Test Reporting

Gaby is an experimental new bot running in the Go issue tracker as @gabyhelp, to try to help automate various mundane things that a machine can do reasonably well, as well as to try to discover new things that a machine can do reasonably well. The name gaby is short for “Go AI Bot”, because one of the purposes of the experiment is to learn what LLMs can be used for effectively, including identifying what they should not be used for. Some of the gaby functionality will involve LLMs; other functionality will not. The guiding principle is to create something that helps maintainers and that maintainers like, which means to use LLMs when they make sense and help but not when they don't. In the long term, the intention is for this code base or a successor version to take over the current functionality of “gopherbot” and become @gopherbot, at which point the @gabyhelp account will be retired. At the moment we are not accepting new code contributions or PRs. We hope to move this code to somewhere more official soon, at which point we will accept contributions. The GitHub Discussion is a good place to leave feedback about @gabyhelp. The bot functionality is implemented in internal packages in subdirectories. This comment gives a brief tour of the structure. An explicit goal for the Gaby code base is that it run well in many different environments, ranging from a maintainer's home server or even Raspberry Pi all the way up to a hosted cloud. (At the moment, Gaby runs on a Linux server in my basement.) Due to this emphasis on portability, Gaby defines its own interfaces for all the functionality it needs from the surrounding environment and then also defines a variety of implementations of those interfaces. Another explicit goal for the Gaby code base is that it be very well tested. (See my [Go Testing talk] for more about why this is so important.) Abstracting the various external functionality into interfaces also helps make testing easier, and some packages also provide explicit testing support. The result of both these goals is that Gaby defines some basic functionality like time-ordered indexing for itself instead of relying on some specific other implementation. In the grand scheme of things, these are a small amount of code to maintain, and the benefits to both portability and testability are significant. Code interacting with services like GitHub and code running on cloud servers is typically difficult to test and therefore undertested. It is an explicit requirement this repo to test all the code, even (and especially) when testing is difficult. A useful command to have available when working in the code is rsc.io/uncover, which prints the package source lines not covered by a unit test. A useful invocation is: The first “go test” command checks that the test passes. The second repeats the test with coverage enabled. Running the test twice this way makes sure that any syntax or type errors reported by the compiler are reported without coverage, because coverage can mangle the error output. After both tests pass and second writes a coverage profile, running “uncover /tmp/c.out” prints the uncovered lines. In this output, there are three error paths that are untested. In general, error paths should be tested, so tests should be written to cover these lines of code. In limited cases, it may not be practical to test a certain section, such as when code is unreachable but left in case of future changes or mistaken assumptions. That part of the code can be labeled with a comment beginning “// Unreachable” or “// unreachable” (usually with explanatory text following), and then uncover will not report it. If a code section should be tested but the test is being deferred to later, that section can be labeled “// Untested” or “// untested” instead. The rsc.io/gaby/internal/testutil package provides a few other testing helpers. The overview of the code now proceeds from bottom up, starting with storage and working up to the actual bot. Gaby needs to manage a few secret keys used to access services. The rsc.io/gaby/internal/secret package defines the interface for obtaining those secrets. The only implementations at the moment are an in-memory map and a disk-based implementation that reads $HOME/.netrc. Future implementations may include other file formats as well as cloud-based secret storage services. Secret storage is intentionally separated from the main database storage, described below. The main database should hold public data, not secrets. Gaby defines the interface it expects from a large language model. The llm.Embedder interface abstracts an LLM that can take a collection of documents and return their vector embeddings, each of type llm.Vector. The only real implementation to date is rsc.io/gaby/internal/gemini. It would be good to add an offline implementation using Ollama as well. For tests that need an embedder but don't care about the quality of the embeddings, llm.QuoteEmbedder copies a prefix of the text into the vector (preserving vector unit length) in a deterministic way. This is good enough for testing functionality like vector search and simplifies tests by avoiding a dependence on a real LLM. At the moment, only the embedding interface is defined. In the future we expect to add more interfaces around text generation and tool use. As noted above, Gaby defines interfaces for all the functionality it needs from its external environment, to admit a wide variety of implementations for both execution and testing. The lowest level interface is storage, defined in rsc.io/gaby/internal/storage. Gaby requires a key-value store that supports ordered traversal of key ranges and atomic batch writes up to a modest size limit (at least a few megabytes). The basic interface is storage.DB. storage.MemDB returns an in-memory implementation useful for testing. Other implementations can be put through their paces using storage.TestDB. The only real storage.DB implementation is rsc.io/gaby/internal/pebble, which is a LevelDB-derived on-disk key-value store developed and used as part of CockroachDB. It is a production-quality local storage implementation and maintains the database as a directory of files. In the future we plan to add an implementation using Google Cloud Firestore, which provides a production-quality key-value lookup as a Cloud service without fixed baseline server costs. (Firestore is the successor to Google Cloud Datastore.) The storage.DB makes the simplifying assumption that storage never fails, or rather that if storage has failed then you'd rather crash your program than try to proceed through typically untested code paths. As such, methods like Get and Set do not return errors. They panic on failure, and clients of a DB can call the DB's Panic method to invoke the same kind of panic if they notice any corruption. It remains to be seen whether this decision is kept. In addition to the usual methods like Get, Set, and Delete, storage.DB defines Lock and Unlock methods that acquire and release named mutexes managed by the database layer. The purpose of these methods is to enable coordination when multiple instances of a Gaby program are running on a serverless cloud execution platform. So far Gaby has only run on an underground basement server (the opposite of cloud), so these have not been exercised much and the APIs may change. In addition to the regular database, package storage also defines storage.VectorDB, a vector database for use with LLM embeddings. The basic operations are Set, Get, and Search. storage.MemVectorDB returns an in-memory implementation that stores the actual vectors in a storage.DB for persistence but also keeps a copy in memory and searches by comparing against all the vectors. When backed by a storage.MemDB, this implementation is useful for testing, but when backed by a persistent database, the implementation suffices for small-scale production use (say, up to a million documents, which would require 3 GB of vectors). It is possible that the package ordering here is wrong and that VectorDB should be defined in the llm package, built on top of storage, and not the current “storage builds on llm”. Because Gaby makes minimal demands of its storage layer, any structure we want to impose must be implemented on top of it. Gaby uses the rsc.io/ordered encoding format to produce database keys that order in useful ways. For example, ordered.Encode("issue", 123) < ordered.Encode("issue", 1001), so that keys of this form can be used to scan through issues in numeric order. In contrast, using something like fmt.Sprintf("issue%d", n) would visit issue 1001 before issue 123 because "1001" < "123". Using this kind of encoding is common when using NoSQL key-value storage. See the rsc.io/ordered package for the details of the specific encoding. One of the implied jobs Gaby has is to collect all the relevant information about an open source project: its issues, its code changes, its documentation, and so on. Those sources are always changing, so derived operations like adding embeddings for documents need to be able to identify what is new and what has been processed already. To enable this, Gaby implements time-stamped—or just “timed”—storage, in which a collection of key-value pairs also has a “by time” index of ((timestamp, key), no-value) pairs to make it possible to scan only the key-value pairs modified after the previous scan. This kind of incremental scan only has to remember the last timestamp processed and then start an ordered key range scan just after that timestamp. This convention is implemented by rsc.io/gaby/internal/timed, along with a [timed.Watcher] that formalizes the incremental scan pattern. Various package take care of downloading state from issue trackers and the like, but then all that state needs to be unified into a common document format that can be indexed and searched. That document format is defined by rsc.io/gaby/internal/docs. A document consists of an ID (conventionally a URL), a document title, and document text. Documents are stored using timed storage, enabling incremental processing of newly added documents . The next stop for any new document is embedding it into a vector and storing that vector in a vector database. The rsc.io/gaby/internal/embeddocs package does this, and there is very little to it, given the abstractions of a document store with incremental scanning, an LLM embedder, and a vector database, all of which are provided by other packages. None of the packages mentioned so far involve network operations, but the next few do. It is important to test those but also equally important not to depend on external network services in the tests. Instead, the package rsc.io/gaby/internal/httprr provides an HTTP record/replay system specifically designed to help testing. It can be run once in a mode that does use external network servers and records the HTTP exchanges, but by default tests look up the expected responses in the previously recorded log, replaying those responses. The result is that code making HTTP request can be tested with real server traffic once and then re-tested with recordings of that traffic afterward. This avoids having to write entire fakes of services but also avoids needing the services to stay available in order for tests to pass. It also typically makes the tests much faster than using the real servers. Gaby uses GitHub in two main ways. First, it downloads an entire copy of the issue tracker state, with incremental updates, into timed storage. Second, it performs actions in the issue tracker, like editing issues or comments, applying labels, or posting new comments. These operations are provided by rsc.io/gaby/internal/github. Gaby downloads the issue tracker state using GitHub's REST API, which makes incremental updating very easy but does not provide access to a few newer features such as project boards and discussions, which are only available in the GraphQL API. Sync'ing using the GraphQL API is left for future work: there is enough data available from the REST API that for now we can focus on what to do with that data and not that a few newer GitHub features are missing. The github package provides two important aids for testing. For issue tracker state, it also allows loading issue data from a simple text-based issue description, avoiding any actual GitHub use at all and making it easier to modify the test data. For issue tracker actions, the github package defaults in tests to not actually making changes, instead diverting edits into an in-memory log. Tests can then check the log to see whether the right edits were requested. The rsc.io/gaby/internal/githubdocs package takes care of adding content from the downloaded GitHub state into the general document store. Currently the only GitHub-derived documents are one document per issue, consisting of the issue title and body. It may be worth experimenting with incorporating issue comments in some way, although they bring with them a significant amount of potential noise. Gaby will need to download and store Gerrit state into the database and then derive documents from it. That code has not yet been written, although rsc.io/gerrit/reviewdb provides a basic version that can be adapted. Gaby will also need to download and store project documentation into the database and derive documents from it corresponding to cutting the page at each heading. That code has been written but is not yet tested well enough to commit. It will be added later. The simplest job Gaby has is to go around fixing new comments, including issue descriptions (which look like comments but are a different kind of GitHub data). The rsc.io/gaby/internal/commentfix package implements this, watching GitHub state incrementally and applying a few kinds of rewrite rules to each new comment or issue body. The commentfix package allows automatically editing text, automatically editing URLs, and automatically hyperlinking text. The next job Gaby has is to respond to new issues with related issues and documents. The rsc.io/gaby/internal/related package implements this, watching GitHub state incrementally for new issues, filtering out ones that should be ignored, and then finding related issues and documents and posting a list. This package was originally intended to identify and automatically close duplicates, but the difference between a duplicate and a very similar or not-quite-fixed issue is too difficult a judgement to make for an LLM. Even so, the act of bringing forward related context that may have been forgotten or never known by the people reading the issue has turned out to be incredibly helpful. All of these pieces are put together in the main program, this package, rsc.io/gaby. The actual main package has no tests yet but is also incredibly straightforward. It does need tests, but we also need to identify ways that the hard-coded policies in the package can be lifted out into data that a natural language interface can manipulate. For example the current policy choices in package main amount to: These could be stored somewhere as data and manipulated and added to by the LLM in response to prompts from maintainers. And other features could be added and configured in a similar way. Exactly how to do this is an important thing to learn in future experimentation. As mentioned above, the two jobs Gaby does already are both fairly simple and straightforward. It seems like a general approach that should work well is well-written, well-tested deterministic traditional functionality such as the comment fixer and related-docs poster, configured by LLMs in response to specific directions or eventually higher-level goals specified by project maintainers. Other functionality that is worth exploring is rules for automatically labeling issues, rules for identifying issues or CLs that need to be pinged, rules for identifying CLs that need maintainer attention or that need submitting, and so on. Another stretch goal might be to identify when an issue needs more information and ask for that information. Of course, it would be very important not to ask for information that is already present or irrelevant, so getting that right would be a very high bar. There is no guarantee that today's LLMs work well enough to build a useful version of that. Another important area of future work will be running Gaby on top of cloud databases and then moving Gaby's own execution into the cloud. Getting it a server with a URL will enable GitHub callbacks instead of the current 2-minute polling loop, which will enable interactive conversations with Gaby. Overall, we believe that there are a few good ideas for ways that LLM-based bots can help make project maintainers' jobs easier and less monotonous, and they are waiting to be found. There are also many bad ideas, and they must be filtered out. Understanding the difference will take significant care, thought, and experimentation. We have work to do.

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.

Package sunrise computes sunrises and sunsets using wikipedia article http://en.wikipedia.org/wiki/Sunrise_equation. Testing at my latitude and longitude in California shows that computed sunrises and sunsets can vary by as much as 2 minutes from those that NOAA reports at http://www.esrl.noaa.gov/gmd/grad/solcalc/sunrise.html.

Package gofpdf implements a PDF document generator with high level support for text, drawing and images. - UTF-8 support - Choice of measurement unit, page format and margins - Page header and footer management - Automatic page breaks, line breaks, and text justification - Inclusion of JPEG, PNG, GIF, TIFF and basic path-only SVG images - Colors, gradients and alpha channel transparency - Outline bookmarks - Internal and external links - TrueType, Type1 and encoding support - Page compression - Lines, Bézier curves, arcs, and ellipses - Rotation, scaling, skewing, translation, and mirroring - Clipping - Document protection - Layers - Templates - Barcodes - Charting facility - Import PDFs as templates gofpdf has no dependencies other than the Go standard library. All tests pass on Linux, Mac and Windows platforms. gofpdf supports UTF-8 TrueType fonts and “right-to-left” languages. Note that Chinese, Japanese, and Korean characters may not be included in many general purpose fonts. For these languages, a specialized font (for example, NotoSansSC for simplified Chinese) can be used. Also, support is provided to automatically translate UTF-8 runes to code page encodings for languages that have fewer than 256 glyphs. To install the package on your system, run Later, to receive updates, run The following Go code generates a simple PDF file. See the functions in the fpdf_test.go file (shown as examples in this documentation) for more advanced PDF examples. If an error occurs in an Fpdf method, an internal error field is set. After this occurs, Fpdf method calls typically return without performing any operations and the error state is retained. This error management scheme facilitates PDF generation since individual method calls do not need to be examined for failure; it is generally sufficient to wait until after Output() is called. For the same reason, if an error occurs in the calling application during PDF generation, it may be desirable for the application to transfer the error to the Fpdf instance by calling the SetError() method or the SetErrorf() method. At any time during the life cycle of the Fpdf instance, the error state can be determined with a call to Ok() or Err(). The error itself can be retrieved with a call to Error(). This package is a relatively straightforward translation from the original FPDF library written in PHP (despite the caveat in the introduction to Effective Go). The API names have been retained even though the Go idiom would suggest otherwise (for example, pdf.GetX() is used rather than simply pdf.X()). The similarity of the two libraries makes the original FPDF website a good source of information. It includes a forum and FAQ. However, some internal changes have been made. Page content is built up using buffers (of type bytes.Buffer) rather than repeated string concatenation. Errors are handled as explained above rather than panicking. Output is generated through an interface of type io.Writer or io.WriteCloser. A number of the original PHP methods behave differently based on the type of the arguments that are passed to them; in these cases additional methods have been exported to provide similar functionality. Font definition files are produced in JSON rather than PHP. A side effect of running go test ./... is the production of a number of example PDFs. These can be found in the gofpdf/pdf directory after the tests complete. Please note that these examples run in the context of a test. In order run an example as a standalone application, you’ll need to examine fpdf_test.go for some helper routines, for example exampleFilename() and summary(). Example PDFs can be compared with reference copies in order to verify that they have been generated as expected. This comparison will be performed if a PDF with the same name as the example PDF is placed in the gofpdf/pdf/reference directory and if the third argument to ComparePDFFiles() in internal/example/example.go is true. (By default it is false.) The routine that summarizes an example will look for this file and, if found, will call ComparePDFFiles() to check the example PDF for equality with its reference PDF. If differences exist between the two files they will be printed to standard output and the test will fail. If the reference file is missing, the comparison is considered to succeed. In order to successfully compare two PDFs, the placement of internal resources must be consistent and the internal creation timestamps must be the same. To do this, the methods SetCatalogSort() and SetCreationDate() need to be called for both files. This is done automatically for all examples. Nothing special is required to use the standard PDF fonts (courier, helvetica, times, zapfdingbats) in your documents other than calling SetFont(). You should use AddUTF8Font() or AddUTF8FontFromBytes() to add a TrueType UTF-8 encoded font. Use RTL() and LTR() methods switch between “right-to-left” and “left-to-right” mode. In order to use a different non-UTF-8 TrueType or Type1 font, you will need to generate a font definition file and, if the font will be embedded into PDFs, a compressed version of the font file. This is done by calling the MakeFont function or using the included makefont command line utility. To create the utility, cd into the makefont subdirectory and run “go build”. This will produce a standalone executable named makefont. Select the appropriate encoding file from the font subdirectory and run the command as in the following example. In your PDF generation code, call AddFont() to load the font and, as with the standard fonts, SetFont() to begin using it. Most examples, including the package example, demonstrate this method. Good sources of free, open-source fonts include Google Fonts and DejaVu Fonts. The draw2d package is a two dimensional vector graphics library that can generate output in different forms. It uses gofpdf for its document production mode. gofpdf is a global community effort and you are invited to make it even better. If you have implemented a new feature or corrected a problem, please consider contributing your change to the project. A contribution that does not directly pertain to the core functionality of gofpdf should be placed in its own directory directly beneath the contrib directory. Here are guidelines for making submissions. Your change should - be compatible with the MIT License - be properly documented - be formatted with go fmt - include an example in fpdf_test.go if appropriate - conform to the standards of golint and go vet, that is, golint . and go vet . should not generate any warnings - not diminish test coverage Pull requests are the preferred means of accepting your changes. gofpdf is released under the MIT License. It is copyrighted by Kurt Jung and the contributors acknowledged below. This package’s code and documentation are closely derived from the FPDF library created by Olivier Plathey, and a number of font and image resources are copied directly from it. Bruno Michel has provided valuable assistance with the code. Drawing support is adapted from the FPDF geometric figures script by David Hernández Sanz. Transparency support is adapted from the FPDF transparency script by Martin Hall-May. Support for gradients and clipping is adapted from FPDF scripts by Andreas Würmser. Support for outline bookmarks is adapted from Olivier Plathey by Manuel Cornes. Layer support is adapted from Olivier Plathey. Support for transformations is adapted from the FPDF transformation script by Moritz Wagner and Andreas Würmser. PDF protection is adapted from the work of Klemen Vodopivec for the FPDF product. Lawrence Kesteloot provided code to allow an image’s extent to be determined prior to placement. Support for vertical alignment within a cell was provided by Stefan Schroeder. Ivan Daniluk generalized the font and image loading code to use the Reader interface while maintaining backward compatibility. Anthony Starks provided code for the Polygon function. Robert Lillack provided the Beziergon function and corrected some naming issues with the internal curve function. Claudio Felber provided implementations for dashed line drawing and generalized font loading. Stani Michiels provided support for multi-segment path drawing with smooth line joins, line join styles, enhanced fill modes, and has helped greatly with package presentation and tests. Templating is adapted by Marcus Downing from the FPDF_Tpl library created by Jan Slabon and Setasign. Jelmer Snoeck contributed packages that generate a variety of barcodes and help with registering images on the web. Jelmer Snoek and Guillermo Pascual augmented the basic HTML functionality with aligned text. Kent Quirk implemented backwards-compatible support for reading DPI from images that support it, and for setting DPI manually and then having it properly taken into account when calculating image size. Paulo Coutinho provided support for static embedded fonts. Dan Meyers added support for embedded JavaScript. David Fish added a generic alias-replacement function to enable, among other things, table of contents functionality. Andy Bakun identified and corrected a problem in which the internal catalogs were not sorted stably. Paul Montag added encoding and decoding functionality for templates, including images that are embedded in templates; this allows templates to be stored independently of gofpdf. Paul also added support for page boxes used in printing PDF documents. Wojciech Matusiak added supported for word spacing. Artem Korotkiy added support of UTF-8 fonts. Dave Barnes added support for imported objects and templates. Brigham Thompson added support for rounded rectangles. Joe Westcott added underline functionality and optimized image storage. Benoit KUGLER contributed support for rectangles with corners of unequal radius, modification times, and for file attachments and annotations. - Remove all legacy code page font support; use UTF-8 exclusively - Improve test coverage as reported by the coverage tool. Example demonstrates the generation of a simple PDF document. Note that since only core fonts are used (in this case Arial, a synonym for Helvetica), an empty string can be specified for the font directory in the call to New(). Note also that the example.Filename() and example.Summary() functions belong to a separate, internal package and are not part of the gofpdf library. If an error occurs at some point during the construction of the document, subsequent method calls exit immediately and the error is finally retrieved with the output call where it can be handled by the application.

