File Saving

Copyright 2016 - 2018 The excelize Authors. All rights reserved. Use of this source code is governed by a BSD-style license that can be found in the LICENSE file. Package excelize providing a set of functions that allow you to write to and read from XLSX files. Support reads and writes XLSX file generated by Microsoft Excel™ 2007 and later. Support save file without losing original charts of XLSX. This library needs Go version 1.8 or later. See https://xuri.me/excelize for more information about this package.

pprof_mac_fix applies a binary patch to the OS X kernel in order to make pprof profiling report accurate values. The public beta of OS X 10.11 El Capitan appears to contain a fix for the underlying kernel bug. It therefore appears that pprof_mac_fix is unnecessary on that system: pprof will just work out of the box. If run on an OS X 10.11 system, pprof_mac_fix will report that the kernel is already correct without any patch. This program is meant to modify the operating system kernel, the program that runs your computer and makes it safe for all the other programs to run. If you damage the kernel, your computer will not be able to boot. Before using this program, ensure you can boot into “recovery mode.” Many recent Macs make this possible by holding down Alt/Option when you hear the boot chime and selecting the “Recovery HD.” Otherwise, you can boot to the opening screen of an install DVD or thumb drive. You have been warned. This program has been used successfully on the following systems: Snow Leopard x86_64 may work too but is untried. An earlier version of this program shipped with a buggy patch for OS X 10.9 Mavericks/Darwin 13.0. If you used the old patch you are encouraged to restore your old kernel and patch using an updated copy of this program: If running http://swtch.com/~rsc/macbug.c crashes your system, you have the buggy patch applied. First, read the warning above. Next, install this program and run it. If the program finds that it knows how to patch your kernel, it will reinvoke itself using sudo, which will prompt for your password and install the new kernel. It saves the old kernel as a numbered file in the kernel source directory (the root directory or, for OS X 10.10 Yosemite, /System/Library/Kernels). Finally, cross your fingers and reboot. If all goes well, running “uname -a” will report the time at which you ran pprof_mac_fix as the kernel build time. If you have a Go tree built at tip, should now say that the CPU profiling tests pass, whereas before they printed failure messages and were marked as skipped. If something goes wrong, you will need to restore the original kernel. To do this, boot into recovery mode. If you are using FileVault whole-disk encryption, start Disk Utility, unlock the disk, and then quit disk utility. (Disk Utility may be an option shown on the recovery mode screen or you may have to select it from the Utilities menu in the top-of-screen menu bar.) Start Terminal and then run these commands: The Mac*HD* pattern matches "Macintosh HD" and "Macintosh HD " [sic]. If you have changed your disk's volume name you may need to use a different pattern (run "mount" to see the mounted disks). I am not sure whether the bless command is strictly necessary. On OS X 10.10 Yosemite, the above command sequence changes to: Reboot. You should be back to the original, unmodified kernel. Either way, you need to be able to start Terminal and, if you are using FileVault whole-disk encryption, Disk Utility. For details on creating a bootable recovery disk or bootable installation disk, see http://support.apple.com/kb/HT4848 and http://lifehacker.com/5928780/. The program rewrites the kernel code that delivers the profiling signals SIGPROF and SIGVTALRM in response to setitimer(2) calls. Instead of delivering the signal to the process as a whole, the new code delivers the signal to the thread whose execution triggered the signal; that is, it delivers the signal to the thread that is actually running and should be profiled. The rewrite only edits code in the function named bsd_ast, which is in charge of little more than delivering these signals. It is therefore unlikely to cause problems in programs not using the signals. Of course, there are no safety nets when changing an operating system kernel; caution is warranted. A more detailed description is at http://research.swtch.com/macpprof.

brbundle package provides asset bundler's runtime that uses Brotli (https://github.com/google/brotli). Source repository is here: https://github.com/pyspa/brbundle To install runtime and commandline tool, type the following command: This package provides four kind of bundles to handle assets: 1. Embedding. Generate .go file that includes binary representation of asset files. This is best for libraries and so on that is needed to be go gettable. 2. Appended to executable. Generate .zip file internally and appended to executables. You can replace assets after building. 3. Single packed binary file. You can specify and import during runtime. I assume this used for DLC. 4. Folder. This is for debugging. You don't have to do anything to import asset brbundle searches assets the following orders: The following command generates .go file: The following command append assets to executable: The following command generates single packed file: The following command generates asset folder. You can use regular cp command even if you don't have to encrypto assets: It is easy to use the assets: Embedded assets and assets appended to executable are available by default. The following functions registers assets in single packed file and local folder: You can save the earth by using brbundle. brbundle middlewares brotli content directly when browser supports it. Currently, more than 90% browsers already support (https://caniuse.com/#feat=brotli). brbundle provides the following frameworks' middleware: net/http: These middlewares also support SPA(Single Page Application). More detail information is on Angular web site (https://angular.io/guide/deployment#routed-apps-must-fallback-to-indexhtml). All samples are in examples folder: https://github.com/pyspa/brbundle/tree/master/examples brbundle uses Brotli by default. If you pass --fast/-f option, brbundle uses Snappy (https://github.com/google/snappy) instead of Brotli. Snappy has low compression ratio, but very fast. brbundle supports encryption. You can generates encryption/decryption key by the following command: When creating bundles, you can pass the key via --crypto/-c option: Keys should be passed the following functions:

