Google API

The fuse_gdrive command makes your Google Drive files accessible as a local mount point. It implements a user space filesystem, using the Fuse and Google Drive APIs, to allow you to access your files in Google Drive just like a regular local filesystem.

Package go_fsspec provides a unified interface for interacting with different cloud storage systems such as AWS S3, Google Cloud Storage, and Azure Blob Storage. go_fsspec offers a simple and powerful way to manage files and directories across multiple cloud providers without having to deal with provider-specific APIs or implementations. go_fsspec contains the following key functionalities: The core interface `CloudStorage` provides a set of common methods for file and directory operations, allowing users to interact with any supported cloud provider using the same interface. Supported operations include creating directories, listing files, downloading and uploading files, and deleting files and directories. Additional methods for downloading/uploading entire directories are also available for bulk operations. Each cloud provider (AWS S3, Google Cloud Storage, Azure Blob Storage) has its own implementation of the `CloudStorage` interface, allowing developers to switch providers with minimal code changes. Future versions of go_fsspec will include support for more cloud providers, advanced file versioning, and cross-cloud transfer capabilities. Contributions and feedback are welcome! Feel free to check out the repository and get involved.

Package api provides functions to trace the google.golang.org/api package. WARNING: Please note we periodically re-generate the endpoint metadata that is used to enrich some tags added by this integration using the latest versions of github.com/googleapis/google-api-go-client (which does not follow semver due to the auto-generated nature of the package). For this reason, there might be unexpected changes in some tag values like service.name and resource.name, depending on the google.golang.org/api that you are using in your project. If this is not an acceptable behavior for your use-case, you can disable this feature using the WithEndpointMetadataDisabled option.

check_cisco_ucs is a Nagios plugin made by Herwig Grimm (herwig.grimm at aon.at) to monitor Cisco UCS rack and blade center hardware. I have used the Google Go progamming language because of no need to install any libraries. The plugin uses the Cisco UCS XML API via HTTPS to do a wide variety of checks. This nagios plugin is free software, and comes with ABSOLUTELY NO WARRANTY. It may be used, redistributed and/or modified under the terms of the GNU General Public Licence (see http://www.fsf.org/licensing/licenses/gpl.txt). tested with: see also: changelog: todo: flags: usage examples:

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 logging contains a Stackdriver Logging client suitable for writing logs. For reading logs, and working with sinks, metrics and monitored resources, see package cloud.google.com/go/logging/logadmin. This client uses Logging API v2. See https://cloud.google.com/logging/docs/api/v2/ for an introduction to the API. Note: This package is in beta. Some backwards-incompatible changes may occur. Use a Client to interact with the Stackdriver Logging API. For most use cases, you'll want to add log entries to a buffer to be periodically flushed (automatically and asynchronously) to the Stackdriver Logging service. You should call Client.Close before your program exits to flush any buffered log entries to the Stackdriver Logging service. For critical errors, you may want to send your log entries immediately. LogSync is slow and will block until the log entry has been sent, so it is not recommended for normal use. An entry payload can be a string, as in the examples above. It can also be any value that can be marshaled to a JSON object, like a map[string]interface{} or a struct: If you have a []byte of JSON, wrap it in json.RawMessage: You may want use a standard log.Logger in your program. An Entry may have one of a number of severity levels associated with it. You can view Stackdriver logs for projects at https://console.cloud.google.com/logs/viewer. Use the dropdown at the top left. When running from a Google Cloud Platform VM, select "GCE VM Instance". Otherwise, select "Google Project" and then the project ID. Logs for organizations, folders and billing accounts can be viewed on the command line with the "gcloud logging read" command. To group all the log entries written during a single HTTP request, create two Loggers, a "parent" and a "child," with different log IDs. Both should be in the same project, and have the same MonitoredResouce type and labels. - Parent entries must have HTTPRequest.Request populated. (Strictly speaking, only the URL is necessary.) - A child entry's timestamp must be within the time interval covered by the parent request (i.e., older than parent.Timestamp, and newer than parent.Timestamp - parent.HTTPRequest.Latency, assuming the parent timestamp marks the end of the request. - The trace field must be populated in all of the entries and match exactly. You should observe the child log entries grouped under the parent on the console. The parent entry will not inherit the severity of its children; you must update the parent severity yourself.

