Search APIs

Package conf is a configuration parser that loads configuration in a struct from files and automatically creates cli flags. Just define a struct with needed configuration. Values are then taken from multiple source in this order of precedence: Default is to use lower cased field names in struct to create command line arguments. Tags can be used to specify different names, command line help message and section in conf file. Format is: conf.Path variable can be set to the path of a configuration file. For default it is initialized to the value of environment variable: Files ending with: will be parsed as INI informal standard: First letter of every key found is upper cased and than, a struct field with same name is searched: If such field name is not found than comparison is made against key specified as first element in tag. conf tries to be modular and easily extensible to support different formats. This is a work in progress, APIs can change.

Package postkr provides access to APIs of epost.kr, Korean post office. The epost.kr provide APIs for track snail-mail and search zip-code. But, I can't access to the tracking API with my key. So, It's not implemented currently. You need own key which is issued by eport.kr. Get one from this link:

Package itunes_search_go provides client for access to iTunes API. See https://affiliate.itunes.apple.com/resources/documentation/itunes-store-web-service-search-api

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 osdb is an API client for opensubtitles.org This is a client for the OSDb protocol. Currently the package only allows movie identification, subtitles search, and download.

Package enmime implements a MIME encoding and decoding library. It's built on top of Go's included mime/multipart support where possible, but is geared towards parsing MIME encoded emails. The enmime API has two conceptual layers. The lower layer is a tree of Part structs, representing each component of a decoded MIME message. The upper layer, called an Envelope provides an intuitive way to interact with a MIME message. Calling ReadParts causes enmime to parse the body of a MIME message into a tree of Part objects, each of which is aware of its content type, filename and headers. The content of a Part is available as a slice of bytes via the Content field. If the part was encoded in quoted-printable or base64, it is decoded prior to being placed in Content. If the Part contains text in a character set other than utf-8, enmime will attempt to convert it to utf-8. To locate a particular Part, pass a custom PartMatcher function into the BreadthMatchFirst() or DepthMatchFirst() methods to search the Part tree. BreadthMatchAll() and DepthMatchAll() will collect all Parts matching your criteria. ReadEnvelope returns an Envelope struct. Behind the scenes a Part tree is constructed, and then sorted into the correct fields of the Envelope. The Envelope contains both the plain text and HTML portions of the email. If there was no plain text Part available, the HTML Part will be down-converted using the html2text library1. The root of the Part tree, as well as slices of the inline and attachment Parts are also available. Every MIME Part has its own headers, accessible via the Part.Header field. The raw headers for an Envelope are available in Root.Header. Envelope also provides helper methods to fetch headers: GetHeader(key) will return the RFC 2047 decoded value of the specified header. AddressList(key) will convert the specified address header into a slice of net/mail.Address values. enmime attempts to be tolerant of poorly encoded MIME messages. In situations where parsing is not possible, the ReadEnvelope and ReadParts functions will return a hard error. If enmime is able to continue parsing the message, it will add an entry to the Errors slice on the relevant Part. After parsing is complete, all Part errors will be appended to the Envelope Errors slice. The Error* constants can be used to identify a specific class of error. Please note that enmime parses messages into memory, so it is not likely to perform well with multi-gigabyte attachments. enmime is open source software released under the MIT License. The latest version can be found at https://github.com/jhillyerd/enmime

Package freegeoip provides an API for searching the geolocation of IP addresses. It uses a database that can be either a local file or a remote resource from a URL. Local databases are monitored by fsnotify and reloaded when the file is either updated or overwritten. Remote databases are automatically downloaded and updated in background so you can focus on using the API and not managing the database.

This file defines the helpers to develop automation. 这个文件定义了一些开发自动化的辅助工具 Such as when running automation we can use trace to visually see where the mouse going to click. 如在运行自动化时，我们可以用trace（跟踪）来直观地看到鼠标要点击的地方。 This example opens https://github.com/, searches for "git", and then gets the header element which gives the description for Git. Rod use https://golang.org/pkg/context to handle cancelations for IO blocking operations, most times it's timeout. Context will be recursively passed to all sub-methods. For example, methods like Page.Context(ctx) will return a clone of the page with the ctx, all the methods of the returned page will use the ctx if they have IO blocking operations. Page.Timeout or Page.WithCancel is just a shortcut for Page.Context. Of course, Browser or Element works the same way. Shows how we can further customize the browser with the launcher library. Usually you use launcher lib to set the browser's command line flags (switches). Doc for flags: https://peter.sh/experiments/chromium-command-line-switches Shows how to change the retry/polling options that is used to query elements. This is useful when you want to customize the element query retry logic. When rod doesn't have a feature that you need. You can easily call the cdp to achieve it. List of cdp API: https://github.com/go-rod/rod/tree/master/lib/proto Shows how to disable headless mode and debug. Rod provides a lot of debug options, you can set them with setter methods or use environment variables. Doc for environment variables: https://pkg.go.dev/github.com/go-rod/rod/lib/defaults We use "Must" prefixed functions to write example code. But in production you may want to use the no-prefix version of them. About why we use "Must" as the prefix, it's similar to https://golang.org/pkg/regexp/#MustCompile Shows how to share a remote object reference between two Eval Shows how to listen for events. Shows how to intercept requests and modify both the request and the response. The entire process of hijacking one request: The --req-> and --res-> are the parts that can be modified. Show how to handle multiple results of an action. Such as when you login a page, the result can be success or wrong password. Example_search shows how to use Search to get element inside nested iframes or shadow DOMs. It works the same as https://developers.google.com/web/tools/chrome-devtools/dom#search Shows how to update the state of the current page. In this example we enable the network domain. Rod uses mouse cursor to simulate clicks, so if a button is moving because of animation, the click may not work as expected. We usually use WaitStable to make sure the target isn't changing anymore. When you want to wait for an ajax request to complete, this example will be useful.

Package roster This tiny service was built to manage rosters with very limited abilities. Check swagger.yml for more information. Tools, libraries and approaches were chosen with a focus on production readiness. There are some technical decisions made to bring more flexibility and scalability to the service. It may look overcomplicated, but there is extensibility and reliability behind the simplicity. There are no frameworks due to simple infrastructure. - MongoDB - chosen because it's easy to shard and has enough search engine power to fulfill service needs; - Swagger - perfectly describes REST APIs and can be used to generate server and client API-code in a single command; - JWT auth - used to secure changes via API. Used because it's a common choice for API auth. - Docker - used to satisfy requirements and build and run the service in isolated environment. Multistage build is made to make resulted image as small as possible. Can be used on any cloud environment or as a part of orchestration systems like k8s; - Heroku - chosen as a simplest hosting with CI/CD features because it is easy to setup and monitor. All core logic (request handlers) is covered with unit-tests. No need to check infrastructure and generated core, because it doesn't change so much, but really hard to test. DB and web layers are isolated. The service is ready to run as a standalone microservice in any environment, e.g. k8s. It is built with a closer look to 12-factor app principle, and can be easily integrated into 12-f infrastructure with small changes or additions. To run the service as a library you need to run the Run function. It handles termination, so no need to set extra context. To run from command-line just call