Package xcore is a set of basic objects for programation (XCache for caches, XDataset for data sets, XLanguage for languages and XTemplate for templates). For GO, the actual existing code includes: - XCache: Application Memory Caches for any purpose, with time control and quantity control of object in the cache and also check changes against original source. It is a thread safe cache. - XDataset: Basic nested data structures for any purpose (template injection, configuration files, database records, etc). - XLanguage: language dependent text tables for internationalization of code. The sources can be text or XML file definitions. - XTemplate: template system with meta language to create complex documents (compatible with any text language, HTML, CSS, JS, PDF, XML, etc), heavily used on CMS systems and others. It is already used on sites that serve more than 60 million pages a month (500 pages per second on pike hour) and can be used on multithreading environment safely. XCache is a library to cache all the data you want into current application memory for a very fast access to the data. The access to the data support multithreading and concurrency. For the same reason, this type of cache is not persistent (if you exit the application) and cannot grow too much (as memory is the limit). However, you can control a timeout of each cache piece, and eventually a comparison function against a source (file, database, etc) to invalid the cache. 1. Declare a new XCache with NewXCache() function: 2. Fill in the cache: Once you have declared the cache, you can fill it with anything you want. The main cache object is an interface{} so you can put here anything you need, from simple variables to complex structures. You need to use the Set function: Note the ID is always a string, so convert a database key to string if needed. 3. To use the cache, just ask for your entry with Get function: 4. To maintain the cache: You may need Del function, to delete a specific entry (maybe because you deleted the record in database). You may also need Clean function to deletes a percentage of the cache, or Flush to deletes it all. The Verify function is used to check cache entries against their sources through the Validator function. Be very careful, if the cache is big or the Validator function is complex (maybe ask for a remote server information), the verification may be VERY slow and huge CPU use. The Count function gives some stats about the cache. 5. How to use Verify Function: This function is recommended when the source is local and fast to check (for instance a language file or a template file). When the source is distant (other cluster database, any rpc source on another network, integration of many parts, etc), it is more recommended to create a function that will delete the cache when needed (on demand cache change). The validator function is a func(id, time.Time) bool function. The first parameter is the ID entry in the cache, the second parameter the time of the entry was created. The validator function returns true is the cache is still valid, or false if it needs to be invalidated. The XCache is thread safe. The cache can be limited in quantity of entries and timeout for data. The cache is automanaged (for invalid expired data) and can be cleaned partially or totally manually. The XLanguage table of text entries can be loaded from XML file, XML string or normal text file or string. It is used to keep a table of id=value set of entries in any languages you need, so it is easy to switch between XLanguage instance based on the required language needed. Obviously, any XLanguage you load in any language should have the same id entries translated, for the same use. The XLanguage object is thread safe 1. loading: You can load any file or XML string directly into the object. 1.1 The XML Format is: NAMEOFTABLE is the name of your table entry, for example "loginform", "user_report", etc. LG is the ISO-3369 2 letters language ID, for example "es" for spanish, "en" for english, "fr" for french, etc. ENTRYNAME is the ID of the entry, for example "greating", "yourname", "submitbutton". ENTRYVALUE is the text for your entry, for example "Hello", "You are:", "Save" if your table is in english. STATUSVALUE is the status of the entry- You may put any value to control your translation over time and processes. 1.2 The flat text format is: ENTRYNAME is the ID of the entry, for example "greating", "yourname", "submitbutton". ENTRYVALUE is the text for your entry, for example "Hello", "You are:", "Save" if your table is in english. There is no name of table or language in this format (you "know" what you are loading). The advantage to use XML format is to have more control over your language, and eventyally add attributes into your entries, for instance you may add attributes translated="yes/no", verified="yes/no", and any other data that your system could insert. The XLanguage will ignore those attributes loading the table. 2. creation: To create a new XLanguage empty structure: There are 4 functions to create the language from a file or string, flat text or XML text: Then you can use the set of basic access functions: SetName/SetLanguage functions are used to set the table name and language of the object (generally to build an object from scratch). GetName/GetLanguage functions are used to get the table name and language of the object (generally when you load it from some source). Set/Get/Del functions are used to add or modify a new entry, read an entry, or deletes an entry in the object. SetStatus/GetStatus functions are used to add or get a status for the entry in the object. To create am XML file from the objet, you can use the GetXML() function 1. Overview: The XDataSet is a set of interfaces and basic classes ready-to-use to build a standard set of data optionally nested and hierarchical, that can be used for any purpose: - Keep complex data in memory. - Create JSON structures. - Inject data into templates. - Interchange database data (records set and record). You can store into it generic supported data, as well as any complex interface structures: - Int - Float - String - Time - Bool - []Int - []Float - []Time - []Bool - XDataSetDef (anything extended with this interface) - []String - Anything else ( interface{} ) - XDataSetCollectionDef (anything extended with this interface) The generic supported data comes with a set of functions to get/set those data directly into the XDataset. Example: Note that all references to XDataset and XDatasetCollection are pointers, always (to be able to modify the values of them). 2. XDatasetDef interface: It is the interface to describe a simple set of data mapped as "name": value, where value can be of any type. The interface implements a good amount of basic methods to get the value on various format such as GetString("name"), GetInt("name"), etc (see below). If the value is another type as asked, the method should contert it if possible. For instance "key":123 required through GetString("key") should return "123". The XDataset type is a simple map[string]interface{} with all the implemented methods and should be enough to use for almost all required cases. However, you can build any complex structure that extends the interface and implements all the required functions to stay compatible with the XDatasetDef. 3. XDatasetCollectionDef Interface: This is the interface used to extend any type of data as a Collection, i-e an array of XDatasetDef. This is a slice of any XDatasetDef compatible data. The interface implements some methods to work on array structure such as Push, Pop, Shift, Unshift and some methods to search data into the array. The XDatasetCollection type is a simple []DatasetDef with all the implemented methods and should be enough to use for almost all required cases. 1. Overview: The XDataSetTS is a DatasetDef structure, thread safe. It is build on the XDataset with the same properties, but is thread safe to protect Read/Write accesses from different thread. Example: You may also build a XDatasetTS to encapsulate a XDatasetDef that is not thread safe, to use it safely Note that all references to XDatasetTS are pointers, always (to be able to modify the values of them). The DatasetTS meet the XDatasetDef interface 1. Overview: This is a class to compile and keep a Template that can be injected with an XDataSet structure of data, with a metalanguage to inject the data. The metalanguage is extremely simple and is made to be useful and **really** separate programation from template code (not like other many generic template systems that just mix code and data). A template is a set of HTML/XML (or any other language) string with a meta language to inject variables and build a final string. The XCore XTemplate system is based on the injection of parameters, language translation strings and data fields directly into the HTML (Or any other language you need) template. The HTML itself (or any other language) is a text code not directly used by the template system, but used to dress the data you want to represent in your preferred language. The variables to inject must be into a XDataSet structure or into a structure extended from XDataSetDef interface. The injection of data is based on a XDataSet structure of values that can be nested into another XDataSet and XDataSetConnection and so on. The template compiler recognize nested arrays to automatically make loops on the information. Templates are made to store reusable HTML code, and overall easily changeable by people that do not know how to write programs. A template can be as simple as a single character (no variables to inject) to a very complex nested, conditional and loops sub-templates. Yes. this is a template, but a very simple one without need to inject any data. Let's go more complex: Having an array of data, we want to paint it beautifull: We can create a template to inject this data into it: 2. Create and use XTemplateData: In sight to create and use templates, you have all those possible options to use: Creates the XTemplate from a string or a file or any other source: Clone the XTemplate: 3. Metalanguage Reference: 3.1 Comments: %-- and --% You may use comments into your template. The comments will be discarded immediately at the compilation of the template and do not interfere with the rest of your code. Example: 3.2 Nested Templates: [[...]] and [[]] You can define new nested templates into your main template A nested template is defined by: The templteid is any combination of lowers letters only (a-z), numbers (0-9), and 3 special chars: . (point) - (dash) and _ (underline). The template is closed with [[]]. There is no limits into nesting templates. Any nested template will inheritate all the father elements and can use father elements too. To call a sub-template, you need to use &&templateid&& syntax (described below in this document). Example: You may use more than one id into the same template to avoid repetition of the same code. The different id's are separated with a pipe | Important note: A template will be visible only on the same level of its declaration. For example, if you put a subtemplate "b" into a subtemplate "a", it will not be visible by &&b&& from the top level, but only into the subtemplate "a". 3.3 Simple Elements: ##...## and {{...}} There are 2 types of simple elements. Language elements and Data injector elements (also called field elements). We "logically" define the 2 type of elements. The separation is only for human logic and template filling, however the language information can perfectly fit into the data to inject (and not use ## entries). 3.3.1 Languages elements: ##entry## All the languages elements should have the format: ##entry##. A language entry is generally anything written into your code or page that does not come from a database, and should adapt to the language of the client visiting your site. Using the languages elements may depend on the internationalization of your page. If your page is going to be in a single language forever, you really dont need to use languages entries. The language elements generally carry titles, menu options, tables headers etc. The language entries are set into the "#" entry of the main template XDataset to inject, and is a XLanguage table. Example: With data to inject: 3.3.2 Field elements: {{fieldname}} Fields values should have the format: {{fieldname}}. Your fields source can be a database or any other preferred repository data source. Example: You can access an element with its path into the data set to inject separating each field level with a > (greater than). This will take the name of the second hobby in the dataset defined upper. (collections are 0 indexed). The 1 denotes the second record of the hobbies XDatasetCollection. If the field is not found, it will be replaced with an empty string. Tecnically your field names can be any string in the dataset. However do not use { } or > into the names of your fields or the XTemplate may not use them correctly. We recommend to use lowercase names with numbers and ._- Accents and UTF8 symbols are also welcome. 3.3.3 Scope: When you use an id to point a value, the template will first search into the available ids of the local level. If no id is found, the it will search into the upper levers if any, and so on. Example: At the level of 'data2', using {{appname}} will get back 'DomCore'. At the level of 'key1', using {{appname}} will get back 'Nested App'. At the level of 'key2', using {{appname}} will get back 'DomCore'. At the level of root, 'data1' or 'detail', using {{appname}} will get back an empty string. 3.3.4 Path access: id>id>id>id At any level into the data array, you can access any entry into the subset array. For instance, taking the previous array of data to inject, let's suppose we are into a nested meta elements at the 'data1' level. You may want to access directly the 'Juan' entry. The path will be: The José's status value from the root will be: 3.4 Meta Elements They consist into an injection of a XDataset, called the "data to inject", into the template. The meta language is directly applied on the structure of the data array. The data to inject is a nested set of variables and values with the structure you want (there is no specific construction rules). You can inject nearly anything into a template meta elements. Example of a data array to inject: You can access directly any data into the array with its relative path (relative to the level you are when the metaelements are applied, see below). There are 4 structured meta elements in the XTemplate templates to use the data to inject: Reference, Loops, Condition and Debug. The structure of the meta elements in the template must follow the structure of the data to inject. 3.4.1 References to another template: &&order&& 3.4.1.1 When order is a single id (characters a-z0-9.-_), it will make a call to a sub template with the same set of data and replace the &&...&& with the result. The level in the data set is not changed. Example based on previous array of Fred's data: 3.4.1.2 When order contains 2 parameters separated by a semicolumn :, then second parameter is used to change the level of the data of array, with the subset with this id. The level in the data set is changed to this sub set. Example based on previous array of Fred's data: 3.4.1.3 When order contains 3 parameters separated by a semicolumn :, the second and third parameters are used to search the name of the new template based on the data fields to inject. This is an indirect access to the template. The name of the subtemplate is build with parameter3 as prefix and the content of parameter2 value. The third parameter must be empty. 3.4.2 Loops: @@order@@ 3.4.2.1 Overview This meta element will loop over each itterance of the set of data and concatenate each created template in the same order. You need to declare a sub template for this element. You may aso declare derivated sub templates for the different possible cases of the loop: For instance, If your main subtemplate for your look is called "hobby", you may need a different template for the first element, last element, Nth element, Element with a value "no" in the sport field, etc. The supported postfixes are: When the array to iterate is empty: - .none (for example "There is no hobby") When the array contains elements, it will search in order, the following template and use the first found: - templateid.key.[value] value is the key of the vector line. If the collection has a named key (string) or is a direct array (0, 1, 2...) - templateid.first if it is the first element of the array set (new from v1.01.11) - templateid.last if it is the first element of the array set (new from v1.01.11) - templateid.even if the line number is even - templateid in all other cases (odd is contained here if even is defined) Since v2.1.7, you can also use the pseudo field {{.counter}} into the loop subtemplate, to get the number of the counter of the loop, it is 1-based (first loop is 1, not 0) 3.4.2.2 When order is a single id (characters a-z0-9.-_), it will make a call to the sub template id with the same subset of data with the same id and replace the @@...@@ for each itterance of the data with the result. Example based on previous array of Fred's data: 3.4.2.3 When order contains 2 parameters separated by a semicolumn :, then first parameter is used to change the level of the data of array, with the subset with this id, and the second one for the template to use. Example based on previous array of Fred's data: 3.4.3 Conditional: ??order?? Makes a call to a subtemplate only if the field exists and have a value. This is very userfull to call a sub template for instance when an image or a video is set. When the condition is not met, it will search for the [id].none template. The conditional element does not change the level in the data set. 3.4.3.1 When order is a single id (characters a-z0-9.-_), it will make a call to the sub template id with the same field in the data and replace the ??...?? with the corresponding template Example based on previous array of Fred's data: 3.4.3.2 When order contains 2 parameters separated by a semicolumn :, then second parameter is used to change the level of the data of array, with the subset with this id. Example based on previous array of Fred's data: If the asked field is a catalog, true/false, numbered, you may also use .[value] subtemplates 3.5 Debug Tools: !!order!! There are two keywords to dump the content of the data set. This is very useful when you dont know the code that calls the template, don't remember some values, or for debug facilities. 3.5.1 !!dump!! Will show the totality of the data set, with ids and values. 3.5.1 !!list!! Will show only the tree of parameters, values are not shown.