Package spanner provides a client for reading and writing to Cloud Spanner databases. See the packages under admin for clients that operate on databases and instances. Note: This package is in beta. Some backwards-incompatible changes may occur. See https://cloud.google.com/spanner/docs/getting-started/go/ for an introduction to Cloud Spanner and additional help on using this API. See https://godoc.org/cloud.google.com/go for authentication, timeouts, connection pooling and similar aspects of this package. To start working with this package, create a client that refers to the database of interest: Remember to close the client after use to free up the sessions in the session pool. Two Client methods, Apply and Single, work well for simple reads and writes. As a quick introduction, here we write a new row to the database and read it back: All the methods used above are discussed in more detail below. Every Cloud Spanner row has a unique key, composed of one or more columns. Construct keys with a literal of type Key: The keys of a Cloud Spanner table are ordered. You can specify ranges of keys using the KeyRange type: By default, a KeyRange includes its start key but not its end key. Use the Kind field to specify other boundary conditions: A KeySet represents a set of keys. A single Key or KeyRange can act as a KeySet. Use the KeySets function to build the union of several KeySets: AllKeys returns a KeySet that refers to all the keys in a table: All Cloud Spanner reads and writes occur inside transactions. There are two types of transactions, read-only and read-write. Read-only transactions cannot change the database, do not acquire locks, and may access either the current database state or states in the past. Read-write transactions can read the database before writing to it, and always apply to the most recent database state. The simplest and fastest transaction is a ReadOnlyTransaction that supports a single read operation. Use Client.Single to create such a transaction. You can chain the call to Single with a call to a Read method. When you only want one row whose key you know, use ReadRow. Provide the table name, key, and the columns you want to read: Read multiple rows with the Read method. It takes a table name, KeySet, and list of columns: Read returns a RowIterator. You can call the Do method on the iterator and pass a callback: RowIterator also follows the standard pattern for the Google Cloud Client Libraries: Always call Stop when you finish using an iterator this way, whether or not you iterate to the end. (Failing to call Stop could lead you to exhaust the database's session quota.) To read rows with an index, use ReadUsingIndex. The most general form of reading uses SQL statements. Construct a Statement with NewStatement, setting any parameters using the Statement's Params map: You can also construct a Statement directly with a struct literal, providing your own map of parameters. Use the Query method to run the statement and obtain an iterator: Once you have a Row, via an iterator or a call to ReadRow, you can extract column values in several ways. Pass in a pointer to a Go variable of the appropriate type when you extract a value. You can extract by column position or name: You can extract all the columns at once: Or you can define a Go struct that corresponds to your columns, and extract into that: For Cloud Spanner columns that may contain NULL, use one of the NullXXX types, like NullString: To perform more than one read in a transaction, use ReadOnlyTransaction: You must call Close when you are done with the transaction. Cloud Spanner read-only transactions conceptually perform all their reads at a single moment in time, called the transaction's read timestamp. Once a read has started, you can call ReadOnlyTransaction's Timestamp method to obtain the read timestamp. By default, a transaction will pick the most recent time (a time where all previously committed transactions are visible) for its reads. This provides the freshest data, but may involve some delay. You can often get a quicker response if you are willing to tolerate "stale" data. You can control the read timestamp selected by a transaction by calling the WithTimestampBound method on the transaction before using it. For example, to perform a query on data that is at most one minute stale, use See the documentation of TimestampBound for more details. To write values to a Cloud Spanner database, construct a Mutation. The spanner package has functions for inserting, updating and deleting rows. Except for the Delete methods, which take a Key or KeyRange, each mutation-building function comes in three varieties. One takes lists of columns and values along with the table name: One takes a map from column names to values: And the third accepts a struct value, and determines the columns from the struct field names: To apply a list of mutations to the database, use Apply: If you need to read before writing in a single transaction, use a ReadWriteTransaction. ReadWriteTransactions may abort and need to be retried. You pass in a function to ReadWriteTransaction, and the client will handle the retries automatically. Use the transaction's BufferWrite method to buffer mutations, which will all be executed at the end of the transaction: Spanner supports DML statements like INSERT, UPDATE and DELETE. Use ReadWriteTransaction.Update to run DML statements. It returns the number of rows affected. (You can call use ReadWriteTransaction.Query with a DML statement. The first call to Next on the resulting RowIterator will return iterator.Done, and the RowCount field of the iterator will hold the number of affected rows.) For large databases, it may be more efficient to partition the DML statement. Use client.PartitionedUpdate to run a DML statement in this way. Not all DML statements can be partitioned. This client has been instrumented to use OpenCensus tracing (http://opencensus.io). To enable tracing, see "Enabling Tracing for a Program" at https://godoc.org/go.opencensus.io/trace. OpenCensus tracing requires Go 1.8 or higher.