Package cue implements contextual logging with "batteries included". It has thorough test coverage and supports logging to stdout/stderr, file, syslog, and network sockets, as well as hosted third-party logging and error/reporting services such as Honeybadger, Loggly, Opbeat, Rollbar, and Sentry. Cue uses atomic operations to compare logging calls to registered collector thresholds. This ensures no-op calls are performed quickly and without lock contention. On a 2015 MacBook Pro, no-op calls take about 16ns/call, meaning tens of millions of calls may be dispatched per second. Uncollected log calls are very cheap. Furthermore, collector thresholds may be altered dynamically at run-time, on a per-collector basis. If debugging logs are needed to troubleshoot a live issue, collector thresholds may be set to the DEBUG level for a short period of time and then restored to their original levels shortly thereafter. See the SetLevel function for details. Logging instances are created via the NewLogger function. A simple convention is to initialize an unexported package logger: Additional context information may be added to the package logger via the log.WithValue and log.WithFields methods: Depending on the collector and log format, output would look something like: Cue simplifies error reporting by logging the given error and message, and then returning the same error value. Hence you can return the log.Error/log.Errorf values in-line: Cue provides Collector implementations for popular error reporting services such as Honeybadger, Rollbar, Sentry, and Opbeat. If one of these collector implementations were registered, the above code would automatically open a new error report, complete with stack trace and context information from the logger instance. See the cue/hosted package for details. Finally, cue provides convenience methods for panic and recovery. Calling Panic or Panicf will log the provided message at the FATAL level and then panic. Calling Recover recovers from panics and logs the recovered value and message at the FATAL level. If a panic is triggered via a cue logger instance's Panic or Panicf methods, Recover recovers from the panic but only emits the single event from the Panic/Panicf method. Cue decouples event generation from event collection. Library and framework authors may generate log events without concern for the details of collection. Event collection is opt-in -- no collectors are registered by default. Event collection, if enabled, should be configured close to a program's main package/function, not by libraries. This gives the event subscriber complete control over the behavior of event collection. Collectors are registered via the Collect and CollectAsync functions. Each collector is registered for a given level threshold. The threshold for a collector may be updated at any time using the SetLevel function. Collect registers fully synchronous event collectors. Logging calls that match a synchronous collector's threshold block until the collector's Collect method returns successfully. This is dangerous if the Collector performs any operations that block or return errors. However, it's simple to use and understand: CollectAsync registers asynchronous collectors. It creates a buffered channel for the collector and starts a worker goroutine to service events. Logging calls return after queuing events to the collector channel. If the channel's buffer is full, the event is dropped and a drop counter is incremented atomically. This ensures asynchronous logging calls never block. The worker goroutine detects changes in the atomic drop counter and surfaces drop events as collector errors. See the cue/collector docs for details on collector error handling. When asynchronous logging is enabled, Close must be called to flush queued events on program termination. Close is safe to call even if asynchronous logging isn't enabled -- it returns immediately if no events are queued. Note that ctrl+c and kill <pid> terminate Go programs without triggering cleanup code. When using asynchronous logging, it's a good idea to register signal handlers to capture SIGINT (ctrl+c) and SIGTERM (kill <pid>). See the os/signals package docs for details. By default, cue collects a single stack frame for any event that matches a registered collector. This ensures collectors may log the file name, package, and line number for any collected event. SetFrames may be used to alter this frame count, or disable frame collection entirely. See the SetFrames function for details. When using error reporting services, SetFrames should be used to increase the errorFrames parameter from the default value of 1 to a value that provides enough stack context to successfully diagnose reported errors. This example logs to both the terminal (stdout) and to file. If the program receives SIGHUP, the file will be reopened (for log rotation). Additional context is added via the .WithValue and .WithFields Logger methods. The formatting may be changed by passing a different formatter to either collector. See the cue/format godocs for details. The context data may also be formatted as JSON for machine parsing if desired. See cue/format.JSONMessage and cue/format.JSONContext. This example shows how to use error reporting services. This example shows quite a few of the cue features: logging to a file that reopens on SIGHUP (for log rotation), logging colored output to stdout, logging to syslog, and reporting errors to Honeybadger.

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 saml contains a partial implementation of the SAML standard in golang. SAML is a standard for identity federation, i.e. either allowing a third party to authenticate your users or allowing third parties to rely on us to authenticate their users. In SAML parlance an Identity Provider (IDP) is a service that knows how to authenticate users. A Service Provider (SP) is a service that delegates authentication to an IDP. If you are building a service where users log in with someone else's credentials, then you are a Service Provider. This package supports implementing both service providers and identity providers. The core package contains the implementation of SAML. The package samlsp provides helper middleware suitable for use in Service Provider applications. The package samlidp provides a rudimentary IDP service that is useful for testing or as a starting point for other integrations. Version 0.4.0 introduces a few breaking changes to the _samlsp_ package in order to make the package more extensible, and to clean up the interfaces a bit. The default behavior remains the same, but you can now provide interface implementations of _RequestTracker_ (which tracks pending requests), _Session_ (which handles maintaining a session) and _OnError_ which handles reporting errors. Public fields of _samlsp.Middleware_ have changed, so some usages may require adjustment. See [issue 231](https://github.com/joshuaalewis/saml/issues/231) for details. The option to provide an IDP metadata URL has been deprecated. Instead, we recommend that you use the `FetchMetadata()` function, or fetch the metadata yourself and use the new `ParseMetadata()` function, and pass the metadata in _samlsp.Options.IDPMetadata_. Similarly, the _HTTPClient_ field is now deprecated because it was only used for fetching metdata, which is no longer directly implemented. The fields that manage how cookies are set are deprecated as well. To customize how cookies are managed, provide custom implementation of _RequestTracker_ and/or _Session_, perhaps by extending the default implementations. The deprecated fields have not been removed from the Options structure, but will be in future. In particular we have deprecated the following fields in _samlsp.Options_: - `Logger` - This was used to emit errors while validating, which is an anti-pattern. - `IDPMetadataURL` - Instead use `FetchMetadata()` - `HTTPClient` - Instead pass httpClient to FetchMetadata - `CookieMaxAge` - Instead assign a custom CookieRequestTracker or CookieSessionProvider - `CookieName` - Instead assign a custom CookieRequestTracker or CookieSessionProvider - `CookieDomain` - Instead assign a custom CookieRequestTracker or CookieSessionProvider - `CookieDomain` - Instead assign a custom CookieRequestTracker or CookieSessionProvider Let us assume we have a simple web application to protect. We'll modify this application so it uses SAML to authenticate users. ```golang package main import ( ) ``` Each service provider must have an self-signed X.509 key pair established. You can generate your own with something like this: We will use `samlsp.Middleware` to wrap the endpoint we want to protect. Middleware provides both an `http.Handler` to serve the SAML specific URLs and a set of wrappers to require the user to be logged in. We also provide the URL where the service provider can fetch the metadata from the IDP at startup. In our case, we'll use [samltest.id](https://samltest.id/), an identity provider designed for testing. ```golang package main import ( ) ``` Next we'll have to register our service provider with the identity provider to establish trust from the service provider to the IDP. For [samltest.id](https://samltest.id/), you can do something like: Navigate to https://samltest.id/upload.php and upload the file you fetched. Now you should be able to authenticate. The flow should look like this: 1. You browse to `localhost:8000/hello` 1. The middleware redirects you to `https://samltest.id/idp/profile/SAML2/Redirect/SSO` 1. samltest.id prompts you for a username and password. 1. samltest.id returns you an HTML document which contains an HTML form setup to POST to `localhost:8000/saml/acs`. The form is automatically submitted if you have javascript enabled. 1. The local service validates the response, issues a session cookie, and redirects you to the original URL, `localhost:8000/hello`. 1. This time when `localhost:8000/hello` is requested there is a valid session and so the main content is served. Please see `example/idp/` for a substantially complete example of how to use the library and helpers to be an identity provider. The SAML standard is huge and complex with many dark corners and strange, unused features. This package implements the most commonly used subset of these features required to provide a single sign on experience. The package supports at least the subset of SAML known as [interoperable SAML](http://saml2int.org). This package supports the Web SSO profile. Message flows from the service provider to the IDP are supported using the HTTP Redirect binding and the HTTP POST binding. Message flows from the IDP to the service provider are supported via the HTTP POST binding. The package can produce signed SAML assertions, and can validate both signed and encrypted SAML assertions. It does not support signed or encrypted requests. The _RelayState_ parameter allows you to pass user state information across the authentication flow. The most common use for this is to allow a user to request a deep link into your site, be redirected through the SAML login flow, and upon successful completion, be directed to the originally requested link, rather than the root. Unfortunately, _RelayState_ is less useful than it could be. Firstly, it is not authenticated, so anything you supply must be signed to avoid XSS or CSRF. Secondly, it is limited to 80 bytes in length, which precludes signing. (See section 3.6.3.1 of SAMLProfiles.) The SAML specification is a collection of PDFs (sadly): - [SAMLCore](http://docs.oasis-open.org/security/saml/v2.0/saml-core-2.0-os.pdf) defines data types. - [SAMLBindings](http://docs.oasis-open.org/security/saml/v2.0/saml-bindings-2.0-os.pdf) defines the details of the HTTP requests in play. - [SAMLProfiles](http://docs.oasis-open.org/security/saml/v2.0/saml-profiles-2.0-os.pdf) describes data flows. - [SAMLConformance](http://docs.oasis-open.org/security/saml/v2.0/saml-conformance-2.0-os.pdf) includes a support matrix for various parts of the protocol. [SAMLtest](https://samltest.id/) is a testing ground for SAML service and identity providers. Please do not report security issues in the issue tracker. Rather, please contact me directly at ross@kndr.org ([PGP Key `78B6038B3B9DFB88`](https://keybase.io/crewjam)).

Package jsonlogic is a Go implementation of JsonLogic as described at http://jsonlogic.com. All example content for all operations, as given on the web site, work as expected. The test suite provided at https://jsonlogic.com/tests.json passes unaltered. var data lookup assumes the passed-in data structure is akin to that provided by a raw json.Unmarshal. Only the following types are supported: We cannot currently query Go native structs, or maps/slices of other native Go types. Incompatibilities may exist in support for JavaScript type coercion. Any incompatibilities found should be reported as bugs.

Package sqlite is a sql/database driver using a CGo-free port of the C SQLite3 library. SQLite is an in-process implementation of a self-contained, serverless, zero-configuration, transactional SQL database engine. This project is sponsored by Schleibinger Geräte Teubert u. Greim GmbH by allowing one of the maintainers to work on it also in office hours. These combinations of GOOS and GOARCH are currently supported https://modern-c.appspot.com/-/builder/?importpath=modernc.org%2fsqlite 2022-11-28 v1.20.0 Support linux/ppc64le. 2022-09-16 v1.19.0: Support frebsd/arm64. 2022-07-26 v1.18.0: Adds support for Go fs.FS based SQLite virtual filesystems, see function New in modernc.org/sqlite/vfs and/or TestVFS in all_test.go 2022-04-24 v1.17.0: Support windows/arm64. 2022-04-04 v1.16.0: Support scalar application defined functions written in Go. 2022-03-13 v1.15.0: Support linux/riscv64. 2021-11-13 v1.14.0: Support windows/amd64. This target had previously only experimental status because of a now resolved memory leak. 2021-09-07 v1.13.0: Support freebsd/amd64. 2021-06-23 v1.11.0: Upgrade to use sqlite 3.36.0, release notes at https://www.sqlite.org/releaselog/3_36_0.html. 2021-05-06 v1.10.6: Fixes a memory corruption issue (https://gitlab.com/cznic/sqlite/-/issues/53). Versions since v1.8.6 were affected and should be updated to v1.10.6. 2021-03-14 v1.10.0: Update to use sqlite 3.35.0, release notes at https://www.sqlite.org/releaselog/3_35_0.html. 2021-03-11 v1.9.0: Support darwin/arm64. 2021-01-08 v1.8.0: Support darwin/amd64. 2020-09-13 v1.7.0: Support linux/arm and linux/arm64. 2020-09-08 v1.6.0: Support linux/386. 2020-09-03 v1.5.0: This project is now completely CGo-free, including the Tcl tests. 2020-08-26 v1.4.0: First stable release for linux/amd64. The database/sql driver and its tests are CGo free. Tests of the translated sqlite3.c library still require CGo. 2020-07-26 v1.4.0-beta1: The project has reached beta status while supporting linux/amd64 only at the moment. The 'extraquick' Tcl testsuite reports and some memory leaks 2019-12-28 v1.2.0-alpha.3: Third alpha fixes issue #19. It also bumps the minor version as the repository was wrongly already tagged with v1.1.0 before. Even though the tag was deleted there are proxies that cached that tag. Thanks /u/garaktailor for detecting the problem and suggesting this solution. 2019-12-26 v1.1.0-alpha.2: Second alpha release adds support for accessing a database concurrently by multiple goroutines and/or processes. v1.1.0 is now considered feature-complete. Next planed release should be a beta with a proper test suite. 2019-12-18 v1.1.0-alpha.1: First alpha release using the new cc/v3, gocc, qbe toolchain. Some primitive tests pass on linux_{amd64,386}. Not yet safe for concurrent access by multiple goroutines. Next alpha release is planed to arrive before the end of this year. 2017-06-10 Windows/Intel no more uses the VM (thanks Steffen Butzer). 2017-06-05 Linux/Intel no more uses the VM (cznic/virtual). To access a Sqlite database do something like A comma separated list of options can be passed to `go generate` via the environment variable GO_GENERATE. Some useful options include for example: To create a debug/development version, issue for example: Note: To run `go generate` you need to have modernc.org/ccgo/v3 installed. See https://sqlite.org/docs.html

Package saml contains a partial implementation of the SAML standard in golang. SAML is a standard for identity federation, i.e. either allowing a third party to authenticate your users or allowing third parties to rely on us to authenticate their users. In SAML parlance an Identity Provider (IDP) is a service that knows how to authenticate users. A Service Provider (SP) is a service that delegates authentication to an IDP. If you are building a service where users log in with someone else's credentials, then you are a Service Provider. This package supports implementing both service providers and identity providers. The core package contains the implementation of SAML. The package samlsp provides helper middleware suitable for use in Service Provider applications. The package samlidp provides a rudimentary IDP service that is useful for testing or as a starting point for other integrations. Version 0.4.0 introduces a few breaking changes to the _samlsp_ package in order to make the package more extensible, and to clean up the interfaces a bit. The default behavior remains the same, but you can now provide interface implementations of _RequestTracker_ (which tracks pending requests), _Session_ (which handles maintaining a session) and _OnError_ which handles reporting errors. Public fields of _samlsp.Middleware_ have changed, so some usages may require adjustment. See [issue 231](https://github.com/crewjam/saml/issues/231) for details. The option to provide an IDP metadata URL has been deprecated. Instead, we recommend that you use the `FetchMetadata()` function, or fetch the metadata yourself and use the new `ParseMetadata()` function, and pass the metadata in _samlsp.Options.IDPMetadata_. Similarly, the _HTTPClient_ field is now deprecated because it was only used for fetching metdata, which is no longer directly implemented. The fields that manage how cookies are set are deprecated as well. To customize how cookies are managed, provide custom implementation of _RequestTracker_ and/or _Session_, perhaps by extending the default implementations. The deprecated fields have not been removed from the Options structure, but will be in future. In particular we have deprecated the following fields in _samlsp.Options_: - `Logger` - This was used to emit errors while validating, which is an anti-pattern. - `IDPMetadataURL` - Instead use `FetchMetadata()` - `HTTPClient` - Instead pass httpClient to FetchMetadata - `CookieMaxAge` - Instead assign a custom CookieRequestTracker or CookieSessionProvider - `CookieName` - Instead assign a custom CookieRequestTracker or CookieSessionProvider - `CookieDomain` - Instead assign a custom CookieRequestTracker or CookieSessionProvider - `CookieDomain` - Instead assign a custom CookieRequestTracker or CookieSessionProvider Let us assume we have a simple web application to protect. We'll modify this application so it uses SAML to authenticate users. ```golang package main import ( ) ``` Each service provider must have an self-signed X.509 key pair established. You can generate your own with something like this: We will use `samlsp.Middleware` to wrap the endpoint we want to protect. Middleware provides both an `http.Handler` to serve the SAML specific URLs and a set of wrappers to require the user to be logged in. We also provide the URL where the service provider can fetch the metadata from the IDP at startup. In our case, we'll use [samltest.id](https://samltest.id/), an identity provider designed for testing. ```golang package main import ( ) ``` Next we'll have to register our service provider with the identity provider to establish trust from the service provider to the IDP. For [samltest.id](https://samltest.id/), you can do something like: Navigate to https://samltest.id/upload.php and upload the file you fetched. Now you should be able to authenticate. The flow should look like this: 1. You browse to `localhost:8000/hello` 1. The middleware redirects you to `https://samltest.id/idp/profile/SAML2/Redirect/SSO` 1. samltest.id prompts you for a username and password. 1. samltest.id returns you an HTML document which contains an HTML form setup to POST to `localhost:8000/saml/acs`. The form is automatically submitted if you have javascript enabled. 1. The local service validates the response, issues a session cookie, and redirects you to the original URL, `localhost:8000/hello`. 1. This time when `localhost:8000/hello` is requested there is a valid session and so the main content is served. Please see `example/idp/` for a substantially complete example of how to use the library and helpers to be an identity provider. The SAML standard is huge and complex with many dark corners and strange, unused features. This package implements the most commonly used subset of these features required to provide a single sign on experience. The package supports at least the subset of SAML known as [interoperable SAML](http://saml2int.org). This package supports the Web SSO profile. Message flows from the service provider to the IDP are supported using the HTTP Redirect binding and the HTTP POST binding. Message flows from the IDP to the service provider are supported via the HTTP POST binding. The package can produce signed SAML assertions, and can validate both signed and encrypted SAML assertions. It does not support signed or encrypted requests. The _RelayState_ parameter allows you to pass user state information across the authentication flow. The most common use for this is to allow a user to request a deep link into your site, be redirected through the SAML login flow, and upon successful completion, be directed to the originally requested link, rather than the root. Unfortunately, _RelayState_ is less useful than it could be. Firstly, it is not authenticated, so anything you supply must be signed to avoid XSS or CSRF. Secondly, it is limited to 80 bytes in length, which precludes signing. (See section 3.6.3.1 of SAMLProfiles.) The SAML specification is a collection of PDFs (sadly): - [SAMLCore](http://docs.oasis-open.org/security/saml/v2.0/saml-core-2.0-os.pdf) defines data types. - [SAMLBindings](http://docs.oasis-open.org/security/saml/v2.0/saml-bindings-2.0-os.pdf) defines the details of the HTTP requests in play. - [SAMLProfiles](http://docs.oasis-open.org/security/saml/v2.0/saml-profiles-2.0-os.pdf) describes data flows. - [SAMLConformance](http://docs.oasis-open.org/security/saml/v2.0/saml-conformance-2.0-os.pdf) includes a support matrix for various parts of the protocol. [SAMLtest](https://samltest.id/) is a testing ground for SAML service and identity providers. Please do not report security issues in the issue tracker. Rather, please contact me directly at ross@kndr.org ([PGP Key `78B6038B3B9DFB88`](https://keybase.io/crewjam)).

