar provides a convenient interface between Lua and Go. It uses Alessandro Arzilli's golua (https://github.com/aarzilli/golua). Most Go values can be passed to Lua: basic types, strings, complex numbers, user-defined types, pointers, composite types, functions, channels, etc. Conversely, most Lua values can be converted to Go values. Composite types are processed recursively. Methods can be called on user-defined types. These methods will be callable using _dot-notation_ rather than colon notation. Arrays, slices, maps and structs can be copied as tables, or alternatively passed over as Lua proxy objects which can be naturally indexed. In the case of structs and string maps, fields have priority over methods. Use 'luar.method(<value>, <method>)(<params>...)' to call shadowed methods. Unexported struct fields are ignored. The "lua" tag is used to match fields in struct conversion. You may pass a Lua table to an imported Go function; if the table is 'array-like' then it is converted to a Go slice; if it is 'map-like' then it is converted to a Go map. Pointer values encode as the value pointed to when unproxified. Usual operators (arithmetic, string concatenation, pairs/ipairs, etc.) work on proxies too. The type of the result depends on the type of the operands. The rules are as follows: - If the operands are of the same type, use this type. - If one type is a Lua number, use the other, user-defined type. - If the types are different and not Lua numbers, convert to a complex proxy, a Lua number, or a Lua string according to the result kind. Channel proxies can be manipulated with the following methods: - close(): Close the channel. - recv() value: Fetch and return a value from the channel. - send(x value): Send a value in the channel. Complex proxies can be manipulated with the following attributes: - real: The real part. - imag: The imaginary part. Slice proxies can be manipulated with the following methods/attributes: - append(x ...value) sliceProxy: Append the elements and return the new slice. The elements must be convertible to the slice element type. - cap: The capacity of the slice. - slice(i, j integer) sliceProxy: Return the sub-slice that ranges from 'i' to 'j' excluded, starting from 1. String proxies can be browsed rune by rune with the pairs/ipairs functions. These runes are encoded as strings in Lua. Indexing a string proxy (starting from 1) will return the corresponding byte as a Lua string. String proxies can be manipulated with the following method: - slice(i, j integer) sliceProxy: Return the sub-string that ranges from 'i' to 'j' excluded, starting from 1. Pointers to structs and structs within pointers are automatically dereferenced. Slices must be looped over with 'ipairs'.

Package nlp provides implementations of selected machine learning algorithms for natural language processing of text corpora. The primary focus is the statistical semantics of plain-text documents supporting semantic analysis and retrieval of semantically similar documents. The package makes use of the Gonum (http://http//www.gonum.org/) library for linear algebra and scientific computing with some inspiration taken from Python's scikit-learn (http://scikit-learn.org/stable/) and Gensim(https://radimrehurek.com/gensim/) The primary intended use case is to support document input as text strings encoded as a matrix of numerical feature vectors called a `term document matrix`. Each column in the matrix corresponds to a document in the corpus and each row corresponds to a unique term occurring in the corpus. The individual elements within the matrix contain the frequency with which each term occurs within each document (referred to as `term frequency`). Whilst textual data from document corpora are the primary intended use case, the algorithms can be used with other types of data from other sources once encoded (vectorised) into a suitable matrix e.g. image data, sound data, users/products, etc. These matrices can be processed and manipulated through the application of additional transformations for weighting features, identifying relationships or optimising the data for analysis, information retrieval and/or predictions. Typically the algorithms in this package implement one of three primary interfaces: One of the implementations of Vectoriser is Pipeline which can be used to wire together pipelines composed of a Vectoriser and one or more Transformers arranged in serial so that the output from each stage forms the input of the next. This can be used to construct a classic LSI (Latent Semantic Indexing) pipeline (vectoriser -> TF.IDF weighting -> Truncated SVD): Whilst they take different inputs, both Vectorisers and Transformers have 3 primary methods:

mcstrings is a tool for manipulating strings in a Minecraft world.

