Each project entry has a link to the project's own API documentation page that has complete documentation for that API.
The API index has a complete, alphabetized index of all the functions in the various projects.
These projects are made available under the Eclipse Public License (EPL). They are copyright 2008-2013 by Rich Hickey and the various contributors.
Note: Not all the projects in Clojure are currently documented on these pages. Please see https://github.com/clojure for the full repository of projects under the Clojure umbrella.
Generic arithmetic interface This library defines generic versions of + - * / as multimethods that can be defined for any type. The minimal required implementations for a type are binary + and * plus unary - and /. Everything else is derived from these automatically. Explicit binary definitions for - and / can be provided for efficiency reasons.
Generic collection interface This library defines generic versions of common collection-related functions as multimethods that can be defined for any type.
Generic comparison interface This library defines generic versions of = not= < > <= >= zero? as multimethods that can be defined for any type. Of the greater/less-than relations, types must minimally implement >.
Generic functor interface (fmap)
Generic math function interface This library defines generic versions of common mathematical functions such as sqrt or sin as multimethods that can be defined for any type.
This library contains the most commonly used monads as well as macros for defining and using monads and useful monadic functions.
Fundamental library of the Clojure language
Non-core data functions.
edn reading.
Graphical object inspector for Clojure data structures.
Start a web browser from Clojure
This file defines polymorphic I/O utility functions for Clojure.
A repl helper to quickly open javadocs.
Conveniently launch a sub-process providing its stdin and collecting its stdout
Top-level main function for Clojure REPL and scripts.
A Pretty Printer for Clojure clojure.pprint implements a flexible system for printing structured data in a pleasing, easy-to-understand format. Basic use of the pretty printer is simple, just call pprint instead of println. More advanced users can use the building blocks provided to create custom output formats. Out of the box, pprint supports a simple structured format for basic data and a specialized format for Clojure source code. More advanced formats, including formats that don't look like Clojure data at all like XML and JSON, can be rendered by creating custom dispatch functions. In addition to the pprint function, this module contains cl-format, a text formatting function which is fully compatible with the format function in Common Lisp. Because pretty printing directives are directly integrated with cl-format, it supports very concise custom dispatch. It also provides a more powerful alternative to Clojure's standard format function. See documentation for pprint and cl-format for more information or complete documentation on the the clojure web site on github.
Reflection on Host Types Alpha - subject to change. Two main entry points: * type-reflect reflects on something that implements TypeReference. * reflect (for REPL use) reflects on the class of an instance, or on a class if passed a class Key features: * Exposes the read side of reflection as pure data. Reflecting on a type returns a map with keys :bases, :flags, and :members. * Canonicalizes class names as Clojure symbols. Types can extend to the TypeReference protocol to indicate that they can be unambiguously resolved as a type name. The canonical format requires one non-Java-ish convention: array brackets are <> instead of [] so they can be part of a Clojure symbol. * Pluggable Reflectors for different implementations. The default JavaReflector is good when you have a class in hand, or use the AsmReflector for "hands off" reflection without forcing classes to load. Platform implementers must: * Create an implementation of Reflector. * Create one or more implementations of TypeReference. * def default-reflector to be an instance that satisfies Reflector.
Utilities meant to be used interactively at the REPL
Set operations such as union/intersection.
Print stack traces oriented towards Clojure, not Java.
Clojure String utilities It is poor form to (:use clojure.string). Instead, use require with :as to specify a prefix, e.g. (ns your.namespace.here (:require [clojure.string :as str])) Design notes for clojure.string: 1. Strings are objects (as opposed to sequences). As such, the string being manipulated is the first argument to a function; passing nil will result in a NullPointerException unless documented otherwise. If you want sequence-y behavior instead, use a sequence. 2. Functions are generally not lazy, and call straight to host methods where those are available and efficient. 3. Functions take advantage of String implementation details to write high-performing loop/recurs instead of using higher-order functions. (This is not idiomatic in general-purpose application code.) 4. When a function is documented to accept a string argument, it will take any implementation of the correct *interface* on the host platform. In Java, this is CharSequence, which is more general than String. In ordinary usage you will almost always pass concrete strings. If you are doing something unusual, e.g. passing a mutable implementation of CharSequence, then thread-safety is your responsibility.