Package elasticclient provides a non-obtrusive, idiomatic and easy-to-use query and aggregation builder for the official Go client (https://github.com/elastic/go-elasticsearch) for the ElasticSearch database (https://www.elastic.co/products/elasticsearch). elasticclient alleviates the need to use extremely nested maps (map[string]interface{}) and serializing queries to JSON manually. It also helps eliminating common mistakes such as misspelling query types, as everything is statically typed. Using `elasticclient` can make your code much easier to write, read and maintain, and significantly reduce the amount of code you write. elasticclient provides a method chaining-style API for building and executing queries and aggregations. It does not wrap the official Go client nor does it require you to change your existing code in order to integrate the library. Queries can be directly built with `elasticclient`, and executed by passing an `*elasticsearch.Client` instance (with optional search parameters). Results are returned as-is from the official client (e.g. `*esapi.Response` objects). Getting started is extremely simple: elasticclient currently supports version 7 of the ElasticSearch Go client. The library cannot currently generate "short queries". For example, whereas ElasticSearch can accept this: { "query": { "term": { "user": "Kimchy" } } } The library will always generate this: This is also true for queries such as "bool", where fields like "must" can either receive one query object, or an array of query objects. `elasticclient` will generate an array even if there's only one query object.

Package enmime implements a MIME encoding and decoding library. It's built on top of Go's included mime/multipart support where possible, but is geared towards parsing MIME encoded emails. The enmime API has two conceptual layers. The lower layer is a tree of Part structs, representing each component of a decoded MIME message. The upper layer, called an Envelope provides an intuitive way to interact with a MIME message. Calling ReadParts causes enmime to parse the body of a MIME message into a tree of Part objects, each of which is aware of its content type, filename and headers. The content of a Part is available as a slice of bytes via the Content field. If the part was encoded in quoted-printable or base64, it is decoded prior to being placed in Content. If the Part contains text in a character set other than utf-8, enmime will attempt to convert it to utf-8. To locate a particular Part, pass a custom PartMatcher function into the BreadthMatchFirst() or DepthMatchFirst() methods to search the Part tree. BreadthMatchAll() and DepthMatchAll() will collect all Parts matching your criteria. ReadEnvelope returns an Envelope struct. Behind the scenes a Part tree is constructed, and then sorted into the correct fields of the Envelope. The Envelope contains both the plain text and HTML portions of the email. If there was no plain text Part available, the HTML Part will be down-converted using the html2text library1. The root of the Part tree, as well as slices of the inline and attachment Parts are also available. Every MIME Part has its own headers, accessible via the Part.Header field. The raw headers for an Envelope are available in Root.Header. Envelope also provides helper methods to fetch headers: GetHeader(key) will return the RFC 2047 decoded value of the specified header. AddressList(key) will convert the specified address header into a slice of net/mail.Address values. enmime attempts to be tolerant of poorly encoded MIME messages. In situations where parsing is not possible, the ReadEnvelope and ReadParts functions will return a hard error. If enmime is able to continue parsing the message, it will add an entry to the Errors slice on the relevant Part. After parsing is complete, all Part errors will be appended to the Envelope Errors slice. The Error* constants can be used to identify a specific class of error. Please note that enmime parses messages into memory, so it is not likely to perform well with multi-gigabyte attachments. enmime is open source software released under the MIT License. The latest version can be found at https://github.com/jhillyerd/enmime

Package enmime implements a MIME encoding and decoding library. It's built on top of Go's included mime/multipart support where possible, but is geared towards parsing MIME encoded emails. The enmime API has two conceptual layers. The lower layer is a tree of Part structs, representing each component of a decoded MIME message. The upper layer, called an Envelope provides an intuitive way to interact with a MIME message. Calling ReadParts causes enmime to parse the body of a MIME message into a tree of Part objects, each of which is aware of its content type, filename and headers. The content of a Part is available as a slice of bytes via the Content field. If the part was encoded in quoted-printable or base64, it is decoded prior to being placed in Content. If the Part contains text in a character set other than utf-8, enmime will attempt to convert it to utf-8. To locate a particular Part, pass a custom PartMatcher function into the BreadthMatchFirst() or DepthMatchFirst() methods to search the Part tree. BreadthMatchAll() and DepthMatchAll() will collect all Parts matching your criteria. ReadEnvelope returns an Envelope struct. Behind the scenes a Part tree is constructed, and then sorted into the correct fields of the Envelope. The Envelope contains both the plain text and HTML portions of the email. If there was no plain text Part available, the HTML Part will be down-converted using the html2text library1. The root of the Part tree, as well as slices of the inline and attachment Parts are also available. Every MIME Part has its own headers, accessible via the Part.Header field. The raw headers for an Envelope are available in Root.Header. Envelope also provides helper methods to fetch headers: GetHeader(key) will return the RFC 2047 decoded value of the specified header. AddressList(key) will convert the specified address header into a slice of net/mail.Address values. enmime attempts to be tolerant of poorly encoded MIME messages. In situations where parsing is not possible, the ReadEnvelope and ReadParts functions will return a hard error. If enmime is able to continue parsing the message, it will add an entry to the Errors slice on the relevant Part. After parsing is complete, all Part errors will be appended to the Envelope Errors slice. The Error* constants can be used to identify a specific class of error. Please note that enmime parses messages into memory, so it is not likely to perform well with multi-gigabyte attachments. enmime is open source software released under the MIT License. The latest version can be found at https://github.com/jhillyerd/enmime

Package freegeoip provides an API for searching the geolocation of IP addresses. It uses a database that can be either a local file or a remote resource from a URL. Local databases are monitored by fsnotify and reloaded when the file is either updated or overwritten. Remote databases are automatically downloaded and updated in background so you can focus on using the API and not managing the database. Also, the freegeoip package provides http handlers that any Go http server (net/http) can use. These handlers can process IP geolocation lookup requests and return data in multiple formats like CSV, XML, JSON and JSONP. It has also an API for supporting custom formats.

Package connpass provides a search method for using the connpass API (See https://connpass.com/about/api/). Construct a query, then search with that on connpass. For example: Specify query parameters by setting fields of a Query object. The search API supports pagenation. Pagenation options can be specified with Start, Order and Count. Pages information is available via ResultSet struct.