Objx - Go package for dealing with maps, slices, JSON and other data. Objx provides the `objx.Map` type, which is a `map[string]interface{}` that exposes a powerful `Get` method (among others) that allows you to easily and quickly get access to data within the map, without having to worry too much about type assertions, missing data, default values etc. Objx uses a preditable pattern to make access data from within `map[string]interface{}` easy. Call one of the `objx.` functions to create your `objx.Map` to get going: NOTE: Any methods or functions with the `Must` prefix will panic if something goes wrong, the rest will be optimistic and try to figure things out without panicking. Use `Get` to access the value you're interested in. You can use dot and array notation too: Once you have sought the `Value` you're interested in, you can use the `Is*` methods to determine its type. Or you can just assume the type, and use one of the strong type methods to extract the real value: If there's no value there (or if it's the wrong type) then a default value will be returned, or you can be explicit about the default value. If you're dealing with a slice of data as a value, Objx provides many useful methods for iterating, manipulating and selecting that data. You can find out more by exploring the index below. A simple example of how to use Objx: Since `objx.Map` is a `map[string]interface{}` you can treat it as such. For example, to `range` the data, do what you would expect:

Package walletdb provides a namespaced database interface for btcwallet. A wallet essentially consists of a multitude of stored data such as private and public keys, key derivation bits, pay-to-script-hash scripts, and various metadata. One of the issues with many wallets is they are tightly integrated. Designing a wallet with loosely coupled components that provide specific functionality is ideal, however it presents a challenge in regards to data storage since each component needs to store its own data without knowing the internals of other components or breaking atomicity. This package solves this issue by providing a pluggable driver, namespaced database interface that is intended to be used by the main wallet daemon. This allows the potential for any backend database type with a suitable driver. Each component, which will typically be a package, can then implement various functionality such as address management, voting pools, and colored coin metadata in their own namespace without having to worry about conflicts with other packages even though they are sharing the same database that is managed by the wallet. A quick overview of the features walletdb provides are as follows: The main entry point is the DB interface. It exposes functionality for creating, retrieving, and removing namespaces. It is obtained via the Create and Open functions which take a database type string that identifies the specific database driver (backend) to use as well as arguments specific to the specified driver. The Namespace interface is an abstraction that provides facilities for obtaining transactions (the Tx interface) that are the basis of all database reads and writes. Unlike some database interfaces that support reading and writing without transactions, this interface requires transactions even when only reading or writing a single key. The Begin function provides an unmanaged transaction while the View and Update functions provide a managed transaction. These are described in more detail below. The Tx interface provides facilities for rolling back or commiting changes that took place while the transaction was active. It also provides the root bucket under which all keys, values, and nested buckets are stored. A transaction can either be read-only or read-write and managed or unmanaged. A managed transaction is one where the caller provides a function to execute within the context of the transaction and the commit or rollback is handled automatically depending on whether or not the provided function returns an error. Attempting to manually call Rollback or Commit on the managed transaction will result in a panic. An unmanaged transaction, on the other hand, requires the caller to manually call Commit or Rollback when they are finished with it. Leaving transactions open for long periods of time can have several adverse effects, so it is recommended that managed transactions are used instead. The Bucket interface provides the ability to manipulate key/value pairs and nested buckets as well as iterate through them. The Get, Put, and Delete functions work with key/value pairs, while the Bucket, CreateBucket, CreateBucketIfNotExists, and DeleteBucket functions work with buckets. The ForEach function allows the caller to provide a function to be called with each key/value pair and nested bucket in the current bucket. As discussed above, all of the functions which are used to manipulate key/value pairs and nested buckets exist on the Bucket interface. The root bucket is the upper-most bucket in a namespace under which data is stored and is created at the same time as the namespace. Use the RootBucket function on the Tx interface to retrieve it. The CreateBucket and CreateBucketIfNotExists functions on the Bucket interface provide the ability to create an arbitrary number of nested buckets. It is a good idea to avoid a lot of buckets with little data in them as it could lead to poor page utilization depending on the specific driver in use. This example demonstrates creating a new database, getting a namespace from it, and using a managed read-write transaction against the namespace to store and retrieve data.