Package dskvs is an embedded, in memory key value store following the REST convention of adressing resources as being 'collections' and 'members'. The main features of dskvs are: In dskvs, a collection contains many members, a member contains a value. A full key is a combination of both the collection and member identifiers to a value. Example: In this example, 'artist' is a collection that contains many artists. 'Daft Punk' is one of those artists. Example: A fullkey can contain many CollKeySep; only the first encountered is considered for the collection name. Every entry of dskvs is saved as a file under a path. If you tell dskvs to use the base path "$HOME/dskvs", it will prepare a filename for your key such as : dskvs will then write the entry at the path : Example: Given that keys have their value escaped, you can safely use any key: Will yield :

Output log to files. By default it writes to xxx.log file and saves xxx.log to xxx.log.<date> and opens an new xxx.log file when an new day begins. And it will also remove log files 7 days ago. Log file name, output dir and log file lifetime can be customized. Extended logging pkg for go. Output log format: eg:

dovel is a SMTP server and web interface that is simple to setup and use. This package has two parts: This binary is the main server, it is configured using a single config file which should be located in ~/.dovel-config.json. This server is responsible to receive your emails and save them according to your config. The other part is the optional web interface that is used to visualize your mail. The structure of this config file is blmayer.dev/x/dovel/config.Config. See that doc for more info. This package also delivers a subpackage called interfaces, it contains structs that are used through this project. Those are also used in templates and you can use them in other projects. Email works in a complex way, DNS records must match your server's configuration. This guide will try to give more detailed information in comparison with the website tutorial. An email server typically listens on ports 25, 2525, 587 or 465 for mail exchange. But their use differ: The current recomendation in to use port 586. To configure this server see blmayer.dev/x/dovel/config.Config. The server itself only receives email, for this feature only the MX record is enough. There are 2 handlers included in this project: The "file" handler gives you multiple inboxes, so you can separate by giving different addresses, for example, email1@my.domain and email2@my.domain, will have different inboxes. Inside each inbox emails are separated by subject. The "gwi" handler is intended for mailing lists, or issues on git repositories, email is added to the open folder, and then separated by subject. See the gwi project for more information. To receive emails you need to setup the MX record in your domain registrar, sending email is more complicated, some receiving servers only need the SPF and PTR records, some also need DKIM and DMARK, adjust according to your needs.

The bookpipeline package contains various tools and functions for the OCR of books, with a focus on distributed OCR using short-lived virtual servers. It also contains several tools that are useful standalone; read the accompanying README for more details. The book pipeline is a way to split the different processes that for book OCR into small jobs, which can be processed when a computer is ready for them. It is currently implemented with Amazon's AWS cloud systems, and can scale from zero to many computers, with jobs being processed faster when more servers are available. Central to the bookpipeline in terms of software is the bookpipeline command, which is part of the rescribe.xyz/bookpipeline package. Presuming you have the go tools installed, you can install it, and useful tools to control the system, with this command: All of the tools provided in the bookpipeline package will give information on what they do and how they work with the '-h' flag, so for example to get usage information on the booktopipeline tool simply run the following: To get the pipeline tools to work for you, you'll need to change the settings in cloudsettings.go, and set up your ~/.aws/credentials appropriately. Most of the time the bookpipeline is expected to be run from potentially short-lived servers on Amazon's EC2 system. EC2 provides servers which have no guaranteed of stability (though in practice they seem to be), called "Spot Instances", which we use for bookpipeline. bookpipeline can handle a process or server being suddenly destroyed without warning (more on this later), so Spot Instances are perfect for us. We have set up a machine image with bookpipeline preinstalled which will launch at bootup, which is all that's needed to launch an bookpipeline instance. Presuming the bookpipeline package has been installed on your computer (see above), the spot instance can be started with the command: You can keep an eye on the servers (spot or otherwise) that are running, and the jobs left to do and in progress, with the "lspipeline" tool (which is also part of the bookpipeline package). It's recommended to use this with the ssh private key for the servers, so that it can also report on what each server is currently doing, but it can run successfully without it. It takes a little while to run, so be patient. It can be run with the command: Spot instances can be terminated with ssh, using their ip address which can be found with lspipeline, like so: The bookpipeline program is run as a service managed by systemd on the servers. The system is fully resiliant in the face of unexpected failures. See the section "How the pipeline works" for details on this. bookpipeline can be managed like any other systemd service. A few examples: Books can be added to the pipeline using the "booktopipeline" tool. This takes a directory of page images as input, and uploads them all to S3, adding a job to the pipeline queue to start processing them. So it can be used like this: Once a book has been finished, it can be downloaded using the "getpipelinebook" tool. This has several options to download specific parts of a book, but the default case will download the best hOCR for each page, PDFs, and the best, conf and graph.png files. Use it like this: To get the plain text from the book, use the hocrtotxt tool, which is part of the rescribe.xyz/utils package. You can get the package, and run the tool, like this: The central part of the book pipeline is several SQS queues, which contain jobs which need to be done by a server running bookpipeline. The exact content of the SQS messages vary according to each queue, as some jobs need more information than others. Each queue is checked at least once every couple of minutes on any server that isn't currently processing a job. When a job is taken from the queue by a process, it is hidden from the queue for 2 minutes so that no other process can take it. Once per minute when processing a job the process sends a message updating the queue, to tell it to keep the job hidden for two minutes. This is called the "heartbeat", as if the process fails for any reason the heartbeat will stop, and in 2 minutes the job will reappear on the queue for another process to have a go at. Once a job is completed successfully it is deleted from the queue. Queue names are defined in cloudsettings.go. queuePreProc Each message in the queuePreProc queue is a bookname, optionally followed by a space and the name of the training to use. Each page of the bookname will be binarised with several different parameters, and then wiped, with each version uploaded to S3, with the path of the preprocessed page, plus the training name if it was provided, will be added to the queueOcrPage queue. The pages are binarised with different parameters as it can be difficult to determine which binarisation level will be best prior to OCR, so several different options are used, and in the queueAnalyse step the best one is chosen, based on the confidence of the OCR output. queueWipeOnly This queue works the same as queuePreProc, except that it doesn't binarise the pages, only runs the wiper. Hence it is designed for books which have been prebinarised. queuePreNoWipe This queue works the same as queuePreProc, except that it doesn'T wipe the pages, only runs the binarisation. It is designed for books which don't have tricky gutters or similar noise around the edges, but do have marginal content which might be inadventently removed by the wiper. queueOcrPage This queue contains the path of individual pages, optionally followed by a space and the name of the training to use. Each page is OCRed, and the results are uploaded to S3. After each page is OCRed, a check is made to see whether all pages that look like they were preprocessed have corresponding .hocr files. If so, the bookname is added to the queueAnalyse queue. queueAnalyse A message on the queueAnalyse queue contains only a book name. The confidences for each page are calculated and saved in the 'conf' file, and the best version of each page is decided upon and saved in the 'best' file. PDFs are then generated, and the confidence graph is generated. The queues should generally only be messed with by the bookpipeline and booktopipeline tools, but if you're feeling ambitious you can take a look at the `addtoqueue` tool. Remember that messages in a queue are hidden for a few minutes when they are read, so for example you couldn't straightforwardly delete a message which was currently being processed by a server, as you wouldn't be able to see it. At present the bookpipeline has some silly limitations of file names for book pages to be recognised. This is something which will be fixed in due course. While bookpipeline was built with cloud based operation in mind, there is also a local mode that can be used to run OCR jobs from a single computer, with all the benefits of preprocessing, choosing the best threshold for each image, graph creation, PDF creation, and so on that the pipeline provides. Several of the commands accept a `-c local` flag for local operation, but now there is also a new command, named rescribe, that is designed to make things much simpler for people just wanting to do some OCR on their local computer. Note that the local mode is not as well tested as the core cloud modes; please report any bugs you find with it.