* Weather API * * # Introduction WeatherAPI.com provides access to weather and geo data via a JSON/XML restful API. It allows developers to create desktop, web and mobile applications using this data very easy. We provide following data through our API: - Real-time weather - 14 day weather forecast - Astronomy - Time zone - Location data - Search or Autocomplete API - NEW: Historical weather - NEW: Future Weather (Upto 300 days ahead) - Weather Alerts - Air Quality Data # Getting Started You need to [signup](https://www.weatherapi.com/signup.aspx) and then you can find your API key under [your account](https://www.weatherapi.com/login.aspx), and start using API right away! We have [code libraries](https://www.weatherapi.com/docs/code-libraries.aspx) for different programming languages like PHP, .net, JAVA, etc. If you find any features missing or have any suggestions, please [contact us](https://www.weatherapi.com/contact.aspx). # Authentication API access to the data is protected by an API key. If at anytime, you find the API key has become vulnerable, please regenerate the key using Regenerate button next to the API key. Authentication to the WeatherAPI.com API is provided by passing your API key as request parameter through an API . ## key parameter key=<YOUR API KEY> * * API version: 1.0.0-oas3 * Generated by: Swagger Codegen (https://github.com/swagger-api/swagger-codegen.git) * Weather API * * # Introduction WeatherAPI.com provides access to weather and geo data via a JSON/XML restful API. It allows developers to create desktop, web and mobile applications using this data very easy. We provide following data through our API: - Real-time weather - 14 day weather forecast - Astronomy - Time zone - Location data - Search or Autocomplete API - NEW: Historical weather - NEW: Future Weather (Upto 300 days ahead) - Weather Alerts - Air Quality Data # Getting Started You need to [signup](https://www.weatherapi.com/signup.aspx) and then you can find your API key under [your account](https://www.weatherapi.com/login.aspx), and start using API right away! We have [code libraries](https://www.weatherapi.com/docs/code-libraries.aspx) for different programming languages like PHP, .net, JAVA, etc. If you find any features missing or have any suggestions, please [contact us](https://www.weatherapi.com/contact.aspx). # Authentication API access to the data is protected by an API key. If at anytime, you find the API key has become vulnerable, please regenerate the key using Regenerate button next to the API key. Authentication to the WeatherAPI.com API is provided by passing your API key as request parameter through an API . ## key parameter key=<YOUR API KEY> * * API version: 1.0.0-oas3 * Generated by: Swagger Codegen (https://github.com/swagger-api/swagger-codegen.git) * Weather API * * # Introduction WeatherAPI.com provides access to weather and geo data via a JSON/XML restful API. It allows developers to create desktop, web and mobile applications using this data very easy. We provide following data through our API: - Real-time weather - 14 day weather forecast - Astronomy - Time zone - Location data - Search or Autocomplete API - NEW: Historical weather - NEW: Future Weather (Upto 300 days ahead) - Weather Alerts - Air Quality Data # Getting Started You need to [signup](https://www.weatherapi.com/signup.aspx) and then you can find your API key under [your account](https://www.weatherapi.com/login.aspx), and start using API right away! We have [code libraries](https://www.weatherapi.com/docs/code-libraries.aspx) for different programming languages like PHP, .net, JAVA, etc. If you find any features missing or have any suggestions, please [contact us](https://www.weatherapi.com/contact.aspx). # Authentication API access to the data is protected by an API key. If at anytime, you find the API key has become vulnerable, please regenerate the key using Regenerate button next to the API key. Authentication to the WeatherAPI.com API is provided by passing your API key as request parameter through an API . ## key parameter key=<YOUR API KEY> * * API version: 1.0.0-oas3 * Generated by: Swagger Codegen (https://github.com/swagger-api/swagger-codegen.git) * Weather API * * # Introduction WeatherAPI.com provides access to weather and geo data via a JSON/XML restful API. It allows developers to create desktop, web and mobile applications using this data very easy. We provide following data through our API: - Real-time weather - 14 day weather forecast - Astronomy - Time zone - Location data - Search or Autocomplete API - NEW: Historical weather - NEW: Future Weather (Upto 300 days ahead) - Weather Alerts - Air Quality Data # Getting Started You need to [signup](https://www.weatherapi.com/signup.aspx) and then you can find your API key under [your account](https://www.weatherapi.com/login.aspx), and start using API right away! We have [code libraries](https://www.weatherapi.com/docs/code-libraries.aspx) for different programming languages like PHP, .net, JAVA, etc. If you find any features missing or have any suggestions, please [contact us](https://www.weatherapi.com/contact.aspx). # Authentication API access to the data is protected by an API key. If at anytime, you find the API key has become vulnerable, please regenerate the key using Regenerate button next to the API key. Authentication to the WeatherAPI.com API is provided by passing your API key as request parameter through an API . ## key parameter key=<YOUR API KEY> * * API version: 1.0.0-oas3 * Generated by: Swagger Codegen (https://github.com/swagger-api/swagger-codegen.git) * Weather API * * # Introduction WeatherAPI.com provides access to weather and geo data via a JSON/XML restful API. It allows developers to create desktop, web and mobile applications using this data very easy. We provide following data through our API: - Real-time weather - 14 day weather forecast - Astronomy - Time zone - Location data - Search or Autocomplete API - NEW: Historical weather - NEW: Future Weather (Upto 300 days ahead) - Weather Alerts - Air Quality Data # Getting Started You need to [signup](https://www.weatherapi.com/signup.aspx) and then you can find your API key under [your account](https://www.weatherapi.com/login.aspx), and start using API right away! We have [code libraries](https://www.weatherapi.com/docs/code-libraries.aspx) for different programming languages like PHP, .net, JAVA, etc. If you find any features missing or have any suggestions, please [contact us](https://www.weatherapi.com/contact.aspx). # Authentication API access to the data is protected by an API key. If at anytime, you find the API key has become vulnerable, please regenerate the key using Regenerate button next to the API key. Authentication to the WeatherAPI.com API is provided by passing your API key as request parameter through an API . ## key parameter key=<YOUR API KEY> * * API version: 1.0.0-oas3 * Generated by: Swagger Codegen (https://github.com/swagger-api/swagger-codegen.git)