Package linq provides methods for querying and manipulating slices, arrays, maps, strings, channels and collections. Authors: Alexander Kalankhodzhaev (kalan), Ahmet Alp Balkan, Cleiton Marques Souza.

Package bitstring implements a fixed length bit string type and bit string manipulation functions

Sprig: Template functions for Go. This package contains a number of utility functions for working with data inside of Go `html/template` and `text/template` files. To add these functions, use the `template.Funcs()` method: Note that you should add the function map before you parse any template files. Date Functions String Functions String Slice Functions: Integer Slice Functions: Conversions: Defaults: OS: File Paths: Encoding: Reflection: typeOf: Takes an interface and returns a string representation of the type. For pointers, this will return a type prefixed with an asterisk(`*`). So a pointer to type `Foo` will be `*Foo`. typeIs: Compares an interface with a string name, and returns true if they match. Note that a pointer will not match a reference. For example `*Foo` will not match `Foo`. typeIsLike: Compares an interface with a string name and returns true if the interface is that `name` or that `*name`. In other words, if the given value matches the given type or is a pointer to the given type, this returns true. kindOf: Takes an interface and returns a string representation of its kind. kindIs: Returns true if the given string matches the kind of the given interface. Note: None of these can test whether or not something implements a given interface, since doing so would require compiling the interface in ahead of time. Data Structures: Lists Functions: These are used to manipulate lists: '{{ list 1 2 3 | reverse | first }}' Dict Functions: These are used to manipulate dicts. Math Functions: Integer functions will convert integers of any width to `int64`. If a string is passed in, functions will attempt to convert with `strconv.ParseInt(s, 1064)`. If this fails, the value will be treated as 0. Crypto Functions: SemVer Functions: These functions provide version parsing and comparisons for SemVer 2 version strings.

Package database provides a block and metadata storage database. This package provides a database layer to store and retrieve block data and arbitrary metadata in a simple and efficient manner. The default backend, ffldb, has a strong focus on speed, efficiency, and robustness. It makes use leveldb for the metadata, flat files for block storage, and strict checksums in key areas to ensure data integrity. A quick overview of the features database provides are as follows: The main entry point is the DB interface. It exposes functionality for transactional-based access and storage of metadata and block data. It is obtained via the Create and Open functions which take a database type string that identifies the specific database driver (backend) to use as well as arguments specific to the specified driver. The Namespace interface is an abstraction that provides facilities for obtaining transactions (the Tx interface) that are the basis of all database reads and writes. Unlike some database interfaces that support reading and writing without transactions, this interface requires transactions even when only reading or writing a single key. The Begin function provides an unmanaged transaction while the View and Update functions provide a managed transaction. These are described in more detail below. The Tx interface provides facilities for rolling back or committing changes that took place while the transaction was active. It also provides the root metadata bucket under which all keys, values, and nested buckets are stored. A transaction can either be read-only or read-write and managed or unmanaged. A managed transaction is one where the caller provides a function to execute within the context of the transaction and the commit or rollback is handled automatically depending on whether or not the provided function returns an error. Attempting to manually call Rollback or Commit on the managed transaction will result in a panic. An unmanaged transaction, on the other hand, requires the caller to manually call Commit or Rollback when they are finished with it. Leaving transactions open for long periods of time can have several adverse effects, so it is recommended that managed transactions are used instead. The Bucket interface provides the ability to manipulate key/value pairs and nested buckets as well as iterate through them. The Get, Put, and Delete functions work with key/value pairs, while the Bucket, CreateBucket, CreateBucketIfNotExists, and DeleteBucket functions work with buckets. The ForEach function allows the caller to provide a function to be called with each key/value pair and nested bucket in the current bucket. As discussed above, all of the functions which are used to manipulate key/value pairs and nested buckets exist on the Bucket interface. The root metadata bucket is the upper-most bucket in which data is stored and is created at the same time as the database. Use the Metadata function on the Tx interface to retrieve it. The CreateBucket and CreateBucketIfNotExists functions on the Bucket interface provide the ability to create an arbitrary number of nested buckets. It is a good idea to avoid a lot of buckets with little data in them as it could lead to poor page utilization depending on the specific driver in use. This example demonstrates creating a new database and using a managed read-write transaction to store and retrieve metadata. This example demonstrates creating a new database, using a managed read-write transaction to store a block, and using a managed read-only transaction to fetch the block.