Package firestore provides a client for reading and writing to a Cloud Firestore database. See https://cloud.google.com/firestore/docs for an introduction to Cloud Firestore and additional help on using the Firestore API. See https://godoc.org/cloud.google.com/go for authentication, timeouts, connection pooling and similar aspects of this package. Note: you can't use both Cloud Firestore and Cloud Datastore in the same project. To start working with this package, create a client with a project ID: In Firestore, documents are sets of key-value pairs, and collections are groups of documents. A Firestore database consists of a hierarchy of alternating collections and documents, referred to by slash-separated paths like "States/California/Cities/SanFrancisco". This client is built around references to collections and documents. CollectionRefs and DocumentRefs are lightweight values that refer to the corresponding database entities. Creating a ref does not involve any network traffic. Use DocumentRef.Get to read a document. The result is a DocumentSnapshot. Call its Data method to obtain the entire document contents as a map. You can also obtain a single field with DataAt, or extract the data into a struct with DataTo. With the type definition we can extract the document's data into a value of type State: Note that this client supports struct tags beginning with "firestore:" that work like the tags of the encoding/json package, letting you rename fields, ignore them, or omit their values when empty. To retrieve multiple documents from their references in a single call, use Client.GetAll. For writing individual documents, use the methods on DocumentReference. Create creates a new document. The first return value is a WriteResult, which contains the time at which the document was updated. Create fails if the document exists. Another method, Set, either replaces an existing document or creates a new one. To update some fields of an existing document, use Update. It takes a list of paths to update and their corresponding values. Use DocumentRef.Delete to delete a document. You can condition Deletes or Updates on when a document was last changed. Specify these preconditions as an option to a Delete or Update method. The check and the write happen atomically with a single RPC. Here we update a doc only if it hasn't changed since we read it. You could also do this with a transaction. To perform multiple writes at once, use a WriteBatch. Its methods chain for convenience. WriteBatch.Commit sends the collected writes to the server, where they happen atomically. You can use SQL to select documents from a collection. Begin with the collection, and build up a query using Select, Where and other methods of Query. Supported operators include `<`, `<=`, `>`, `>=`, `==`, and 'array-contains'. Call the Query's Documents method to get an iterator, and use it like the other Google Cloud Client iterators. To get all the documents in a collection, you can use the collection itself as a query. Use a transaction to execute reads and writes atomically. All reads must happen before any writes. Transaction creation, commit, rollback and retry are handled for you by the Client.RunTransaction method; just provide a function and use the read and write methods of the Transaction passed to it.

rcloadenv reads environment variables from the Google Cloud RuntimeConfig API. It outputs environment variables as separate lines (e.g. export VARIABLE_NAME=value) so that the output can be sourced to set the variables in a shell. If an environment variable is already set, it does not override it. The config name is set via the environment variable GOOGLE_RUNTIME_CONFIG_NAME If not set, the command exits without outputting. See https://cloud.google.com/deployment-manager/runtime-configurator/create-and-delete-runtimeconfig-resources for how to create a config and set variable values with the Cloud SDK.

Package gdrive provides an afero Fs interface to Google Drive API

Copyright 2024 Google LLC Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. Tries to use the guidelines at https://cloud.google.com/apis/design for the gRPC API where possible. TODO: permissive deadlines for all RPC calls Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. Tries to use the guidelines at https://cloud.google.com/apis/design for the gRPC API where possible.

Copyright 2024 Google LLC Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. Tries to use the guidelines at https://cloud.google.com/apis/design for the gRPC API where possible. TODO: permissive deadlines for all RPC calls Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. Tries to use the guidelines at https://cloud.google.com/apis/design for the gRPC API where possible.

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.

