matplotlib.github.com/2.0.2/devel/contributing.html at main · matplotlib/matplotlib.github.com

History

584 lines (558 loc) · 42.3 KB

Raw

100

101

102

103

104

105

106

107

108

109

110

111

112

113

114

115

116

117

118

119

120

121

122

123

124

125

126

127

128

129

130

131

132

133

134

135

136

137

138

139

140

141

142

143

144

145

146

147

148

149

150

151

152

153

154

155

156

157

158

159

160

161

162

163

164

165

166

167

168

169

170

171

172

173

174

175

176

177

178

179

180

181

182

183

184

185

186

187

188

189

190

191

192

193

194

195

196

197

198

199

200

201

202

203

204

205

206

207

208

209

210

211

212

213

214

215

216

217

218

219

220

221

222

223

224

225

226

227

228

229

230

231

232

233

234

235

236

237

238

239

240

241

242

243

244

245

246

247

248

249

250

251

252

253

254

255

256

257

258

259

260

261

262

263

264

265

266

267

268

269

270

271

272

273

274

275

276

277

278

279

280

281

282

283

284

285

286

287

288

289

290

291

292

293

294

295

296

297

298

299

300

301

302

303

304

305

306

307

308

309

310

311

312

313

314

315

316

317

318

319

320

321

322

323

324

325

326

327

328

329

330

331

332

333

334

335

336

337

338

339

340

341

342

343

344

345

346

347

348

349

350

351

352

353

354

355

356

357

358

359

360

361

362

363

364

365

366

367

368

369

370

371

372

373

374

375

376

377

378

379

380

381

382

383

384

385

386

387

388

389

390

391

392

393

394

395

396

397

398

399

400

401

402

403

404

405

406

407

408

409

410

411

412

413

414

415

416

417

418

419

420

421

422

423

424

425

426

427

428

429

430

431

432

433

434

435

436

437

438

439

440

441

442

443

444

445

446

447

448

449

450

451

452

453

454

455

456

457

458

459

460

461

462

463

464

465

466

467

468

469

470

471

472

473

474

475

476

477

478

479

480

481

482

483

484

485

486

487

488

489

490

491

492

493

494

495

496

497

498

499

500

501

502

503

504

505

506

507

508

509

510

511

512

513

514

515

516

517

518

519

520

521

522

523

524

525

526

527

528

529

530

531

532

533

534

535

536

537

538

539

540

541

542

543

544

545

546

547

548

549

550

551

552

553

554

555

556

557

558

559

560

561

562

563

564

565

566

567

568

569

570

571

572

573

574

575

576

577

578

579

580

581

582

583

584

<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"

"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">

<head>

<title>Contributing — Matplotlib 2.0.2 documentation</title>

type="text/css" />

type="text/css" />

var DOCUMENTATION_OPTIONS = {

URL_ROOT: '../',

VERSION: '2.0.2',

COLLAPSE_INDEX: false,

FILE_SUFFIX: '.html',

HAS_SOURCE: true,

SOURCELINK_SUFFIX: '.txt'

};

</script>

title="Search within Matplotlib 2.0.2 documentation"

href="../_static/opensearch.xml"/>

</head>

<body>

<div id="unreleased-message"> You are reading an old version of the documentation (v2.0.2). For the latest version see <a href="https://matplotlib.org/stable/devel/contributing.html">https://matplotlib.org/stable/devel/contributing.html</a></div>

</map>

</div>

<h3>Navigation</h3>

<ul>

<a href="../genindex.html" title="General Index"

accesskey="I">index</a></li>

<a href="../py-modindex.html" title="Python Module Index"

>modules</a> |</li>

<a href="testing.html" title="Developer’s tips for testing"

accesskey="N">next</a> |</li>

<a href="index.html" title="The Matplotlib Developers’ Guide"

accesskey="P">previous</a> |</li>

<li><a href="../examples/index.html">examples</a>| </li>

<li><a href="../gallery.html">gallery</a>| </li>

<li><a href="../api/pyplot_summary.html">pyplot</a>| </li>

<li><a href="index.html" accesskey="U">The Matplotlib Developers’ Guide</a> »</li>