Sprig: Template functions for Go. This package contains a number of utility functions for working with data inside of Go `html/template` and `text/template` files. To add these functions, use the `template.Funcs()` method: Note that you should add the function map before you parse any template files. Date Functions String Functions String Slice Functions: Integer Slice Functions: Conversions: Defaults: OS: File Paths: Encoding: Reflection: typeOf: Takes an interface and returns a string representation of the type. For pointers, this will return a type prefixed with an asterisk(`*`). So a pointer to type `Foo` will be `*Foo`. typeIs: Compares an interface with a string name, and returns true if they match. Note that a pointer will not match a reference. For example `*Foo` will not match `Foo`. typeIsLike: Compares an interface with a string name and returns true if the interface is that `name` or that `*name`. In other words, if the given value matches the given type or is a pointer to the given type, this returns true. kindOf: Takes an interface and returns a string representation of its kind. kindIs: Returns true if the given string matches the kind of the given interface. Note: None of these can test whether or not something implements a given interface, since doing so would require compiling the interface in ahead of time. Data Structures: Lists Functions: These are used to manipulate lists: '{{ list 1 2 3 | reverse | first }}' Dict Functions: These are used to manipulate dicts. Math Functions: Integer functions will convert integers of any width to `int64`. If a string is passed in, functions will attempt to convert with `strconv.ParseInt(s, 1064)`. If this fails, the value will be treated as 0. Crypto Functions: SemVer Functions: These functions provide version parsing and comparisons for SemVer 2 version strings.

Package linq provides methods for querying and manipulating slices, arrays, maps, strings, channels and collections. Authors: Alexander Kalankhodzhaev (kalan), Ahmet Alp Balkan

Package linq provides methods for querying and manipulating slices, arrays, maps, strings, channels and collections. Authors: Alexander Kalankhodzhaev (kalan), Ahmet Alp Balkan, Cleiton Marques Souza.

Sprig: Template functions for Go. This package contains a number of utility functions for working with data inside of Go `html/template` and `text/template` files. To add these functions, use the `template.Funcs()` method: Note that you should add the function map before you parse any template files. Date Functions String Functions String Slice Functions: Integer Slice Functions: Conversions: Defaults: OS: File Paths: Encoding: Reflection: typeOf: Takes an interface and returns a string representation of the type. For pointers, this will return a type prefixed with an asterisk(`*`). So a pointer to type `Foo` will be `*Foo`. typeIs: Compares an interface with a string name, and returns true if they match. Note that a pointer will not match a reference. For example `*Foo` will not match `Foo`. typeIsLike: Compares an interface with a string name and returns true if the interface is that `name` or that `*name`. In other words, if the given value matches the given type or is a pointer to the given type, this returns true. kindOf: Takes an interface and returns a string representation of its kind. kindIs: Returns true if the given string matches the kind of the given interface. Note: None of these can test whether or not something implements a given interface, since doing so would require compiling the interface in ahead of time. Data Structures: Lists Functions: These are used to manipulate lists: '{{ list 1 2 3 | reverse | first }}' Dict Functions: These are used to manipulate dicts. Math Functions: Integer functions will convert integers of any width to `int64`. If a string is passed in, functions will attempt to convert with `strconv.ParseInt(s, 1064)`. If this fails, the value will be treated as 0. Crypto Functions: SemVer Functions: These functions provide version parsing and comparisons for SemVer 2 version strings.

