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1 .. _overview:
1 .. _overview:
2
2
3 ============
3 ============
4 Introduction
4 Introduction
5 ============
5 ============
6
6
7 Overview
7 Overview
8 ========
8 ========
9
9
10 One of Python's most useful features is its interactive interpreter.
10 One of Python's most useful features is its interactive interpreter.
11 This system allows very fast testing of ideas without the overhead of
11 This system allows very fast testing of ideas without the overhead of
12 creating test files as is typical in most programming languages.
12 creating test files as is typical in most programming languages.
13 However, the interpreter supplied with the standard Python distribution
13 However, the interpreter supplied with the standard Python distribution
14 is somewhat limited for extended interactive use.
14 is somewhat limited for extended interactive use.
15
15
16 The goal of IPython is to create a comprehensive environment for
16 The goal of IPython is to create a comprehensive environment for
17 interactive and exploratory computing. To support this goal, IPython
17 interactive and exploratory computing. To support this goal, IPython
18 has two main components:
18 has three main components:
19
19
20 * An enhanced interactive Python shell.
20 * An enhanced interactive Python shell.
21 * A decoupled two-process communication model, which allows for multiple
22 clients to connect to a computation kernel, most notably the web-based
23 :ref:`notebook <htmlnotebook>`
21 * An architecture for interactive parallel computing.
24 * An architecture for interactive parallel computing.
22
25
23 All of IPython is open source (released under the revised BSD license).
26 All of IPython is open source (released under the revised BSD license).
24
27
25 Enhanced interactive Python shell
28 Enhanced interactive Python shell
26 =================================
29 =================================
27
30
28 IPython's interactive shell (:command:`ipython`), has the following goals,
31 IPython's interactive shell (:command:`ipython`), has the following goals,
29 amongst others:
32 amongst others:
30
33
31 1. Provide an interactive shell superior to Python's default. IPython
34 1. Provide an interactive shell superior to Python's default. IPython
32 has many features for object introspection, system shell access,
35 has many features for object introspection, system shell access,
33 and its own special command system for adding functionality when
36 and its own special command system for adding functionality when
34 working interactively. It tries to be a very efficient environment
37 working interactively. It tries to be a very efficient environment
35 both for Python code development and for exploration of problems
38 both for Python code development and for exploration of problems
36 using Python objects (in situations like data analysis).
39 using Python objects (in situations like data analysis).
37
40
38 2. Serve as an embeddable, ready to use interpreter for your own
41 2. Serve as an embeddable, ready to use interpreter for your own
39 programs. IPython can be started with a single call from inside
42 programs. IPython can be started with a single call from inside
40 another program, providing access to the current namespace. This
43 another program, providing access to the current namespace. This
41 can be very useful both for debugging purposes and for situations
44 can be very useful both for debugging purposes and for situations
42 where a blend of batch-processing and interactive exploration are
45 where a blend of batch-processing and interactive exploration are
43 needed. New in the 0.9 version of IPython is a reusable wxPython
46 needed. New in the 0.9 version of IPython is a reusable wxPython
44 based IPython widget.
47 based IPython widget.
45
48
46 3. Offer a flexible framework which can be used as the base
49 3. Offer a flexible framework which can be used as the base
47 environment for other systems with Python as the underlying
50 environment for other systems with Python as the underlying
48 language. Specifically scientific environments like Mathematica,
51 language. Specifically scientific environments like Mathematica,
49 IDL and Matlab inspired its design, but similar ideas can be
52 IDL and Matlab inspired its design, but similar ideas can be
50 useful in many fields.
53 useful in many fields.
51
54
52 4. Allow interactive testing of threaded graphical toolkits. IPython
55 4. Allow interactive testing of threaded graphical toolkits. IPython
53 has support for interactive, non-blocking control of GTK, Qt and
56 has support for interactive, non-blocking control of GTK, Qt and
54 WX applications via special threading flags. The normal Python
57 WX applications via special threading flags. The normal Python
55 shell can only do this for Tkinter applications.
58 shell can only do this for Tkinter applications.