Macros that expand to repeated copies of a template expression.
A unit testing framework. ASSERTIONS The core of the library is the "is" macro, which lets you make assertions of any arbitrary expression: (is (= 4 (+ 2 2))) (is (instance? Integer 256)) (is (.startsWith "abcde" "ab")) You can type an "is" expression directly at the REPL, which will print a message if it fails. user> (is (= 5 (+ 2 2))) FAIL in (:1) expected: (= 5 (+ 2 2)) actual: (not (= 5 4)) false The "expected:" line shows you the original expression, and the "actual:" shows you what actually happened. In this case, it shows that (+ 2 2) returned 4, which is not = to 5. Finally, the "false" on the last line is the value returned from the expression. The "is" macro always returns the result of the inner expression. There are two special assertions for testing exceptions. The "(is (thrown? c ...))" form tests if an exception of class c is thrown: (is (thrown? ArithmeticException (/ 1 0))) "(is (thrown-with-msg? c re ...))" does the same thing and also tests that the message on the exception matches the regular expression re: (is (thrown-with-msg? ArithmeticException #"Divide by zero" (/ 1 0))) DOCUMENTING TESTS "is" takes an optional second argument, a string describing the assertion. This message will be included in the error report. (is (= 5 (+ 2 2)) "Crazy arithmetic") In addition, you can document groups of assertions with the "testing" macro, which takes a string followed by any number of assertions. The string will be included in failure reports. Calls to "testing" may be nested, and all of the strings will be joined together with spaces in the final report, in a style similar to RSpec <http://rspec.info/> (testing "Arithmetic" (testing "with positive integers" (is (= 4 (+ 2 2))) (is (= 7 (+ 3 4)))) (testing "with negative integers" (is (= -4 (+ -2 -2))) (is (= -1 (+ 3 -4))))) Note that, unlike RSpec, the "testing" macro may only be used INSIDE a "deftest" or "with-test" form (see below). DEFINING TESTS There are two ways to define tests. The "with-test" macro takes a defn or def form as its first argument, followed by any number of assertions. The tests will be stored as metadata on the definition. (with-test (defn my-function [x y] (+ x y)) (is (= 4 (my-function 2 2))) (is (= 7 (my-function 3 4)))) As of Clojure SVN rev. 1221, this does not work with defmacro. See http://code.google.com/p/clojure/issues/detail?id=51 The other way lets you define tests separately from the rest of your code, even in a different namespace: (deftest addition (is (= 4 (+ 2 2))) (is (= 7 (+ 3 4)))) (deftest subtraction (is (= 1 (- 4 3))) (is (= 3 (- 7 4)))) This creates functions named "addition" and "subtraction", which can be called like any other function. Therefore, tests can be grouped and composed, in a style similar to the test framework in Peter Seibel's "Practical Common Lisp" <http://www.gigamonkeys.com/book/practical-building-a-unit-test-framework.html> (deftest arithmetic (addition) (subtraction)) The names of the nested tests will be joined in a list, like "(arithmetic addition)", in failure reports. You can use nested tests to set up a context shared by several tests. RUNNING TESTS Run tests with the function "(run-tests namespaces...)": (run-tests 'your.namespace 'some.other.namespace) If you don't specify any namespaces, the current namespace is used. To run all tests in all namespaces, use "(run-all-tests)". By default, these functions will search for all tests defined in a namespace and run them in an undefined order. However, if you are composing tests, as in the "arithmetic" example above, you probably do not want the "addition" and "subtraction" tests run separately. In that case, you must define a special function named "test-ns-hook" that runs your tests in the correct order: (defn test-ns-hook [] (arithmetic)) Note: test-ns-hook prevents execution of fixtures (see below). OMITTING TESTS FROM PRODUCTION CODE You can bind the variable "*load-tests*" to false when loading or compiling code in production. This will prevent any tests from being created by "with-test" or "deftest". FIXTURES Fixtures allow you to run code before and