Package dom provides GopherJS and Go bindings for the JavaScript DOM APIs. This package is an in progress effort of providing idiomatic Go bindings for the DOM, wrapping the JavaScript DOM APIs. The API is neither complete nor frozen yet, but a great amount of the DOM is already useable. While the package tries to be idiomatic Go, it also tries to stick closely to the JavaScript APIs, so that one does not need to learn a new set of APIs if one is already familiar with it. One decision that hasn't been made yet is what parts exactly should be part of this package. It is, for example, possible that the canvas APIs will live in a separate package. On the other hand, types such as StorageEvent (the event that gets fired when the HTML5 storage area changes) will be part of this package, simply due to how the DOM is structured – even if the actual storage APIs might live in a separate package. This might require special care to avoid circular dependencies. The documentation for some of the identifiers is based on the MDN Web Docs by Mozilla Contributors (https://developer.mozilla.org/en-US/docs/Web/API), licensed under CC-BY-SA 2.5 (https://creativecommons.org/licenses/by-sa/2.5/). The usual entry point of using the dom package is by using the GetWindow() function which will return a Window, from which you can get things such as the current Document. The DOM has a big amount of different element and event types, but they all follow three interfaces. All functions that work on or return generic elements/events will return one of the three interfaces Element, HTMLElement or Event. In these interface values there will be concrete implementations, such as HTMLParagraphElement or FocusEvent. It's also not unusual that values of type Element also implement HTMLElement. In all cases, type assertions can be used. Example: Several functions in the JavaScript DOM return "live" collections of elements, that is collections that will be automatically updated when elements get removed or added to the DOM. Our bindings, however, return static slices of elements that, once created, will not automatically reflect updates to the DOM. This is primarily done so that slices can actually be used, as opposed to a form of iterator, but also because we think that magically changing data isn't Go's nature and that snapshots of state are a lot easier to reason about. This does not, however, mean that all objects are snapshots. Elements, events and generally objects that aren't slices or maps are simple wrappers around JavaScript objects, and as such attributes as well as method calls will always return the most current data. To reflect this behaviour, these bindings use pointers to make the semantics clear. Consider the following example: The above example will print `true`. Some objects in the JS API have two versions of attributes, one that returns a string and one that returns a DOMTokenList to ease manipulation of string-delimited lists. Some other objects only provide DOMTokenList, sometimes DOMSettableTokenList. To simplify these bindings, only the DOMTokenList variant will be made available, by the type TokenList. In cases where the string attribute was the only way to completely replace the value, our TokenList will provide Set([]string) and SetString(string) methods, which will be able to accomplish the same. Additionally, our TokenList will provide methods to convert it to strings and slices. This package has a relatively stable API. However, there will be backwards incompatible changes from time to time. This is because the package isn't complete yet, as well as because the DOM is a moving target, and APIs do change sometimes. While an attempt is made to reduce changing function signatures to a minimum, it can't always be guaranteed. Sometimes mistakes in the bindings are found that require changing arguments or return values. Interfaces defined in this package may also change on a semi-regular basis, as new methods are added to them. This happens because the bindings aren't complete and can never really be, as new features are added to the DOM. If you depend on none of the APIs changing unexpectedly, you're advised to vendor this package.

Package linq provides methods for querying and manipulating slices, arrays, maps, strings, channels and collections. Authors: Alexander Kalankhodzhaev (kalan), Ahmet Alp Balkan, Cleiton Marques Souza.

Package linq provides methods for querying and manipulating slices, arrays, maps, strings, channels and collections. Authors: Alexander Kalankhodzhaev (kalan), Ahmet Alp Balkan, Cleiton Marques Souza.

Package linq provides methods for querying and manipulating slices, arrays, maps, strings, channels and collections. Authors: Alexander Kalankhodzhaev (kalan), Ahmet Alp Balkan, Cleiton Marques Souza.