56
59
57 Main features of the interactive shell
60 Main features of the interactive shell
58 --------------------------------------
61 --------------------------------------
59
62
60 * Dynamic object introspection. One can access docstrings, function
63 * Dynamic object introspection. One can access docstrings, function
61 definition prototypes, source code, source files and other details
64 definition prototypes, source code, source files and other details
62 of any object accessible to the interpreter with a single
65 of any object accessible to the interpreter with a single
63 keystroke (:samp:`?`, and using :samp:`??` provides additional detail).
66 keystroke (:samp:`?`, and using :samp:`??` provides additional detail).
64
67
65 * Searching through modules and namespaces with :samp:`*` wildcards, both
68 * Searching through modules and namespaces with :samp:`*` wildcards, both
66 when using the :samp:`?` system and via the :samp:`%psearch` command.
69 when using the :samp:`?` system and via the :samp:`%psearch` command.
67
70
68 * Completion in the local namespace, by typing :kbd:`TAB` at the prompt.
71 * Completion in the local namespace, by typing :kbd:`TAB` at the prompt.
69 This works for keywords, modules, methods, variables and files in the
72 This works for keywords, modules, methods, variables and files in the
70 current directory. This is supported via the readline library, and
73 current directory. This is supported via the readline library, and
71 full access to configuring readline's behavior is provided.
74 full access to configuring readline's behavior is provided.
72 Custom completers can be implemented easily for different purposes
75 Custom completers can be implemented easily for different purposes
73 (system commands, magic arguments etc.)
76 (system commands, magic arguments etc.)
74
77
75 * Numbered input/output prompts with command history (persistent
78 * Numbered input/output prompts with command history (persistent
76 across sessions and tied to each profile), full searching in this
79 across sessions and tied to each profile), full searching in this
77 history and caching of all input and output.
80 history and caching of all input and output.
78
81
79 * User-extensible 'magic' commands. A set of commands prefixed with
82 * User-extensible 'magic' commands. A set of commands prefixed with
80 :samp:`%` is available for controlling IPython itself and provides
83 :samp:`%` is available for controlling IPython itself and provides
81 directory control, namespace information and many aliases to
84 directory control, namespace information and many aliases to
82 common system shell commands.
85 common system shell commands.
83
86
84 * Alias facility for defining your own system aliases.
87 * Alias facility for defining your own system aliases.
85
88
86 * Complete system shell access. Lines starting with :samp:`!` are passed
89 * Complete system shell access. Lines starting with :samp:`!` are passed
87 directly to the system shell, and using :samp:`!!` or :samp:`var = !cmd`
90 directly to the system shell, and using :samp:`!!` or :samp:`var = !cmd`
88 captures shell output into python variables for further use.
91 captures shell output into python variables for further use.
89
92
90 * Background execution of Python commands in a separate thread.
93 * Background execution of Python commands in a separate thread.
91 IPython has an internal job manager called jobs, and a
94 IPython has an internal job manager called jobs, and a
92 convenience backgrounding magic function called :samp:`%bg`.
95 convenience backgrounding magic function called :samp:`%bg`.
93
96
94 * The ability to expand python variables when calling the system shell. In a
97 * The ability to expand python variables when calling the system shell. In a
95 shell command, any python variable prefixed with :samp:`$` is expanded. A
98 shell command, any python variable prefixed with :samp:`$` is expanded. A
96 double :samp:`$$` allows passing a literal :samp:`$` to the shell (for access
99 double :samp:`$$` allows passing a literal :samp:`$` to the shell (for access
97 to shell and environment variables like :envvar:`PATH`).
100 to shell and environment variables like :envvar:`PATH`).
98
101
99 * Filesystem navigation, via a magic :samp:`%cd` command, along with a
102 * Filesystem navigation, via a magic :samp:`%cd` command, along with a
100 persistent bookmark system (using :samp:`%bookmark`) for fast access to
103 persistent bookmark system (using :samp:`%bookmark`) for fast access to
101 frequently visited directories.
104 frequently visited directories.
102
105
103 * A lightweight persistence framework via the :samp:`%store` command, which
106 * A lightweight persistence framework via the :samp:`%store` command, which
104 allows you to save arbitrary Python variables. These get restored
107 allows you to save arbitrary Python variables. These get restored
105 automatically when your session restarts.