after tests, to set up the context in which tests should be run. A fixture is just a function that calls another function passed as an argument. It looks like this: (defn my-fixture [f] Perform setup, establish bindings, whatever. (f) Then call the function we were passed. Tear-down / clean-up code here. ) Fixtures are attached to namespaces in one of two ways. "each" fixtures are run repeatedly, once for each test function created with "deftest" or "with-test". "each" fixtures are useful for establishing a consistent before/after state for each test, like clearing out database tables. "each" fixtures can be attached to the current namespace like this: (use-fixtures :each fixture1 fixture2 ...) The fixture1, fixture2 are just functions like the example above. They can also be anonymous functions, like this: (use-fixtures :each (fn [f] setup... (f) cleanup...)) The other kind of fixture, a "once" fixture, is only run once, around ALL the tests in the namespace. "once" fixtures are useful for tasks that only need to be performed once, like establishing database connections, or for time-consuming tasks. Attach "once" fixtures to the current namespace like this: (use-fixtures :once fixture1 fixture2 ...) Note: Fixtures and test-ns-hook are mutually incompatible. If you are using test-ns-hook, fixture functions will *never* be run. SAVING TEST OUTPUT TO A FILE All the test reporting functions write to the var *test-out*. By default, this is the same as *out*, but you can rebind it to any PrintWriter. For example, it could be a file opened with clojure.java.io/writer. EXTENDING TEST-IS (ADVANCED) You can extend the behavior of the "is" macro by defining new methods for the "assert-expr" multimethod. These methods are called during expansion of the "is" macro, so they should return quoted forms to be evaluated. You can plug in your own test-reporting framework by rebinding the "report" function: (report event) The 'event' argument is a map. It will always have a :type key, whose value will be a keyword signaling the type of event being reported. Standard events with :type value of :pass, :fail, and :error are called when an assertion passes, fails, and throws an exception, respectively. In that case, the event will also have the following keys: :expected The form that was expected to be true :actual A form representing what actually occurred :message The string message given as an argument to 'is' The "testing" strings will be a list in "*testing-contexts*", and the vars being tested will be a list in "*testing-vars*". Your "report" function should wrap any printing calls in the "with-test-out" macro, which rebinds *out* to the current value of *test-out*. For additional event types, see the examples in the code.
This file defines a generic tree walker for Clojure data structures. It takes any data structure (list, vector, map, set, seq), calls a function on every element, and uses the return value of the function in place of the original. This makes it fairly easy to write recursive search-and-replace functions, as shown in the examples. Note: "walk" supports all Clojure data structures EXCEPT maps created with sorted-map-by. There is no (obvious) way to retrieve the sorting function.
XML reading/writing.
Functional hierarchical zipper, with navigation, editing, and enumeration. See Huet
A library for reduction and parallel folding. Alpha and subject to change. Note that fold and its derivatives require Java 7+ or Java 6 + jsr166y.jar for fork/join support. See Clojure's pom.xml for the dependency info.
Socket server support
clojure.test extension for JUnit-compatible XML output. JUnit (http://junit.org/) is the most popular unit-testing library for Java. As such, tool support for JUnit output formats is common. By producing compatible output from tests, this tool support can be exploited. To use, wrap any calls to clojure.test/run-tests in the with-junit-output macro, like this: (use 'clojure.test) (use 'clojure.test.junit) (with-junit-output (run-tests 'my.cool.library)) To write the output to a file, rebind clojure.test/*test-out* to your own PrintWriter (perhaps opened using clojure.java.io/writer).