Package execstub provides stubbing for a usage of a command line api which is based on an executable discovered using the environment <PATH> or some sort of <HOME>+<Bin> configuration. What is a usage of a command line api? Its when you spawn a sub-process using a programming language API. Think go exec.Cmd.Run(..), java Runtime.exec(..), python subprocess.run(..). The sub-process execution will yield an outcome consisting of: side effects (e.g. a file created when executing touch). bytes or string in std-out and/or std-err. an exit code. The executed binary is typically specified using a path like argument. It can be: a absolute path a relative path the name of the binary Discovering the executable How the binary is discovered depends on the art the specified path like argument. The goal of the discovery process is to transform the path like specification into an absolute path, so that if the specification is done with: absolute path nothing is left to be done relative path it will be appended to the current directory to form an absolute path name of the binary a file with that name will be search in the directories specified by the PATH environment variable. The first found will be used. On some platforms known and specified file extensions (e.g. .exe) will be appended to the name during the search. Even when using absolute paths, you may decide to put a customization strategy using some process environment variable. We call this the home-bin-dir strategy. E.g. Java executed base on JAVA_HOME or JRE_HOME with the java executable located at ${JAVA_HOME}/bin/java Stubbing mechanism The aim os stubbing is to replace at execution time the actual executable with a fake one which will yield some kind of pre-defined known outcome. This can be done if there is step in the binary discovery which can be tweaked so that the stud-executable is discovered instead of the actual one. It is the case if binary is specified by name and discovered using PATH or when absolute path is used but with a customization layer in place based on defined environment home variable. The mechanism will just have to mutate the PATH or set the home variable accordingly. Stubbing become complicated if the specification is based on absolute (without customization layer) or relative path because it will require e.g.: a file overley to hide the original executable a change of the current directory an in the flight replacement of the original executable and a rollback. These are either not desirable, or too heavy especially in a unit-test-ish context. The execstub module will therefore only provide stubbing for PATH and Home-Bin-Dir based discovery. Design elements Modeling the command line usage We have basically 3 aspects to model: Starting the process It is modeled using StubRequest which hold the the command name and the execution argument so that the fake execution process can be function of them. Execution The outcome can be a static sum of known in advance stderr, stdout and exit code. This is referred to as static mode. It may also be desirale to have some side effects, e.g.: related to the execution itself like creating a file or related to the unit-test as counting the number of calls In other constellations the outocome may requires some computation to determine stderr/stdout/exicode as function of the request. We refer to these cases as dynamic mode. The execution is therefore modelled as function namely StubFunc. Thus, if required the StubFunc corresponding to the current stubbing will be looked-up and run. Outcome The stderr/stdout/exit-code part of the outcome is modeled as ExecOutcome. The execution the the stubfunc may result however in an error. Such error is not an actual sub-process execution erroneous outcome. It therefore must be modeled separately as opposed to be added to stderr and setting a non-zero exit code. Such and error can be communicated by using the ExecOutcome field InternalErrTxt. Stub-Executable It is the fake executable used to effectuate the overall outcome. It may release the outcome by itself. It may also cooperate with a test helper to achieve the outcome. The following command line is used: /tmp/go-build720053430/b001/xyz.test -test.run=TestHelperProcess -- arg1 arg2 arg3 It is not possible to use the test helper directly because we will need to inject the args test.run and -- at the actual execution call site. Two kinds of stub-executable are provided: bash based, which uses a bash script exec base, which used an go based executable Obviously the go based one is bound to support more platform than the bash based one. Both executable are genric and need context information about the stubbing for which they will be used. This context data is modeled as CmdConfig and saved as file alongside the executable. Inter process communication (IPC) to support dynamic outcomes The invocation of a StubFunc to produce a dynamic outcome is done in the unit test process. There is no means to access the stub function directly from the fake process execution. IPC is used here to allow the fake process to issue a StubRequest and receive an ExecOutcome. The Serialization/Deserialization mechanism needed for IPC must be understood by both parties (mind bash) and satisfy a domain specific requirement of been able to cope with multiline sterr and stdout. We choose a combination of : base64 to encode the discrete data (e.g. stderr, stdout) and comma separated value (easily encoded and decoded in bash) for envelope encoding Named pipes are used for the actual data transport, because they are file based and easily handle in different setups (e.g. in bash). Stubbing Setup An ExecStubber is provided to manage the stubbing setup. Its key feature is to setup an invokation of a StubFunc to replace the execution of a process, See ExecStubber.WhenExecDoStubFunc(...). It allows settings beyond the basic requirement of specifying the executable to be stubbed and a StubFunc replacement. This is modeled using Settings, which provides the following configuration options: Selecting and customizing the discovery mode (PATH vs. Home-Bin-Dir) Selecting the stub executable (Bash vs. Exec(go based)) Selecting the stubbing mode (static vs. dynamic) Specifying the test process helper method name specifying a timeout for a stub sub-process execution A stubbing setup is identified by a key. The key can be use to: unwind the setup(Unregister(..)) access the stubbing data basis of static requests (FindAllPersistedStubRequests, DeleteAllPersistedStubRequests ). Concurrency and parallelism The mutation of the process environment is the key enabling mechanism of Execstub. The process environment must therefore be guarded against issues of concurrency and parallelism. This also mean that is not possible to have a parallel stubbing setup for the same executable within a test process. The outcome will otherwise be non-deterministic because the setting will likely override each other. ExecStubber provides a locking mechanism to realize the serialization of the mutation of environment. For this to work correctly however there must only be one ExecStubber per unit test process. Note that the code under test can still execute its sub-processes concurrently or in parallel. The correctness of the outcome here dependents on the implementation of the StubFunc function being used. Static outcomes without side effect are of course always deterministic.

Package scrape provides a searching api on top of golang.org/x/net/html

Package freegeoip provides an API for searching the geolocation of IP addresses. It uses a database that can be either a local file or a remote resource from a URL. Local databases are monitored by fsnotify and reloaded when the file is either updated or overwritten. Remote databases are automatically downloaded and updated in background so you can focus on using the API and not managing the database.

Package enmime implements a MIME encoding and decoding library. It's built on top of Go's included mime/multipart support where possible, but is geared towards parsing MIME encoded emails. The enmime API has two conceptual layers. The lower layer is a tree of Part structs, representing each component of a decoded MIME message. The upper layer, called an Envelope provides an intuitive way to interact with a MIME message. Calling ReadParts causes enmime to parse the body of a MIME message into a tree of Part objects, each of which is aware of its content type, filename and headers. The content of a Part is available as a slice of bytes via the Content field. If the part was encoded in quoted-printable or base64, it is decoded prior to being placed in Content. If the Part contains text in a character set other than utf-8, enmime will attempt to convert it to utf-8. To locate a particular Part, pass a custom PartMatcher function into the BreadthMatchFirst() or DepthMatchFirst() methods to search the Part tree. BreadthMatchAll() and DepthMatchAll() will collect all Parts matching your criteria. ReadEnvelope returns an Envelope struct. Behind the scenes a Part tree is constructed, and then sorted into the correct fields of the Envelope. The Envelope contains both the plain text and HTML portions of the email. If there was no plain text Part available, the HTML Part will be down-converted using the html2text library1. The root of the Part tree, as well as slices of the inline and attachment Parts are also available. Every MIME Part has its own headers, accessible via the Part.Header field. The raw headers for an Envelope are available in Root.Header. Envelope also provides helper methods to fetch headers: GetHeader(key) will return the RFC 2047 decoded value of the specified header. AddressList(key) will convert the specified address header into a slice of net/mail.Address values. enmime attempts to be tolerant of poorly encoded MIME messages. In situations where parsing is not possible, the ReadEnvelope and ReadParts functions will return a hard error. If enmime is able to continue parsing the message, it will add an entry to the Errors slice on the relevant Part. After parsing is complete, all Part errors will be appended to the Envelope Errors slice. The Error* constants can be used to identify a specific class of error. Please note that enmime parses messages into memory, so it is not likely to perform well with multi-gigabyte attachments. enmime is open source software released under the MIT License. The latest version can be found at https://github.com/jhillyerd/enmime

This example opens https://github.com/, searches for "git", and then gets the header element which gives the description for Git. Rod use https://golang.org/pkg/context to handle cancelations for IO blocking operations, most times it's timeout. Context will be recursively passed to all sub-methods. For example, methods like Page.Context(ctx) will return a clone of the page with the ctx, all the methods of the returned page will use the ctx if they have IO blocking operations. Page.Timeout or Page.WithCancel is just a shortcut for Page.Context. Of course, Browser or Element works the same way. Shows how we can further customize the browser with the launcher library. Usually you use launcher lib to set the browser's command line flags (switches). Doc for flags: https://peter.sh/experiments/chromium-command-line-switches Shows how to change the retry/polling options that is used to query elements. This is useful when you want to customize the element query retry logic. When rod doesn't have a feature that you need. You can easily call the cdp to achieve it. List of cdp API: https://chromedevtools.github.io/devtools-protocol Shows how to disable headless mode and debug. Rod provides a lot of debug options, you can set them with setter methods or use environment variables. Doc for environment variables: https://pkg.go.dev/github.com/go-rod/rod/lib/defaults We use "Must" prefixed functions to write example code. But in production you may want to use the no-prefix version of them. About why we use "Must" as the prefix, it's similar to https://golang.org/pkg/regexp/#MustCompile Shows how to share a remote object reference between two Eval Shows how to listen for events. Shows how to intercept requests and modify both the request and the response. The entire process of hijacking one request: The --req-> and --res-> are the parts that can be modified. Show how to handle multiple results of an action. Such as when you login a page, the result can be success or wrong password. Example_search shows how to use Search to get element inside nested iframes or shadow DOMs. It works the same as https://developers.google.com/web/tools/chrome-devtools/dom#search Shows how to update the state of the current page. In this example we enable the network domain. Rod uses mouse cursor to simulate clicks, so if a button is moving because of animation, the click may not work as expected. We usually use WaitStable to make sure the target isn't changing anymore. When you want to wait for an ajax request to complete, this example will be useful.