108 automatically when your session restarts.
106
109
107 * Automatic indentation (optional) of code as you type (through the
110 * Automatic indentation (optional) of code as you type (through the
108 readline library).
111 readline library).
109
112
110 * Macro system for quickly re-executing multiple lines of previous
113 * Macro system for quickly re-executing multiple lines of previous
111 input with a single name. Macros can be stored persistently via
114 input with a single name. Macros can be stored persistently via
112 :samp:`%store` and edited via :samp:`%edit`.
115 :samp:`%store` and edited via :samp:`%edit`.
113
116
114 * Session logging (you can then later use these logs as code in your
117 * Session logging (you can then later use these logs as code in your
115 programs). Logs can optionally timestamp all input, and also store
118 programs). Logs can optionally timestamp all input, and also store
116 session output (marked as comments, so the log remains valid
119 session output (marked as comments, so the log remains valid
117 Python source code).
120 Python source code).
118
121
119 * Session restoring: logs can be replayed to restore a previous
122 * Session restoring: logs can be replayed to restore a previous
120 session to the state where you left it.
123 session to the state where you left it.
121
124
122 * Verbose and colored exception traceback printouts. Easier to parse
125 * Verbose and colored exception traceback printouts. Easier to parse
123 visually, and in verbose mode they produce a lot of useful
126 visually, and in verbose mode they produce a lot of useful
124 debugging information (basically a terminal version of the cgitb
127 debugging information (basically a terminal version of the cgitb
125 module).
128 module).
126
129
127 * Auto-parentheses: callable objects can be executed without
130 * Auto-parentheses: callable objects can be executed without
128 parentheses: :samp:`sin 3` is automatically converted to :samp:`sin(3)`.
131 parentheses: :samp:`sin 3` is automatically converted to :samp:`sin(3)`.
129
132
130 * Auto-quoting: using :samp:`,`, or :samp:`;` as the first character forces
133 * Auto-quoting: using :samp:`,`, or :samp:`;` as the first character forces
131 auto-quoting of the rest of the line: :samp:`,my_function a b` becomes
134 auto-quoting of the rest of the line: :samp:`,my_function a b` becomes
132 automatically :samp:`my_function("a","b")`, while :samp:`;my_function a b`
135 automatically :samp:`my_function("a","b")`, while :samp:`;my_function a b`
133 becomes :samp:`my_function("a b")`.
136 becomes :samp:`my_function("a b")`.
134
137
135 * Extensible input syntax. You can define filters that pre-process
138 * Extensible input syntax. You can define filters that pre-process
136 user input to simplify input in special situations. This allows
139 user input to simplify input in special situations. This allows
137 for example pasting multi-line code fragments which start with
140 for example pasting multi-line code fragments which start with
138 :samp:`>>>` or :samp:`...` such as those from other python sessions or the
141 :samp:`>>>` or :samp:`...` such as those from other python sessions or the
139 standard Python documentation.
142 standard Python documentation.
140
143
141 * Flexible configuration system. It uses a configuration file which
144 * Flexible configuration system. It uses a configuration file which
142 allows permanent setting of all command-line options, module
145 allows permanent setting of all command-line options, module
143 loading, code and file execution. The system allows recursive file
146 loading, code and file execution. The system allows recursive file
144 inclusion, so you can have a base file with defaults and layers
147 inclusion, so you can have a base file with defaults and layers
145 which load other customizations for particular projects.
148 which load other customizations for particular projects.
146
149
147 * Embeddable. You can call IPython as a python shell inside your own
150 * Embeddable. You can call IPython as a python shell inside your own
148 python programs. This can be used both for debugging code or for
151 python programs. This can be used both for debugging code or for
149 providing interactive abilities to your programs with knowledge
152 providing interactive abilities to your programs with knowledge
150 about the local namespaces (very useful in debugging and data
153 about the local namespaces (very useful in debugging and data
151 analysis situations).
154 analysis situations).