clojure.test extensions for the Test Anything Protocol (TAP) TAP is a simple text-based syntax for reporting test results. TAP was originally developed for Perl, and now has implementations in several languages. For more information on TAP, see http://testanything.org/ and http://search.cpan.org/~petdance/TAP-1.0.0/TAP.pm To use this library, wrap any calls to clojure.test/run-tests in the with-tap-output macro, like this: (use 'clojure.test) (use 'clojure.test.tap) (with-tap-output (run-tests 'my.cool.library))
Facilities for async programming and communication. go blocks are dispatched over an internal thread pool, which defaults to 8 threads. The size of this pool can be modified using the Java system property `clojure.core.async.pool-size`.
core.async HIGHLY EXPERIMENTAL feature exploration Caveats: 1. Everything defined in this namespace is experimental, and subject to change or deletion without warning. 2. Many features provided by this namespace are highly coupled to implementation details of core.async. Potential features which operate at higher levels of abstraction are suitable for inclusion in the examples. 3. Features provided by this namespace MAY be promoted to clojure.core.async at a later point in time, but there is no guarantee any of them will.
The public contracts programming functions and macros for clojure.core.contracts.
Functions/macros variants of the ones that can be found in clojure.core (note to other contrib members: feel free to add to this lib)
Compile-time string interpolation for Clojure.
core.memoize is a memoization library offering functionality above Clojure's core `memoize` function in the following ways: **Pluggable memoization** core.memoize allows for different back-end cache implmentations to be used as appropriate without changing the memoization modus operandi. **Manipulable memoization** Because core.memoize allows you to access a function's memoization store, you do interesting things like clear it, modify it, and save it for later.
An implementation of the confluently persistent vector data structure introduced in Bagwell, Rompf, "RRB-Trees: Efficient Immutable Vectors", EPFL-REPORT-169879, September, 2011. RRB-Trees build upon Clojure's PersistentVectors, adding logarithmic time concatenation and slicing. The main API entry points are clojure.core.rrb-vector/catvec, performing vector concatenation, and clojure.core.rrb-vector/subvec, which produces a new vector containing the appropriate subrange of the input vector (in contrast to clojure.core/subvec, which returns a view on the input vector). core.rrb-vector's vectors can store objects or unboxed primitives. The implementation allows for seamless interoperability with clojure.lang.PersistentVector, clojure.core.Vec (more commonly known as gvec) and clojure.lang.APersistentVector$SubVector instances: clojure.core.rrb-vector/catvec and clojure.core.rrb-vector/subvec convert their inputs to clojure.core.rrb-vector.rrbt.Vector instances whenever necessary (this is a very fast constant time operation for PersistentVector and gvec; for SubVector it is O(log n), where n is the size of the underlying vector). clojure.core.rrb-vector also exports its own versions of vector and vector-of and vec which always produce clojure.core.rrb-vector.rrbt.Vector instances. Note that vector-of accepts :object as one of the possible type arguments, in addition to keywords naming primitive types.
This namespace contains typed wrapper macros, type aliases and functions for type checking Clojure code. check-ns is the interface for checking namespaces, cf for checking individual forms.
This namespace contains annotations and helper macros for type checking core.async code. Ensure clojure.core.async is require'd before performing type checking. go use go chan use chan buffer use buffer (similar for other buffer constructors)
Utilities for all implementations of the type checker
A contract system a la racket/contract. Main entry point is the `contract` macro.
This namespace contains easy tools for hole driven development
Extensible languages in Clojure, a la Racket's #lang. This is a simple library that monkey patches clojure.core/load to be extensible to different backends. `monkey-patch-extensible-load` does the actual monkey-patching and must be called explicitly. `lang-dispatch` is a map from keywords to alternative `load` functions (of type [String -> nil]). The corresponding function will be used to load a file according its :lang metadata entry in the `ns` form. To add a new implementation, use (alter-var-root lang-dispatch assoc :new-impl my-load) eg. A file with a `ns` form (ns fancy-ns-form {:lang :new-impl}) will use `my-load` to load the file.