Package captcha implements generation and verification of image and audio CAPTCHAs. A captcha solution is the sequence of digits 0-9 with the defined length. There are two captcha representations: image and audio. An image representation is a PNG-encoded image with the solution printed on it in such a way that makes it hard for computers to solve it using OCR. An audio representation is a WAVE-encoded (8 kHz unsigned 8-bit) sound with the spoken solution (currently in English, Russian, Chinese, and Japanese). To make it hard for computers to solve audio captcha, the voice that pronounces numbers has random speed and pitch, and there is a randomly generated background noise mixed into the sound. This package doesn't require external files or libraries to generate captcha representations; it is self-contained. To make captchas one-time, the package includes a memory storage that stores captcha ids, their solutions, and expiration time. Used captchas are removed from the store immediately after calling Verify or VerifyString, while unused captchas (user loaded a page with captcha, but didn't submit the form) are collected automatically after the predefined expiration time. Developers can also provide custom store (for example, which saves captcha ids and solutions in database) by implementing Store interface and registering the object with SetCustomStore. Captchas are created by calling New, which returns the captcha id. Their representations, though, are created on-the-fly by calling WriteImage or WriteAudio functions. Created representations are not stored anywhere, but subsequent calls to these functions with the same id will write the same captcha solution. Reload function will create a new different solution for the provided captcha, allowing users to "reload" captcha if they can't solve the displayed one without reloading the whole page. Verify and VerifyString are used to verify that the given solution is the right one for the given captcha id. Server provides an http.Handler which can serve image and audio representations of captchas automatically from the URL. It can also be used to reload captchas. Refer to Server function documentation for details, or take a look at the example in "capexample" subdirectory.

Package grab provides a HTTP download manager implementation. Get is the most simple way to download a file: Get will download the given URL and save it to the given destination directory. The destination filename will be determined automatically by grab using Content-Disposition headers returned by the remote server, or by inspecting the requested URL path. An empty destination string or "." means the transfer will be stored in the current working directory. If a destination file already exists, grab will assume it is a complete or partially complete download of the requested file. If the remote server supports resuming interrupted downloads, grab will resume downloading from the end of the partial file. If the server does not support resumed downloads, the file will be retransferred in its entirety. If the file is already complete, grab will return successfully. For control over the HTTP client, destination path, auto-resume, checksum validation and other settings, create a Client: You can monitor the progress of downloads while they are transferring:

Package protokit is a library that makes it easy to create your own protoc plugins. It has excellent test coverage, and saves you so much time! There are two main things this library provides; a parser for parsing protobuf files into some well-defined structs, and an abstraction to make it simple to write your own protoc plugins. For a quick view of how to get started, see https://godoc.org/github.com/pseudomuto/protokit#example-RunPlugin If you want see/try a working example, check out the examples in https://github.com/pseudomuto/protokit/tree/master/examples.

Package grpcreplay supports the capture and replay of gRPC calls. Its main goal is to improve testing. Once you capture the calls of a test that runs against a real service, you have an "automatic mock" that can be replayed against the same test, yielding a unit test that is fast and flake-free. To record a sequence of gRPC calls to a file, create a Recorder and pass its DialOptions to grpc.Dial: It is essential to close the Recorder when the interaction is finished. There is also a NewRecorderWriter function for capturing to an arbitrary io.Writer. To replay a captured file, create a Replayer and ask it for a (fake) connection. We don't actually have to dial a server. (Since we're reading the file and not writing it, we don't have to be as careful about the error returned from Close). A test might use random or time-sensitive values, for instance to create unique resources for isolation from other tests. The test therefore has initial values, such as the current time, or a random seed, that differ from run to run. You must record this initial state and re-establish it on replay. To record the initial state, serialize it into a []byte and pass it as the second argument to NewRecorder: On replay, get the bytes from Replayer.Initial: Recorders and replayers have support for running callbacks before messages are written to or read from the replay file. A Recorder has a BeforeFunc that can modify a request or response before it is written to the replay file. The actual RPCs sent to the service during recording remain unaltered; only what is saved in the replay file can be changed. A Replayer has a BeforeFunc that can modify a request before it is sent for matching. Example uses for these callbacks include customized logging, or scrubbing data before RPCs are written to the replay file. If requests are modified by the callbacks during recording, it is important to perform the same modifications to the requests when replaying, or RPC matching on replay will fail. A common way to analyze and modify the various messages is to use a type switch. A nondeterministic program may invoke RPCs in a different order each time it is run. The order in which RPCs are called during recording may differ from the order during replay. The replayer matches incoming to recorded requests by method name and request contents, so nondeterminism is only a concern for identical requests that result in different responses. A nondeterministic program whose behavior differs depending on the order of such RPCs probably has a race condition: since both the recorded sequence of RPCs and the sequence during replay are valid orderings, the program should behave the same under both. The same is not true of streaming RPCs. The replayer matches streams only by method name, since it has no other information at the time the stream is opened. Two streams with the same method name that are started concurrently may replay in the wrong order. Besides the differences in replay mentioned above, other differences may cause issues for some programs. We list them here. The Replayer delivers a response to an RPC immediately, without waiting for other incoming RPCs. This can violate causality. For example, in a Pub/Sub program where one goroutine publishes and another subscribes, during replay the Subscribe call may finish before the Publish call begins. For streaming RPCs, the Replayer delivers the result of Send and Recv calls in the order they were recorded. No attempt is made to match message contents. At present, this package does not record or replay stream headers and trailers, or the result of the CloseSend method.

Command csvsplit splits a .csv into multiple, smaller files. Resulting files will be saved as 1.csv, 2.csv, etc. in the currect directory, unless the -output flag is used. Requires Go to be installed first, https://golang.org/doc/install. Basic usage: csvsplit -records <number of records> <file> Number of records per file Output filename / path (optional) Number of header lines in the input file to add to each ouput file (optional, default=0) Split file.csv into files with 300 records a piece. Accept csv data from stdin. Split file.csv into files with 40 records a piece and two header lines (preserved in all files). You can use the -output flag to customize the resulting filenames. The below will generate custom_filename-001.csv, custom_filename-002.csv, etc.. Split file.csv into files with 37 records a piece into the subfolder 'stuff'.