Package dohyo provides a wrapper for Sumo Logic Search Job API tasks. Documentation for the API can be found here: https://help.sumologic.com/APIs/Search-Job-API/About-the-Search-Job-API

Package osdb is an API client for opensubtitles.org This is a client for the OSDb protocol. Currently the package only allows movie identification, subtitles search, and download.

Package errors provides simple error handling primitives. The traditional error handling idiom in Go is roughly akin to which applied recursively up the call stack results in error reports without context or debugging information. The errors package allows programmers to add context to the failure path in their code in a way that does not destroy the original value of the error. The errors.Annotate function returns a new error that adds context to the original error by recording a stack trace at the point Annotate is called, and the supplied message. For example If additional control is required the errors.AddStack and errors.WithMessage functions destructure errors.Annotate into its component operations of annotating an error with a stack trace and an a message, respectively. Using errors.Annotate constructs a stack of errors, adding context to the preceding error. Depending on the nature of the error it may be necessary to reverse the operation of errors.Annotate to retrieve the original error for inspection. Any error value which implements this interface can be inspected by errors.Cause. errors.Cause will recursively retrieve the topmost error which does not implement causer, which is assumed to be the original cause. For example: causer interface is not exported by this package, but is considered a part of stable public API. errors.Unwrap is also available: this will retrieve the next error in the chain. All error values returned from this package implement fmt.Formatter and can be formatted by the fmt package. The following verbs are supported New, Errorf, Annotate, and Annotatef record a stack trace at the point they are invoked. This information can be retrieved with the StackTracer interface that returns a StackTrace. Where errors.StackTrace is defined as The Frame type represents a call site in the stack trace. Frame supports the fmt.Formatter interface that can be used for printing information about the stack trace of this error. For example: See the documentation for Frame.Format for more details. errors.Find can be used to search for an error in the error chain.

Package scrape provides a searching api on top of golang.org/x/net/html

Package stringset provides the capabilities of a standard Set with strings, including the standard set operations and a specialized ability to have a "negative" set for intersections. Negative sets are useful for inverting the sense of a set when combining them using Intersection. Negative sets do not change the behavior of any other set operations, including Union and Difference. Negative operations were created for managing a set of tags, where it is useful to be able to search for items that contain some tags but do not contain others. The API is designed to be chainable so that common operations become one-liners, and it is designed to be easy to use with slices of strings. This package does not return errors. Set operations should be fast and chainable; adding items more than once, or attempting to remove things that don't exist are not errors.

Package freegeoip provides an API for searching the geolocation of IP addresses. It uses a database that can be either a local file or a remote resource from a URL. Local databases are monitored by fsnotify and reloaded when the file is either updated or overwritten. Remote databases are automatically downloaded and updated in background so you can focus on using the API and not managing the database. Also, the freegeoip package provides http handlers that any Go http server (net/http) can use. These handlers can process IP geolocation lookup requests and return data in multiple formats like CSV, XML, JSON and JSONP. It has also an API for supporting custom formats.

Package epaecho provides programmatic access to the EPA's Compliance History "All Data Facility Search" API (http://echo.epa.gov).

Package freegeoip provides an API for searching the geolocation of IP addresses. It uses a database that can be either a local file or a remote resource from a URL. Local databases are monitored by fsnotify and reloaded when the file is either updated or overwritten. Remote databases are automatically downloaded and updated in background so you can focus on using the API and not managing the database.

nHentai-go - A web scraping library for pulling doujinshi from nhentai after the public api was taken down. Provides the ability to search based on keyword, tag or id, with id providing full infomation about the doujinshi.