Front end for actual implementation in clojure.core.typed.load1. Indirection is necessary to delay loading core.typed as long as possible.
Implementation of clojure.core.typed.load.
Adds runtime checks where annotations are instead of type checking
An implementation of persistent sorted maps and sets based on AVL trees which can be used as drop-in replacements for Clojure's built-in sorted maps and sets based on red-black trees. Apart from the standard sorted collection API, the provided map and set types support the transients API and several additional logarithmic time operations: rank queries via clojure.core/nth (select element by rank) and clojure.data.avl/rank-of (discover rank of element), "nearest key" lookups via clojure.data.avl/nearest, splits by key and index via clojure.data.avl/split-key and clojure.data.avl/split-at, respectively, and subsets/submaps using clojure.data.avl/subrange.
Functions for working with base64 encodings.
Persistent collections based on 2-3 finger trees.
Read/write fressian data. See http://www.edn-format.org/
JavaScript Object Notation (JSON) parser/generator. See http://www.json.org/
A priority map is very similar to a sorted map, but whereas a sorted map produces a sequence of the entries sorted by key, a priority map produces the entries sorted by value. In addition to supporting all the functions a sorted map supports, a priority map can also be thought of as a queue of [item priority] pairs. To support usage as a versatile priority queue, priority maps also support conj/peek/pop operations. The standard way to construct a priority map is with priority-map: user=> (def p (priority-map :a 2 :b 1 :c 3 :d 5 :e 4 :f 3)) #'user/p user=> p {:b 1, :a 2, :c 3, :f 3, :e 4, :d 5} So :b has priority 1, :a has priority 2, and so on. Notice how the priority map prints in an order sorted by its priorities (i.e., the map's values) We can use assoc to assign a priority to a new item: user=> (assoc p :g 1) {:b 1, :g 1, :a 2, :c 3, :f 3, :e 4, :d 5} or to assign a new priority to an extant item: user=> (assoc p :c 4) {:b 1, :a 2, :f 3, :c 4, :e 4, :d 5} We can remove an item from the priority map: user=> (dissoc p :e) {:b 1, :a 2, :c 3, :f 3, :d 5} An alternative way to add to the priority map is to conj a [item priority] pair: user=> (conj p [:g 0]) {:g 0, :b 1, :a 2, :c 3, :f 3, :e 4, :d 5} or use into: user=> (into p [[:g 0] [:h 1] [:i 2]]) {:g 0, :b 1, :h 1, :a 2, :i 2, :c 3, :f 3, :e 4, :d 5} Priority maps are countable: user=> (count p) 6 Like other maps, equivalence is based not on type, but on contents. In other words, just as a sorted-map can be equal to a hash-map, so can a priority-map. user=> (= p {:b 1, :a 2, :c 3, :f 3, :e 4, :d 5}) true You can test them for emptiness: user=> (empty? (priority-map)) true user=> (empty? p) false You can test whether an item is in the priority map: user=> (contains? p :a) true user=> (contains? p :g) false It is easy to look up the priority of a given item, using any of the standard map mechanisms: user=> (get p :a) 2 user=> (get p :g 10) 10 user=> (p :a) 2 user=> (:a p) 2 Priority maps derive much of their utility by providing priority-based seq. Note that no guarantees are made about the order in which items of the same priority appear. user=> (seq p) ([:b 1] [:a 2] [:c 3] [:f 3] [:e 4] [:d 5]) Because no guarantees are made about the order of same-priority items, note that rseq might not be an exact reverse of the seq. It is only guaranteed to be in descending order. user=> (rseq p) ([:d 5] [:e 4] [:c 3] [:f 3] [:a 2] [:b 1]) This means first/rest/next/for/map/etc. all operate in priority order. user=> (first p) [:b 1] user=> (rest p) ([:a 2] [:c 3] [:f 3] [:e 4] [:d 5]) Priority maps support metadata: user=> (meta (with-meta p {:extra :info})) {:extra :info} But perhaps most importantly, priority maps can also function as priority queues. peek, like first, gives you the first [item priority] pair in the collection. pop removes the first [item priority] from the collection. (Note that unlike rest, which returns a seq, pop returns a priority map). user=> (peek p) [:b 1] user=> (pop p) {:a 2, :c 3, :f 3, :e 4, :d 5} It is also possible to use a custom comparator: user=> (priority-map-by > :a 1 :b 2 :c 3) {:c 3, :b 2, :a 1} Sometimes, it is desirable to have a map where the values contain more information than just the priority. For example, let's say you want a map like: {:a [2 :apple], :b [1 :banana], :c [3 :carrot]} and you want to sort the map by the numeric priority found in the pair. A common mistake is to try to solve this with a custom comparator: (priority-map (fn [[priority1 _] [priority2 _]] (< priority1 priority2)) :a [2 :apple], :b [1 :banana], :c [3 :carrot]) This will not work! In Clojure, like Java, all comparators must be total orders, meaning that you can't have a tie unless the objects you are comparing are in fact equal. The above comparator breaks that rule because [2 :apple] and [2 :apricot] tie, but are not equal. The correct way to construct such a priority map is by specifying a keyfn, which is used to extract the true priority from the priority map's vals. (Note: It might seem a little odd that the priority-extraction function is called a *key*fn, even though it is applied to the map's values. This terminology is based on the docstring of clojure.core/sort-by, which uses `keyfn` for the function which extracts the sort order.) In the above example, user=> (priority-map-keyfn first :a [2 :apple], :b [1 :banana], :c [3 :carrot]) {:b [1 :banana], :a [2 :apple], :c [3 :carrot]} You can also combine a keyfn with a comparator that operates on the extracted priorities: user=> (priority-map-keyfn-by first > :a [2 :apple], :b [1 :banana], :c [3 :carrot]) {:c [3 :carrot], :a [2 :apple], :b [1 :banana]} All of these operations are efficient. Generally speaking, most operations are O(log n) where n is the number of distinct priorities. Some operations (for example, straightforward lookup of an item's priority, or testing whether a given item is in the priority map) are as efficient as Clojure's built-in map. The key to this efficiency is that internally, not only does the priority map store an ordinary hash map of items to priority, but it also stores a sorted map that maps priorities to sets of items with that priority. A typical textbook priority queue data structure supports at the ability to add a [item priority] pair to the queue, and to pop/peek the next [item priority] pair. But many real-world applications of priority queues require more features, such as the ability to test whether something is already in the queue, or to reassign a priority. For example, a standard formulation of Dijkstra's algorithm requires the ability to reduce the priority number associated with a given item. Once you throw persistence into the mix with the desire to adjust priorities, the traditional structures just don't work that well. This particular blend of Clojure's built-in hash sets, hash maps, and sorted maps proved to be a great way to implement an especially flexible persistent priority queue. Connoisseurs of algorithms will note that this structure's peek operation is not O(1) as it would be if based upon a heap data structure, but I feel this is a small concession for the blend of persistence, priority reassignment, and priority-sorted seq, which can be quite expensive to achieve with a heap (I did actually try this for comparison). Furthermore, this peek's logarithmic behavior is quite good (on my computer I can do a million peeks at a priority map with a million items in 750ms). Also, consider that peek and pop usually follow one another, and even with a heap, pop is logarithmic. So the net combination of peek and pop is not much different between this versatile formulation of a priority map and a more limited heap-based one. In a nutshell, peek, although not O(1), is unlikely to be the bottleneck in your program. All in all, I hope you will find priority maps to be an easy-to-use and useful addition to Clojure's assortment of built-in maps (hash-map and sorted-map).
Functions to parse XML into lazy sequences and lazy trees and emit these as text.
Data type for xml pull events
Shared private code for data.xml namespaces
JVM implementation of the emitter details
Data types for xml nodes: Element, CData and Comment
System for filtering trees and nodes generated by zip.clj in general, and xml trees in particular.