</ul>

</div>

</a>

Travis-CI: <a href="https://travis-ci.org/matplotlib/matplotlib">

</a>

<h3><a href="../contents.html">Table Of Contents</a></h3>

<ul>

<li><a class="reference internal" href="#">Contributing</a><ul>

<li><a class="reference internal" href="#submitting-a-bug-report">Submitting a bug report</a></li>

<li><a class="reference internal" href="#retrieving-and-installing-the-latest-version-of-the-code">Retrieving and installing the latest version of the code</a></li>

<li><a class="reference internal" href="#contributing-code">Contributing code</a><ul>

<li><a class="reference internal" href="#how-to-contribute">How to contribute</a></li>

<li><a class="reference internal" href="#contributing-pull-requests">Contributing pull requests</a></li>

<li><a class="reference internal" href="#issues-for-new-contributors">Issues for New Contributors</a></li>

</ul>

</li>

<li><a class="reference internal" href="#other-ways-to-contribute">Other ways to contribute</a></li>

<li><a class="reference internal" href="#coding-guidelines">Coding guidelines</a><ul>

<li><a class="reference internal" href="#new-modules-and-files-installation">New modules and files: installation</a></li>

<li><a class="reference internal" href="#c-c-extensions">C/C++ extensions</a></li>

<li><a class="reference internal" href="#keyword-argument-processing">Keyword argument processing</a></li>

<li><a class="reference internal" href="#developing-a-new-backend">Developing a new backend</a></li>

<li><a class="reference internal" href="#writing-examples">Writing examples</a></li>

</ul>

</li>

</ul>

</li>

</ul>

<h3>Related Topics</h3>

<ul>

<li><a href="../contents.html">Documentation overview</a><ul>

<li><a href="index.html">The Matplotlib Developers’ Guide</a><ul>

<li>Previous: <a href="index.html" title="previous chapter">The Matplotlib Developers’ Guide</a></li>

<li>Next: <a href="testing.html" title="next chapter">Developer’s tips for testing</a></li>

</ul></li>

</ul>

</div>

<li><a href="../_sources/devel/contributing.rst.txt"

rel="nofollow">Show Source</a></li>

</ul>

</div>

<h3>Quick search</h3>

</form>

</div>

</div>

<h1>Contributing<a class="headerlink" href="#contributing" title="Permalink to this headline">¶</a></h1>

This project is a community effort, and everyone is welcome to

contribute.

The project is hosted on <a class="reference external" href="https://github.com/matplotlib/matplotlib">https://github.com/matplotlib/matplotlib</a>

<h2>Submitting a bug report<a class="headerlink" href="#submitting-a-bug-report" title="Permalink to this headline">¶</a></h2>

If you find a bug in the code or documentation, do not hesitate to submit a

ticket to the

<a class="reference external" href="https://github.com/matplotlib/matplotlib/issues">Bug Tracker</a>. You are

also welcome to post feature requests or pull requests.

</div>

<h2>Retrieving and installing the latest version of the code<a class="headerlink" href="#retrieving-and-installing-the-latest-version-of-the-code" title="Permalink to this headline">¶</a></h2>

When working on the Matplotlib source, setting up a <a class="reference external" href="http://docs.python-guide.org/en/latest/dev/virtualenvs/">virtual

environment</a> or a

<a class="reference external" href="http://conda.pydata.org/docs/using/envs.html">conda environment</a> is

recommended.

Warning

If you already have a version of Matplotlib installed, use an

virtual environment or uninstall using the same method you used

to install it. Installing multiple versions of Matplotlib via different

methods into the same environment may not always work as expected.

</div>

We use <a class="reference external" href="https://git-scm.com/">Git</a> for version control and

<a class="reference external" href="https://github.com/">GitHub</a> for hosting our main repository.