CompileDaemon is a very simple compile daemon for Go. CompileDaemon watches your .go files in a directory and invokes `go build` if a file changes. In its simplest form, the defaults will do. With the current working directory set to the source directory you can simply… … and it will recompile your code whenever you save a source file. If you want it to also run your program each time it builds you might add… … and it will also keep a copy of your program running. Killing the old one and starting a new one each time you build. For advanced usage you can also supply the changed file to the command by doing… …but note that this will not be set on the first start. You may find that you need to exclude some directories and files from monitoring, such as a .git repository or emacs temporary files… If you want to monitor files other than .go and .c files you might… There are command line options.

Extensible Go library for creating fast, SSR-first frontend avoiding vanilla templating downsides. Creating asynchronous and dynamic layout parts is a complex problem for larger projects using `html/template`. Library tries to simplify this process. Let's go straight into a simple example. Then, we will dig into details, step by step, how it works. Kyoto provides a simple net/http handlers and function wrappers to handle pages rendering and serving. See functions inside of nethttp.go file for details and advanced usage. Example: Kyoto provides a way to define components. It's a very common approach for modern libraries to manage frontend parts. In kyoto each component is a context receiver, which returns it's state. Each component becomes a part of the page or top-level component, which executes component asynchronously and gets a state future object. In that way your components are executing in a non-blocking way. Pages are just top-level components, where you can configure rendering and page related stuff. Example: As an option, you can wrap component with another function to accept additional paramenters from top-level page/component. Example: Kyoto provides a context, which holds common objects like http.ResponseWriter, *http.Request, etc. See kyoto.Context for details. Example: Kyoto provides a set of parameters and functions to provide a comfortable template building process. You can configure template building parameters with kyoto.TemplateConf configuration. See template.go for available functions and kyoto.TemplateConfiguration for configuration details. Example: Kyoto provides a way to simplify building dynamic UIs. For this purpose it has a feature named actions. Logic is pretty simple. Client calls an action (sends a request to the server). Action is executing on server side and server is sending updated component markup to the client which will be morphed into DOM. That's it. To use actions, you need to go through a few steps. You'll need to include a client into page (JS functions for communication) and register an actions handler for a needed component. Let's start from including a client. Then, let's register an actions handler for a needed component. That's all! Now we ready to use actions to provide a dynamic UI. Example: In this example you can see provided modifications to the quick start example. First, we've added a state and name into our components' markup. In this way we are saving our components' state between actions and find a component root. Unfortunately, we have to manually provide a component name for now, we haven't found a way to provide it dynamically. Second, we've added a reload button with onclick function call. We're using a function Action provided by a client. Action triggering will be described in details later. Third, we've added an action handler inside of our component. This handler will be executed when a client calls an action with a corresponding name. It's highly recommended to keep components' state as small as possible. It will be transmitted on each action call. Kyoto have multiple ways to trigger actions. Now we will check them one by one. This is the simplest way to trigger an action. It's just a function call with a referer (usually 'this', f.e. button) as a first argument (used to determine root), action name as a second argument and arguments as a rest. Arguments must to be JSON serializable. It's possible to trigger an action of another component. If you want to call an action of parent component, use $ prefix in action name. If you want to call an action of component by id, use <id:action> as an action name. This is a specific action which is triggered when a form is submitted. Usually called in onsubmit="..." attribute of a form. You'll need to implement 'Submit' action to handle this trigger. This is a special HTML attribute which will trigger an action on page load. This may be useful for components' lazy loading. With this special HTML attributes you can trigger an action with interval. Useful for components that must to be updated over time (f.e. charts, stats, etc). You can use this trigger with ssa:poll and ssa:poll.interval HTML attributes. This one attribute allows you to trigger an action when an element is visible on the screen. May be useful for lazy loading. Kyoto provides a way to control action flow. For now, it's possible to control display style on component call and push multiple UI updates to the client during a single action. Because kyoto makes a roundtrip to the server every time an action is triggered on the page, there are cases where the page may not react immediately to a user event (like a click). That's why the library provides a way to easily control display attributes on action call. You can use this HTML attribute to control display during action call. At the end of an action the layout will be restored. A small note. Don't forget to set a default display for loading elements like spinners and loaders. You can push multiple component UI updates during a single action call. Just call kyoto.ActionFlush(ctx, state) to initiate an update. Kyoto provides a way to control action rendering. Now there is at least 2 rendering options after an action call: morph (default) and replace. Morph will try to morph received markup to the current one with morphdom library. In case of an error, or explicit "replace" mode, markup will be replaced with x.outerHTML = '...'.

Ardi is a command-line tool for compiling, uploading, and watching logs for your usb connected arduino board. Ardi allows you to develop in an environment you feel comfortable, without being forced to use arduino's web or desktop IDEs. Ardi's "--watch" flag allows you to auto re-compile and upload on save, saving you time and improving efficiency. Ardi should work for all boards and platforms supported by arduino-cli. Run "ardi init" to download all supported platforms and index files to ensure maximum board support. To initialize only for a specific platform, run "ardi init <platform_id>" or "ardi init <platform_id@version>". To see a list of supported platforms and associated IDs, run "ardi platform list". To see a list of all supported boards and their associated platforms and fqbns run "ardi board list". (Note board fqbn will only be filled in once platform is initialized) Once initialized run "ardi go <sketch_dir> --watch --verbose" and ardi will try to auto detect your board, compile your sketch, upload, watch for changes in your sketch file, and re-compile and re-upload. You can also run, "ardi compile <sketch_directory> --fqbn <board_fqbn>" to only compile and skip uploading. Ardi also includes a basic library manager. Run "ardi lib init" in your project directory to initialize it as an ardi project directory. Once initialized, you can use "ardi lib add <lib_name>" to add libraries, "ardi lib remove <lib_name>", "ardi lib install" to install missing libraries defined in ardi.json, and "ardi lib search <searchFilter>" to search existing libraries. Ardi stores all its platform data in "~/.ardi/" to avoid any conflicts with existing "arduino-cli" installations. Usage: Available Commands: Flags: Use "ardi [command] --help" for more information about a command.