Utilities for dealing with the JVM's classpath
Support for recursively converting Java beans to Clojure and vice versa.
A Clojure interface to SQL databases via JDBC clojure.java.jdbc provides a simple abstraction for CRUD (create, read, update, delete) operations on a SQL database, along with basic transaction support. Basic DDL operations are also supported (create table, drop table, access to table metadata). Maps are used to represent records, making it easy to store and retrieve data. Results can be processed using any standard sequence operations. For most operations, Java's PreparedStatement is used so your SQL and parameters can be represented as simple vectors where the first element is the SQL string, with ? for each parameter, and the remaining elements are the parameter values to be substituted. In general, operations return the number of rows affected, except for a single record insert where any generated keys are returned (as a map). For more documentation, see: http://clojure-doc.org/articles/ecosystem/java_jdbc/home.html
Optional specifications for use with Clojure 1.9 or later.
JMX support for Clojure Usage (require '[clojure.java.jmx :as jmx]) What beans do I have? (jmx/mbean-names "*:*") -> #<HashSet [java.lang:type=MemoryPool,name=CMS Old Gen, java.lang:type=Memory, ...] What attributes does a bean have? (jmx/attribute-names "java.lang:type=Memory") -> (:Verbose :ObjectPendingFinalizationCount :HeapMemoryUsage :NonHeapMemoryUsage) What is the value of an attribute? (jmx/read "java.lang:type=Memory" :ObjectPendingFinalizationCount) -> 0 (jmx/read "java.lang:type=Memory" [:HeapMemoryUsage :NonHeapMemoryUsage]) -> {:NonHeapMemoryUsage {:used 16674024, :max 138412032, :init 24317952, :committed 24317952}, :HeapMemoryUsage {:used 18619064, :max 85393408, :init 0, :committed 83230720}} Can't I just have *all* the attributes in a Clojure map? (jmx/mbean "java.lang:type=Memory") -> {:NonHeapMemoryUsage {:used 16674024, :max 138412032, :init 24317952, :committed 24317952}, :HeapMemoryUsage {:used 18619064, :max 85393408, :init 0, :committed 83230720}, :ObjectPendingFinalizationCount 0, :Verbose false} Can I find and invoke an operation? (jmx/operation-names "java.lang:type=Memory") -> (:gc) (jmx/invoke "java.lang:type=Memory" :gc) -> nil What about some other process? Just run *any* of the above code inside a with-connection: (jmx/with-connection {:host "localhost", :port 3000} (jmx/mbean "java.lang:type=Memory")) -> {:ObjectPendingFinalizationCount 0, :HeapMemoryUsage ... etc.} Can I serve my own beans? Sure, just drop a Clojure ref into an instance of clojure.java.jmx.Bean, and the bean will expose read-only attributes for every key/value pair in the ref: (jmx/register-mbean (create-bean (ref {:string-attribute "a-string"})) "my.namespace:name=Value")
Efficient, functional algorithms for generating lazy sequences for common combinatorial functions. (See the source code for a longer description.)