Package gohg is a Go client library for using the Mercurial dvcs via it's Command Server. For Mercurial see: http://mercurial.selenic.com. For the Hg Command Server see: http://mercurial.selenic.com/wiki/CommandServer. ▪ Mercurial For Mercurial any version starting from 1.9 should be ok, cause that's the one where the Command Server was introduced. If you send wrong options to it through gohg, or commands or options not yet supported (or obsolete) in your Hg version, you'll simply get back an error from Hg itself, as gohg does not check them. But on the other hand gohg allows issuing new commands, not yet implemented by gohg; see further. ▪ Go Currently gohg is currently developed with Go1.2.1. Though I started with the Go1.0 versions, I can't remember having had to change one or two minor things when moving to Go1.1.1. Updating to Go1.1.2 required no changes at all. I had an issue though with Go1.2, on Windows only, causing some tests using os.exec.Command to fail. I'll have to look into that further, to find out if I should report a bug. ▪ Platform I'm developing and testing both on Windows 7 and Ubuntu 12.04/13.04/13.10. But I suppose it should work on any other platform that supports Hg and Go. Only Go and it's standard library. And Mercurial should be installed of course. At the commandline type: to have gohg available in your GOPATH. Start with importing the gohg package. Examples: All interaction with the Mercurial Command Server (Hg CS from now on) happens through the HgClient type, of which you have to create an instance: Then you can connect the Hg CS as follows: 1. The Hg executable: The first parameter is the Mercurial command to use (which 'hg'). You can leave it blanc to let the gohg tool use the default Mercurial command on the system. Having a parameter for the Hg command allows for using a different Hg version, for testing purposes for instance. 2. The repository path: The second parameter is the path to the repository you want to work on. You can leave it blanc to have gohg use the repository it can find for the current path you are running the program in (searching upward in the folder tree eventually). 3. The config for the session: The third parameter allows to provide extra configuration for the session. Though this is currently not implemented yet. 4. Should gohg create a new repo before connecting? This fourth parameter allows you to indicate that you want gohg to first create a new Mercurial repo if it does not already exist in the path given by the second parameter. See the documentation for more detailed info. 5. The returnvalue: The HgClient.Connect() method eventually returns an error, so you can check if the connection succeeded, and if it is safe to go on. Once the work is done, you can disconnect the Hg CS using a typical Go idiom: The gohg tool sets some environment variables for the Hg CS session, to ensure it's good working: Once we have a connection to a Hg CS we can do some work with the repository. This is done with commands, and gohg offers 3 ways to use them. 1. The command methods of the HgClient type. 2. The HgCmd type. 3. The ExecCmd() method of the HgClient type. Each of which has its own reason of existence. Commands return a byte slice containing the resulting data, and eventually an error. But there are a few exceptions (see api docs). If a command fails, the returned error contains 5 elements: 1) the name of the internal routine where the error was trapped, 2) the name of the HgClient command that was run, 3) the returncode by Mercurial, 4) the full command that was passed to the Hg CS, and 5) the eventual error message returned by Mercurial. So the command could return something like the following in the err variable when it fails: The command aliases (like 'id' for 'identify') are not implemented. But there are examples in identify.go and showconfig.go of how you can easily implement them yourself. This is the easiest way, a kind of convenience. And the most readable too. A con is that as a user you cannot know the exact command that was passed to Hg, without some extra mechanics. Each command has the same name as the corresponding Hg command, except it starts with a capital letter of course. An example (also see examples/example1.go): Note that these methods all use the HgCmd type internally. As such they are convenience wrappers around that type. You could also consider them as a kind of syntactic sugar. If you just want to simply issue a command, nothing more, they are the way to go. The only way to obtain the commandstring sent to Hg when using these command methods, is by calling the HgClient.ShowLastCmd() method afterwards before issuing any other commands: Using the HgCmd type is kind of the standard way. It is a struct that you can instantiate for any command, and for which you can set elements Name, Options and Params (see the api docs for more details). It allows for building the command step by step, and also to query the exact command that will be sent to the Hg CS. A pro of this method is that it allows you to obtain the exact command string that will be passed to Mercurial before it is performed, by calling the CmdLine() method of HgCmd. This could be handy for logging, or for showing feedback to the user in a GUI program. (You could even call CmdLine() several times, and show the building of the command step by step.) An example (also see examples/example2.go): As you can see, this way requires some more coding. The source code will also show you that the HgCmd type is indeed used as the underlying type for the convenience HgClient commands, in all the New<hg-command>Cmd() constructors. The HgClient type has an extra method ExecCmd(), allowing you to pass a fully custom built command to Hg. It accepts a string slice that is supposed to contain all the elements of the complete command, as you would type it at the command line. It could be a convenient way for performing commands that are not yet implemented in gohg, or to make use of extensions to Hg (for which gohg offers no support (yet?)). An example (also see examples/example3.go): Just like on the commandline, options come before parameters. Options to commands use the same name as the long form of the Mercurial option they represent, but start with the necessary capital letter. An options value can be of type bool, int or string. You just pass the value as the parameter to the option (= type conversion of the value to the option type). You can pass any number of options, as the elements of a slice. Options can occur more than once if appropriate (see the ones marked with '[+]' in the Mercurial help). Parameters are used to provide any arguments for a command that are not options. They are passed in as a string or a slice of strings, depending on the command. These parameters typically contain revisions, paths or filenames and so. The gohg tool only checks if the options the caller gives are valid for that command. It does not check if the values are valid for the combination of that command and that option, as that is done by Mercurial. No need to implement that again. If an option is not valid for a command, it is silently ignored, so it is not passed to the Hg CS. A few options are not implemented, as they seemed not relevant for use with this tool (for instance: the global --color option, or the --print0 option for status). The gohg tool only returns errors, with an as clear as possible message, and never uses log.Fatal() nor panics, even if those may seem appropriate. It leaves it up to the caller to do that eventually. It's not up to this library to decide whether to do a retry or to abort the complete application. ▪ The following config settings are fixated in the code (at least for now): ▪ As mentioned earlier, passing config info is not implemented yet. ▪ Currently the only support for extensions to Mercurial is through the ExecCmd method. ▪ If multiple Hg CSs are used against the same repo, it is up to Mercurial to handle this correctly. ▪ Mercurial is always run in english. Internationalization is not necessary here, as the conversation with Hg is internal to the application. Please note that this tool is still in it's very early stages. If you have suggestions or requests, or experience any problems, please use the issue tracker at https://bitbucket.org/gohg/gohg/issues?status=new&status=open. Or you could send a patch or a pull request. Copyright 2012-2014, The gohg Authors. All rights reserved. Use of this source code is governed by a BSD style license that can be found in the LICENSE.md file.

Package errors provides simple error handling primitives. The traditional error handling idiom in Go is roughly akin to which applied recursively up the call stack results in error reports without context or debugging information. The errors package allows programmers to add context to the failure path in their code in a way that does not destroy the original value of the error. The errors.Annotate function returns a new error that adds context to the original error by recording a stack trace at the point Annotate is called, and the supplied message. For example If additional control is required the errors.AddStack and errors.WithMessage functions destructure errors.Annotate into its component operations of annotating an error with a stack trace and an a message, respectively. Using errors.Annotate constructs a stack of errors, adding context to the preceding error. Depending on the nature of the error it may be necessary to reverse the operation of errors.Annotate to retrieve the original error for inspection. Any error value which implements this interface can be inspected by errors.Cause. errors.Cause will recursively retrieve the topmost error which does not implement causer, which is assumed to be the original cause. For example: causer interface is not exported by this package, but is considered a part of stable public API. errors.Unwrap is also available: this will retrieve the next error in the chain. All error values returned from this package implement fmt.Formatter and can be formatted by the fmt package. The following verbs are supported New, Errorf, Annotate, and Annotatef record a stack trace at the point they are invoked. This information can be retrieved with the StackTracer interface that returns a StackTrace. Where errors.StackTrace is defined as The Frame type represents a call site in the stack trace. Frame supports the fmt.Formatter interface that can be used for printing information about the stack trace of this error. For example: See the documentation for Frame.Format for more details. errors.Find can be used to search for an error in the error chain.

Package errors provides simple error handling primitives. The traditional error handling idiom in Go is roughly akin to which applied recursively up the call stack results in error reports without context or debugging information. The errors package allows programmers to add context to the failure path in their code in a way that does not destroy the original value of the error. The errors.Annotate function returns a new error that adds context to the original error by recording a stack trace at the point Annotate is called, and the supplied message. For example If additional control is required the errors.AddStack and errors.WithMessage functions destructure errors.Annotate into its component operations of annotating an error with a stack trace and an a message, respectively. Using errors.Annotate constructs a stack of errors, adding context to the preceding error. Depending on the nature of the error it may be necessary to reverse the operation of errors.Annotate to retrieve the original error for inspection. Any error value which implements this interface can be inspected by errors.Cause. errors.Cause will recursively retrieve the topmost error which does not implement causer, which is assumed to be the original cause. For example: causer interface is not exported by this package, but is considered a part of stable public API. errors.Unwrap is also available: this will retrieve the next error in the chain. All error values returned from this package implement fmt.Formatter and can be formatted by the fmt package. The following verbs are supported New, Errorf, Annotate, and Annotatef record a stack trace at the point they are invoked. This information can be retrieved with the StackTracer interface that returns a StackTrace. Where errors.StackTrace is defined as The Frame type represents a call site in the stack trace. Frame supports the fmt.Formatter interface that can be used for printing information about the stack trace of this error. For example: See the documentation for Frame.Format for more details. errors.Find can be used to search for an error in the error chain.