A dynamic and extensible music library organizer Demlo is a music library organizer. It can encode, fix case, change folder hierarchy according to tags or file properties, tag from an online database, copy covers while ignoring duplicates or those below a quality threshold, and much more. It makes it possible to manage your libraries uniformly and dynamically. You can write your own rules to fit your needs best. Demlo aims at being as lightweight and portable as possible. Its major runtime dependency is the transcoder FFmpeg. The scripts are written in Lua for portability and speed while allowing virtually unlimited extensibility. Usage: For usage options, see: First Demlo creates a list of all input files. When a folder is specified, all files matching the extensions from the 'extensions' variable will be appended to the list. Identical files are appended only once. Next all files get analyzed: - The audio file details (tags, stream properties, format properties, etc.) are stored into the 'input' variable. The 'output' variable gets its default values from 'input', or from an index file if specified from command-line. If no index has been specified and if an attached cuesheet is found, all cuesheet details are appended accordingly. Cuesheet tags override stream tags, which override format tags. Finally, still without index, tags can be retrieved from Internet if the command-line option is set. - If a prescript has been specified, it gets executed. It makes it possible to adjust the input values and global variables before running the other scripts. - The scripts, if any, get executed in the lexicographic order of their basename. The 'output' variable is transformed accordingly. Scripts may contain rules such as defining a new file name, new tags, new encoding properties, etc. You can use conditions on input values to set the output properties, which makes it virtually possible to process a full music library in one single run. - If a postscript has been specified, it gets executed. It makes it possible to adjust the output of the script for the current run only. - Demlo makes some last-minute tweaking if need be: it adjusts the bitrate, the path, the encoding parameters, and so on. - A preview of changes is displayed. - When applying changes, the covers get copied if required and the audio file gets processed: tags are modified as specified, the file is re-encoded if required, and the output is written to the appropriate folder. When destination already exists, the 'exist' action is executed. The program's default behaviour can be changed from the user configuration file. (See the 'Files' section for a template.) Most command-line flags default value can be changed. The configuration file is loaded on startup, before parsing the command-line options. Review the default value of the CLI flags with 'demlo -h'. If you wish to use no configuration file, set the environment variable DEMLORC to ".". Scripts can contain any safe Lua code. Some functions like 'os.execute' are not available for security reasons. It is not possible to print to the standard output/error unless running in debug mode and using the 'debug' function. See the 'sandbox.go' file for a list of allowed functions and variables. Lua patterns are replaced by Go regexps. See https://github.com/google/re2/wiki/Syntax. Scripts have no requirements at all. However, to be useful, they should set values of the 'output' table detailed in the 'Variables' section. You can use the full power of the Lua to set the variables dynamically. For instance: 'input' and 'output' are both accessible from any script. All default functions and variables (excluding 'output') are reset on every script call to enforce consistency. Local variables are lost from one script call to another. Global variables are preserved. Use this feature to pass data like options or new functions. 'output' structure consistency is guaranteed at the start of every script. Demlo will only extract the fields with the right type as described in the 'Variables' section. Warning: Do not abuse of global variables, especially when processing non-fixed size data (e.g. tables). Data could grow big and slow down the program. By default, when the destination exists, Demlo will append a suffix to the output destination. This behaviour can be changed from the 'exist' action specified by the user. Demlo comes with a few default actions. The 'exist' action works just like scripts with the following differences: - Any change to 'output.path' will be skipped. - An additional variable is accessible from the action: 'existinfo' holds the file details of the existing files in the same fashion as 'input'. This allows for comparing the input file and the existing destination. The writing rules can be tweaked the following way: Word of caution: overwriting breaks Demlo's rule of not altering existing files. It can lead to undesired results if the overwritten file is also part of the (yet to be processed) input. The overwrite capability can be useful when syncing music libraries however. The user scripts should be generic. Therefore they may not properly handle some uncommon input values. Tweak the input with temporary overrides from command-line. The prescript and postscript defined on command-line will let you run arbitrary code that is run before and after all other scripts, respectively. Use global variables to transfer data and parameters along. If the prescript and postscript end up being too long, consider writing a demlo script. You can also define shell aliases or use wrapper scripts as convenience. The 'input' table describes the file: Bitrate is in bits per seconds (bps). That is, for 320 kbps you would specify The 'time' is the modification time of the file. It holds the sec seconds and nsec nanoseconds since January 1, 1970 UTC. The entry 'streams' and 'format' are as returned by It gives access to most metadata that FFmpeg can return. For instance, to get the duration of the track in seconds, query the variable 'input.format.duration'. Since there may be more than one stream (covers, other data), the first audio stream is assumed to be the music stream. For convenience, the index of the music stream is stored in 'audioindex'. The tags returned by FFmpeg are found in streams, format and in the cuesheet. To make tag queries easier, all tags are stored in the 'tags' table, with the following precedence: You can remove a tag by setting it to 'nil' or the empty string. This is equivalent, except that 'nil' saves some memory during the process. The 'output' table describes the transformation to apply to the file: The 'parameters' array holds the CLI parameters passed to FFmpeg. It can be anything supported by FFmpeg, although this variable is supposed to hold encoding information. See the 'Examples' section. The 'embeddedcovers', 'externalcovers' and 'onlinecover' variables are detailed in the 'Covers' section. The 'write' variable is covered in the 'Existing destination' section. The 'rmsrc' variable is a boolean: when true, Demlo removes the source file after processing. This can speed up the process when not re-encoding. This option is ignored for multi-track files. For convenience, the following shortcuts are provided: Demlo provides some non-standard Lua functions to ease scripting. Display a message on stderr if debug mode is on. Return lowercase string without non-alphanumeric characters nor leading zeros. Return the relation coefficient of the two input strings. The result is a float in 0.0...1.0, 0.0 means no relation at all, 1.0 means identical strings. A format is a container in FFmpeg's terminology. 'output.parameters' contains CLI flags passed to FFmpeg. They are meant to set the stream codec, the bitrate, etc. If 'output.parameters' is {'-c:a', 'copy'} and the format is identical, then taglib will be used instead of FFmpeg. Use this rule from a (post)script to disable encoding by setting the same format and the copy parameters. This speeds up the process. The official scripts are usually very smart at guessing the right values. They might make mistakes however. If you are unsure, you can (and you are advised to) preview the results before proceeding. The 'diff' preview is printed to stderr. A JSON preview of the changes is printed to stdout if stdout is redirected. The initial values of the 'output' table can be completed with tags fetched from the MusicBrainz database. Audio files are fingerprinted for the queries, so even with initially wrong file names and tags, the right values should still be retrieved. The front album cover can also be retrieved. Proxy parameters will be fetched automatically from the 'http_proxy' and 'https_proxy' environment variables. As this process requires network access it can be quite slow. Nevertheless, Demlo is specifically optimized for albums, so that network queries are used for only one track per album, when possible. Some tracks can be released on different albums: Demlo tries to guess it from the tags, but if the tags are wrong there is no way to know which one it is. There is a case where the selection can be controlled: let's assume we have tracks A, B and C from the same album Z. A and B were also released in album Y, whereas C was release in Z only. Tags for A will be checked online; let's assume it gets tagged to album Y. B will use A details, so album Y too. Then C does not match neither A's nor B's album, so another online query will be made and it will be tagged to album Z. This is slow and does not yield the expected result. Now let's call Tags for C will be queried online, and C will be tagged to Z. Then both A and B will match album Z so they will be tagged using C details, which is the desired result. Conclusion: when using online tagging, the first argument should be the lesser known track of the album. Demlo can set the output variables according to the values set in a text file before calling the script. The input values are ignored as well as online tagging, but it is still possible to access the input table from scripts. This 'index' file is formatted in JSON. It corresponds to what Demlo outputs when printing the JSON preview. This is valid JSON except for the missing beginning and the missing end. It makes it possible to concatenate and to append to existing index files. Demlo will automatically complete the missing parts so that it becomes valid JSON. The index file is useful when you want to edit tags manually: You can redirect the output to a file, edit the content manually with your favorite text editor, then run Demlo again with the index as argument. See the 'Examples' section. This feature can also be used to interface Demlo with other programs. Demlo can manage embedded covers as well as external covers. External covers are queried from files matching known extensions in the file's folder. Embedded covers are queried from static video streams in the file. Covers are accessed from The embedded covers are indexed numerically by order of appearance in the streams. The first cover will be at index 1 and so on. This is not necessarily the index of the stream. 'inputcover' is the following structure: 'format' is the picture format. FFmpeg makes a distinction between format and codec, but it is not useful for covers. The name of the format is specified by Demlo, not by FFmpeg. Hence the 'jpeg' name, instead of 'mjpeg' as FFmpeg puts it. 'width' and 'height' hold the size in pixels. 'checksum' can be used to identify files uniquely. For performance reasons, only a partial checksum is performed. This variable is typically used for skipping duplicates. Cover transformations are specified in 'outputcover' has the following structure: The format is specified by FFmpeg this time. See the comments on 'format' for 'inputcover'. 'parameters' is used in the same fashion as 'output.parameters'. User configuration: This must be a Lua file. See the 'demlorc' file provided with this package for an exhaustive list of options. Folder containing the official scripts: User script folder: Create this folder and add your own scripts inside. This folder takes precedence over the system folder, so scripts with the same name will be found in the user folder first. The following examples will not proceed unless the '-p' command-line option is true. Important: you _must_ use single quotes for the runtime Lua command to prevent expansion. Inside the Lua code, use double quotes for strings and escape single quotes. Show default options: Preview changes made by the default scripts: Use 'alternate' script if found in user or system script folder (user folder first): Add the Lua file to the list of scripts. This feature is convenient if you want to write scripts that are too complex to fit on the command-line, but not generic enough to fit the user or system script folders. Remove all script from the list, then add '30-case' and '60-path' scripts. Note that '30-case' will be run before '60-path'. Do not use any script but '60-path'. The file content is unchanged and the file is renamed to a dynamically computed destination. Demlo performs an instant rename if destination is on the same device. Otherwise it copies the file and removes the source. Use the default scripts (if set in configuration file), but do not re-encode: Set 'artist' to the value of 'composer', and 'title' to be preceded by the new value of 'artist', then apply the default script. Do not re-encode. Order in runtime script matters. Mind the double quotes. Set track number to first number in input file name: Use the default scripts but keep original value for the 'artist' tag: 1) Preview default scripts transformation and save it to an index. 2) Edit file to fix any potential mistake. 3) Run Demlo over the same files using the index information only. Same as above but generate output filename according to the custom '61-rename' script. The numeric prefix is important: it ensures that '61-rename' will be run after all the default tag related scripts and after '60-path'. Otherwise, if a change in tags would occur later on, it would not affect the renaming script. Retrieve tags from Internet: Same as above but for a whole album, and saving the result to an index: Only download the cover for the album corresponding to the track. Use 'rmsrc' to avoid duplicating the audio file. Change tags inplace with entries from MusicBrainz: Set tags to titlecase while casing AC-DC correctly: To easily switch between formats from command-line, create one script per format (see 50-encoding.lua), e.g. ogg.lua and flac.lua. Then Add support for non-default formats from CLI: Overwrite existing destination if input is newer: ffmpeg(1), ffprobe(1), http://www.lua.org/pil/contents.html