You can check out the latest sources with the command (see

<a class="reference internal" href="gitwash/set_up_fork.html#set-up-fork">Set up your fork</a> for more details):

<div class="highlight-default"><div class="highlight"><pre>git clone git@github.com:matplotlib/matplotlib.git

</pre></div>

</div>

and navigate to the <code class="file docutils literal">matplotlib</code> directory.

To make sure the tests run locally you must build against the correct version

of freetype. To configure the build system to fetch and build it either export

the env <code class="docutils literal">MPLLOCALFREETYPE</code> as:

<div class="highlight-default"><div class="highlight"><pre>export MPLLOCALFREETYPE=1

</pre></div>

</div>

or copy <code class="file docutils literal">setup.cfg.template</code> to <code class="file docutils literal">setup.cfg</code> and edit it to contain

<div class="highlight-default"><div class="highlight"><pre>[test]

local_freetype = True

</pre></div>

</div>

To install Matplotlib (and compile the c-extensions) run the following

command from the top-level directory

<div class="highlight-default"><div class="highlight"><pre>pip install -v -e ./

</pre></div>

</div>

This installs Matplotlib in ‘editable/develop mode’, i.e., builds

everything and places the correct link entries in the install

directory so that python will be able to import Matplotlib from the

source directory. Thus, any changes to the <code class="docutils literal">*.py</code> files will be

reflected the next time you import the library. If you change the

c-extension source (which might happen if you change branches) you

will need to run:

<div class="highlight-default"><div class="highlight"><pre>python setup.py build

</pre></div>

</div>

or re-run <code class="docutils literal">pip install -v -e ./</code>.

Alternatively, if you do

</pre></div>

</div>

all of the files will be copied to the installation directory however,

you will have to rerun this command every time the source is changed.

Additionally you will need to copy <code class="file docutils literal">setup.cfg.template</code> to

<code class="file docutils literal">setup.cfg</code> and edit it to contain

<div class="highlight-default"><div class="highlight"><pre>[test]

local_freetype = True

tests = True

</pre></div>

</div>

In either case you can then run the tests to check your work

environment is set up properly:

<div class="highlight-default"><div class="highlight"><pre>python tests.py

</pre></div>

</div>

Note

Additional dependencies for testing: <a class="reference external" href="https://nose.readthedocs.io/en/latest/">nose</a> (version 1.0 or later), <a class="reference external" href="https://docs.python.org/dev/library/unittest.mock.html">mock</a> (if python < 3.3), <a class="reference external" href="https://www.ghostscript.com/">Ghostscript</a>, <a class="reference external" href="https://inkscape.org">Inkscape</a>

</div>

See also

<li><a class="reference internal" href="testing.html#testing">Developer’s tips for testing</a></li>

</ul>

</div>

<h2>Contributing code<a class="headerlink" href="#contributing-code" title="Permalink to this headline">¶</a></h2>

<h3>How to contribute<a class="headerlink" href="#how-to-contribute" title="Permalink to this headline">¶</a></h3>

The preferred way to contribute to Matplotlib is to fork the <a class="reference external" href="https://github.com/matplotlib/matplotlib/">main

repository</a> on GitHub,

then submit a “pull request” (PR):

<li><a class="reference external" href="https://github.com/join">Create an account</a> on

GitHub if you do not already have one.

</li>

<li>Fork the <a class="reference external" href="https://github.com/matplotlib/matplotlib">project repository</a>: click on the ‘Fork’ button

near the top of the page. This creates a copy of the code under your

account on the GitHub server.

</li>

<li>Clone this copy to your local disk:

<div class="highlight-default"><div class="highlight"><pre>$ git clone git@github.com:YourLogin/matplotlib.git

</pre></div>

</div>

</li>

<li>Create a branch to hold your changes:

<div class="highlight-default"><div class="highlight"><pre>$ git checkout -b my-feature origin/master

</pre></div>

</div>

and start making changes. Never work in the <code class="docutils literal">master</code> branch!