Package fs provides a filesystem-backed Kivik driver. This driver is very much a work in progress. Please refer to the GitHub page for current status and ongoing changes. https://github.com/go-kivik/fsdb Bug reports, feature requests, and pull requests are always welcome. Current development is primarily focused around using fsdb for testing of CouchDB applications, and bootstraping CouchDB applications. Use the `fs` driver name when using this driver. The DSN should be an existing directory on the local filesystem. Access control is managed by your filesystem permissions. Database names represent directories under the path provided to `kivik.New`. For example: would look for document files in `/home/usr/some/path/foo`. This driver supports three types of connection strings to the New() method: CouchDB allows databases and document IDs to contain a slash (/) character. This is not permitted in most operating systems/filenames, to be stored directly on the filesystem this way. Therefore, it is necessary for this package to escape certain characters in filenames. This is done as conservatively as possible. The escaping rules are:

Command pigeon generates parsers in Go from a PEG grammar. This version is a fork: https://github.com/fy0/pigeon From Wikipedia [0]: Its features and syntax are inspired by the PEG.js project [1], while the implementation is loosely based on [2]. Formal presentation of the PEG theory by Bryan Ford is also an important reference [3]. An introductory blog post can be found at [4]. The pigeon tool must be called with PEG input as defined by the accepted PEG syntax below. The grammar may be provided by a file or read from stdin. The generated parser is written to stdout by default. The following options can be specified: If the code blocks in the grammar (see below, section "Code block") are golint- and go vet-compliant, then the resulting generated code will also be golint- and go vet-compliant. The generated code doesn't use any third-party dependency unless code blocks in the grammar require such a dependency. The accepted syntax for the grammar is formally defined in the grammar/pigeon.peg file, using the PEG syntax. What follows is an informal description of this syntax. Identifiers, whitespace, comments and literals follow the same notation as the Go language, as defined in the language specification (http://golang.org/ref/spec#Source_code_representation): The grammar must be Unicode text encoded in UTF-8. New lines are identified by the \n character (U+000A). Space (U+0020), horizontal tabs (U+0009) and carriage returns (U+000D) are considered whitespace and are ignored except to separate tokens. A PEG grammar consists of a set of rules. A rule is an identifier followed by a rule definition operator and an expression. An optional display name - a string literal used in error messages instead of the rule identifier - can be specified after the rule identifier. E.g.: The rule definition operator can be any one of those: A rule is defined by an expression. The following sections describe the various expression types. Expressions can be grouped by using parentheses, and a rule can be referenced by its identifier in place of an expression. The choice expression is a list of expressions that will be tested in the order they are defined. The first one that matches will be used. Expressions are separated by the forward slash character "/". E.g.: Because the first match is used, it is important to think about the order of expressions. For example, in this rule, "<=" would never be used because the "<" expression comes first: The sequence expression is a list of expressions that must all match in that same order for the sequence expression to be considered a match. Expressions are separated by whitespace. E.g.: A labeled expression consists of an identifier followed by a colon ":" and an expression. A labeled expression introduces a variable named with the label that can be referenced in the code blocks in the same scope. The variable will have the value of the expression that follows the colon. E.g.: The variable is typed as an empty interface, and the underlying type depends on the following: For terminals (character and string literals, character classes and the any matcher), the value is []byte. E.g.: For predicates (& and !), the value is always nil. E.g.: For a sequence, the value is a slice of empty interfaces, one for each expression value in the sequence. The underlying types of each value in the slice follow the same rules described here, recursively. E.g.: For a repetition (+ and *), the value is a slice of empty interfaces, one for each repetition. The underlying types of each value in the slice follow the same rules described here, recursively. E.g.: For a choice expression, the value is that of the matching choice. E.g.: For the optional expression (?), the value is nil or the value of the expression. E.g.: Of course, the type of the value can be anything once an action code block is used. E.g.: An expression prefixed with the ampersand "&" is the "and" predicate expression: it is considered a match if the following expression is a match, but it does not consume any input. An expression prefixed with the exclamation point "!" is the "not" predicate expression: it is considered a match if the following expression is not a match, but it does not consume any input. E.g.: The expression following the & and ! operators can be a code block. In that case, the code block must return a bool and an error. The operator's semantic is the same, & is a match if the code block returns true, ! is a match if the code block returns false. The code block has access to any labeled value defined in its scope. E.g.: An expression followed by "*", "?" or "+" is a match if the expression occurs zero or more times ("*"), zero or one time "?" or one or more times ("+") respectively. The match is greedy, it will match as many times as possible. E.g. A literal matcher tries to match the input against a single character or a string literal. The literal may be a single-quoted single character, a double-quoted string or a backtick-quoted raw string. The same rules as in Go apply regarding the allowed characters and escapes. The literal may be followed by a lowercase "i" (outside the ending quote) to indicate that the match is case-insensitive. E.g.: A character class matcher tries to match the input against a class of characters inside square brackets "[...]". Inside the brackets, characters represent themselves and the same escapes as in string literals are available, except that the single- and double-quote escape is not valid, instead the closing square bracket "]" must be escaped to be used. Character ranges can be specified using the "[a-z]" notation. Unicode classes can be specified using the "[\pL]" notation, where L is a single-letter Unicode class of characters, or using the "[\p{Class}]" notation where Class is a valid Unicode class (e.g. "Latin"). As for string literals, a lowercase "i" may follow the matcher (outside the ending square bracket) to indicate that the match is case-insensitive. A "^" as first character inside the square brackets indicates that the match is inverted (it is a match if the input does not match the character class matcher). E.g.: The any matcher is represented by the dot ".". It matches any character except the end of file, thus the "!." expression is used to indicate "match the end of file". E.g.: Code blocks can be added to generate custom Go code. There are three kinds of code blocks: the initializer, the action and the predicate. All code blocks appear inside curly braces "{...}". The initializer must appear first in the grammar, before any rule. It is copied as-is (minus the wrapping curly braces) at the top of the generated parser. It may contain function declarations, types, variables, etc. just like any Go file. Every symbol declared here will be available to all other code blocks. Although the initializer is optional in a valid grammar, it is usually required to generate a valid Go source code file (for the package clause). E.g.: Action code blocks are code blocks declared after an expression in a rule. Those code blocks are turned into a method on the "*current" type in the generated source code. The method receives any labeled expression's value as argument (as any) and must return two values, the first being the value of the expression (an any), and the second an error. If a non-nil error is returned, it is added to the list of errors that the parser will return. E.g.: Predicate code blocks are code blocks declared immediately after the and "&" or the not "!" operators. Like action code blocks, predicate code blocks are turned into a method on the "*current" type in the generated source code. The method receives any labeled expression's value as argument (as any) and must return two opt, the first being a bool and the second an error. If a non-nil error is returned, it is added to the list of errors that the parser will return. E.g.: State change code blocks are code blocks starting with "#". In contrast to action and predicate code blocks, state change code blocks are allowed to modify values in the global "state" store (see below). State change code blocks are turned into a method on the "*current" type in the generated source code. The method is passed any labeled expression's value as an argument (of type any) and must return a value of type error. If a non-nil error is returned, it is added to the list of errors that the parser will return, note that the parser does NOT backtrack if a non-nil error is returned. E.g: The "*current" type is a struct that provides four useful fields that can be accessed in action, state change, and predicate code blocks: "pos", "text", "state" and "globalStore". The "pos" field indicates the current position of the parser in the source input. It is itself a struct with three fields: "line", "col" and "offset". Line is a 1-based line number, col is a 1-based column number that counts runes from the start of the line, and offset is a 0-based byte offset. The "text" field is the slice of bytes of the current match. It is empty in a predicate code block. The "state" field is a global store, with backtrack support, of type "map[string]any". The values in the store are tied to the parser's backtracking, in particular if a rule fails to match then all updates to the state that occurred in the process of matching the rule are rolled back. For a key-value store that is not tied to the parser's backtracking, see the "globalStore". The values in the "state" store are available for read access in action and predicate code blocks, any changes made to the "state" store will be reverted once the action or predicate code block is finished running. To update values in the "state" use state change code blocks ("#{}"). IMPORTANT: The "globalStore" field is a global store of type "map[string]any", which allows to store arbitrary values, which are available in action and predicate code blocks for read as well as write access. It is important to notice, that the global store is completely independent from the backtrack mechanism of PEG and is therefore not set back to its old state during backtrack. The initialization of the global store may be achieved by using the GlobalStore function (http://godoc.org/github.com/mna/pigeon/test/predicates#GlobalStore). Be aware, that all keys starting with "_pigeon" are reserved for internal use of pigeon and should not be used nor modified. Those keys are treated as internal implementation details and therefore there are no guarantees given in regards of API stability. With options -support-left-recursion pigeon supports left recursion. E.g.: Supports indirect recursion: The implementation is based on the [Left-recursive PEG Grammars][9] article that links to [Left Recursion in Parsing Expression Grammars][10] and [Packrat Parsers Can Support Left Recursion][11] papers. References: pigeon supports an extension of the classical PEG syntax called failure labels, proposed by Maidl et al. in their paper "Error Reporting in Parsing Expression Grammars" [7]. The used syntax for the introduced expressions is borrowed from their lpeglabel [8] implementation. This extension allows to signal different kinds of errors and to specify, which recovery pattern should handle a given label. With labeled failures it is possible to distinguish between an ordinary failure and an error. Usually, an ordinary failure is produced when the matching of a character fails, and this failure is caught by ordered choice. An error (a non-ordinary failure), by its turn, is produced by the throw operator and may be caught by the recovery operator. In pigeon, the recovery expression consists of the regular expression, the recovery expression and a set of labels to be matched. First, the regular expression is tried. If this fails with one of the provided labels, the recovery expression is tried. If this fails as well, the error is propagated. E.g.: To signal a failure condition, the throw expression is used. E.g.: For concrete examples, how to use throw and recover, have a look at the examples "labeled_failures" and "thrownrecover" in the "test" folder. The implementation of the throw and recover operators work as follows: The failure recover expression adds the recover expression for every failure label to the recovery stack and runs the regular expression. The throw expression checks the recovery stack in reversed order for the provided failure label. If the label is found, the respective recovery expression is run. If this expression is successful, the parser continues the processing of the input. If the recovery expression is not successful, the parsing fails and the parser starts to backtrack. If throw and recover expressions are used together with global state, it is the responsibility of the author of the grammar to reset the global state to a valid state during the recovery operation. The parser generated by pigeon exports a few symbols so that it can be used as a package with public functions to parse input text. The exported API is: See the godoc page of the generated parser for the test/predicates grammar for an example documentation page of the exported API: http://godoc.org/github.com/mna/pigeon/test/predicates. Like the grammar used to generate the parser, the input text must be UTF-8-encoded Unicode. The start rule of the parser is the first rule in the PEG grammar used to generate the parser. A call to any of the Parse* functions returns the value generated by executing the grammar on the provided input text, and an optional error. Typically, the grammar should generate some kind of abstract syntax tree (AST), but for simple grammars it may evaluate the result immediately, such as in the examples/calculator example. There are no constraints imposed on the author of the grammar, it can return whatever is needed. When the parser returns a non-nil error, the error is always of type errList, which is defined as a slice of errors ([]error). Each error in the list is of type *parserError. This is a struct that has an "Inner" field that can be used to access the original error. So if a code block returns some well-known error like: The original error can be accessed this way: By default the parser will continue after an error is returned and will cumulate all errors found during parsing. If the grammar reaches a point where it shouldn't continue, a panic statement can be used to terminate parsing. The panic will be caught at the top-level of the Parse* call and will be converted into a *parserError like any error, and an errList will still be returned to the caller. The divide by zero error in the examples/calculator grammar leverages this feature (no special code is needed to handle division by zero, if it happens, the runtime panics and it is recovered and returned as a parsing error). Providing good error reporting in a parser is not a trivial task. Part of it is provided by the pigeon tool, by offering features such as filename, position, expected literals and rule name in the error message, but an important part of good error reporting needs to be done by the grammar author. For example, many programming languages use double-quotes for string literals. Usually, if the opening quote is found, the closing quote is expected, and if none is found, there won't be any other rule that will match, there's no need to backtrack and try other choices, an error should be added to the list and the match should be consumed. In order to do this, the grammar can look something like this: This is just one example, but it illustrates the idea that error reporting needs to be thought out when designing the grammar. Because the above mentioned error types (errList and parserError) are not exported, additional steps have to be taken, ff the generated parser is used as library package in other packages (e.g. if the same parser is used in multiple command line tools). One possible implementation for exported errors (based on interfaces) and customized error reporting (caret style formatting of the position, where the parsing failed) is available in the json example and its command line tool: http://godoc.org/github.com/mna/pigeon/examples/json Generated parsers have user-provided code mixed with pigeon code in the same package, so there is no package boundary in the resulting code to prevent access to unexported symbols. What is meant to be implementation details in pigeon is also available to user code - which doesn't mean it should be used. For this reason, it is important to precisely define what is intended to be the supported API of pigeon, the parts that will be stable in future versions. The "stability" of the version 1.0 API attempts to make a similar guarantee as the Go 1 compatibility [5]. The following lists what part of the current pigeon code falls under that guarantee (features may be added in the future): The pigeon command-line flags and arguments: those will not be removed and will maintain the same semantics. The explicitly exported API generated by pigeon. See [6] for the documentation of this API on a generated parser. The PEG syntax, as documented above. The code blocks (except the initializer) will always be generated as methods on the *current type, and this type is guaranteed to have the fields pos (type position) and text (type []byte). There are no guarantees on other fields and methods of this type. The position type will always have the fields line, col and offset, all defined as int. There are no guarantees on other fields and methods of this type. The type of the error value returned by the Parse* functions, when not nil, will always be errList defined as a []error. There are no guarantees on methods of this type, other than the fact it implements the error interface. Individual errors in the errList will always be of type *parserError, and this type is guaranteed to have an Inner field that contains the original error value. There are no guarantees on other fields and methods of this type. The above guarantee is given to the version 1.0 (https://github.com/mna/pigeon/releases/tag/v1.0.0) of pigeon, which has entered maintenance mode (bug fixes only). The current master branch includes the development toward a future version 2.0, which intends to further improve pigeon. While the given API stability should be maintained as far as it makes sense, breaking changes may be necessary to be able to improve pigeon. The new version 2.0 API has not yet stabilized and therefore changes to the API may occur at any time. References:

Package lingua accurately detects the natural language of written text, be it long or short. Its task is simple: It tells you which language some text is written in. This is very useful as a preprocessing step for linguistic data in natural language processing applications such as text classification and spell checking. Other use cases, for instance, might include routing e-mails to the right geographically located customer service department, based on the e-mails' languages. Language detection is often done as part of large machine learning frameworks or natural language processing applications. In cases where you don't need the full-fledged functionality of those systems or don't want to learn the ropes of those, a small flexible library comes in handy. So far, the only other comprehensive open source library in the Go ecosystem for this task is Whatlanggo (https://github.com/abadojack/whatlanggo). Unfortunately, it has two major drawbacks: 1. Detection only works with quite lengthy text fragments. For very short text snippets such as Twitter messages, it does not provide adequate results. 2. The more languages take part in the decision process, the less accurate are the detection results. Lingua aims at eliminating these problems. It nearly does not need any configuration and yields pretty accurate results on both long and short text, even on single words and phrases. It draws on both rule-based and statistical methods but does not use any dictionaries of words. It does not need a connection to any external API or service either. Once the library has been downloaded, it can be used completely offline. Compared to other language detection libraries, Lingua's focus is on quality over quantity, that is, getting detection right for a small set of languages first before adding new ones. Currently, 75 languages are supported. They are listed as variants of type Language. Lingua is able to report accuracy statistics for some bundled test data available for each supported language. The test data for each language is split into three parts: 1. a list of single words with a minimum length of 5 characters 2. a list of word pairs with a minimum length of 10 characters 3. a list of complete grammatical sentences of various lengths Both the language models and the test data have been created from separate documents of the Wortschatz corpora (https://wortschatz.uni-leipzig.de) offered by Leipzig University, Germany. Data crawled from various news websites have been used for training, each corpus comprising one million sentences. For testing, corpora made of arbitrarily chosen websites have been used, each comprising ten thousand sentences. From each test corpus, a random unsorted subset of 1000 single words, 1000 word pairs and 1000 sentences has been extracted, respectively. Given the generated test data, I have compared the detection results of Lingua, and Whatlanggo running over the data of Lingua's supported 75 languages. Additionally, I have added Google's CLD3 (https://github.com/google/cld3/) to the comparison with the help of the gocld3 bindings (https://github.com/jmhodges/gocld3). Languages that are not supported by CLD3 or Whatlanggo are simply ignored during the detection process. Lingua clearly outperforms its contenders. Every language detector uses a probabilistic n-gram (https://en.wikipedia.org/wiki/N-gram) model trained on the character distribution in some training corpus. Most libraries only use n-grams of size 3 (trigrams) which is satisfactory for detecting the language of longer text fragments consisting of multiple sentences. For short phrases or single words, however, trigrams are not enough. The shorter the input text is, the less n-grams are available. The probabilities estimated from such few n-grams are not reliable. This is why Lingua makes use of n-grams of sizes 1 up to 5 which results in much more accurate prediction of the correct language. A second important difference is that Lingua does not only use such a statistical model, but also a rule-based engine. This engine first determines the alphabet of the input text and searches for characters which are unique in one or more languages. If exactly one language can be reliably chosen this way, the statistical model is not necessary anymore. In any case, the rule-based engine filters out languages that do not satisfy the conditions of the input text. Only then, in a second step, the probabilistic n-gram model is taken into consideration. This makes sense because loading less language models means less memory consumption and better runtime performance. In general, it is always a good idea to restrict the set of languages to be considered in the classification process using the respective api methods. If you know beforehand that certain languages are never to occur in an input text, do not let those take part in the classifcation process. The filtering mechanism of the rule-based engine is quite good, however, filtering based on your own knowledge of the input text is always preferable. There might be classification tasks where you know beforehand that your language data is definitely not written in Latin, for instance. The detection accuracy can become better in such cases if you exclude certain languages from the decision process or just explicitly include relevant languages. Knowing about the most likely language is nice but how reliable is the computed likelihood? And how less likely are the other examined languages in comparison to the most likely one? In the example below, a slice of ConfidenceValue is returned containing those languages which the calling instance of LanguageDetector has been built from. The entries are sorted by their confidence value in descending order. Each value is a probability between 0.0 and 1.0. The probabilities of all languages will sum to 1.0. If the language is unambiguously identified by the rule engine, the value 1.0 will always be returned for this language. The other languages will receive a value of 0.0. By default, Lingua uses lazy-loading to load only those language models on demand which are considered relevant by the rule-based filter engine. For web services, for instance, it is rather beneficial to preload all language models into memory to avoid unexpected latency while waiting for the service response. If you want to enable the eager-loading mode, you can do it as seen below. Multiple instances of LanguageDetector share the same language models in memory which are accessed asynchronously by the instances. By default, Lingua returns the most likely language for a given input text. However, there are certain words that are spelled the same in more than one language. The word `prologue`, for instance, is both a valid English and French word. Lingua would output either English or French which might be wrong in the given context. For cases like that, it is possible to specify a minimum relative distance that the logarithmized and summed up probabilities for each possible language have to satisfy. It can be stated as seen below. Be aware that the distance between the language probabilities is dependent on the length of the input text. The longer the input text, the larger the distance between the languages. So if you want to classify very short text phrases, do not set the minimum relative distance too high. Otherwise Unknown will be returned most of the time as in the example below. This is the return value for cases where language detection is not reliably possible.

Package tracing provides a tracing library, in order to allow for precise automatic grading in CPSC 416. A trace provides a precise, ordered representation of what your assignment code is doing (well, what it says it's doing), which can be used to assess some things that are unclear from either unit testing or code inspection. These include correct concurrency management, as well as properly following any sequencing/causality rules required by the protocol you are implementing. The tracing library is split into two parts: the tracing server TracingServer, and the tracing client Tracer. You should have one instance of Tracer per network node, and you should first get access to a Trace and then you can record an action by calling Trace.RecordAction(action). A Trace is a set of recorded actions that are associated with a unique trace ID. With traces, actions are recorded as part of traces. Each report will be defined as a struct type, whose fields will list the details of a given action. These reports generally double as logging statements, which can be turned off and on with Tracer.SetShouldPrint. The TracingServer will aggregate all recorded actions and write them out to a JSON file, which can be used both for grading and for debugging via external processing. Moreover, tracing server generates a ShiViz-compatible log that can be used with ShiViz to visualize the execution of the system.