Package pipl provides a way to interact programmatically with the PIPL API in Golang. For more detailed information on the PIPL search API and what we're actually wrapping, check out their official API reference: https://docs.pipl.com/reference/#overview

Package enmime implements a MIME encoding and decoding library. It's built on top of Go's included mime/multipart support where possible, but is geared towards parsing MIME encoded emails. The enmime API has two conceptual layers. The lower layer is a tree of Part structs, representing each component of a decoded MIME message. The upper layer, called an Envelope provides an intuitive way to interact with a MIME message. Calling ReadParts causes enmime to parse the body of a MIME message into a tree of Part objects, each of which is aware of its content type, filename and headers. The content of a Part is available as a slice of bytes via the Content field. If the part was encoded in quoted-printable or base64, it is decoded prior to being placed in Content. If the Part contains text in a character set other than utf-8, enmime will attempt to convert it to utf-8. To locate a particular Part, pass a custom PartMatcher function into the BreadthMatchFirst() or DepthMatchFirst() methods to search the Part tree. BreadthMatchAll() and DepthMatchAll() will collect all Parts matching your criteria. ReadEnvelope returns an Envelope struct. Behind the scenes a Part tree is constructed, and then sorted into the correct fields of the Envelope. The Envelope contains both the plain text and HTML portions of the email. If there was no plain text Part available, the HTML Part will be down-converted using the html2text library1. The root of the Part tree, as well as slices of the inline and attachment Parts are also available. Every MIME Part has its own headers, accessible via the Part.Header field. The raw headers for an Envelope are available in Root.Header. Envelope also provides helper methods to fetch headers: GetHeader(key) will return the RFC 2047 decoded value of the specified header. AddressList(key) will convert the specified address header into a slice of net/mail.Address values. enmime attempts to be tolerant of poorly encoded MIME messages. In situations where parsing is not possible, the ReadEnvelope and ReadParts functions will return a hard error. If enmime is able to continue parsing the message, it will add an entry to the Errors slice on the relevant Part. After parsing is complete, all Part errors will be appended to the Envelope Errors slice. The Error* constants can be used to identify a specific class of error. Please note that enmime parses messages into memory, so it is not likely to perform well with multi-gigabyte attachments. enmime is open source software released under the MIT License. The latest version can be found at https://github.com/jhillyerd/enmime

Package rod is a high-level driver directly based on DevTools Protocol. This example opens https://github.com/, searches for "git", and then gets the header element which gives the description for Git. Rod use https://golang.org/pkg/context to handle cancellations for IO blocking operations, most times it's timeout. Context will be recursively passed to all sub-methods. For example, methods like Page.Context(ctx) will return a clone of the page with the ctx, all the methods of the returned page will use the ctx if they have IO blocking operations. Page.Timeout or Page.WithCancel is just a shortcut for Page.Context. Of course, Browser or Element works the same way. Shows how we can further customize the browser with the launcher library. Usually you use launcher lib to set the browser's command line flags (switches). Doc for flags: https://peter.sh/experiments/chromium-command-line-switches Shows how to change the retry/polling options that is used to query elements. This is useful when you want to customize the element query retry logic. When rod doesn't have a feature that you need. You can easily call the cdp to achieve it. List of cdp API: https://github.com/apedem/rod/tree/master/lib/proto Shows how to disable headless mode and debug. Rod provides a lot of debug options, you can set them with setter methods or use environment variables. Doc for environment variables: https://pkg.go.dev/github.com/apedem/rod/lib/defaults We use "Must" prefixed functions to write example code. But in production you may want to use the no-prefix version of them. About why we use "Must" as the prefix, it's similar to https://golang.org/pkg/regexp/#MustCompile Shows how to share a remote object reference between two Eval Shows how to listen for events. Shows how to intercept requests and modify both the request and the response. The entire process of hijacking one request: The --req-> and --res-> are the parts that can be modified. Show how to handle multiple results of an action. Such as when you login a page, the result can be success or wrong password. Example_search shows how to use Search to get element inside nested iframes or shadow DOMs. It works the same as https://developers.google.com/web/tools/chrome-devtools/dom#search Shows how to update the state of the current page. In this example we enable the network domain. Rod uses mouse cursor to simulate clicks, so if a button is moving because of animation, the click may not work as expected. We usually use WaitStable to make sure the target isn't changing anymore. When you want to wait for an ajax request to complete, this example will be useful.

Package esquery provides a non-obtrusive, idiomatic and easy-to-use query and aggregation builder for the official Go client (https://github.com/elastic/go-elasticsearch) for the ElasticSearch database (https://www.elastic.co/products/elasticsearch). esquery alleviates the need to use extremely nested maps (map[string]interface{}) and serializing queries to JSON manually. It also helps eliminating common mistakes such as misspelling query types, as everything is statically typed. Using `esquery` can make your code much easier to write, read and maintain, and significantly reduce the amount of code you write. esquery provides a method chaining-style API for building and executing queries and aggregations. It does not wrap the official Go client nor does it require you to change your existing code in order to integrate the library. Queries can be directly built with `esquery`, and executed by passing an `*elasticsearch.Client` instance (with optional search parameters). Results are returned as-is from the official client (e.g. `*esapi.Response` objects). Getting started is extremely simple: esquery currently supports version 7 of the ElasticSearch Go client. The library cannot currently generate "short queries". For example, whereas ElasticSearch can accept this: { "query": { "term": { "user": "Kimchy" } } } The library will always generate this: This is also true for queries such as "bool", where fields like "must" can either receive one query object, or an array of query objects. `esquery` will generate an array even if there's only one query object.

Package conf is a configuration parser that loads configuration in a struct from files and automatically creates cli flags. Just define a struct with needed configuration. Values are then taken from multiple source in this order of precedence: Default is to use lower cased field names in struct to create command line arguments. Tags can be used to specify different names, command line help message and section in conf file. Format is: conf.Path variable can be set to the path of a configuration file. For default it is initialized to the value of environment variable: Files ending with: will be parsed as INI informal standard: First letter of every key found is upper cased and than, a struct field with same name is searched: If such field name is not found than comparison is made against key specified as first element in tag. conf tries to be modular and easily extensible to support different formats. This is a work in progress, APIs can change.

Package stringset provides the capabilities of a standard Set with strings, including the standard set operations and a specialized ability to have a "negative" set for intersections. Negative sets are useful for inverting the sense of a set when combining them using Intersection. Negative sets do not change the behavior of any other set operations, including Union and Difference. Negative operations were created for managing a set of tags, where it is useful to be able to search for items that contain some tags but do not contain others. The API is designed to be chainable so that common operations become one-liners, and it is designed to be easy to use with slices of strings. This package does not return errors. Set operations should be fast and chainable; adding items more than once, or attempting to remove things that don't exist are not errors.

SBWeb is the web-service for course work of developers34 team. It's supposed to search and hire specialists of building industry. Environment variables AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY must be specified. If environment variable PORT is specified then its value will override value of config API address. If environment variable REDIS_URL is specified then its value will override value of config SM DBAddress. If environment variable DATABASE_URL is specified then its value will override value of config DB DBAddress. To run application you need to specify the "cfg" parameter that receives path to config file formatted as JSON. Config has this structure:

Package freegeoip provides an API for searching the geolocation of IP addresses. It uses a database that can be either a local file or a remote resource from a URL. Local databases are monitored by fsnotify and reloaded when the file is either updated or overwritten. Remote databases are automatically downloaded and updated in background so you can focus on using the API and not managing the database. Also, the freegeoip package provides http handlers that any Go http server (net/http) can use. These handlers can process IP geolocation lookup requests and return data in multiple formats like CSV, XML, JSON and JSONP. It has also an API for supporting custom formats.