Overview Monresql is a specialized library designed to facilitate efficient data replication, transfer, and synchronization from MongoDB to PostgreSQL databases. Inspired by similar tools like Moresql, Monresql focuses on unidirectional data movement, ensuring seamless integration and synchronization between MongoDB documents and PostgreSQL tables. Key Features Data Replication: Efficiently replicate data from MongoDB collections to corresponding PostgreSQL tables. Incremental Updates: Support for incremental updates to keep PostgreSQL data up-to-date without full data reloads. Performance Optimization: Optimizes data transfer processes for minimal latency and optimal resource utilization. API Reference LoadFieldsMap() Loads a mapping file to define how MongoDB documents should be mapped to PostgreSQL tables. ValidateOrCreatePostgresTable() Validates the existence of a PostgreSQL table to ensure it's ready for data replication. Replicate() Initiates the data replication process from MongoDB to PostgreSQL based on the loaded mapping. Sync() Starts the synchronization process, ensuring that changes in MongoDB are reflected in PostgreSQL in real-time and also save the marker to sync from the last stopped mark if the service stopped NewSyncOptions() NewSyncOptions will return the pointer of the syncoptions struct with default values of &syncOptions{checkpoint: true, checkPointPeriod: time.Minute * 1, lastEpoch: 0, reportPeriod: time.Minute * 1} then you can edit and change the values by set methods