152
155
153 * Easy debugger access. You can set IPython to call up an enhanced version of
156 * Easy debugger access. You can set IPython to call up an enhanced version of
154 the Python debugger (pdb) every time there is an uncaught exception. This
157 the Python debugger (pdb) every time there is an uncaught exception. This
155 drops you inside the code which triggered the exception with all the data
158 drops you inside the code which triggered the exception with all the data
156 live and it is possible to navigate the stack to rapidly isolate the source
159 live and it is possible to navigate the stack to rapidly isolate the source
157 of a bug. The :samp:`%run` magic command (with the :samp:`-d` option) can run
160 of a bug. The :samp:`%run` magic command (with the :samp:`-d` option) can run
158 any script under pdb's control, automatically setting initial breakpoints for
161 any script under pdb's control, automatically setting initial breakpoints for
159 you. This version of pdb has IPython-specific improvements, including
162 you. This version of pdb has IPython-specific improvements, including
160 tab-completion and traceback coloring support. For even easier debugger
163 tab-completion and traceback coloring support. For even easier debugger
161 access, try :samp:`%debug` after seeing an exception. winpdb is also
164 access, try :samp:`%debug` after seeing an exception. winpdb is also
162 supported, see ipy_winpdb extension.
165 supported, see ipy_winpdb extension.
163
166
164 * Profiler support. You can run single statements (similar to
167 * Profiler support. You can run single statements (similar to
165 :samp:`profile.run()`) or complete programs under the profiler's control.
168 :samp:`profile.run()`) or complete programs under the profiler's control.
166 While this is possible with standard cProfile or profile modules,
169 While this is possible with standard cProfile or profile modules,
167 IPython wraps this functionality with magic commands (see :samp:`%prun`
170 IPython wraps this functionality with magic commands (see :samp:`%prun`
168 and :samp:`%run -p`) convenient for rapid interactive work.
171 and :samp:`%run -p`) convenient for rapid interactive work.
169
172
170 * Doctest support. The special :samp:`%doctest_mode` command toggles a mode
173 * Doctest support. The special :samp:`%doctest_mode` command toggles a mode
171 that allows you to paste existing doctests (with leading :samp:`>>>`
174 that allows you to paste existing doctests (with leading :samp:`>>>`
172 prompts and whitespace) and uses doctest-compatible prompts and
175 prompts and whitespace) and uses doctest-compatible prompts and
173 output, so you can use IPython sessions as doctest code.
176 output, so you can use IPython sessions as doctest code.
174
177
178 Decoupled two-process model
179 ==============================
180
181 IPython has abstracted and extended the notion of a traditional
182 *Read-Evaluate-Print Loop* (REPL) environment by decoupling the *evaluation*
183 into its own process. We call this process a kernel: it receives execution
184 instructions from clients and communicates the results back to them.
185
186 This decoupling allows us to have several clients connected to the same
187 kernel, and even allows clients and kernels to live on different machines.
188 With the exclusion of the traditional single process terminal-based IPython
189 (what you start if you run ``ipython`` without any subcommands), all
190 other IPython machinery uses this two-process model. This includes ``ipython
191 console``, ``ipython qtconsole``, and ``ipython notebook``.
192
193 As an example, this means that when you start ``ipython qtconsole``, you're
194 really starting two processes, a kernel and a Qt-based client can send
195 commands to and receive results from that kernel. If there is already a kernel
196 running that you want to connect to, you can pass the ``--existing`` flag
197 which will skip initiating a new kernel and connect to the most recent kernel,
198 instead. To connect to a specific kernel once you have several kernels
199 running, use the ``%connect_info`` magic to get the unique connection file,
200 which will be something like ``--existing kernel-19732.json`` but with
201 different numbers which correspond to the Process ID of the kernel.
202
203 You can read more about using :ref:`ipython qtconsole <qtconsole>`, and
204 :ref:`ipython notebook <htmlnotebook>`. There is also a :ref:`message spec
205 <messaging>` which documents the protocol for communication between kernels
206 and clients.