</li>

<li>Work on this copy, on your computer, using Git to do the version

control. When you’re done editing e.g., <code class="docutils literal">lib/matplotlib/collections.py</code>,

do:

<div class="highlight-default"><div class="highlight"><pre>$ git add lib/matplotlib/collections.py

$ git commit

</pre></div>

</div>

to record your changes in Git, then push them to GitHub with:

<div class="highlight-default"><div class="highlight"><pre>$ git push -u origin my-feature

</pre></div>

</div>

</li>

</ol>

</div></blockquote>

Finally, go to the web page of your fork of the Matplotlib repo,

and click ‘Pull request’ to send your changes to the maintainers for review.

You may want to consider sending an email to the mailing list for more

visibility.

See also

<li><a class="reference external" href="https://git-scm.com/documentation">Git documentation</a></li>

<li><a class="reference internal" href="gitwash/development_workflow.html#development-workflow">Development workflow</a>.</li>

<li><a class="reference internal" href="gitwash/index.html#using-git">Working with Matplotlib source code</a></li>

</ul>

</div>

<h3>Contributing pull requests<a class="headerlink" href="#contributing-pull-requests" title="Permalink to this headline">¶</a></h3>

It is recommended to check that your contribution complies with the following

rules before submitting a pull request:

<li>If your pull request addresses an issue, please use the title to describe

the issue and mention the issue number in the pull request description

to ensure a link is created to the original issue.

</li>

<li>All public methods should have informative docstrings with sample

usage when appropriate. Use the

<a class="reference external" href="https://github.com/numpy/numpy/blob/master/doc/HOWTO_DOCUMENT.rst.txt">numpy docstring standard</a>

</li>

<li>Formatting should follow <a class="reference external" href="https://www.python.org/dev/peps/pep-0008/">PEP8 recommendation</a>. You should consider

installing/enabling automatic PEP8 checking in your editor. Part of the

test suite is checking PEP8 compliance, things go smoother if the code is

mostly PEP8 compliant to begin with.

</li>

<li>Each high-level plotting function should have a simple example in

the <code class="docutils literal">Example</code> section of the docstring. This should be as simple as

possible to demonstrate the method. More complex examples should go

in the <code class="docutils literal">examples</code> tree.

</li>

<li>Changes (both new features and bugfixes) should be tested. See

<a class="reference internal" href="testing.html#testing">Developer’s tips for testing</a> for more details.

</li>

<li>Import the following modules using the standard scipy conventions:

<div class="highlight-default"><div class="highlight"><pre>import numpy as np

import numpy.ma as ma

import matplotlib as mpl

import matplotlib.pyplot as plt

import matplotlib.cbook as cbook

import matplotlib.patches as mpatches

</pre></div>

</div>

</li>

<li>If your change is a major new feature, add an entry to the <code class="docutils literal">What's new</code>

section by adding a new file in <code class="docutils literal">doc/users/whats_new</code> (see

<code class="file docutils literal">doc/users/whats_new/README</code> for more information).

</li>

<li>If you change the API in a backward-incompatible way, please

document it in <code class="xref py py-obj docutils literal">doc/api/api_changes</code>, by adding a new file describing your

changes (see <code class="file docutils literal">doc/api/api_changes/README</code> for more information)

</li>

<li>See below for additional points about

<a class="reference internal" href="#keyword-argument-processing">Keyword argument processing</a>, if code in your pull request

does that.

</li>

</ul>

</div></blockquote>

In addition, you can check for common programming errors with the following

tools:

<li>Code with a good unittest coverage (at least 70%, better 100%), check

with:

<div class="highlight-default"><div class="highlight"><pre>pip install coverage

python tests.py --with-coverage

</pre></div>

</div>

</li>

<li>No pyflakes warnings, check with:

<div class="highlight-default"><div class="highlight"><pre>pip install pyflakes

pyflakes path/to/module.py

</pre></div>

</div>

</li>

</ul>

</div></blockquote>

Note

The current state of the Matplotlib code base is not compliant with all

of those guidelines, but we expect that enforcing those constraints on all

new contributions will move the overall code base quality in the right

direction.