Package gofpdf implements a PDF document generator with high level support for text, drawing and images. • Choice of measurement unit, page format and margins • Page header and footer management • Automatic page breaks, line breaks, and text justification • Inclusion of JPEG, PNG, GIF, TIFF and basic path-only SVG images • Colors, gradients and alpha channel transparency • Outline bookmarks • Internal and external links • TrueType, Type1 and encoding support • Page compression • Lines, Bézier curves, arcs, and ellipses • Rotation, scaling, skewing, translation, and mirroring • Clipping • Document protection • Layers • Templates • Barcodes gofpdf has no dependencies other than the Go standard library. All tests pass on Linux, Mac and Windows platforms. Like FPDF version 1.7, from which gofpdf is derived, this package does not yet support UTF-8 fonts. In particular, languages that require more than one code page such as Chinese, Japanese, and Arabic are not currently supported. This is explained in issue 109. However, support is provided to automatically translate UTF-8 runes to code page encodings for languages that have fewer than 256 glyphs. To install the package on your system, run Later, to receive updates, run The following Go code generates a simple PDF file. See the functions in the fpdf_test.go file (shown as examples in this documentation) for more advanced PDF examples. If an error occurs in an Fpdf method, an internal error field is set. After this occurs, Fpdf method calls typically return without performing any operations and the error state is retained. This error management scheme facilitates PDF generation since individual method calls do not need to be examined for failure; it is generally sufficient to wait until after Output() is called. For the same reason, if an error occurs in the calling application during PDF generation, it may be desirable for the application to transfer the error to the Fpdf instance by calling the SetError() method or the SetErrorf() method. At any time during the life cycle of the Fpdf instance, the error state can be determined with a call to Ok() or Err(). The error itself can be retrieved with a call to Error(). This package is a relatively straightforward translation from the original FPDF library written in PHP (despite the caveat in the introduction to Effective Go). The API names have been retained even though the Go idiom would suggest otherwise (for example, pdf.GetX() is used rather than simply pdf.X()). The similarity of the two libraries makes the original FPDF website a good source of information. It includes a forum and FAQ. However, some internal changes have been made. Page content is built up using buffers (of type bytes.Buffer) rather than repeated string concatenation. Errors are handled as explained above rather than panicking. Output is generated through an interface of type io.Writer or io.WriteCloser. A number of the original PHP methods behave differently based on the type of the arguments that are passed to them; in these cases additional methods have been exported to provide similar functionality. Font definition files are produced in JSON rather than PHP. A side effect of running "go test ./..." is the production of a number of example PDFs. These can be found in the gofpdf/pdf directory after the tests complete. Please note that these examples run in the context of a test. In order run an example as a standalone application, you'll need to examine fpdf_test.go for some helper routines, for example exampleFilename() and summary(). Example PDFs can be compared with reference copies in order to verify that they have been generated as expected. This comparison will be performed if a PDF with the same name as the example PDF is placed in the gofpdf/pdf/reference directory. The routine that summarizes an example will look for this file and, if found, will call ComparePDFFiles() to check the example PDF for equality with its reference PDF. If differences exist between the two files they will be printed to standard output and the test will fail. If the reference file is missing, the comparison is considered to succeed. In order to successfully compare two PDFs, the placement of internal resources must be consistent and the internal creation timestamps must be the same. To do this, the methods SetCatalogSort() and SetCreationDate() need to be called for both files. This is done automatically for all examples. Nothing special is required to use the standard PDF fonts (courier, helvetica, times, zapfdingbats) in your documents other than calling SetFont(). In order to use a different TrueType or Type1 font, you will need to generate a font definition file and, if the font will be embedded into PDFs, a compressed version of the font file. This is done by calling the MakeFont function or using the included makefont command line utility. To create the utility, cd into the makefont subdirectory and run "go build". This will produce a standalone executable named makefont. Select the appropriate encoding file from the font subdirectory and run the command as in the following example. In your PDF generation code, call AddFont() to load the font and, as with the standard fonts, SetFont() to begin using it. Most examples, including the package example, demonstrate this method. Good sources of free, open-source fonts include http://www.google.com/fonts/ and http://dejavu-fonts.org/. The draw2d package (https://github.com/llgcode/draw2d) is a two dimensional vector graphics library that can generate output in different forms. It uses gofpdf for its document production mode. gofpdf is a global community effort and you are invited to make it even better. If you have implemented a new feature or corrected a problem, please consider contributing your change to the project. A contribution that does not directly pertain to the core functionality of gofpdf should be placed in its own directory directly beneath the `contrib` directory. Here are guidelines for making submissions. Your change should • be compatible with the MIT License • be properly documented • be formatted with `go fmt` • include an example in fpdf_test.go if appropriate • conform to the standards of golint (https://github.com/golang/lint) and go vet (https://godoc.org/golang.org/x/tools/cmd/vet), that is, `golint .` and `go vet .` should not generate any warnings • not diminish test coverage (https://blog.golang.org/cover) Pull requests (https://help.github.com/articles/using-pull-requests/) work nicely as a means of contributing your changes. gofpdf is released under the MIT License. It is copyrighted by Kurt Jung and the contributors acknowledged below. This package's code and documentation are closely derived from the FPDF library (http://www.fpdf.org/) created by Olivier Plathey, and a number of font and image resources are copied directly from it. Drawing support is adapted from the FPDF geometric figures script by David Hernández Sanz. Transparency support is adapted from the FPDF transparency script by Martin Hall-May. Support for gradients and clipping is adapted from FPDF scripts by Andreas Würmser. Support for outline bookmarks is adapted from Olivier Plathey by Manuel Cornes. Layer support is adapted from Olivier Plathey. Support for transformations is adapted from the FPDF transformation script by Moritz Wagner and Andreas Würmser. PDF protection is adapted from the work of Klemen Vodopivec for the FPDF product. Lawrence Kesteloot provided code to allow an image's extent to be determined prior to placement. Support for vertical alignment within a cell was provided by Stefan Schroeder. Ivan Daniluk generalized the font and image loading code to use the Reader interface while maintaining backward compatibility. Anthony Starks provided code for the Polygon function. Robert Lillack provided the Beziergon function and corrected some naming issues with the internal curve function. Claudio Felber provided implementations for dashed line drawing and generalized font loading. Stani Michiels provided support for multi-segment path drawing with smooth line joins, line join styles, enhanced fill modes, and has helped greatly with package presentation and tests. Templating is adapted by Marcus Downing from the FPDF_Tpl library created by Jan Slabon and Setasign. Jelmer Snoeck contributed packages that generate a variety of barcodes and help with registering images on the web. Jelmer Snoek and Guillermo Pascual augmented the basic HTML functionality with aligned text. Kent Quirk implemented backwards-compatible support for reading DPI from images that support it, and for setting DPI manually and then having it properly taken into account when calculating image size. Paulo Coutinho provided support for static embedded fonts. Bruno Michel has provided valuable assistance with the code. • Handle UTF-8 source text natively. Until then, automatic translation of UTF-8 runes to code page bytes is provided. • Improve test coverage as reported by the coverage tool. This example demonstrates the generation of a simple PDF document. Note that since only core fonts are used (in this case Arial, a synonym for Helvetica), an empty string can be specified for the font directory in the call to New(). Note also that the example.Filename() and example.Summary() functions belong to a separate, internal package and are not part of the gofpdf library. If an error occurs at some point during the construction of the document, subsequent method calls exit immediately and the error is finally retrieved with the output call where it can be handled by the application.

Package validate provides methods to validate a swagger specification, as well as tools to validate data against their schema. This package follows Swagger 2.0. specification (aka OpenAPI 2.0). Reference can be found here: https://github.com/OAI/OpenAPI-Specification/blob/master/versions/2.0.md. Validates a spec document (from JSON or YAML) against the JSON schema for swagger, then checks a number of extra rules that can't be expressed in JSON schema. Entry points: Reported as errors: Reported as warnings: The schema validation toolkit validates data against JSON-schema-draft 04 schema. It is tested against the full json-schema-testing-suite (https://github.com/json-schema-org/JSON-Schema-Test-Suite), except for the optional part (bignum, ECMA regexp, ...). It supports the complete JSON-schema vocabulary, including keywords not supported by Swagger (e.g. additionalItems, ...) Entry points: With the current version of this package, the following aspects of swagger are not yet supported:

Package gofpdf implements a PDF document generator with high level support for text, drawing and images. - UTF-8 support - Choice of measurement unit, page format and margins - Page header and footer management - Automatic page breaks, line breaks, and text justification - Inclusion of JPEG, PNG, GIF, TIFF and basic path-only SVG images - Colors, gradients and alpha channel transparency - Outline bookmarks - Internal and external links - TrueType, Type1 and encoding support - Page compression - Lines, Bézier curves, arcs, and ellipses - Rotation, scaling, skewing, translation, and mirroring - Clipping - Document protection - Layers - Templates - Barcodes - Charting facility - Import PDFs as templates gofpdf has no dependencies other than the Go standard library. All tests pass on Linux, Mac and Windows platforms. gofpdf supports UTF-8 TrueType fonts and “right-to-left” languages. Note that Chinese, Japanese, and Korean characters may not be included in many general purpose fonts. For these languages, a specialized font (for example, NotoSansSC for simplified Chinese) can be used. Also, support is provided to automatically translate UTF-8 runes to code page encodings for languages that have fewer than 256 glyphs. This repository will not be maintained, at least for some unknown duration. But it is hoped that gofpdf has a bright future in the open source world. Due to Go’s promise of compatibility, gofpdf should continue to function without modification for a longer time than would be the case with many other languages. Forks should be based on the last viable commit. Tools such as active-forks can be used to select a fork that looks promising for your needs. If a particular fork looks like it has taken the lead in attracting followers, this README will be updated to point people in that direction. The efforts of all contributors to this project have been deeply appreciated. Best wishes to all of you. To install the package on your system, run Later, to receive updates, run The following Go code generates a simple PDF file. See the functions in the fpdf_test.go file (shown as examples in this documentation) for more advanced PDF examples. If an error occurs in an Fpdf method, an internal error field is set. After this occurs, Fpdf method calls typically return without performing any operations and the error state is retained. This error management scheme facilitates PDF generation since individual method calls do not need to be examined for failure; it is generally sufficient to wait until after Output() is called. For the same reason, if an error occurs in the calling application during PDF generation, it may be desirable for the application to transfer the error to the Fpdf instance by calling the SetError() method or the SetErrorf() method. At any time during the life cycle of the Fpdf instance, the error state can be determined with a call to Ok() or Err(). The error itself can be retrieved with a call to Error(). This package is a relatively straightforward translation from the original FPDF library written in PHP (despite the caveat in the introduction to Effective Go). The API names have been retained even though the Go idiom would suggest otherwise (for example, pdf.GetX() is used rather than simply pdf.X()). The similarity of the two libraries makes the original FPDF website a good source of information. It includes a forum and FAQ. However, some internal changes have been made. Page content is built up using buffers (of type bytes.Buffer) rather than repeated string concatenation. Errors are handled as explained above rather than panicking. Output is generated through an interface of type io.Writer or io.WriteCloser. A number of the original PHP methods behave differently based on the type of the arguments that are passed to them; in these cases additional methods have been exported to provide similar functionality. Font definition files are produced in JSON rather than PHP. A side effect of running go test ./... is the production of a number of example PDFs. These can be found in the gofpdf/pdf directory after the tests complete. Please note that these examples run in the context of a test. In order run an example as a standalone application, you’ll need to examine fpdf_test.go for some helper routines, for example exampleFilename() and summary(). Example PDFs can be compared with reference copies in order to verify that they have been generated as expected. This comparison will be performed if a PDF with the same name as the example PDF is placed in the gofpdf/pdf/reference directory and if the third argument to ComparePDFFiles() in internal/example/example.go is true. (By default it is false.) The routine that summarizes an example will look for this file and, if found, will call ComparePDFFiles() to check the example PDF for equality with its reference PDF. If differences exist between the two files they will be printed to standard output and the test will fail. If the reference file is missing, the comparison is considered to succeed. In order to successfully compare two PDFs, the placement of internal resources must be consistent and the internal creation timestamps must be the same. To do this, the methods SetCatalogSort() and SetCreationDate() need to be called for both files. This is done automatically for all examples. Nothing special is required to use the standard PDF fonts (courier, helvetica, times, zapfdingbats) in your documents other than calling SetFont(). You should use AddUTF8Font() or AddUTF8FontFromBytes() to add a TrueType UTF-8 encoded font. Use RTL() and LTR() methods switch between “right-to-left” and “left-to-right” mode. In order to use a different non-UTF-8 TrueType or Type1 font, you will need to generate a font definition file and, if the font will be embedded into PDFs, a compressed version of the font file. This is done by calling the MakeFont function or using the included makefont command line utility. To create the utility, cd into the makefont subdirectory and run “go build”. This will produce a standalone executable named makefont. Select the appropriate encoding file from the font subdirectory and run the command as in the following example. In your PDF generation code, call AddFont() to load the font and, as with the standard fonts, SetFont() to begin using it. Most examples, including the package example, demonstrate this method. Good sources of free, open-source fonts include Google Fonts and DejaVu Fonts. The draw2d package is a two dimensional vector graphics library that can generate output in different forms. It uses gofpdf for its document production mode. gofpdf is a global community effort and you are invited to make it even better. If you have implemented a new feature or corrected a problem, please consider contributing your change to the project. A contribution that does not directly pertain to the core functionality of gofpdf should be placed in its own directory directly beneath the contrib directory. Here are guidelines for making submissions. Your change should - be compatible with the MIT License - be properly documented - be formatted with go fmt - include an example in fpdf_test.go if appropriate - conform to the standards of golint and go vet, that is, golint . and go vet . should not generate any warnings - not diminish test coverage Pull requests are the preferred means of accepting your changes. gofpdf is released under the MIT License. It is copyrighted by Kurt Jung and the contributors acknowledged below. This package’s code and documentation are closely derived from the FPDF library created by Olivier Plathey, and a number of font and image resources are copied directly from it. Bruno Michel has provided valuable assistance with the code. Drawing support is adapted from the FPDF geometric figures script by David Hernández Sanz. Transparency support is adapted from the FPDF transparency script by Martin Hall-May. Support for gradients and clipping is adapted from FPDF scripts by Andreas Würmser. Support for outline bookmarks is adapted from Olivier Plathey by Manuel Cornes. Layer support is adapted from Olivier Plathey. Support for transformations is adapted from the FPDF transformation script by Moritz Wagner and Andreas Würmser. PDF protection is adapted from the work of Klemen Vodopivec for the FPDF product. Lawrence Kesteloot provided code to allow an image’s extent to be determined prior to placement. Support for vertical alignment within a cell was provided by Stefan Schroeder. Ivan Daniluk generalized the font and image loading code to use the Reader interface while maintaining backward compatibility. Anthony Starks provided code for the Polygon function. Robert Lillack provided the Beziergon function and corrected some naming issues with the internal curve function. Claudio Felber provided implementations for dashed line drawing and generalized font loading. Stani Michiels provided support for multi-segment path drawing with smooth line joins, line join styles, enhanced fill modes, and has helped greatly with package presentation and tests. Templating is adapted by Marcus Downing from the FPDF_Tpl library created by Jan Slabon and Setasign. Jelmer Snoeck contributed packages that generate a variety of barcodes and help with registering images on the web. Jelmer Snoek and Guillermo Pascual augmented the basic HTML functionality with aligned text. Kent Quirk implemented backwards-compatible support for reading DPI from images that support it, and for setting DPI manually and then having it properly taken into account when calculating image size. Paulo Coutinho provided support for static embedded fonts. Dan Meyers added support for embedded JavaScript. David Fish added a generic alias-replacement function to enable, among other things, table of contents functionality. Andy Bakun identified and corrected a problem in which the internal catalogs were not sorted stably. Paul Montag added encoding and decoding functionality for templates, including images that are embedded in templates; this allows templates to be stored independently of gofpdf. Paul also added support for page boxes used in printing PDF documents. Wojciech Matusiak added supported for word spacing. Artem Korotkiy added support of UTF-8 fonts. Dave Barnes added support for imported objects and templates. Brigham Thompson added support for rounded rectangles. Joe Westcott added underline functionality and optimized image storage. Benoit KUGLER contributed support for rectangles with corners of unequal radius, modification times, and for file attachments and annotations. - Remove all legacy code page font support; use UTF-8 exclusively - Improve test coverage as reported by the coverage tool. Example demonstrates the generation of a simple PDF document. Note that since only core fonts are used (in this case Arial, a synonym for Helvetica), an empty string can be specified for the font directory in the call to New(). Note also that the example.Filename() and example.Summary() functions belong to a separate, internal package and are not part of the gofpdf library. If an error occurs at some point during the construction of the document, subsequent method calls exit immediately and the error is finally retrieved with the output call where it can be handled by the application.