Math functions that deal intelligently with the various types in Clojure's numeric tower, as well as math functions commonly found in Scheme implementations. expt - (expt x y) is x to the yth power, returns an exact number if the base is an exact number, and the power is an integer, otherwise returns a double. abs - (abs n) is the absolute value of n gcd - (gcd m n) returns the greatest common divisor of m and n lcm - (lcm m n) returns the least common multiple of m and n When floor, ceil, and round are passed doubles, we just defer to the corresponding functions in Java's Math library. Java's behavior is somewhat strange (floor and ceil return doubles rather than integers, and round on large doubles yields spurious results) but it seems best to match Java's semantics. On exact numbers (ratios and decimals), we can have cleaner semantics. floor - (floor n) returns the greatest integer less than or equal to n. If n is an exact number, floor returns an integer, otherwise a double. ceil - (ceil n) returns the least integer greater than or equal to n. If n is an exact number, ceil returns an integer, otherwise a double. round - (round n) rounds to the nearest integer. round always returns an integer. round rounds up for values exactly in between two integers. sqrt - Implements the sqrt behavior I'm accustomed to from PLT Scheme, specifically, if the input is an exact number, and is a square of an exact number, the output will be exact. The downside is that for the common case (inexact square root), some extra computation is done to look for an exact square root first. So if you need blazingly fast square root performance, and you know you're just going to need a double result, you're better off calling java's Math/sqrt, or alternatively, you could just convert your input to a double before calling this sqrt function. If Clojure ever gets complex numbers, then this function will need to be updated (so negative inputs yield complex outputs). exact-integer-sqrt - Implements a math function from the R6RS Scheme standard. (exact-integer-sqrt k) where k is a non-negative integer, returns [s r] where k = s^2+r and k < (s+1)^2. In other words, it returns the floor of the square root and the "remainder".
Analyzer for clojure code, host agnostic. Entry point: * analyze Platform implementers must provide dynamic bindings for: * macroexpand-1 * parse * create-var * var? Setting up the global env is also required, see clojure.tools.analyzer.env See clojure.tools.analyzer.core-test for an example on how to setup the analyzer.
Utilities for AST walking/updating
Utilities for querying tools.analyzer ASTs with Datomic
Utilities for pass scheduling
Analyzer for clojurescript code, extends tools.analyzer with JS specific passes/forms
Analyzer for clojure code, extends tools.analyzer with JVM specific passes/forms
Logging macros which delegate to a specific logging implementation. At runtime a specific implementation is selected from, in order, slf4j, Apache commons-logging, log4j, and finally java.util.logging. The logging implementation can be expliticly determined by using binding or alter-var-root to change the value of *logger-factory* to another implementation of clojure.tools.logging.impl/LoggerFactory (see also the *-factory functions in the impl namespace).
Protocols used to allow access to logging implementations. This namespace only need be used by those providing logging implementations to be consumed by the core api.
Local macros and symbol macros Local macros are defined by a macrolet form. They are usable only inside its body. Symbol macros can be defined globally (defsymbolmacro) or locally (symbol-macrolet). A symbol macro defines a form that replaces a symbol during macro expansion. Function arguments and symbols bound in let forms are not subject to symbol macro expansion. Local macros are most useful in the definition of the expansion of another macro, they may be used anywhere. Global symbol macros can be used only inside a with-symbol-macros form.
This namespace is DEPRECATED; most functions have been moved to other namespaces
Bidirectional graphs of dependencies and dependent objects.
Track namespace dependencies and changes by monitoring file-modification timestamps
Read and track namespace information from files
Search for namespace declarations in directories and JAR files.
Refactoring tool to move a Clojure namespace from one name/file to another, and update all references to that namespace in your other Clojure source files. WARNING: This code is ALPHA and subject to change. It also modifies and deletes your source files! Make sure you have a backup or version control.
Parse Clojure namespace (ns) declarations and extract dependencies.
Force reloading namespaces on demand or through a dependency tracker
REPL utilities for working with namespaces
Dependency tracker which can compute which namespaces need to be reloaded after files have changed. This is the low-level implementation that requires you to find the namespace dependencies yourself: most uses will interact with the wrappers in clojure.tools.namespace.file and clojure.tools.namespace.dir or the public API in clojure.tools.namespace.repl.
High level nREPL client support.
A netstring and bencode implementation for Clojure.
A proof-of-concept command-line client for nREPL. Please see e.g. reply for a proper command-line nREPL client @ https://github.com/trptcolin/reply/
Support for persistent, cross-connection REPL sessions.
Misc utilities used in nREPL's implementation (potentially also useful for anyone extending it).
Default server implementations
A clojure reader in clojure
An EDN reader in clojure
This file defines simple tracing macros to help you see what your code is doing.