Package errors provides simple error handling primitives. The traditional error handling idiom in Go is roughly akin to which applied recursively up the call stack results in error reports without context or debugging information. The errors package allows programmers to add context to the failure path in their code in a way that does not destroy the original value of the error. The errors.Annotate function returns a new error that adds context to the original error by recording a stack trace at the point Annotate is called, and the supplied message. For example If additional control is required the errors.AddStack and errors.WithMessage functions destructure errors.Annotate into its component operations of annotating an error with a stack trace and an a message, respectively. Using errors.Annotate constructs a stack of errors, adding context to the preceding error. Depending on the nature of the error it may be necessary to reverse the operation of errors.Annotate to retrieve the original error for inspection. Any error value which implements this interface can be inspected by errors.Cause. errors.Cause will recursively retrieve the topmost error which does not implement causer, which is assumed to be the original cause. For example: causer interface is not exported by this package, but is considered a part of stable public API. errors.Unwrap is also available: this will retrieve the next error in the chain. All error values returned from this package implement fmt.Formatter and can be formatted by the fmt package. The following verbs are supported New, Errorf, Annotate, and Annotatef record a stack trace at the point they are invoked. This information can be retrieved with the StackTracer interface that returns a StackTrace. Where errors.StackTrace is defined as The Frame type represents a call site in the stack trace. Frame supports the fmt.Formatter interface that can be used for printing information about the stack trace of this error. For example: See the documentation for Frame.Format for more details. errors.Find can be used to search for an error in the error chain.

Package siahe provides a simple API for storing key/value(s) and retrieving the stored values by doing efficient prefix search on the keys.

Implement SASL / SCRAM-SHA-256 authentication. See RFC 5802, "Salted Challenge Response Authentication Mechanism (SCRAM) SASL and GSS-API Mechanisms". See PostgreSQL docs for how SASL is implemented in the PostgreSQL FE/BE protocol: Package pq is a pure Go Postgres driver for the database/sql package. In most cases clients will use the database/sql package instead of using this package directly. For example: You can also connect to a database using a URL. For example: Similarly to libpq, when establishing a connection using pq you are expected to supply a connection string containing zero or more parameters. A subset of the connection parameters supported by libpq are also supported by pq. Additionally, pq also lets you specify run-time parameters (such as search_path or work_mem) directly in the connection string. This is different from libpq, which does not allow run-time parameters in the connection string, instead requiring you to supply them in the options parameter. For compatibility with libpq, the following special connection parameters are supported: Valid values for sslmode are: See http://www.postgresql.org/docs/current/static/libpq-connect.html#LIBPQ-CONNSTRING for more information about connection string parameters. Use single quotes for values that contain whitespace: A backslash will escape the next character in values: Note that the connection parameter client_encoding (which sets the text encoding for the connection) may be set but must be "UTF8", matching with the same rules as Postgres. It is an error to provide any other value. In addition to the parameters listed above, any run-time parameter that can be set at backend start time can be set in the connection string. For more information, see http://www.postgresql.org/docs/current/static/runtime-config.html. Most environment variables as specified at http://www.postgresql.org/docs/current/static/libpq-envars.html supported by libpq are also supported by pq. If any of the environment variables not supported by pq are set, pq will panic during connection establishment. Environment variables have a lower precedence than explicitly provided connection parameters. The pgpass mechanism as described in http://www.postgresql.org/docs/current/static/libpq-pgpass.html is supported, but on Windows PGPASSFILE must be specified explicitly. database/sql does not dictate any specific format for parameter markers in query strings, and pq uses the Postgres-native ordinal markers, as shown above. The same marker can be reused for the same parameter: pq does not support the LastInsertId() method of the Result type in database/sql. To return the identifier of an INSERT (or UPDATE or DELETE), use the Postgres RETURNING clause with a standard Query or QueryRow call: For more details on RETURNING, see the Postgres documentation: For additional instructions on querying see the documentation for the database/sql package. Parameters pass through driver.DefaultParameterConverter before they are handled by this package. When the binary_parameters connection option is enabled, []byte values are sent directly to the backend as data in binary format. This package returns the following types for values from the PostgreSQL backend: All other types are returned directly from the backend as []byte values in text format. pq may return errors of type *pq.Error which can be interrogated for error details: See the pq.Error type for details. You can perform bulk imports by preparing a statement returned by pq.CopyIn (or pq.CopyInSchema) in an explicit transaction (sql.Tx). The returned statement handle can then be repeatedly "executed" to copy data into the target table. After all data has been processed you should call Exec() once with no arguments to flush all buffered data. Any call to Exec() might return an error which should be handled appropriately, but because of the internal buffering an error returned by Exec() might not be related to the data passed in the call that failed. CopyIn uses COPY FROM internally. It is not possible to COPY outside of an explicit transaction in pq. Usage example: PostgreSQL supports a simple publish/subscribe model over database connections. See http://www.postgresql.org/docs/current/static/sql-notify.html for more information about the general mechanism. To start listening for notifications, you first have to open a new connection to the database by calling NewListener. This connection can not be used for anything other than LISTEN / NOTIFY. Calling Listen will open a "notification channel"; once a notification channel is open, a notification generated on that channel will effect a send on the Listener.Notify channel. A notification channel will remain open until Unlisten is called, though connection loss might result in some notifications being lost. To solve this problem, Listener sends a nil pointer over the Notify channel any time the connection is re-established following a connection loss. The application can get information about the state of the underlying connection by setting an event callback in the call to NewListener. A single Listener can safely be used from concurrent goroutines, which means that there is often no need to create more than one Listener in your application. However, a Listener is always connected to a single database, so you will need to create a new Listener instance for every database you want to receive notifications in. The channel name in both Listen and Unlisten is case sensitive, and can contain any characters legal in an identifier (see http://www.postgresql.org/docs/current/static/sql-syntax-lexical.html#SQL-SYNTAX-IDENTIFIERS for more information). Note that the channel name will be truncated to 63 bytes by the PostgreSQL server. You can find a complete, working example of Listener usage at http://godoc.org/github.com/lib/pq/example/listen.

Package Nationbuilder provides an API client for the Nationbuilder remote API. In order to use it a client must be instantiated with a nation slug and remote API key. Create a nationbuilder client Call an endpoint Some endpoints have specific options available to them - for example the people search endpoint. In that case a special PeopleSearchOptions type can be passed to the client API call. In other cases where results can be paginated then a standard Options object can be provided to the api call specifying the max number of items to return (the limit) and providing the page token and nonce used to return a paginated resource. If a resource supports pagination then it provides a Next and Prev method which will return a suitably configured Options object or nil in the event that there are no more results. Alongside the resource requested, endpoints return a results object with information on the status code encountered and any error that was encountered. Make sure to call: to check whether an error has occurred.

Package freegeoip provides an API for searching the geolocation of IP addresses. It uses a database that can be either a local file or a remote resource from a URL. Local databases are monitored by fsnotify and reloaded when the file is either updated or overwritten. Remote databases are automatically downloaded and updated in background so you can focus on using the API and not managing the database.