Package gofpdf implements a PDF document generator with high level support for text, drawing and images. - UTF-8 support - Choice of measurement unit, page format and margins - Page header and footer management - Automatic page breaks, line breaks, and text justification - Inclusion of JPEG, PNG, GIF, TIFF and basic path-only SVG images - Colors, gradients and alpha channel transparency - Outline bookmarks - Internal and external links - TrueType, Type1 and encoding support - Page compression - Lines, Bézier curves, arcs, and ellipses - Rotation, scaling, skewing, translation, and mirroring - Clipping - Document protection - Layers - Templates - Barcodes - Charting facility - Import PDFs as templates gofpdf has no dependencies other than the Go standard library. All tests pass on Linux, Mac and Windows platforms. gofpdf supports UTF-8 TrueType fonts and “right-to-left” languages. Note that Chinese, Japanese, and Korean characters may not be included in many general purpose fonts. For these languages, a specialized font (for example, NotoSansSC for simplified Chinese) can be used. Also, support is provided to automatically translate UTF-8 runes to code page encodings for languages that have fewer than 256 glyphs. This repository will not be maintained, at least for some unknown duration. But it is hoped that gofpdf has a bright future in the open source world. Due to Go’s promise of compatibility, gofpdf should continue to function without modification for a longer time than would be the case with many other languages. Forks should be based on the last viable commit. Tools such as active-forks can be used to select a fork that looks promising for your needs. If a particular fork looks like it has taken the lead in attracting followers, this README will be updated to point people in that direction. The efforts of all contributors to this project have been deeply appreciated. Best wishes to all of you. To install the package on your system, run Later, to receive updates, run The following Go code generates a simple PDF file. See the functions in the fpdf_test.go file (shown as examples in this documentation) for more advanced PDF examples. If an error occurs in an Fpdf method, an internal error field is set. After this occurs, Fpdf method calls typically return without performing any operations and the error state is retained. This error management scheme facilitates PDF generation since individual method calls do not need to be examined for failure; it is generally sufficient to wait until after Output() is called. For the same reason, if an error occurs in the calling application during PDF generation, it may be desirable for the application to transfer the error to the Fpdf instance by calling the SetError() method or the SetErrorf() method. At any time during the life cycle of the Fpdf instance, the error state can be determined with a call to Ok() or Err(). The error itself can be retrieved with a call to Error(). This package is a relatively straightforward translation from the original FPDF library written in PHP (despite the caveat in the introduction to Effective Go). The API names have been retained even though the Go idiom would suggest otherwise (for example, pdf.GetX() is used rather than simply pdf.X()). The similarity of the two libraries makes the original FPDF website a good source of information. It includes a forum and FAQ. However, some internal changes have been made. Page content is built up using buffers (of type bytes.Buffer) rather than repeated string concatenation. Errors are handled as explained above rather than panicking. Output is generated through an interface of type io.Writer or io.WriteCloser. A number of the original PHP methods behave differently based on the type of the arguments that are passed to them; in these cases additional methods have been exported to provide similar functionality. Font definition files are produced in JSON rather than PHP. A side effect of running go test ./... is the production of a number of example PDFs. These can be found in the gofpdf/pdf directory after the tests complete. Please note that these examples run in the context of a test. In order run an example as a standalone application, you’ll need to examine fpdf_test.go for some helper routines, for example exampleFilename() and summary(). Example PDFs can be compared with reference copies in order to verify that they have been generated as expected. This comparison will be performed if a PDF with the same name as the example PDF is placed in the gofpdf/pdf/reference directory and if the third argument to ComparePDFFiles() in internal/example/example.go is true. (By default it is false.) The routine that summarizes an example will look for this file and, if found, will call ComparePDFFiles() to check the example PDF for equality with its reference PDF. If differences exist between the two files they will be printed to standard output and the test will fail. If the reference file is missing, the comparison is considered to succeed. In order to successfully compare two PDFs, the placement of internal resources must be consistent and the internal creation timestamps must be the same. To do this, the methods SetCatalogSort() and SetCreationDate() need to be called for both files. This is done automatically for all examples. Nothing special is required to use the standard PDF fonts (courier, helvetica, times, zapfdingbats) in your documents other than calling SetFont(). You should use AddUTF8Font() or AddUTF8FontFromBytes() to add a TrueType UTF-8 encoded font. Use RTL() and LTR() methods switch between “right-to-left” and “left-to-right” mode. In order to use a different non-UTF-8 TrueType or Type1 font, you will need to generate a font definition file and, if the font will be embedded into PDFs, a compressed version of the font file. This is done by calling the MakeFont function or using the included makefont command line utility. To create the utility, cd into the makefont subdirectory and run “go build”. This will produce a standalone executable named makefont. Select the appropriate encoding file from the font subdirectory and run the command as in the following example. In your PDF generation code, call AddFont() to load the font and, as with the standard fonts, SetFont() to begin using it. Most examples, including the package example, demonstrate this method. Good sources of free, open-source fonts include Google Fonts and DejaVu Fonts. The draw2d package is a two dimensional vector graphics library that can generate output in different forms. It uses gofpdf for its document production mode. gofpdf is a global community effort and you are invited to make it even better. If you have implemented a new feature or corrected a problem, please consider contributing your change to the project. A contribution that does not directly pertain to the core functionality of gofpdf should be placed in its own directory directly beneath the contrib directory. Here are guidelines for making submissions. Your change should - be compatible with the MIT License - be properly documented - be formatted with go fmt - include an example in fpdf_test.go if appropriate - conform to the standards of golint and go vet, that is, golint . and go vet . should not generate any warnings - not diminish test coverage Pull requests are the preferred means of accepting your changes. gofpdf is released under the MIT License. It is copyrighted by Kurt Jung and the contributors acknowledged below. This package’s code and documentation are closely derived from the FPDF library created by Olivier Plathey, and a number of font and image resources are copied directly from it. Bruno Michel has provided valuable assistance with the code. Drawing support is adapted from the FPDF geometric figures script by David Hernández Sanz. Transparency support is adapted from the FPDF transparency script by Martin Hall-May. Support for gradients and clipping is adapted from FPDF scripts by Andreas Würmser. Support for outline bookmarks is adapted from Olivier Plathey by Manuel Cornes. Layer support is adapted from Olivier Plathey. Support for transformations is adapted from the FPDF transformation script by Moritz Wagner and Andreas Würmser. PDF protection is adapted from the work of Klemen Vodopivec for the FPDF product. Lawrence Kesteloot provided code to allow an image’s extent to be determined prior to placement. Support for vertical alignment within a cell was provided by Stefan Schroeder. Ivan Daniluk generalized the font and image loading code to use the Reader interface while maintaining backward compatibility. Anthony Starks provided code for the Polygon function. Robert Lillack provided the Beziergon function and corrected some naming issues with the internal curve function. Claudio Felber provided implementations for dashed line drawing and generalized font loading. Stani Michiels provided support for multi-segment path drawing with smooth line joins, line join styles, enhanced fill modes, and has helped greatly with package presentation and tests. Templating is adapted by Marcus Downing from the FPDF_Tpl library created by Jan Slabon and Setasign. Jelmer Snoeck contributed packages that generate a variety of barcodes and help with registering images on the web. Jelmer Snoek and Guillermo Pascual augmented the basic HTML functionality with aligned text. Kent Quirk implemented backwards-compatible support for reading DPI from images that support it, and for setting DPI manually and then having it properly taken into account when calculating image size. Paulo Coutinho provided support for static embedded fonts. Dan Meyers added support for embedded JavaScript. David Fish added a generic alias-replacement function to enable, among other things, table of contents functionality. Andy Bakun identified and corrected a problem in which the internal catalogs were not sorted stably. Paul Montag added encoding and decoding functionality for templates, including images that are embedded in templates; this allows templates to be stored independently of gofpdf. Paul also added support for page boxes used in printing PDF documents. Wojciech Matusiak added supported for word spacing. Artem Korotkiy added support of UTF-8 fonts. Dave Barnes added support for imported objects and templates. Brigham Thompson added support for rounded rectangles. Joe Westcott added underline functionality and optimized image storage. Benoit KUGLER contributed support for rectangles with corners of unequal radius, modification times, and for file attachments and annotations. - Remove all legacy code page font support; use UTF-8 exclusively - Improve test coverage as reported by the coverage tool. Example demonstrates the generation of a simple PDF document. Note that since only core fonts are used (in this case Arial, a synonym for Helvetica), an empty string can be specified for the font directory in the call to New(). Note also that the example.Filename() and example.Summary() functions belong to a separate, internal package and are not part of the gofpdf library. If an error occurs at some point during the construction of the document, subsequent method calls exit immediately and the error is finally retrieved with the output call where it can be handled by the application.

Package assert, for writing checks in unit tests This package provides functions to reduce the amount of code needed to write simple assertions. It implements the best practice pattern where the output of a failure explains what the check "got" and what it wanted. The assert functions are defined such that writing requires less code but still are easy to understand. It works by decorating the standard testing.T type in your test and report (Fatal) the offending asserting call if a check fails. Example which will report Examples: (using the dot import) You can create and use your own checks by implementing the RelationalOperator.

Schob is a client for "shovey", a mechanism for pushing jobs to client nodes. Currently it's specific to goiardi, but a more general implementation is planned. Running schob requires a goiardi server (both to send jobs to the schob client, and for the schob client to send reports to) and serf running with the goiardi server and on every client node that will run shovey jobs. The `knife-shove` plugin from https://github.com/ctdk/knife-shove is required to submit and administer shovey jobs. Schob has the following golang dependencies outside of the standard library: go-flags, toml, logger, the go-chef chef library, serf, go-uuid, and the chefcrypto library from goiardi (only for tests). The easiest way to install these dependencies is to include the `-t` flag when using `go get` to install schob. The easiest way to install schob is with the shovey-jobs cookbook, located at https://github.com/ctdk/shovey-jobs. At the moment it only supports Debian, though, so for now installing on non-Debian platforms will have to install schob by hand. If you already have a binary you can skip to number 2. 0. Set up go and configure go. (http://golang.org/doc/install.html) Alternately, if you downloaded a precompiled binary, put that binary somewhere in your PATH. 3. Make sure goiardi is running on its server, along with serf, and that it's configured to use serf and shovey. You will also need to make the RSA public/private key pair for signing and verifying shovey jobs. 4. Start up serf on the node, making sure that it joins the same serf cluster goairdi's serf is running in. 5. Make sure the shovey signing public RSA key is installed on the node. 6. Create a whitelist.json file for the node, with whitelisted jobs that are allowed to run on the node. See the example whitelist.json file in `test/whitelist.json` for guidance. 7. Run schob. Schob can take a configuration file (an example is provided in `test/schob-example.conf`, or it can use the following command line options: Once schob is running on a node, run jobs on it with the `knife-shove` plugin. The full documentation for that can be found at https://github.com/ctdk/knife-shove, but here's a cheat sheet: 1. Fork the repository on Github 2. Create a named feature branch (like `add_component_x`) 3. Write your change 4. Write tests for your change (if applicable) 5. Run the tests, ensuring they all pass 6. Submit a Pull Request using Github * goiardi (https://github.com/ctdk/goiardi) * knife-shove (https://github.com/ctdk/knife-shove) * shovey-jobs cookbook (https://github.com/ctdk/shovey-jobs) * Goiardi's shovey documentation (https://github.com/ctdk/goiardi/blob/serfing/README.md#shovey) * Shovey API documentation (https://github.com/ctdk/goiardi/blob/serfing/shovey_api.md) Jeremy Bingham (<jbingham@gmail.com>) Schob is licensed under the Apache 2.0 License. See the LICENSE file for details. "Schob" is German for "shoved".

Package gofpdf implements a PDF document generator with high level support for text, drawing and images. • Choice of measurement unit, page format and margins • Page header and footer management • Automatic page breaks, line breaks, and text justification • Inclusion of JPEG, PNG, GIF, TIFF and basic path-only SVG images • Colors, gradients and alpha channel transparency • Outline bookmarks • Internal and external links • TrueType, Type1 and encoding support • Page compression • Lines, Bézier curves, arcs, and ellipses • Rotation, scaling, skewing, translation, and mirroring • Clipping • Document protection • Layers • Templates • Barcodes gofpdf has no dependencies other than the Go standard library. All tests pass on Linux, Mac and Windows platforms. Like FPDF version 1.7, from which gofpdf is derived, this package does not yet support UTF-8 fonts. In particular, languages that require more than one code page such as Chinese, Japanese, and Arabic are not currently supported. This is explained in issue 109. However, support is provided to automatically translate UTF-8 runes to code page encodings for languages that have fewer than 256 glyphs. To install the package on your system, run Later, to receive updates, run The following Go code generates a simple PDF file. See the functions in the fpdf_test.go file (shown as examples in this documentation) for more advanced PDF examples. If an error occurs in an Fpdf method, an internal error field is set. After this occurs, Fpdf method calls typically return without performing any operations and the error state is retained. This error management scheme facilitates PDF generation since individual method calls do not need to be examined for failure; it is generally sufficient to wait until after Output() is called. For the same reason, if an error occurs in the calling application during PDF generation, it may be desirable for the application to transfer the error to the Fpdf instance by calling the SetError() method or the SetErrorf() method. At any time during the life cycle of the Fpdf instance, the error state can be determined with a call to Ok() or Err(). The error itself can be retrieved with a call to Error(). This package is a relatively straightforward translation from the original FPDF library written in PHP (despite the caveat in the introduction to Effective Go). The API names have been retained even though the Go idiom would suggest otherwise (for example, pdf.GetX() is used rather than simply pdf.X()). The similarity of the two libraries makes the original FPDF website a good source of information. It includes a forum and FAQ. However, some internal changes have been made. Page content is built up using buffers (of type bytes.Buffer) rather than repeated string concatenation. Errors are handled as explained above rather than panicking. Output is generated through an interface of type io.Writer or io.WriteCloser. A number of the original PHP methods behave differently based on the type of the arguments that are passed to them; in these cases additional methods have been exported to provide similar functionality. Font definition files are produced in JSON rather than PHP. A side effect of running "go test ./..." is the production of a number of example PDFs. These can be found in the gofpdf/pdf directory after the tests complete. Please note that these examples run in the context of a test. In order run an example as a standalone application, you'll need to examine fpdf_test.go for some helper routines, for example exampleFilename() and summary(). Example PDFs can be compared with reference copies in order to verify that they have been generated as expected. This comparison will be performed if a PDF with the same name as the example PDF is placed in the gofpdf/pdf/reference directory. The routine that summarizes an example will look for this file and, if found, will call ComparePDFFiles() to check the example PDF for equality with its reference PDF. If differences exist between the two files they will be printed to standard output and the test will fail. If the reference file is missing, the comparison is considered to succeed. In order to successfully compare two PDFs, the placement of internal resources must be consistent and the internal creation timestamps must be the same. To do this, the methods SetCatalogSort() and SetCreationDate() need to be called for both files. This is done automatically for all examples. Nothing special is required to use the standard PDF fonts (courier, helvetica, times, zapfdingbats) in your documents other than calling SetFont(). In order to use a different TrueType or Type1 font, you will need to generate a font definition file and, if the font will be embedded into PDFs, a compressed version of the font file. This is done by calling the MakeFont function or using the included makefont command line utility. To create the utility, cd into the makefont subdirectory and run "go build". This will produce a standalone executable named makefont. Select the appropriate encoding file from the font subdirectory and run the command as in the following example. In your PDF generation code, call AddFont() to load the font and, as with the standard fonts, SetFont() to begin using it. Most examples, including the package example, demonstrate this method. Good sources of free, open-source fonts include http://www.google.com/fonts/ and http://dejavu-fonts.org/. The draw2d package (https://github.com/llgcode/draw2d) is a two dimensional vector graphics library that can generate output in different forms. It uses gofpdf for its document production mode. gofpdf is a global community effort and you are invited to make it even better. If you have implemented a new feature or corrected a problem, please consider contributing your change to the project. A contribution that does not directly pertain to the core functionality of gofpdf should be placed in its own directory directly beneath the `contrib` directory. Here are guidelines for making submissions. Your change should • be compatible with the MIT License • be properly documented • be formatted with `go fmt` • include an example in fpdf_test.go if appropriate • conform to the standards of golint (https://github.com/golang/lint) and go vet (https://godoc.org/golang.org/x/tools/cmd/vet), that is, `golint .` and `go vet .` should not generate any warnings • not diminish test coverage (https://blog.golang.org/cover) Pull requests (https://help.github.com/articles/using-pull-requests/) work nicely as a means of contributing your changes. gofpdf is released under the MIT License. It is copyrighted by Kurt Jung and the contributors acknowledged below. This package's code and documentation are closely derived from the FPDF library (http://www.fpdf.org/) created by Olivier Plathey, and a number of font and image resources are copied directly from it. Drawing support is adapted from the FPDF geometric figures script by David Hernández Sanz. Transparency support is adapted from the FPDF transparency script by Martin Hall-May. Support for gradients and clipping is adapted from FPDF scripts by Andreas Würmser. Support for outline bookmarks is adapted from Olivier Plathey by Manuel Cornes. Layer support is adapted from Olivier Plathey. Support for transformations is adapted from the FPDF transformation script by Moritz Wagner and Andreas Würmser. PDF protection is adapted from the work of Klemen Vodopivec for the FPDF product. Lawrence Kesteloot provided code to allow an image's extent to be determined prior to placement. Support for vertical alignment within a cell was provided by Stefan Schroeder. Ivan Daniluk generalized the font and image loading code to use the Reader interface while maintaining backward compatibility. Anthony Starks provided code for the Polygon function. Robert Lillack provided the Beziergon function and corrected some naming issues with the internal curve function. Claudio Felber provided implementations for dashed line drawing and generalized font loading. Stani Michiels provided support for multi-segment path drawing with smooth line joins, line join styles, enhanced fill modes, and has helped greatly with package presentation and tests. Templating is adapted by Marcus Downing from the FPDF_Tpl library created by Jan Slabon and Setasign. Jelmer Snoeck contributed packages that generate a variety of barcodes and help with registering images on the web. Jelmer Snoek and Guillermo Pascual augmented the basic HTML functionality with aligned text. Kent Quirk implemented backwards-compatible support for reading DPI from images that support it, and for setting DPI manually and then having it properly taken into account when calculating image size. Paulo Coutinho provided support for static embedded fonts. Bruno Michel has provided valuable assistance with the code. • Handle UTF-8 source text natively. Until then, automatic translation of UTF-8 runes to code page bytes is provided. • Improve test coverage as reported by the coverage tool. This example demonstrates the generation of a simple PDF document. Note that since only core fonts are used (in this case Arial, a synonym for Helvetica), an empty string can be specified for the font directory in the call to New(). Note also that the example.Filename() and example.Summary() functions belong to a separate, internal package and are not part of the gofpdf library. If an error occurs at some point during the construction of the document, subsequent method calls exit immediately and the error is finally retrieved with the output call where it can be handled by the application.

Package gofpdf implements a PDF document generator with high level support for text, drawing and images. • Choice of measurement unit, page format and margins • Page header and footer management • Automatic page breaks, line breaks, and text justification • Inclusion of JPEG, PNG, GIF and basic path-only SVG images • Colors, gradients and alpha channel transparency • Outline bookmarks • Internal and external links • TrueType, Type1 and encoding support • Page compression • Lines, Bézier curves, arcs, and ellipses • Rotation, scaling, skewing, translation, and mirroring • Clipping • Document protection gofpdf has no dependencies other than the Go standard library. All tests pass on Linux, Mac and Windows platforms. Like FPDF version 1.7, from which gofpdf is derived, this package does not yet support UTF-8 fonts. However, support is provided to translate UTF-8 runes to code page encodings. This package's code and documentation are closely derived from the FPDF library created by Olivier Plathey, and a number of font and image resources are copied directly from it. Drawing support is adapted from the FPDF geometric figures script by David Hernández Sanz. Transparency support is adapted from the FPDF transparency script by Martin Hall-May. Support for gradients and clipping is adapted from FPDF scripts by Andreas Würmser. Support for outline bookmarks is adapted from Olivier Plathey by Manuel Cornes. Support for transformations is adapted from the FPDF transformation script by Moritz Wagner and Andreas Würmser. PDF protection is adapted from the work of Klemen Vodopivec for the FPDF product. Lawrence Kesteloot provided code to allow an image's extent to be determined prior to placement. Support for vertical alignment within a cell was provided by Stefan Schroeder. Ivan Daniluk generalized the font and image loading code to use the Reader interface while maintaining backward compatibility. Anthony Starks provided code for the Polygon function. Bruno Michel has provided valuable assistance with the code. The FPDF website is http://www.fpdf.org/. gofpdf is copyrighted by Kurt Jung and is released under the MIT License. To install the package on your system, run Later, to receive updates, run The following Go code generates a simple PDF. See the tutorials in the fpdf_test.go file (shown as examples in this documentation) for more advanced PDF examples. If an error occurs in an Fpdf method, an internal error field is set. After this occurs, Fpdf method calls typically return without performing any operations and the error state is retained. This error management scheme facilitates PDF generation since individual method calls do not need to be examined for failure; it is generally sufficient to wait until after Output() is called. For the same reason, if an error occurs in the calling application during PDF generation, it may be desirable for the application to transfer the error to the Fpdf instance by calling the SetError() method or the SetErrorf() method. At any time during the life cycle of the Fpdf instance, the error state can be determined with a call to Ok() or Err(). The error itself can be retrieved with a call to Error(). This package is a relatively straightforward translation from the original FPDF library written in PHP (despite the caveat in the introduction to Effective Go). The API names have been retained even though the Go idiom would suggest otherwise (for example, pdf.GetX() is used rather than simply pdf.X()). The similarity of the two libraries makes the original FPDF website a good source of information. It includes a forum and FAQ. However, some internal changes have been made. Page content is built up using buffers (of type bytes.Buffer) rather than repeated string concatenation. Errors are handled as explained above rather than panicking. Output is generated through an interface of type io.Writer or io.WriteCloser. A number of the original PHP methods behave differently based on the type of the arguments that are passed to them; in these cases additional methods have been exported to provide similar functionality. Font definition files are produced in JSON rather than PHP. A side effect of running "go test" is the production of the tutorial PDFs. These can be found in the gofpdf/pdf directory after the tests complete. Nothing special is required to use the standard PDF fonts (courier, helvetica, times, zapfdingbats) in your documents other than calling SetFont(). In order to use a different TrueType or Type1 font, you will need to generate a font definition file and, if the font will be embedded into PDFs, a compressed version of the font file. This is done by calling the MakeFont function or using the included makefont command line utility. To create the utility, cd into the makefont subdirectory and run "go build". This will produce a standalone executable named makefont. Select the appropriate encoding file from the font subdirectory and run the command as in the following example. In your PDF generation code, call AddFont() to load the font and, as with the standard fonts, SetFont() to begin using it. See tutorial 7 for an example. Good sources of free, open-source fonts include http://www.google.com/fonts/ and http://dejavu-fonts.org/. • Handle UTF-8 source text natively. Until then, automatic translation of UTF-8 runes to code page bytes is provided. • Improve test coverage as reported by the coverage tool.