**Please use xcore/v2** **The version 1 is obsolete.** Package xcore is a set of basic objects for programation (XCache for caches, XDataset for data sets, XLanguage for languages and XTemplate for templates). For GO, the actual existing code includes: - XCache: Application Memory Caches for any purpose, with time control and quantity control of object in the cache and also check changes against original source. It is a thread safe cache. - XDataset: Basic nested data structures for any purpose (template injection, configuration files, database records, etc). - XLanguage: language dependent text tables for internationalization of code. The sources can be text or XML file definitions. - XTemplate: template system with meta language to create complex documents (compatible with any text language, HTML, CSS, JS, PDF, XML, etc), heavily used on CMS systems and others. It is already used on sites that serve more than 60 million pages a month (500 pages per second on pike hour) and can be used on multithreading environment safely. XCache is a library to cache all the data you want into current application memory for a very fast access to the data. The access to the data support multithreading and concurrency. For the same reason, this type of cache is not persistent (if you exit the application) and cannot grow too much (as memory is the limit). However, you can control a timeout of each cache piece, and eventually a comparison function against a source (file, database, etc) to invalid the cache. 1. Declare a new XCache with NewXCache() function: 2. Fill in the cache: Once you have declared the cache, you can fill it with anything you want. The main cache object is an interface{} so you can put here anything you need, from simple variables to complex structures. You need to use the Set function: Note the ID is always a string, so convert a database key to string if needed. 3. To use the cache, just ask for your entry with Get function: 4. To maintain the cache: You may need Del function, to delete a specific entry (maybe because you deleted the record in database). You may also need Clean function to deletes a percentage of the cache, or Flush to deletes it all. The Verify function is used to check cache entries against their sources through the Validator function. Be very careful, if the cache is big or the Validator function is complex (maybe ask for a remote server information), the verification may be VERY slow and huge CPU use. The Count function gives some stats about the cache. 5. How to use Verify Function: This function is recommended when the source is local and fast to check (for instance a language file or a template file). When the source is distant (other cluster database, any rpc source on another network, integration of many parts, etc), it is more recommended to create a function that will delete the cache when needed (on demand cache change). The validator function is a func(id, time.Time) bool function. The first parameter is the ID entry in the cache, the second parameter the time of the entry was created. The validator function returns true is the cache is still valid, or false if it needs to be invalidated. The XCache is thread safe. The cache can be limited in quantity of entries and timeout for data. The cache is automanaged (for invalid expired data) and can be cleaned partially or totally manually. The XLanguage table of text entries can be loaded from XML file, XML string or normal text file or string. It is used to keep a table of id=value set of entries in any languages you need, so it is easy to switch between XLanguage instance based on the required language needed. Obviously, any XLanguage you load in any language should have the same id entries translated, for the same use. 1. loading: You can load any file or XML string directly into the object. 1.1 The XML Format is: NAMEOFTABLE is the name of your table entry, for example "loginform", "user_report", etc. LG is the ISO-3369 2 letters language ID, for example "es" for spanish, "en" for english, "fr" for french, etc. ENTRYNAME is the ID of the entry, for example "greating", "yourname", "submitbutton". ENTRYVALUE is the text for your entry, for example "Hello", "You are:", "Save" if your table is in english. 1.2 The flat text format is: ENTRYNAME is the ID of the entry, for example "greating", "yourname", "submitbutton". ENTRYVALUE is the text for your entry, for example "Hello", "You are:", "Save" if your table is in english. There is no name of table or language in this format (you "know" what you are loading). The advantage to use XML format is to have more control over your language, and eventyally add attributes into your entries, for instance you may add attributes translated="yes/no", verified="yes/no", and any other data that your system could insert. The XLanguage will ignore those attributes loading the table. 2. creation: To create a new XLanguage empty structure: There are 4 functions to create the language from a file or string, flat text or XML text: Then you can use the set of basic access functions: SetName/SetLanguage functions are used to set the table name and language of the object (generally to build an object from scratch). GetName/GetLanguage functions are used to get the table name and language of the object (generally when you load it from some source). Set/Get/Del functions are used to add or modify a new entry, read an entry, or deletes an entry in the object. 1. Overview: The XDataSet is a set of interfaces and basic classes ready-to-use to build a standard set of data optionally nested and hierarchical, that can be used for any purpose: - Keep complex data in memory. - Create JSON structures. - Inject data into templates. - Interchange database data (records set and record). You can store into it generic supported data, as well as any complex interface structures: - Int - Float - String - Time - Bool - []Int - []Float - []Time - []Bool - XDataSetDef (anything extended with this interface) - []String - Anything else ( interface{} ) - XDataSetCollectionDef (anything extended with this interface) The generic supported data comes with a set of functions to get/set those data directly into the XDataset. Example: Note that all references to XDataset and XDatasetCollection are pointers, always (to be able to modify the values of them). 2. XDatasetDef interface: It is the interface to describe a simple set of data mapped as "name": value, where value can be of any type. The interface implements a good amount of basic methods to get the value on various format such as GetString("name"), GetInt("name"), etc (see below). If the value is another type as asked, the method should contert it if possible. For instance "key":123 required through GetString("key") should return "123". The XDataset type is a simple map[string]interface{} with all the implemented methods and should be enough to use for almost all required cases. However, you can build any complex structure that extends the interface and implements all the required functions to stay compatible with the XDatasetDef. 3. XDatasetCollectionDef Interface: This is the interface used to extend any type of data as a Collection, i-e an array of XDatasetDef. This is a slice of any XDatasetDef compatible data. The interface implements some methods to work on array structure such as Push, Pop, Shift, Unshift and some methods to search data into the array. The XDatasetCollection type is a simple []DatasetDef with all the implemented methods and should be enough to use for almost all required cases. 1. Overview: This is a class to compile and keep a Template that can be injected with an XDataSet structure of data, with a metalanguage to inject the data. The metalanguage is extremely simple and is made to be useful and **really** separate programation from template code (not like other many generic template systems that just mix code and data). A template is a set of HTML/XML (or any other language) string with a meta language to inject variables and build a final string. The XCore XTemplate system is based on the injection of parameters, language translation strings and data fields directly into the HTML (Or any other language you need) template. The HTML itself (or any other language) is a text code not directly used by the template system, but used to dress the data you want to represent in your preferred language. The variables to inject must be into a XDataSet structure or into a structure extended from XDataSetDef interface. The injection of data is based on a XDataSet structure of values that can be nested into another XDataSet and XDataSetConnection and so on. The template compiler recognize nested arrays to automatically make loops on the information. Templates are made to store reusable HTML code, and overall easily changeable by people that do not know how to write programs. A template can be as simple as a single character (no variables to inject) to a very complex nested, conditional and loops sub-templates. Yes. this is a template, but a very simple one without need to inject any data. Let's go more complex: Having an array of data, we want to paint it beautifull: We can create a template to inject this data into it: 2. Create and use XTemplateData: In sight to create and use templates, you have all those possible options to use: Creates the XTemplate from a string or a file or any other source: 3. Metalanguage Reference: 3.1 Comments: %-- and --% You may use comments into your template. The comments will be discarded immediately at the compilation of the template and do not interfere with the rest of your code. Example: 3.2 Nested Templates: [[...]] and [[]] You can define new nested templates into your main template A nested template is defined by: The templteid is any combination of lowers letters only (a-z), numbers (0-9), and 3 special chars: . (point) - (dash) and _ (underline). The template is closed with [[]]. There is no limits into nesting templates. Any nested template will inheritate all the father elements and can use father elements too. To call a sub-template, you need to use &&templateid&& syntax (described below in this document). Example: You may use more than one id into the same template to avoid repetition of the same code. The different id's are separated with a pipe | Important note: A template will be visible only on the same level of its declaration. For example, if you put a subtemplate "b" into a subtemplate "a", it will not be visible by &&b&& from the top level, but only into the subtemplate "a". 3.3 Simple Elements: ##...## and {{...}} There are 2 types of simple elements. Language elements and Data injector elements (also called field elements). We "logically" define the 2 type of elements. The separation is only for human logic and template filling, however the language information can perfectly fit into the data to inject (and not use ## entries). 3.3.1 Languages elements: ##entry## All the languages elements should have the format: ##entry##. A language entry is generally anything written into your code or page that does not come from a database, and should adapt to the language of the client visiting your site. Using the languages elements may depend on the internationalization of your page. If your page is going to be in a single language forever, you really dont need to use languages entries. The language elements generally carry titles, menu options, tables headers etc. The language entries are set into the "#" entry of the main template XDataset to inject, and is a XLanguage table. Example: With data to inject: 3.3.2 Field elements: {{fieldname}} Fields values should have the format: {{fieldname}}. Your fields source can be a database or any other preferred repository data source. Example: You can access an element with its path into the data set to inject separating each field level with a > (greater than). This will take the name of the second hobby in the dataset defined upper. (collections are 0 indexed). The 1 denotes the second record of the hobbies XDatasetCollection. If the field is not found, it will be replaced with an empty string. Tecnically your field names can be any string in the dataset. However do not use { } or > into the names of your fields or the XTemplate may not use them correctly. We recommend to use lowercase names with numbers and ._- Accents and UTF8 symbols are also welcome. 3.3.3 Scope: When you use an id to point a value, the template will first search into the available ids of the local level. If no id is found, the it will search into the upper levers if any, and so on. Example: At the level of 'data2', using {{appname}} will get back 'DomCore'. At the level of 'key1', using {{appname}} will get back 'Nested App'. At the level of 'key2', using {{appname}} will get back 'DomCore'. At the level of root, 'data1' or 'detail', using {{appname}} will get back an empty string. 3.3.4 Path access: id>id>id>id At any level into the data array, you can access any entry into the subset array. For instance, taking the previous array of data to inject, let's suppose we are into a nested meta elements at the 'data1' level. You may want to access directly the 'Juan' entry. The path will be: The José's status value from the root will be: 3.4 Meta Elements They consist into an injection of a XDataset, called the "data to inject", into the template. The meta language is directly applied on the structure of the data array. The data to inject is a nested set of variables and values with the structure you want (there is no specific construction rules). You can inject nearly anything into a template meta elements. Example of a data array to inject: You can access directly any data into the array with its relative path (relative to the level you are when the metaelements are applied, see below). There are 4 structured meta elements in the XTemplate templates to use the data to inject: Reference, Loops, Condition and Debug. The structure of the meta elements in the template must follow the structure of the data to inject. 3.4.1 References to another template: &&order&& 3.4.1.1 When order is a single id (characters a-z0-9.-_), it will make a call to a sub template with the same set of data and replace the &&...&& with the result. The level in the data set is not changed. Example based on previous array of Fred's data: 3.4.1.2 When order contains 2 parameters separated by a semicolumn :, then second parameter is used to change the level of the data of array, with the subset with this id. The level in the data set is changed to this sub set. Example based on previous array of Fred's data: 3.4.1.3 When order contains 3 parameters separated by a semicolumn :, the second and third parameters are used to search the name of the new template based on the data fields to inject. This is an indirect access to the template. The name of the subtemplate is build with parameter3 as prefix and the content of parameter2 value. The third parameter must be empty. 3.4.2 Loops: @@order@@ 3.4.2.1 Overview This meta element will loop over each itterance of the set of data and concatenate each created template in the same order. You need to declare a sub template for this element. You may aso declare derivated sub templates for the different possible cases of the loop: For instance, If your main subtemplate for your look is called "hobby", you may need a different template for the first element, last element, Nth element, Element with a value "no" in the sport field, etc. The supported postfixes are: When the array to iterate is empty: - .none (for example "There is no hobby") When the array contains elements, it will search in order, the following template and use the first found: - templateid.key.[value] value is the key of the vector line. If the collection has a named key (string) or is a direct array (0, 1, 2...) - templateid.first if it is the first element of the array set (new from v1.01.11) - templateid.last if it is the first element of the array set (new from v1.01.11) - templateid.even if the line number is even - templateid in all other cases (odd is contained here if even is defined) 3.4.2.2 When order is a single id (characters a-z0-9.-_), it will make a call to the sub template id with the same subset of data with the same id and replace the @@...@@ for each itterance of the data with the result. Example based on previous array of Fred's data: 3.4.2.3 When order contains 2 parameters separated by a semicolumn :, then first parameter is used to change the level of the data of array, with the subset with this id, and the second one for the template to use. Example based on previous array of Fred's data: 3.4.3 Conditional: ??order?? Makes a call to a subtemplate only if the field exists and have a value. This is very userfull to call a sub template for instance when an image or a video is set. When the condition is not met, it will search for the [id].none template. The conditional element does not change the level in the data set. 3.4.3.1 When order is a single id (characters a-z0-9.-_), it will make a call to the sub template id with the same field in the data and replace the ??...?? with the corresponding template Example based on previous array of Fred's data: 3.4.3.2 When order contains 2 parameters separated by a semicolumn :, then second parameter is used to change the level of the data of array, with the subset with this id. Example based on previous array of Fred's data: If the asked field is a catalog, true/false, numbered, you may also use .[value] subtemplates 3.5 Debug Tools: !!order!! There are two keywords to dump the content of the data set. This is very useful when you dont know the code that calls the template, don't remember some values, or for debug facilities. 3.5.1 !!dump!! Will show the totality of the data set, with ids and values. 3.5.1 !!list!! Will show only the tree of parameters, values are not shown.

Command goimports updates your Go import lines, adding missing ones and removing unreferenced ones. It's a drop-in replacement for your editor's gofmt-on-save hook. It has the same command-line interface as gofmt and formats your code in the same way. For emacs, make sure you have the latest go-mode.el: Then in your .emacs file: For vim, set "gofmt_command" to "goimports": For GoSublime, follow the steps described here: For other editors, you probably know what to do. Happy hacking!

Package schematic implements the parsing of Schematic files for Dragonfly. Due to the format of schematics, only blocks with an ID smaller than 256 are supported. This means that new blocks are not supported. Due to new blocks not being supported, this package does not provide methods to save blocks to a schematic. The Schematic struct provided by the schematic package implements Dragonfly's world.Structure interface, allowing for a high throughput for schematic pasting and easy usage. See World.BuildStructure for pasting a schematic.

Copyright 2016 - 2018 The excelize Authors. All rights reserved. Use of this source code is governed by a BSD-style license that can be found in the LICENSE file. Package excelize providing a set of functions that allow you to write to and read from XLSX files. Support reads and writes XLSX file generated by Microsoft Excel™ 2007 and later. Support save file without losing original charts of XLSX. This library needs Go version 1.8 or later. See https://xuri.me/excelize for more information about this package.