207
208
175 Interactive parallel computing
209 Interactive parallel computing
176 ==============================
210 ==============================
177
211
178 Increasingly, parallel computer hardware, such as multicore CPUs, clusters and
212 Increasingly, parallel computer hardware, such as multicore CPUs, clusters and
179 supercomputers, is becoming ubiquitous. Over the last 3 years, we have
213 supercomputers, is becoming ubiquitous. Over the last 8 years, we have
180 developed an architecture within IPython that allows such hardware to be used
214 developed an architecture within IPython that allows such hardware to be used
181 quickly and easily from Python. Moreover, this architecture is designed to
215 quickly and easily from Python. Moreover, this architecture is designed to
182 support interactive and collaborative parallel computing.
216 support interactive and collaborative parallel computing.
183
217
184 The main features of this system are:
218 The main features of this system are:
185
219
186 * Quickly parallelize Python code from an interactive Python/IPython session.
220 * Quickly parallelize Python code from an interactive Python/IPython session.
187
221
188 * A flexible and dynamic process model that be deployed on anything from
222 * A flexible and dynamic process model that be deployed on anything from
189 multicore workstations to supercomputers.
223 multicore workstations to supercomputers.
190
224
191 * An architecture that supports many different styles of parallelism, from
225 * An architecture that supports many different styles of parallelism, from
192 message passing to task farming. And all of these styles can be handled
226 message passing to task farming. And all of these styles can be handled
193 interactively.
227 interactively.
194
228
195 * Both blocking and fully asynchronous interfaces.
229 * Both blocking and fully asynchronous interfaces.
196
230
197 * High level APIs that enable many things to be parallelized in a few lines
231 * High level APIs that enable many things to be parallelized in a few lines
198 of code.
232 of code.
199
233
200 * Write parallel code that will run unchanged on everything from multicore
234 * Write parallel code that will run unchanged on everything from multicore
201 workstations to supercomputers.
235 workstations to supercomputers.
202
236
203 * Full integration with Message Passing libraries (MPI).
237 * Full integration with Message Passing libraries (MPI).
204
238
205 * Capabilities based security model with full encryption of network connections.
239 * Capabilities based security model with full encryption of network connections.
206
240
207 * Share live parallel jobs with other users securely. We call this
241 * Share live parallel jobs with other users securely. We call this
208 collaborative parallel computing.
242 collaborative parallel computing.
209
243
210 * Dynamically load balanced task farming system.
244 * Dynamically load balanced task farming system.
211
245
212 * Robust error handling. Python exceptions raised in parallel execution are
246 * Robust error handling. Python exceptions raised in parallel execution are
213 gathered and presented to the top-level code.
247 gathered and presented to the top-level code.
214
248
215 For more information, see our :ref:`overview <parallel_index>` of using IPython
249 For more information, see our :ref:`overview <parallel_index>` of using IPython
216 for parallel computing.
250 for parallel computing.
217
251
218 Portability and Python requirements
252 Portability and Python requirements
219 -----------------------------------
253 -----------------------------------
220
254
221 As of the 0.11 release, IPython works with Python 2.6 and 2.7. Versions 0.9 and
255 As of the 0.11 release, IPython works with Python 2.6 and 2.7. Versions 0.9 and
222 0.10 worked with Python 2.4 and above. IPython now also supports Python 3,
256 0.10 worked with Python 2.4 and above. IPython now also supports Python 3,
223 although for now the code for this is separate, and kept up to date with the
257 although for now the code for this is separate, and kept up to date with the
224 main IPython repository. In the future, these will converge to a single codebase
258 main IPython repository. In the future, these will converge to a single codebase
225 which can be automatically translated using 2to3.
259 which can be automatically translated using 2to3.
226
260
227 IPython is known to work on the following operating systems:
261 IPython is known to work on the following operating systems:
228
262
229 * Linux
263 * Linux
230 * Most other Unix-like OSs (AIX, Solaris, BSD, etc.)
264 * Most other Unix-like OSs (AIX, Solaris, BSD, etc.)
231 * Mac OS X
265 * Mac OS X
232 * Windows (CygWin, XP, Vista, etc.)
266 * Windows (CygWin, XP, Vista, etc.)
233
267
234 See :ref:`here <install_index>` for instructions on how to install IPython.
268 See :ref:`here <install_index>` for instructions on how to install IPython.
235
269
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