Package squalor provides SQL utility routines, such as validation of models against table schemas, marshalling and unmarshalling of model structs into table rows and programmatic construction of SQL statements. While squalor uses the database/sql package, the SQL it utilizes is MySQL specific (e.g. REPLACE, INSERT ON DUPLICATE KEY UPDATE, etc). Given a simple table definition: And a model for a row of the table: The BindModel method will validate that the model and the table definition are compatible. For example, it would be an error for the User.ID field to have the type string. The table definition is loaded from the database allowing custom checks such as verifying the existence of indexes. While fields are often primitive types such as int64 or string, it is sometimes desirable to use a custom type. This can be accomplished by having the type implement the sql.Scanner and driver.Valuer interfaces. For example, you might create a GzippedText type which automatically compresses the value when it is written to the database and uncompressed when it is read: The Insert method is used to insert one or more rows in a table. You can pass either a struct or a pointer to a struct. Multiple rows can be inserted at once. Doing so offers convenience and performance. When multiple rows are batch inserted the returned error corresponds to the first SQL error encountered which may make it impossible to determine which row caused the error. If the rows correspond to different tables the order of insertion into the tables is undefined. If you care about the order of insertion into multiple tables and determining which row is causing an insertion error, structure your calls to Insert appropriately (i.e. insert into a single table or insert a single row). After a successful insert on a table with an auto increment primary key, the auto increment will be set back in the corresponding field of the object. For example, if the user table was defined as: Then we could create a new user by doing: The Replace method replaces a row in table, either inserting the row if it doesn't exist, or deleting and then inserting the row. See the MySQL docs for the difference between REPLACE, UPDATE and INSERT ON DUPLICATE KEY UPDATE (Upsert). The Update method updates a row in a table, returning the number of rows modified. The Upsert method inserts or updates a row. The Get method retrieves a single row by primary key and binds the result columns to a struct. The delete method deletes rows by primary key. See the documentation for DB.Delete for performance limitations when batch deleting multiple rows from a table with a primary key composed of multiple columns. To support optimistic locking with a column storing the version number, one field in a model object can be marked to serve as the lock. Modifying the example above: Now, the Update method will ensure that the object has not been concurrently modified when writing, by constraining the update by the version number. If the update is successful, the version number will be both incremented on the model (in-memory), as well as in the database. Programmatic construction of SQL queries prohibits SQL injection attacks while keeping query construction both readable and similar to SQL itself. Support is provided for most of the SQL DML (data manipulation language), though the constructed queries are targetted to MySQL. DB provides wrappers for the sql.Query and sql.QueryRow interfaces. The Rows struct returned from Query has an additional StructScan method for binding the columns for a row result to a struct. QueryRow can be used to easily query and scan a single value: In addition to the convenience of inserting, deleting and updating table rows using a struct, attention has been paid to performance. Since squalor is carefully constructing the SQL queries for insertion, deletion and update, it eschews the use of placeholders in favor of properly escaping values in the query. With the Go MySQL drivers, this saves a roundtrip to the database for each query because queries with placeholders must be prepared before being executed. Marshalling and unmarshalling of data from structs utilizes reflection, but care is taken to minimize the use of reflection in order to improve performance. For example, reflection data for models is cached when the model is bound to a table. Batch operations are utilized when possible. The Delete, Insert, Replace, Update and Upsert operations will perform multiple operations per SQL statement. This can provide an order of magnitude speed improvement over performing the mutations one row at a time due to minimizing the network overhead.

Package mangle is a sanitization / data masking library for Go (golang). This library provides functionality to sanitize text and HTML data. This can be integrated into tools that export or manipulate databases/files so that confidential data is not exposed to staging, development or testing systems. Install mangle: Try the command line tool: For basic usage of mangle as a Go library for strings, see the Example below. For usage using io.Reader/io.Writer for text and html, see the manglefile source code. Secure - every non-punctuation, non-tag word is replaced, with no reuse of source words. Fast - around 350,000 words/sec ("War and Peace" mangled in < 2s). Deterministic - words are selected from a corpus deterministically - subsequent runs will result in the same word replacements as long as the user secret is not changed. This allows automated tests to run against the sanitized data, as well as for efficient rsync's of mangled versions of large slowly changing data sets. Accurate - maintains a high level of resemblance to the source text, to allow for realistic testing of search indexes, page layout etc. Replacement words are all natural words from a user defined corpus. Source text word length, punctuation, title case and all caps, HTML tags and attributes are maintained. Reads a corpus from a file, initializes a Mangle, runs a string through it and prints the output.