Tiffany is command-line tool for rendering to TIFF any image from Google Static Maps. It downloads, georeferences, and labels any satellite image from the Static Maps API. You can use this to prepare labeled data for downstream tasks such as in computer vision (object detection, semantic segmentation, etc.) You can get the binaries from our Github releases: https://github.com/thinkingmachines/tiffany/releases Or, you can compile this from source by cloning the repository and building it: Usage instructions can be found in the README: https://github.com/thinkingmachines/tiffany/blob/master/README.md Simply fork the Github repository and make a Pull Request. We're open to any kind of contribution, but we'd definitely appreciate (1) implementation of new features (2) writing documentation and (3) testing. MIT License (c) 2019, Thinking Machines Data Science

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.

Package cql provides tools for parsing and evaluating CQL. This example demonstrates the CQL API by finding Observations that were effective during a measurement period.

Package aetools helps writting, testing and analysing Google App Engine applications. The aetools package implements a simple API to export the entity data from Datastore as a JSON stream, as well as load a JSON stream back into the Datastore. This can be used as a simple way to express state into a unit test, to backup a development environment state that can be shared with team members, or to make quick batch changes to data offline, like setting up configuration entities via Remote API. The goal is to provide both an API and a set of executable tools that uses that API, allowing for maximum flexibility. The functions Load, LoadJSON, Dump and DumpJSON operate using JSON data that represents datastore entities. Each entity is mapped to a JSON Object, where each entity property name is an Object atribute, and each property value is the corresponding Object atribute value. The property value is encoded using a JSON primitive, when possible. When the primitives are not sufficient to represent the property value, a JSON Object with the attributes "type" and "value" is used. The "type" attribute is a Datastore type, and value is a json-primitive serialization of that value. For instance, Blobs are encoded as a base64 JSON string, and time.Time values are encoded using the time.RFC3339 layout, also as strings. Datastore Keys are aways encoded as a JSON Array that represents the Key Path, including ancestors, but without the application ID. This is done to allow the entity key to be more readable and to be application independent. Currently, they don't support namespaces. Multiple properties are represented as a JSON Array of values described above. Unindexed properties are aways JSON objects with the "indexed" attribute set to false. This format is intended to make use of the JSON types as much as possible, so an entity can be easily represented as a text file, suitable for read or SCM checkin. The exported data format can also be used as an alternative way to export from Datastore, and then load the results right into other service, such as Google BigQuery or MongoDB. The package aetools/bundle contains a sample webapp to help you manage and stream datastore entities into BigQuery. The bundle uses the aetools/bigquerysync functions to infer an usefull schema from datastore statistics, and sync your entity data into BigQuery. The command aetools/remote_api is a Remote API client that exposes the Load and Dump functions to make backup and restore of development environment state quick and easy. This tool can also help setting up Q.A. or Production apps, but should be used with care.

Package grpcgcp provides grpc supports for Google Cloud APIs. For now it provides connection management with affinity support. Note: "channel" is analagous to "connection" in our context. Usage: 1. First, initialize the api configuration. There are two ways: 2. Make ClientConn with specific DialOptions to enable grpc_gcp load balancer with provided configuration. And specify gRPC-GCP interceptors.

Package bugsnag captures errors in real-time and reports them to Bugsnag (http://bugsnag.com). Using bugsnag-go is a three-step process. 1. As early as possible in your program configure the notifier with your APIKey. This sets up handling of panics that would otherwise crash your app. 2. Add bugsnag to places that already catch panics. For example you should add it to the HTTP server when you call ListenAndServer: If that's not possible, for example because you're using Google App Engine, you can also wrap each HTTP handler manually: 3. To notify Bugsnag of an error that is not a panic, pass it to bugsnag.Notify. This will also log the error message using the configured Logger. For detailed integration instructions see https://bugsnag.com/docs/notifiers/go. The only required configuration is the Bugsnag API key which can be obtained by clicking "Settings" on the top of https://bugsnag.com/ after signing up. We also recommend you set the ReleaseStage, AppType, and AppVersion if these make sense for your deployment workflow. If you need to attach extra data to Bugsnag notifications you can do that using the rawData mechanism. Most of the functions that send errors to Bugsnag allow you to pass in any number of interface{} values as rawData. The rawData can consist of the Severity, Context, User or MetaData types listed below, and there is also builtin support for *http.Requests. If you want to add custom tabs to your bugsnag dashboard you can pass any value in as rawData, and then process it into the event's metadata using a bugsnag.OnBeforeNotify() hook. If necessary you can pass Configuration in as rawData, or modify the Configuration object passed into OnBeforeNotify hooks. Configuration passed in this way only affects the current notification.

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.