The Bolo Monitoring and Analytics Daemon bmad is an agent designed to execute monitoring and analytics checks at periodic configured intervals, submitting results up to a Bolo server. --config, -c FILE --test, -t --match, -m REGEX --noop, -n --help, -h Profiling: --cpuprofile --memprofile --blockprofile bmad configs are YAML config files, describing global configuration, as well as all the checks that should be run. Below is an example configuration with all available directives filled in with their defaults: Any files ending in '.conf' in the include_dir directory will be automatically loaded as additional hashes of check configurations, which are merged in with any found in the main config file. If there are any duplicate check names found, the earliest seen takes precedence. Running checks is the primary purpose of bmad. Checks are scheduled, and run. Once complete, their standard output is captured and sent up to bolo. In addition to this, metadata regarding the check execution will automatically be sent up to bolo, to enable easier monitoring of the monitoring system. If the check is a bulk check, and is configured to do so, its return code will be processed, and a STATE result will be sent up to bolo as well. As you may have surmised by now, checks come in two flavors: regular, and bulk. Regular checks are single events, usually reporting the STATE of a specific thing and perhaps some related COUNTERS or SAMPLES. Bulk checks generally run a whole bunch of tests, and submit a large amount of performance data up to bolo. Bulk checks are always run at their regular interval, and circumvent bmad's retry logic, As mentioned above, they also can be configured to have their success/failure submitted up as a STATE message. Checks share many directives as the main config file, to override the global defaults. Any check-specific settings take precedence over the global values (since that's generally what one would expect of an override). For the case of environment variables, the hash of environment variables is merged together, with any conflicts being chosen in favor of the check-specific value. Below are all the available check configuration directives: For proper retry and status submission, checks must exit with an exit code that indicates its STATE, according to the following values: Here's a real world example of /etc/bmad.conf: And an example /etc/bmad.d/sar.conf NOTE: the /etc/bmad.d/sar.conf file has checks defined at the top level of the file, and does not contain a 'checks' key, like /etc/bmad.conf. Written by Geoff Franks <geoff.franks@gmail.com>

Package CloudForest implements ensembles of decision trees for machine learning in pure Go (golang to search engines). It allows for a number of related algorithms for classification, regression, feature selection and structure analysis on heterogeneous numerical/categorical data with missing values. These include: Breiman and Cutler's Random Forest for Classification and Regression Adaptive Boosting (AdaBoost) Classification Gradiant Boosting Tree Regression Entropy and Cost driven classification L1 regression Feature selection with artificial contrasts Proximity and model structure analysis Roughly balanced bagging for unbalanced classification The API hasn't stabilized yet and may change rapidly. Tests and benchmarks have been performed only on embargoed data sets and can not yet be released. Library Documentation is in code and can be viewed with godoc or live at: http://godoc.org/github.com/IlyaLab/CloudForest Documentation of command line utilities and file formats can be found in README.md, which can be viewed fromated on github: http://github.com/IlyaLab/CloudForest Pull requests and bug reports are welcome. CloudForest was created by Ryan Bressler and is being developed in the Shumelivich Lab at the Institute for Systems Biology for use on genomic/biomedical data with partial support from The Cancer Genome Atlas and the Inova Translational Medicine Institute. CloudForest is intended to provide fast, comprehensible building blocks that can be used to implement ensembles of decision trees. CloudForest is written in Go to allow a data scientist to develop and scale new models and analysis quickly instead of having to modify complex legacy code. Data structures and file formats are chosen with use in multi threaded and cluster environments in mind. Go's support for function types is used to provide a interface to run code as data is percolated through a tree. This method is flexible enough that it can extend the tree being analyzed. Growing a decision tree using Breiman and Cutler's method can be done in an anonymous function/closure passed to a tree's root node's Recurse method: This allows a researcher to include whatever additional analysis they need (importance scores, proximity etc) in tree growth. The same Recurse method can also be used to analyze existing forests to tabulate scores or extract structure. Utilities like leafcount and errorrate use this method to tabulate data about the tree in collection objects. Decision tree's are grown with the goal of reducing "Impurity" which is usually defined as Gini Impurity for categorical targets or mean squared error for numerical targets. CloudForest grows trees against the Target interface which allows for alternative definitions of impurity. CloudForest includes several alternative targets: Additional targets can be stacked on top of these target to add boosting functionality: Repeatedly splitting the data and searching for the best split at each node of a decision tree are the most computationally intensive parts of decision tree learning and CloudForest includes optimized code to perform these tasks. Go's slices are used extensively in CloudForest to make it simple to interact with optimized code. Many previous implementations of Random Forest have avoided reallocation by reordering data in place and keeping track of start and end indexes. In go, slices pointing at the same underlying arrays make this sort of optimization transparent. For example a function like: can return left and right slices that point to the same underlying array as the original slice of cases but these slices should not have their values changed. Functions used while searching for the best split also accepts pointers to reusable slices and structs to maximize speed by keeping memory allocations to a minimum. BestSplitAllocs contains pointers to these items and its use can be seen in functions like: For categorical predictors, BestSplit will also attempt to intelligently choose between 4 different implementations depending on user input and the number of categories. These include exhaustive, random, and iterative searches for the best combination of categories implemented with bitwise operations against int and big.Int. See BestCatSplit, BestCatSplitIter, BestCatSplitBig and BestCatSplitIterBig. All numerical predictors are handled by BestNumSplit which relies on go's sorting package. Training a Random forest is an inherently parallel process and CloudForest is designed to allow parallel implementations that can tackle large problems while keeping memory usage low by writing and using data structures directly to/from disk. Trees can be grown in separate go routines. The growforest utility provides an example of this that uses go routines and channels to grow trees in parallel and write trees to disk as the are finished by the "worker" go routines. The few summary statistics like mean impurity decrease per feature (importance) can be calculated using thread safe data structures like RunningMean. Trees can also be grown on separate machines. The .sf stochastic forest format allows several small forests to be combined by concatenation and the ForestReader and ForestWriter structs allow these forests to be accessed tree by tree (or even node by node) from disk. For data sets that are too big to fit in memory on a single machine Tree.Grow and FeatureMatrix.BestSplitter can be reimplemented to load candidate features from disk, distributed database etc. By default cloud forest uses a fast heuristic for missing values. When proposing a split on a feature with missing data the missing cases are removed and the impurity value is corrected to use three way impurity which reduces the bias towards features with lots of missing data: Missing values in the target variable are left out of impurity calculations. This provided generally good results at a fraction of the computational costs of imputing data. Optionally, feature.ImputeMissing or featurematrixImputeMissing can be called before forest growth to impute missing values to the feature mean/mode which Brieman [2] suggests as a fast method for imputing values. This forest could also be analyzed for proximity (using leafcount or tree.GetLeaves) to do the more accurate proximity weighted imputation Brieman describes. Experimental support is provided for 3 way splitting which splits missing cases onto a third branch. [2] This has so far yielded mixed results in testing. At some point in the future support may be added for local imputing of missing values during tree growth as described in [3] [1] http://www.stat.berkeley.edu/~breiman/RandomForests/cc_home.htm#missing1 [2] https://code.google.com/p/rf-ace/ [3] http://projecteuclid.org/DPubS?verb=Display&version=1.0&service=UI&handle=euclid.aoas/1223908043&page=record In CloudForest data is stored using the FeatureMatrix struct which contains Features. The Feature struct implements storage and methods for both categorical and numerical data and calculations of impurity etc and the search for the best split. The Target interface abstracts the methods of Feature that are needed for a feature to be predictable. This allows for the implementation of alternative types of regression and classification. Trees are built from Nodes and Splitters and stored within a Forest. Tree has a Grow implements Brieman and Cutler's method (see extract above) for growing a tree. A GrowForest method is also provided that implements the rest of the method including sampling cases but it may be faster to grow the forest to disk as in the growforest utility. Prediction and Voting is done using Tree.Vote and CatBallotBox and NumBallotBox which implement the VoteTallyer interface.

Package CloudForest implements ensembles of decision trees for machine learning in pure Go (golang to search engines). It allows for a number of related algorithms for classification, regression, feature selection and structure analysis on heterogeneous numerical/categorical data with missing values. These include: Breiman and Cutler's Random Forest for Classification and Regression Adaptive Boosting (AdaBoost) Classification Gradiant Boosting Tree Regression Entropy and Cost driven classification L1 regression Feature selection with artificial contrasts Proximity and model structure analysis Roughly balanced bagging for unbalanced classification The API hasn't stabilized yet and may change rapidly. Tests and benchmarks have been performed only on embargoed data sets and can not yet be released. Library Documentation is in code and can be viewed with godoc or live at: http://godoc.org/github.com/IlyaLab/CloudForest Documentation of command line utilities and file formats can be found in README.md, which can be viewed fromated on github: http://github.com/IlyaLab/CloudForest Pull requests and bug reports are welcome. CloudForest was created by Ryan Bressler and is being developed in the Shumelivich Lab at the Institute for Systems Biology for use on genomic/biomedical data with partial support from The Cancer Genome Atlas and the Inova Translational Medicine Institute. CloudForest is intended to provide fast, comprehensible building blocks that can be used to implement ensembles of decision trees. CloudForest is written in Go to allow a data scientist to develop and scale new models and analysis quickly instead of having to modify complex legacy code. Data structures and file formats are chosen with use in multi threaded and cluster environments in mind. Go's support for function types is used to provide a interface to run code as data is percolated through a tree. This method is flexible enough that it can extend the tree being analyzed. Growing a decision tree using Breiman and Cutler's method can be done in an anonymous function/closure passed to a tree's root node's Recurse method: This allows a researcher to include whatever additional analysis they need (importance scores, proximity etc) in tree growth. The same Recurse method can also be used to analyze existing forests to tabulate scores or extract structure. Utilities like leafcount and errorrate use this method to tabulate data about the tree in collection objects. Decision tree's are grown with the goal of reducing "Impurity" which is usually defined as Gini Impurity for categorical targets or mean squared error for numerical targets. CloudForest grows trees against the Target interface which allows for alternative definitions of impurity. CloudForest includes several alternative targets: Additional targets can be stacked on top of these target to add boosting functionality: Repeatedly splitting the data and searching for the best split at each node of a decision tree are the most computationally intensive parts of decision tree learning and CloudForest includes optimized code to perform these tasks. Go's slices are used extensively in CloudForest to make it simple to interact with optimized code. Many previous implementations of Random Forest have avoided reallocation by reordering data in place and keeping track of start and end indexes. In go, slices pointing at the same underlying arrays make this sort of optimization transparent. For example a function like: can return left and right slices that point to the same underlying array as the original slice of cases but these slices should not have their values changed. Functions used while searching for the best split also accepts pointers to reusable slices and structs to maximize speed by keeping memory allocations to a minimum. BestSplitAllocs contains pointers to these items and its use can be seen in functions like: For categorical predictors, BestSplit will also attempt to intelligently choose between 4 different implementations depending on user input and the number of categories. These include exhaustive, random, and iterative searches for the best combination of categories implemented with bitwise operations against int and big.Int. See BestCatSplit, BestCatSplitIter, BestCatSplitBig and BestCatSplitIterBig. All numerical predictors are handled by BestNumSplit which relies on go's sorting package. Training a Random forest is an inherently parallel process and CloudForest is designed to allow parallel implementations that can tackle large problems while keeping memory usage low by writing and using data structures directly to/from disk. Trees can be grown in separate go routines. The growforest utility provides an example of this that uses go routines and channels to grow trees in parallel and write trees to disk as the are finished by the "worker" go routines. The few summary statistics like mean impurity decrease per feature (importance) can be calculated using thread safe data structures like RunningMean. Trees can also be grown on separate machines. The .sf stochastic forest format allows several small forests to be combined by concatenation and the ForestReader and ForestWriter structs allow these forests to be accessed tree by tree (or even node by node) from disk. For data sets that are too big to fit in memory on a single machine Tree.Grow and FeatureMatrix.BestSplitter can be reimplemented to load candidate features from disk, distributed database etc. By default cloud forest uses a fast heuristic for missing values. When proposing a split on a feature with missing data the missing cases are removed and the impurity value is corrected to use three way impurity which reduces the bias towards features with lots of missing data: Missing values in the target variable are left out of impurity calculations. This provided generally good results at a fraction of the computational costs of imputing data. Optionally, feature.ImputeMissing or featurematrixImputeMissing can be called before forest growth to impute missing values to the feature mean/mode which Brieman [2] suggests as a fast method for imputing values. This forest could also be analyzed for proximity (using leafcount or tree.GetLeaves) to do the more accurate proximity weighted imputation Brieman describes. Experimental support is provided for 3 way splitting which splits missing cases onto a third branch. [2] This has so far yielded mixed results in testing. At some point in the future support may be added for local imputing of missing values during tree growth as described in [3] [1] http://www.stat.berkeley.edu/~breiman/RandomForests/cc_home.htm#missing1 [2] https://code.google.com/p/rf-ace/ [3] http://projecteuclid.org/DPubS?verb=Display&version=1.0&service=UI&handle=euclid.aoas/1223908043&page=record In CloudForest data is stored using the FeatureMatrix struct which contains Features. The Feature struct implements storage and methods for both categorical and numerical data and calculations of impurity etc and the search for the best split. The Target interface abstracts the methods of Feature that are needed for a feature to be predictable. This allows for the implementation of alternative types of regression and classification. Trees are built from Nodes and Splitters and stored within a Forest. Tree has a Grow implements Brieman and Cutler's method (see extract above) for growing a tree. A GrowForest method is also provided that implements the rest of the method including sampling cases but it may be faster to grow the forest to disk as in the growforest utility. Prediction and Voting is done using Tree.Vote and CatBallotBox and NumBallotBox which implement the VoteTallyer interface.

Package sqlite is a CGo-free port of SQLite. SQLite is an in-process implementation of a self-contained, serverless, zero-configuration, transactional SQL database engine. Builder results available at 2021-06-23 v1.11.0: Upgrade to use sqlite 3.36.0, release notes at https://www.sqlite.org/releaselog/3_36_0.html. 2021-05-06 v1.10.6: Fixes a memory corruption issue (https://gitlab.com/cznic/sqlite/-/issues/53). Versions since v1.8.6 were affected and should be updated to v1.10.6. 2021-03-14 v1.10.0: Update to use sqlite 3.35.0, release notes at https://www.sqlite.org/releaselog/3_35_0.html. 2021-03-11 v1.9.0: Support darwin/arm64. 2021-01-08 v1.8.0: Support darwin/amd64. 2020-09-13 v1.7.0: Support linux/arm and linux/arm64. 2020-09-08 v1.6.0: Support linux/386. 2020-09-03 v1.5.0: This project is now completely CGo-free, including the Tcl tests. 2020-08-26 v1.4.0: First stable release for linux/amd64. The database/sql driver and its tests are CGo free. Tests of the translated sqlite3.c library still require CGo. 2020-07-26 v1.4.0-beta1: The project has reached beta status while supporting linux/amd64 only at the moment. The 'extraquick' Tcl testsuite reports and some memory leaks 2019-12-28 v1.2.0-alpha.3: Third alpha fixes issue #19. It also bumps the minor version as the repository was wrongly already tagged with v1.1.0 before. Even though the tag was deleted there are proxies that cached that tag. Thanks /u/garaktailor for detecting the problem and suggesting this solution. 2019-12-26 v1.1.0-alpha.2: Second alpha release adds support for accessing a database concurrently by multiple goroutines and/or processes. v1.1.0 is now considered feature-complete. Next planed release should be a beta with a proper test suite. 2019-12-18 v1.1.0-alpha.1: First alpha release using the new cc/v3, gocc, qbe toolchain. Some primitive tests pass on linux_{amd64,386}. Not yet safe for concurrent access by multiple goroutines. Next alpha release is planed to arrive before the end of this year. 2017-06-10 Windows/Intel no more uses the VM (thanks Steffen Butzer). 2017-06-05 Linux/Intel no more uses the VM (cznic/virtual). To access a Sqlite database do something like These combinations of GOOS and GOARCH are currently supported The windows/amd64 has currently experimental/preview status. Tcl tests report an unresolved yet memory leak, see https://gitlab.com/cznic/sqlite/-/issues/23 for more details. Planned platforms and architectures A comma separated list of options can be passed to `go generate` via the environment variable GO_GENERATE. Some useful options include for example: To create a debug/development version, issue for example: Note: To run `go generate` you need to have modernc.org/ccgo/v3 installed. See https://sqlite.org/docs.html

Package gofpdf implements a PDF document generator with high level support for text, drawing and images. • Choice of measurement unit, page format and margins • Page header and footer management • Automatic page breaks, line breaks, and text justification • Inclusion of JPEG, PNG, GIF, TIFF and basic path-only SVG images • Colors, gradients and alpha channel transparency • Outline bookmarks • Internal and external links • TrueType, Type1 and encoding support • Page compression • Lines, Bézier curves, arcs, and ellipses • Rotation, scaling, skewing, translation, and mirroring • Clipping • Document protection • Layers • Templates • Barcodes gofpdf has no dependencies other than the Go standard library. All tests pass on Linux, Mac and Windows platforms. Like FPDF version 1.7, from which gofpdf is derived, this package does not yet support UTF-8 fonts. In particular, languages that require more than one code page such as Chinese, Japanese, and Arabic are not currently supported. This is explained in issue 109. However, support is provided to automatically translate UTF-8 runes to code page encodings for languages that have fewer than 256 glyphs. To install the package on your system, run Later, to receive updates, run The following Go code generates a simple PDF file. See the functions in the fpdf_test.go file (shown as examples in this documentation) for more advanced PDF examples. If an error occurs in an Fpdf method, an internal error field is set. After this occurs, Fpdf method calls typically return without performing any operations and the error state is retained. This error management scheme facilitates PDF generation since individual method calls do not need to be examined for failure; it is generally sufficient to wait until after Output() is called. For the same reason, if an error occurs in the calling application during PDF generation, it may be desirable for the application to transfer the error to the Fpdf instance by calling the SetError() method or the SetErrorf() method. At any time during the life cycle of the Fpdf instance, the error state can be determined with a call to Ok() or Err(). The error itself can be retrieved with a call to Error(). This package is a relatively straightforward translation from the original FPDF library written in PHP (despite the caveat in the introduction to Effective Go). The API names have been retained even though the Go idiom would suggest otherwise (for example, pdf.GetX() is used rather than simply pdf.X()). The similarity of the two libraries makes the original FPDF website a good source of information. It includes a forum and FAQ. However, some internal changes have been made. Page content is built up using buffers (of type bytes.Buffer) rather than repeated string concatenation. Errors are handled as explained above rather than panicking. Output is generated through an interface of type io.Writer or io.WriteCloser. A number of the original PHP methods behave differently based on the type of the arguments that are passed to them; in these cases additional methods have been exported to provide similar functionality. Font definition files are produced in JSON rather than PHP. A side effect of running "go test ./..." is the production of a number of example PDFs. These can be found in the gofpdf/pdf directory after the tests complete. Please note that these examples run in the context of a test. In order run an example as a standalone application, you'll need to examine fpdf_test.go for some helper routines, for example exampleFilename() and summary(). Example PDFs can be compared with reference copies in order to verify that they have been generated as expected. This comparison will be performed if a PDF with the same name as the example PDF is placed in the gofpdf/pdf/reference directory. The routine that summarizes an example will look for this file and, if found, will call ComparePDFFiles() to check the example PDF for equality with its reference PDF. If differences exist between the two files they will be printed to standard output and the test will fail. If the reference file is missing, the comparison is considered to succeed. In order to successfully compare two PDFs, the placement of internal resources must be consistent and the internal creation timestamps must be the same. To do this, the methods SetCatalogSort() and SetCreationDate() need to be called for both files. This is done automatically for all examples. Nothing special is required to use the standard PDF fonts (courier, helvetica, times, zapfdingbats) in your documents other than calling SetFont(). In order to use a different TrueType or Type1 font, you will need to generate a font definition file and, if the font will be embedded into PDFs, a compressed version of the font file. This is done by calling the MakeFont function or using the included makefont command line utility. To create the utility, cd into the makefont subdirectory and run "go build". This will produce a standalone executable named makefont. Select the appropriate encoding file from the font subdirectory and run the command as in the following example. In your PDF generation code, call AddFont() to load the font and, as with the standard fonts, SetFont() to begin using it. Most examples, including the package example, demonstrate this method. Good sources of free, open-source fonts include http://www.google.com/fonts/ and http://dejavu-fonts.org/. The draw2d package (https://github.com/llgcode/draw2d) is a two dimensional vector graphics library that can generate output in different forms. It uses gofpdf for its document production mode. gofpdf is a global community effort and you are invited to make it even better. If you have implemented a new feature or corrected a problem, please consider contributing your change to the project. A contribution that does not directly pertain to the core functionality of gofpdf should be placed in its own directory directly beneath the `contrib` directory. Here are guidelines for making submissions. Your change should • be compatible with the MIT License • be properly documented • be formatted with `go fmt` • include an example in fpdf_test.go if appropriate • conform to the standards of golint (https://github.com/golang/lint) and go vet (https://godoc.org/golang.org/x/tools/cmd/vet), that is, `golint .` and `go vet .` should not generate any warnings • not diminish test coverage (https://blog.golang.org/cover) Pull requests (https://help.github.com/articles/using-pull-requests/) work nicely as a means of contributing your changes. gofpdf is released under the MIT License. It is copyrighted by Kurt Jung and the contributors acknowledged below. This package's code and documentation are closely derived from the FPDF library (http://www.fpdf.org/) created by Olivier Plathey, and a number of font and image resources are copied directly from it. Drawing support is adapted from the FPDF geometric figures script by David Hernández Sanz. Transparency support is adapted from the FPDF transparency script by Martin Hall-May. Support for gradients and clipping is adapted from FPDF scripts by Andreas Würmser. Support for outline bookmarks is adapted from Olivier Plathey by Manuel Cornes. Layer support is adapted from Olivier Plathey. Support for transformations is adapted from the FPDF transformation script by Moritz Wagner and Andreas Würmser. PDF protection is adapted from the work of Klemen Vodopivec for the FPDF product. Lawrence Kesteloot provided code to allow an image's extent to be determined prior to placement. Support for vertical alignment within a cell was provided by Stefan Schroeder. Ivan Daniluk generalized the font and image loading code to use the Reader interface while maintaining backward compatibility. Anthony Starks provided code for the Polygon function. Robert Lillack provided the Beziergon function and corrected some naming issues with the internal curve function. Claudio Felber provided implementations for dashed line drawing and generalized font loading. Stani Michiels provided support for multi-segment path drawing with smooth line joins, line join styles, enhanced fill modes, and has helped greatly with package presentation and tests. Templating is adapted by Marcus Downing from the FPDF_Tpl library created by Jan Slabon and Setasign. Jelmer Snoeck contributed packages that generate a variety of barcodes and help with registering images on the web. Jelmer Snoek and Guillermo Pascual augmented the basic HTML functionality with aligned text. Kent Quirk implemented backwards-compatible support for reading DPI from images that support it, and for setting DPI manually and then having it properly taken into account when calculating image size. Paulo Coutinho provided support for static embedded fonts. Bruno Michel has provided valuable assistance with the code. • Handle UTF-8 source text natively. Until then, automatic translation of UTF-8 runes to code page bytes is provided. • Improve test coverage as reported by the coverage tool. This example demonstrates the generation of a simple PDF document. Note that since only core fonts are used (in this case Arial, a synonym for Helvetica), an empty string can be specified for the font directory in the call to New(). Note also that the example.Filename() and example.Summary() functions belong to a separate, internal package and are not part of the gofpdf library. If an error occurs at some point during the construction of the document, subsequent method calls exit immediately and the error is finally retrieved with the output call where it can be handled by the application.

Package gofpdf implements a PDF document generator with high level support for text, drawing and images. - UTF-8 support - Choice of measurement unit, page format and margins - Page header and footer management - Automatic page breaks, line breaks, and text justification - Inclusion of JPEG, PNG, GIF, TIFF and basic path-only SVG images - Colors, gradients and alpha channel transparency - Outline bookmarks - Internal and external links - TrueType, Type1 and encoding support - Page compression - Lines, Bézier curves, arcs, and ellipses - Rotation, scaling, skewing, translation, and mirroring - Clipping - Document protection - Layers - Templates - Barcodes - Charting facility - Import PDFs as templates gofpdf has no dependencies other than the Go standard library. All tests pass on Linux, Mac and Windows platforms. gofpdf supports UTF-8 TrueType fonts and “right-to-left” languages. Note that Chinese, Japanese, and Korean characters may not be included in many general purpose fonts. For these languages, a specialized font (for example, NotoSansSC for simplified Chinese) can be used. Also, support is provided to automatically translate UTF-8 runes to code page encodings for languages that have fewer than 256 glyphs. This repository will not be maintained, at least for some unknown duration. But it is hoped that gofpdf has a bright future in the open source world. Due to Go’s promise of compatibility, gofpdf should continue to function without modification for a longer time than would be the case with many other languages. Forks should be based on the last viable commit. Tools such as active-forks can be used to select a fork that looks promising for your needs. If a particular fork looks like it has taken the lead in attracting followers, this README will be updated to point people in that direction. The efforts of all contributors to this project have been deeply appreciated. Best wishes to all of you. To install the package on your system, run Later, to receive updates, run The following Go code generates a simple PDF file. See the functions in the fpdf_test.go file (shown as examples in this documentation) for more advanced PDF examples. If an error occurs in an Fpdf method, an internal error field is set. After this occurs, Fpdf method calls typically return without performing any operations and the error state is retained. This error management scheme facilitates PDF generation since individual method calls do not need to be examined for failure; it is generally sufficient to wait until after Output() is called. For the same reason, if an error occurs in the calling application during PDF generation, it may be desirable for the application to transfer the error to the Fpdf instance by calling the SetError() method or the SetErrorf() method. At any time during the life cycle of the Fpdf instance, the error state can be determined with a call to Ok() or Err(). The error itself can be retrieved with a call to Error(). This package is a relatively straightforward translation from the original FPDF library written in PHP (despite the caveat in the introduction to Effective Go). The API names have been retained even though the Go idiom would suggest otherwise (for example, pdf.GetX() is used rather than simply pdf.X()). The similarity of the two libraries makes the original FPDF website a good source of information. It includes a forum and FAQ. However, some internal changes have been made. Page content is built up using buffers (of type bytes.Buffer) rather than repeated string concatenation. Errors are handled as explained above rather than panicking. Output is generated through an interface of type io.Writer or io.WriteCloser. A number of the original PHP methods behave differently based on the type of the arguments that are passed to them; in these cases additional methods have been exported to provide similar functionality. Font definition files are produced in JSON rather than PHP. A side effect of running go test ./... is the production of a number of example PDFs. These can be found in the gofpdf/pdf directory after the tests complete. Please note that these examples run in the context of a test. In order run an example as a standalone application, you’ll need to examine fpdf_test.go for some helper routines, for example exampleFilename() and summary(). Example PDFs can be compared with reference copies in order to verify that they have been generated as expected. This comparison will be performed if a PDF with the same name as the example PDF is placed in the gofpdf/pdf/reference directory and if the third argument to ComparePDFFiles() in internal/example/example.go is true. (By default it is false.) The routine that summarizes an example will look for this file and, if found, will call ComparePDFFiles() to check the example PDF for equality with its reference PDF. If differences exist between the two files they will be printed to standard output and the test will fail. If the reference file is missing, the comparison is considered to succeed. In order to successfully compare two PDFs, the placement of internal resources must be consistent and the internal creation timestamps must be the same. To do this, the methods SetCatalogSort() and SetCreationDate() need to be called for both files. This is done automatically for all examples. Nothing special is required to use the standard PDF fonts (courier, helvetica, times, zapfdingbats) in your documents other than calling SetFont(). You should use AddUTF8Font() or AddUTF8FontFromBytes() to add a TrueType UTF-8 encoded font. Use RTL() and LTR() methods switch between “right-to-left” and “left-to-right” mode. In order to use a different non-UTF-8 TrueType or Type1 font, you will need to generate a font definition file and, if the font will be embedded into PDFs, a compressed version of the font file. This is done by calling the MakeFont function or using the included makefont command line utility. To create the utility, cd into the makefont subdirectory and run “go build”. This will produce a standalone executable named makefont. Select the appropriate encoding file from the font subdirectory and run the command as in the following example. In your PDF generation code, call AddFont() to load the font and, as with the standard fonts, SetFont() to begin using it. Most examples, including the package example, demonstrate this method. Good sources of free, open-source fonts include Google Fonts and DejaVu Fonts. The draw2d package is a two dimensional vector graphics library that can generate output in different forms. It uses gofpdf for its document production mode. gofpdf is a global community effort and you are invited to make it even better. If you have implemented a new feature or corrected a problem, please consider contributing your change to the project. A contribution that does not directly pertain to the core functionality of gofpdf should be placed in its own directory directly beneath the contrib directory. Here are guidelines for making submissions. Your change should - be compatible with the MIT License - be properly documented - be formatted with go fmt - include an example in fpdf_test.go if appropriate - conform to the standards of golint and go vet, that is, golint . and go vet . should not generate any warnings - not diminish test coverage Pull requests are the preferred means of accepting your changes. gofpdf is released under the MIT License. It is copyrighted by Kurt Jung and the contributors acknowledged below. This package’s code and documentation are closely derived from the FPDF library created by Olivier Plathey, and a number of font and image resources are copied directly from it. Bruno Michel has provided valuable assistance with the code. Drawing support is adapted from the FPDF geometric figures script by David Hernández Sanz. Transparency support is adapted from the FPDF transparency script by Martin Hall-May. Support for gradients and clipping is adapted from FPDF scripts by Andreas Würmser. Support for outline bookmarks is adapted from Olivier Plathey by Manuel Cornes. Layer support is adapted from Olivier Plathey. Support for transformations is adapted from the FPDF transformation script by Moritz Wagner and Andreas Würmser. PDF protection is adapted from the work of Klemen Vodopivec for the FPDF product. Lawrence Kesteloot provided code to allow an image’s extent to be determined prior to placement. Support for vertical alignment within a cell was provided by Stefan Schroeder. Ivan Daniluk generalized the font and image loading code to use the Reader interface while maintaining backward compatibility. Anthony Starks provided code for the Polygon function. Robert Lillack provided the Beziergon function and corrected some naming issues with the internal curve function. Claudio Felber provided implementations for dashed line drawing and generalized font loading. Stani Michiels provided support for multi-segment path drawing with smooth line joins, line join styles, enhanced fill modes, and has helped greatly with package presentation and tests. Templating is adapted by Marcus Downing from the FPDF_Tpl library created by Jan Slabon and Setasign. Jelmer Snoeck contributed packages that generate a variety of barcodes and help with registering images on the web. Jelmer Snoek and Guillermo Pascual augmented the basic HTML functionality with aligned text. Kent Quirk implemented backwards-compatible support for reading DPI from images that support it, and for setting DPI manually and then having it properly taken into account when calculating image size. Paulo Coutinho provided support for static embedded fonts. Dan Meyers added support for embedded JavaScript. David Fish added a generic alias-replacement function to enable, among other things, table of contents functionality. Andy Bakun identified and corrected a problem in which the internal catalogs were not sorted stably. Paul Montag added encoding and decoding functionality for templates, including images that are embedded in templates; this allows templates to be stored independently of gofpdf. Paul also added support for page boxes used in printing PDF documents. Wojciech Matusiak added supported for word spacing. Artem Korotkiy added support of UTF-8 fonts. Dave Barnes added support for imported objects and templates. Brigham Thompson added support for rounded rectangles. Joe Westcott added underline functionality and optimized image storage. Benoit KUGLER contributed support for rectangles with corners of unequal radius, modification times, and for file attachments and annotations. - Remove all legacy code page font support; use UTF-8 exclusively - Improve test coverage as reported by the coverage tool. Example demonstrates the generation of a simple PDF document. Note that since only core fonts are used (in this case Arial, a synonym for Helvetica), an empty string can be specified for the font directory in the call to New(). Note also that the example.Filename() and example.Summary() functions belong to a separate, internal package and are not part of the gofpdf library. If an error occurs at some point during the construction of the document, subsequent method calls exit immediately and the error is finally retrieved with the output call where it can be handled by the application.

PrettyTest is a simple testing library for golang. It aims to simplify/prettify testing in golang. It features: * a simple assertion vocabulary for better readability * customizable formatters through interfaces * before/after functions * integrated with the go test command * pretty and colorful output with reports This is the skeleton of a typical prettytest test file: See example/example_test.go and prettytest_test.go for comprehensive usage examples.

go-junit-report converts `go test` output to a JUnit compatible XML report. See README.md for more information and usage examples.

Package gofpdf implements a PDF document generator with high level support for text, drawing and images. • Choice of measurement unit, page format and margins • Page header and footer management • Automatic page breaks, line breaks, and text justification • Inclusion of JPEG, PNG, GIF and basic path-only SVG images • Colors, gradients and alpha channel transparency • Outline bookmarks • Internal and external links • TrueType, Type1 and encoding support • Page compression • Lines, Bézier curves, arcs, and ellipses • Rotation, scaling, skewing, translation, and mirroring • Clipping • Document protection • Layers • Templates gofpdf has no dependencies other than the Go standard library. All tests pass on Linux, Mac and Windows platforms. Like FPDF version 1.7, from which gofpdf is derived, this package does not yet support UTF-8 fonts. However, support is provided to translate UTF-8 runes to code page encodings. To install the package on your system, run Later, to receive updates, run The following Go code generates a simple PDF file. See the functions in the fpdf_test.go file (shown as examples in this documentation) for more advanced PDF examples. If an error occurs in an Fpdf method, an internal error field is set. After this occurs, Fpdf method calls typically return without performing any operations and the error state is retained. This error management scheme facilitates PDF generation since individual method calls do not need to be examined for failure; it is generally sufficient to wait until after Output() is called. For the same reason, if an error occurs in the calling application during PDF generation, it may be desirable for the application to transfer the error to the Fpdf instance by calling the SetError() method or the SetErrorf() method. At any time during the life cycle of the Fpdf instance, the error state can be determined with a call to Ok() or Err(). The error itself can be retrieved with a call to Error(). This package is a relatively straightforward translation from the original FPDF library written in PHP (despite the caveat in the introduction to Effective Go). The API names have been retained even though the Go idiom would suggest otherwise (for example, pdf.GetX() is used rather than simply pdf.X()). The similarity of the two libraries makes the original FPDF website a good source of information. It includes a forum and FAQ. However, some internal changes have been made. Page content is built up using buffers (of type bytes.Buffer) rather than repeated string concatenation. Errors are handled as explained above rather than panicking. Output is generated through an interface of type io.Writer or io.WriteCloser. A number of the original PHP methods behave differently based on the type of the arguments that are passed to them; in these cases additional methods have been exported to provide similar functionality. Font definition files are produced in JSON rather than PHP. A side effect of running "go test ./..." is the production of a number of example PDFs. These can be found in the gofpdf/pdf directory after the tests complete. Please note that these examples run in the context of a test. In order run an example as a standalone application, you'll need to examine fpdf_test.go for some helper routines, for example exampleFilename() and summary(). Example PDFs can be compared with reference copies in order to verify that they have been generated as expected. This comparison will be performed if a PDF with the same name as the example PDF is placed in the gofpdf/pdf/reference directory. The routine that summarizes an example will look for this file and, if found, will call ComparePDFFiles() to check the example PDF for equality with its reference PDF. If differences exist between the two files they will be printed to standard output and the test will fail. If the reference file is missing, the comparison is considered to succeed. In order to successfully compare two PDFs, the placement of internal resources must be consistent and the internal creation timestamps must be the same. To do this, the methods SetCatalogSort() and SetCreationDate() need to be called for both files. This is done automatically for all examples. Nothing special is required to use the standard PDF fonts (courier, helvetica, times, zapfdingbats) in your documents other than calling SetFont(). In order to use a different TrueType or Type1 font, you will need to generate a font definition file and, if the font will be embedded into PDFs, a compressed version of the font file. This is done by calling the MakeFont function or using the included makefont command line utility. To create the utility, cd into the makefont subdirectory and run "go build". This will produce a standalone executable named makefont. Select the appropriate encoding file from the font subdirectory and run the command as in the following example. In your PDF generation code, call AddFont() to load the font and, as with the standard fonts, SetFont() to begin using it. Most examples, including the package example, demonstrate this method. Good sources of free, open-source fonts include http://www.google.com/fonts/ and http://dejavu-fonts.org/. The draw2d package (https://github.com/llgcode/draw2d) is a two dimensional vector graphics library that can generate output in different forms. It uses gofpdf for its document production mode. gofpdf is a global community effort and you are invited to make it even better. If you have implemented a new feature or corrected a problem, please consider contributing your change to the project. A contribution that does not directly pertain to the core functionality of gofpdf should be placed in its own directory directly beneath the `contrib` directory. Here are guidelines for making submissions. Your change should • be compatible with the MIT License • be properly documented • be formatted with `go fmt` • include an example in fpdf_test.go if appropriate • conform to the standards of golint (https://github.com/golang/lint) and go vet (https://godoc.org/golang.org/x/tools/cmd/vet), that is, `golint .` and `go vet .` should not generate any warnings • not diminish test coverage (https://blog.golang.org/cover) Pull requests (https://help.github.com/articles/using-pull-requests/) work nicely as a means of contributing your changes. gofpdf is released under the MIT License. It is copyrighted by Kurt Jung and the contributors acknowledged below. This package's code and documentation are closely derived from the FPDF library (http://www.fpdf.org/) created by Olivier Plathey, and a number of font and image resources are copied directly from it. Drawing support is adapted from the FPDF geometric figures script by David Hernández Sanz. Transparency support is adapted from the FPDF transparency script by Martin Hall-May. Support for gradients and clipping is adapted from FPDF scripts by Andreas Würmser. Support for outline bookmarks is adapted from Olivier Plathey by Manuel Cornes. Layer support is adapted from Olivier Plathey. Support for transformations is adapted from the FPDF transformation script by Moritz Wagner and Andreas Würmser. PDF protection is adapted from the work of Klemen Vodopivec for the FPDF product. Lawrence Kesteloot provided code to allow an image's extent to be determined prior to placement. Support for vertical alignment within a cell was provided by Stefan Schroeder. Ivan Daniluk generalized the font and image loading code to use the Reader interface while maintaining backward compatibility. Anthony Starks provided code for the Polygon function. Robert Lillack provided the Beziergon function and corrected some naming issues with the internal curve function. Claudio Felber provided implementations for dashed line drawing and generalized font loading. Stani Michiels provided support for multi-segment path drawing with smooth line joins, line join styles, enhanced fill modes, and has helped greatly with package presentation and tests. Templating is adapted by Marcus Downing from the FPDF_Tpl library created by Jan Slabon and Setasign. Jelmer Snoeck contributed packages that generate a variety of barcodes and help with registering images on the web. Additionally, he augmented the basic HTML functionality with aligned text. Bruno Michel has provided valuable assistance with the code. • Handle UTF-8 source text natively. Until then, automatic translation of UTF-8 runes to code page bytes is provided. • Improve test coverage as reported by the coverage tool. This example demonstrates the generation of a simple PDF document. Note that since only core fonts are used (in this case Arial, a synonym for Helvetica), an empty string can be specified for the font directory in the call to New(). Note also that the example.Filename() and example.Summary() functions belong to a separate, internal package and are not part of the gofpdf library. If an error occurs at some point during the construction of the document, subsequent method calls exit immediately and the error is finally retreived with the output call where it can be handled by the application.

Package gofpdf implements a PDF document generator with high level support for text, drawing and images. - UTF-8 support - Choice of measurement unit, page format and margins - Page header and footer management - Automatic page breaks, line breaks, and text justification - Inclusion of JPEG, PNG, GIF, TIFF and basic path-only SVG images - Colors, gradients and alpha channel transparency - Outline bookmarks - Internal and external links - TrueType, Type1 and encoding support - Page compression - Lines, Bézier curves, arcs, and ellipses - Rotation, scaling, skewing, translation, and mirroring - Clipping - Document protection - Layers - Templates - Barcodes - Charting facility - Import PDFs as templates gofpdf has no dependencies other than the Go standard library. All tests pass on Linux, Mac and Windows platforms. gofpdf supports UTF-8 TrueType fonts and “right-to-left” languages. Note that Chinese, Japanese, and Korean characters may not be included in many general purpose fonts. For these languages, a specialized font (for example, NotoSansSC for simplified Chinese) can be used. Also, support is provided to automatically translate UTF-8 runes to code page encodings for languages that have fewer than 256 glyphs. This repository will not be maintained, at least for some unknown duration. But it is hoped that gofpdf has a bright future in the open source world. Due to Go’s promise of compatibility, gofpdf should continue to function without modification for a longer time than would be the case with many other languages. Forks should be based on the last viable commit. Tools such as active-forks can be used to select a fork that looks promising for your needs. If a particular fork looks like it has taken the lead in attracting followers, this README will be updated to point people in that direction. The efforts of all contributors to this project have been deeply appreciated. Best wishes to all of you. To install the package on your system, run Later, to receive updates, run The following Go code generates a simple PDF file. See the functions in the fpdf_test.go file (shown as examples in this documentation) for more advanced PDF examples. If an error occurs in an Fpdf method, an internal error field is set. After this occurs, Fpdf method calls typically return without performing any operations and the error state is retained. This error management scheme facilitates PDF generation since individual method calls do not need to be examined for failure; it is generally sufficient to wait until after Output() is called. For the same reason, if an error occurs in the calling application during PDF generation, it may be desirable for the application to transfer the error to the Fpdf instance by calling the SetError() method or the SetErrorf() method. At any time during the life cycle of the Fpdf instance, the error state can be determined with a call to Ok() or Err(). The error itself can be retrieved with a call to Error(). This package is a relatively straightforward translation from the original FPDF library written in PHP (despite the caveat in the introduction to Effective Go). The API names have been retained even though the Go idiom would suggest otherwise (for example, pdf.GetX() is used rather than simply pdf.X()). The similarity of the two libraries makes the original FPDF website a good source of information. It includes a forum and FAQ. However, some internal changes have been made. Page content is built up using buffers (of type bytes.Buffer) rather than repeated string concatenation. Errors are handled as explained above rather than panicking. Output is generated through an interface of type io.Writer or io.WriteCloser. A number of the original PHP methods behave differently based on the type of the arguments that are passed to them; in these cases additional methods have been exported to provide similar functionality. Font definition files are produced in JSON rather than PHP. A side effect of running go test ./... is the production of a number of example PDFs. These can be found in the gofpdf/pdf directory after the tests complete. Please note that these examples run in the context of a test. In order run an example as a standalone application, you’ll need to examine fpdf_test.go for some helper routines, for example exampleFilename() and summary(). Example PDFs can be compared with reference copies in order to verify that they have been generated as expected. This comparison will be performed if a PDF with the same name as the example PDF is placed in the gofpdf/pdf/reference directory and if the third argument to ComparePDFFiles() in internal/example/example.go is true. (By default it is false.) The routine that summarizes an example will look for this file and, if found, will call ComparePDFFiles() to check the example PDF for equality with its reference PDF. If differences exist between the two files they will be printed to standard output and the test will fail. If the reference file is missing, the comparison is considered to succeed. In order to successfully compare two PDFs, the placement of internal resources must be consistent and the internal creation timestamps must be the same. To do this, the methods SetCatalogSort() and SetCreationDate() need to be called for both files. This is done automatically for all examples. Nothing special is required to use the standard PDF fonts (courier, helvetica, times, zapfdingbats) in your documents other than calling SetFont(). You should use AddUTF8Font() or AddUTF8FontFromBytes() to add a TrueType UTF-8 encoded font. Use RTL() and LTR() methods switch between “right-to-left” and “left-to-right” mode. In order to use a different non-UTF-8 TrueType or Type1 font, you will need to generate a font definition file and, if the font will be embedded into PDFs, a compressed version of the font file. This is done by calling the MakeFont function or using the included makefont command line utility. To create the utility, cd into the makefont subdirectory and run “go build”. This will produce a standalone executable named makefont. Select the appropriate encoding file from the font subdirectory and run the command as in the following example. In your PDF generation code, call AddFont() to load the font and, as with the standard fonts, SetFont() to begin using it. Most examples, including the package example, demonstrate this method. Good sources of free, open-source fonts include Google Fonts and DejaVu Fonts. The draw2d package is a two dimensional vector graphics library that can generate output in different forms. It uses gofpdf for its document production mode. gofpdf is a global community effort and you are invited to make it even better. If you have implemented a new feature or corrected a problem, please consider contributing your change to the project. A contribution that does not directly pertain to the core functionality of gofpdf should be placed in its own directory directly beneath the contrib directory. Here are guidelines for making submissions. Your change should - be compatible with the MIT License - be properly documented - be formatted with go fmt - include an example in fpdf_test.go if appropriate - conform to the standards of golint and go vet, that is, golint . and go vet . should not generate any warnings - not diminish test coverage Pull requests are the preferred means of accepting your changes. gofpdf is released under the MIT License. It is copyrighted by Kurt Jung and the contributors acknowledged below. This package’s code and documentation are closely derived from the FPDF library created by Olivier Plathey, and a number of font and image resources are copied directly from it. Bruno Michel has provided valuable assistance with the code. Drawing support is adapted from the FPDF geometric figures script by David Hernández Sanz. Transparency support is adapted from the FPDF transparency script by Martin Hall-May. Support for gradients and clipping is adapted from FPDF scripts by Andreas Würmser. Support for outline bookmarks is adapted from Olivier Plathey by Manuel Cornes. Layer support is adapted from Olivier Plathey. Support for transformations is adapted from the FPDF transformation script by Moritz Wagner and Andreas Würmser. PDF protection is adapted from the work of Klemen Vodopivec for the FPDF product. Lawrence Kesteloot provided code to allow an image’s extent to be determined prior to placement. Support for vertical alignment within a cell was provided by Stefan Schroeder. Ivan Daniluk generalized the font and image loading code to use the Reader interface while maintaining backward compatibility. Anthony Starks provided code for the Polygon function. Robert Lillack provided the Beziergon function and corrected some naming issues with the internal curve function. Claudio Felber provided implementations for dashed line drawing and generalized font loading. Stani Michiels provided support for multi-segment path drawing with smooth line joins, line join styles, enhanced fill modes, and has helped greatly with package presentation and tests. Templating is adapted by Marcus Downing from the FPDF_Tpl library created by Jan Slabon and Setasign. Jelmer Snoeck contributed packages that generate a variety of barcodes and help with registering images on the web. Jelmer Snoek and Guillermo Pascual augmented the basic HTML functionality with aligned text. Kent Quirk implemented backwards-compatible support for reading DPI from images that support it, and for setting DPI manually and then having it properly taken into account when calculating image size. Paulo Coutinho provided support for static embedded fonts. Dan Meyers added support for embedded JavaScript. David Fish added a generic alias-replacement function to enable, among other things, table of contents functionality. Andy Bakun identified and corrected a problem in which the internal catalogs were not sorted stably. Paul Montag added encoding and decoding functionality for templates, including images that are embedded in templates; this allows templates to be stored independently of gofpdf. Paul also added support for page boxes used in printing PDF documents. Wojciech Matusiak added supported for word spacing. Artem Korotkiy added support of UTF-8 fonts. Dave Barnes added support for imported objects and templates. Brigham Thompson added support for rounded rectangles. Joe Westcott added underline functionality and optimized image storage. Benoit KUGLER contributed support for rectangles with corners of unequal radius, modification times, and for file attachments and annotations. - Remove all legacy code page font support; use UTF-8 exclusively - Improve test coverage as reported by the coverage tool. Example demonstrates the generation of a simple PDF document. Note that since only core fonts are used (in this case Arial, a synonym for Helvetica), an empty string can be specified for the font directory in the call to New(). Note also that the example.Filename() and example.Summary() functions belong to a separate, internal package and are not part of the gofpdf library. If an error occurs at some point during the construction of the document, subsequent method calls exit immediately and the error is finally retrieved with the output call where it can be handled by the application.

Package golangNeo4jBoltDriver implements a driver for the Neo4J Bolt Protocol. The driver is compatible with Golang's sql.driver interface, but aims to implement a more complete featureset in line with what Neo4J and Bolt provides. As such, there are multiple interfaces the user can choose from. It's highly recommended that the user use the Neo4J-specific interfaces as they are more flexible and efficient than the provided sql.driver compatible methods. The interface tries to be consistent throughout. The sql.driver interfaces are standard, but the Neo4J-specific ones contain a naming convention of either "Neo" or "Pipeline". The "Neo" ones are the basic interfaces for making queries to Neo4j and it's expected that these would be used the most. The "Pipeline" ones are to support Bolt's pipelining features. Pipelines allow the user to send Neo4j many queries at once and have them executed by the database concurrently. This is useful if you have a bunch of queries that aren't necessarily dependant on one another, and you want to get better performance. The internal APIs will also pipeline statements where it is able to reliably do so, but by manually using the pipelining feature you can maximize your throughput. The API provides connection pooling using the `NewDriverPool` method. This allows you to pass it the maximum number of open connections to be used in the pool. Once this limit is hit, any new clients will have to wait for a connection to become available again. The sql driver is registered as "neo4j-bolt". The sql.driver interface is much more limited than what bolt and neo4j supports. In some cases, concessions were made in order to make that interface work with the neo4j way of doing things. The main instance of this is the marshalling of objects to/from the sql.driver.Value interface. In order to support object types that aren't supported by this interface, the internal encoding package is used to marshal these objects to byte strings. This ultimately makes for a less efficient and more 'clunky' implementation. A glaring instance of this is passing parameters. Neo4j expects named parameters but the driver interface can only really support positional parameters. To get around this, the user must create a map[string]interface{} of their parameters and marshal it to a driver.Value using the encoding.Marshal function. Similarly, the user must unmarshal data returned from the queries using the encoding.Unmarshal function, then use type assertions to retrieve the proper type. In most cases the driver will return the data from neo as the proper go-specific types. For integers they always come back as int64 and floats always come back as float64. This is for the convenience of the user and acts similarly to go's JSON interface. This prevents the user from having to use reflection to get these values. Internally, the types are always transmitted over the wire with as few bytes as possible. There are also cases where no go-specific type matches the returned values, such as when you query for a node, relationship, or path. The driver exposes specific structs which represent this data in the 'structures.graph' package. There are 4 types - Node, Relationship, UnboundRelationship, and Path. The driver returns interface{} objects which must have their types properly asserted to get the data out. There are some limitations to the types of collections the driver supports. Specifically, maps should always be of type map[string]interface{} and lists should always be of type []interface{}. It doesn't seem that the Bolt protocol supports uint64 either, so the biggest number it can send right now is the int64 max. The URL format is: `bolt://(user):(password)@(host):(port)` Schema must be `bolt`. User and password is only necessary if you are authenticating. TLS is supported by using query parameters on the connection string, like so: `bolt://host:port?tls=true&tls_no_verify=false` The supported query params are: * timeout - the number of seconds to set the connection timeout to. Defaults to 60 seconds. * tls - Set to 'true' or '1' if you want to use TLS encryption * tls_no_verify - Set to 'true' or '1' if you want to accept any server certificate (for testing, not secure) * tls_ca_cert_file - path to a custom ca cert for a self-signed TLS cert * tls_cert_file - path to a cert file for this client (need to verify this is processed by Neo4j) * tls_key_file - path to a key file for this client (need to verify this is processed by Neo4j) Errors returned from the API support wrapping, so if you receive an error from the library, it might be wrapping other errors. You can get the innermost error by using the `InnerMost` method. Failure messages from Neo4J are reported, along with their metadata, as an error. In order to get the failure message metadata from a wrapped error, you can do so by calling `err.(*errors.Error).InnerMost().(messages.FailureMessage).Metadata` If there is an error with the database connection, you should get a sql/driver ErrBadConn as per the best practice recommendations of the Golang SQL Driver. However, this error may be wrapped, so you might have to call `InnerMost` to get it, as specified above.

Package httpexpect helps with end-to-end HTTP and REST API testing. See example directory: There are two common ways to test API with httpexpect: The second approach works only if the server is a Go module and its handler can be imported in tests. Concrete behaviour is determined by Client implementation passed to Config struct. If you're using http.Client, set its Transport field (http.RoundTriper) to one of the following: Note that http handler can be usually obtained from http framework you're using. E.g., echo framework provides either http.Handler. You can also provide your own implementation of RequestFactory (creates http.Request), or Client (gets http.Request and returns http.Response). If you're starting server from tests, it's very handy to use net/http/httptest. Whenever values are checked for equality in httpexpect, they are converted to "canonical form": This is equivalent to subsequently json.Marshal() and json.Unmarshal() the value and currently is implemented so. When some check fails, failure is reported. If non-fatal failures are used (see Reporter interface), execution is continued and instance that was checked is marked as failed. If specific instance is marked as failed, all subsequent checks are ignored for this instance and for any child instances retrieved after failure. Example:

Pact Go enables consumer driven contract testing, providing a mock service and DSL for the consumer project, and interaction playback and verification for the service provider project. Consumer side Pact testing is an isolated test that ensures a given component is able to collaborate with another (remote) component. Pact will automatically start a Mock server in the background that will act as the collaborators' test double. This implies that any interactions expected on the Mock server will be validated, meaning a test will fail if all interactions were not completed, or if unexpected interactions were found: A typical consumer-side test would look something like this: If this test completed successfully, a Pact file should have been written to ./pacts/my_consumer-my_provider.json containing all of the interactions expected to occur between the Consumer and Provider. In addition to verbatim value matching, you have 3 useful matching functions in the `dsl` package that can increase expressiveness and reduce brittle test cases. Here is a complex example that shows how all 3 terms can be used together: This example will result in a response body from the mock server that looks like: See the examples in the dsl package and the matcher tests (https://github.com/teetachp/pact-go/blob/master/dsl/matcher_test.go) for more matching examples. NOTE: You will need to use valid Ruby regular expressions (http://ruby-doc.org/core-2.1.5/Regexp.html) and double escape backslashes. Read more about flexible matching (https://github.com/teetachp/pact-ruby/wiki/Regular-expressions-and-type-matching-with-Pact. Provider side Pact testing, involves verifying that the contract - the Pact file - can be satisfied by the Provider. A typical Provider side test would like something like: The `VerifyProvider` will handle all verifications, treating them as subtests and giving you granular test reporting. If you don't like this behaviour, you may call `VerifyProviderRaw` directly and handle the errors manually. Note that `PactURLs` may be a list of local pact files or remote based urls (possibly from a Pact Broker - http://docs.pact.io/documentation/sharings_pacts.html). Pact reads the specified pact files (from remote or local sources) and replays the interactions against a running Provider. If all of the interactions are met we can say that both sides of the contract are satisfied and the test passes. When validating a Provider, you have 3 options to provide the Pact files: 1. Use "PactURLs" to specify the exact set of pacts to be replayed: Options 2 and 3 are particularly useful when you want to validate that your Provider is able to meet the contracts of what's in Production and also the latest in development. See this [article](http://rea.tech/enter-the-pact-matrix-or-how-to-decouple-the-release-cycles-of-your-microservices/) for more on this strategy. Each interaction in a pact should be verified in isolation, with no context maintained from the previous interactions. So how do you test a request that requires data to exist on the provider? Provider states are how you achieve this using Pact. Provider states also allow the consumer to make the same request with different expected responses (e.g. different response codes, or the same resource with a different subset of data). States are configured on the consumer side when you issue a dsl.Given() clause with a corresponding request/response pair. Configuring the provider is a little more involved, and (currently) requires running an API endpoint to configure any [provider states](http://docs.pact.io/documentation/provider_states.html) during the verification process. The option you must provide to the dsl.VerifyRequest is: An example route using the standard Go http package might look like this: See the examples or read more at http://docs.pact.io/documentation/provider_states.html. See the Pact Broker (http://docs.pact.io/documentation/sharings_pacts.html) documentation for more details on the Broker and this article (http://rea.tech/enter-the-pact-matrix-or-how-to-decouple-the-release-cycles-of-your-microservices/) on how to make it work for you. Publishing using Go code: Publishing from the CLI: Use a cURL request like the following to PUT the pact to the right location, specifying your consumer name, provider name and consumer version. The following flags are required to use basic authentication when publishing or retrieving Pact files to/from a Pact Broker: Pact Go uses a simple log utility (logutils - https://github.com/hashicorp/logutils) to filter log messages. The CLI already contains flags to manage this, should you want to control log level in your tests, you can set it like so:

Package saml contains a partial implementation of the SAML standard in golang. SAML is a standard for identity federation, i.e. either allowing a third party to authenticate your users or allowing third parties to rely on us to authenticate their users. In SAML parlance an Identity Provider (IDP) is a service that knows how to authenticate users. A Service Provider (SP) is a service that delegates authentication to an IDP. If you are building a service where users log in with someone else's credentials, then you are a Service Provider. This package supports implementing both service providers and identity providers. The core package contains the implementation of SAML. The package samlsp provides helper middleware suitable for use in Service Provider applications. The package samlidp provides a rudimentary IDP service that is useful for testing or as a starting point for other integrations. Version 0.4.0 introduces a few breaking changes to the _samlsp_ package in order to make the package more extensible, and to clean up the interfaces a bit. The default behavior remains the same, but you can now provide interface implementations of _RequestTracker_ (which tracks pending requests), _Session_ (which handles maintaining a session) and _OnError_ which handles reporting errors. Public fields of _samlsp.Middleware_ have changed, so some usages may require adjustment. See [issue 231](https://github.com/crewjam/saml/issues/231) for details. The option to provide an IDP metadata URL has been deprecated. Instead, we recommend that you use the `FetchMetadata()` function, or fetch the metadata yourself and use the new `ParseMetadata()` function, and pass the metadata in _samlsp.Options.IDPMetadata_. Similarly, the _HTTPClient_ field is now deprecated because it was only used for fetching metdata, which is no longer directly implemented. The fields that manage how cookies are set are deprecated as well. To customize how cookies are managed, provide custom implementation of _RequestTracker_ and/or _Session_, perhaps by extending the default implementations. The deprecated fields have not been removed from the Options structure, but will be in future. In particular we have deprecated the following fields in _samlsp.Options_: - `Logger` - This was used to emit errors while validating, which is an anti-pattern. - `IDPMetadataURL` - Instead use `FetchMetadata()` - `HTTPClient` - Instead pass httpClient to FetchMetadata - `CookieMaxAge` - Instead assign a custom CookieRequestTracker or CookieSessionProvider - `CookieName` - Instead assign a custom CookieRequestTracker or CookieSessionProvider - `CookieDomain` - Instead assign a custom CookieRequestTracker or CookieSessionProvider - `CookieDomain` - Instead assign a custom CookieRequestTracker or CookieSessionProvider Let us assume we have a simple web application to protect. We'll modify this application so it uses SAML to authenticate users. ```golang package main import ( ) ``` Each service provider must have an self-signed X.509 key pair established. You can generate your own with something like this: We will use `samlsp.Middleware` to wrap the endpoint we want to protect. Middleware provides both an `http.Handler` to serve the SAML specific URLs and a set of wrappers to require the user to be logged in. We also provide the URL where the service provider can fetch the metadata from the IDP at startup. In our case, we'll use [samltest.id](https://samltest.id/), an identity provider designed for testing. ```golang package main import ( ) ``` Next we'll have to register our service provider with the identity provider to establish trust from the service provider to the IDP. For [samltest.id](https://samltest.id/), you can do something like: Navigate to https://samltest.id/upload.php and upload the file you fetched. Now you should be able to authenticate. The flow should look like this: 1. You browse to `localhost:8000/hello` 1. The middleware redirects you to `https://samltest.id/idp/profile/SAML2/Redirect/SSO` 1. samltest.id prompts you for a username and password. 1. samltest.id returns you an HTML document which contains an HTML form setup to POST to `localhost:8000/saml/acs`. The form is automatically submitted if you have javascript enabled. 1. The local service validates the response, issues a session cookie, and redirects you to the original URL, `localhost:8000/hello`. 1. This time when `localhost:8000/hello` is requested there is a valid session and so the main content is served. Please see `example/idp/` for a substantially complete example of how to use the library and helpers to be an identity provider. The SAML standard is huge and complex with many dark corners and strange, unused features. This package implements the most commonly used subset of these features required to provide a single sign on experience. The package supports at least the subset of SAML known as [interoperable SAML](http://saml2int.org). This package supports the Web SSO profile. Message flows from the service provider to the IDP are supported using the HTTP Redirect binding and the HTTP POST binding. Message flows from the IDP to the service provider are supported via the HTTP POST binding. The package can produce signed SAML assertions, and can validate both signed and encrypted SAML assertions. It does not support signed or encrypted requests. The _RelayState_ parameter allows you to pass user state information across the authentication flow. The most common use for this is to allow a user to request a deep link into your site, be redirected through the SAML login flow, and upon successful completion, be directed to the originally requested link, rather than the root. Unfortunately, _RelayState_ is less useful than it could be. Firstly, it is not authenticated, so anything you supply must be signed to avoid XSS or CSRF. Secondly, it is limited to 80 bytes in length, which precludes signing. (See section 3.6.3.1 of SAMLProfiles.) The SAML specification is a collection of PDFs (sadly): - [SAMLCore](http://docs.oasis-open.org/security/saml/v2.0/saml-core-2.0-os.pdf) defines data types. - [SAMLBindings](http://docs.oasis-open.org/security/saml/v2.0/saml-bindings-2.0-os.pdf) defines the details of the HTTP requests in play. - [SAMLProfiles](http://docs.oasis-open.org/security/saml/v2.0/saml-profiles-2.0-os.pdf) describes data flows. - [SAMLConformance](http://docs.oasis-open.org/security/saml/v2.0/saml-conformance-2.0-os.pdf) includes a support matrix for various parts of the protocol. [SAMLtest](https://samltest.id/) is a testing ground for SAML service and identity providers. Please do not report security issues in the issue tracker. Rather, please contact me directly at ross@kndr.org ([PGP Key `78B6038B3B9DFB88`](https://keybase.io/crewjam)).