</div>

See also

<li><a class="reference internal" href="#coding-guidelines">Coding guidelines</a></li>

<li><a class="reference internal" href="testing.html#testing">Developer’s tips for testing</a></li>

<li><a class="reference internal" href="documenting_mpl.html#documenting-matplotlib">Developer’s tips for documenting matplotlib</a></li>

</ul>

</div>

<h3>Issues for New Contributors<a class="headerlink" href="#issues-for-new-contributors" title="Permalink to this headline">¶</a></h3>

New contributors should look for the following tags when looking for issues.

We strongly recommend that new contributors tackle

<a class="reference external" href="https://github.com/matplotlib/matplotlib/labels/new-contributor-friendly">new-contributor-friendly</a>

issues (easy, well documented issues, that do not require an understanding of

the different submodules of Matplotlib) and

issues. This helps the contributor become familiar with the contribution

workflow, and for the core devs to become acquainted with the contributor;

besides which, we frequently underestimate how easy an issue is to solve!

</div>

<h2>Other ways to contribute<a class="headerlink" href="#other-ways-to-contribute" title="Permalink to this headline">¶</a></h2>

Code is not the only way to contribute to Matplotlib. For instance,

documentation is also a very important part of the project and often doesn’t

get as much attention as it deserves. If you find a typo in the documentation,

or have made improvements, do not hesitate to send an email to the mailing

list or submit a GitHub pull request. Full documentation can be found under

the doc/ directory.

It also helps us if you spread the word: reference the project from your blog

and articles or link to it from your website!

</div>

<h2>Coding guidelines<a class="headerlink" href="#coding-guidelines" title="Permalink to this headline">¶</a></h2>

<h3>New modules and files: installation<a class="headerlink" href="#new-modules-and-files-installation" title="Permalink to this headline">¶</a></h3>

<li>If you have added new files or directories, or reorganized existing

ones, make sure the new files are included in the match patterns in

<code class="file docutils literal">MANIFEST.in</code>, and/or in <code class="xref py py-obj docutils literal">package_data</code> in <code class="xref py py-obj docutils literal">setup.py</code>.</li>

</ul>

</div>

<h3>C/C++ extensions<a class="headerlink" href="#c-c-extensions" title="Permalink to this headline">¶</a></h3>

<li>Extensions may be written in C or C++.</li>

<li>Code style should conform to PEP7 (understanding that PEP7 doesn’t

address C++, but most of its admonitions still apply).</li>

<li>Python/C interface code should be kept separate from the core C/C++

code. The interface code should be named <code class="xref py py-obj docutils literal">FOO_wrap.cpp</code> or

<code class="xref py py-obj docutils literal">FOO_wrapper.cpp</code>.</li>

<li>Header file documentation (aka docstrings) should be in Numpydoc

format. We don’t plan on using automated tools for these

docstrings, and the Numpydoc format is well understood in the

scientific Python community.</li>

</ul>

</div>

<h3>Keyword argument processing<a class="headerlink" href="#keyword-argument-processing" title="Permalink to this headline">¶</a></h3>

Matplotlib makes extensive use of <code class="docutils literal">**kwargs</code> for pass-through

customizations from one function to another. A typical example is in

<a class="reference internal" href="../api/pyplot_api.html#matplotlib.pyplot.text" title="matplotlib.pyplot.text"><code class="xref py py-func docutils literal">matplotlib.pyplot.text()</code></a>. The definition of the pylab text

function is a simple pass-through to

<a class="reference internal" href="../api/_as_gen/matplotlib.axes.Axes.text.html#matplotlib.axes.Axes.text" title="matplotlib.axes.Axes.text"><code class="xref py py-meth docutils literal">matplotlib.axes.Axes.text()</code></a>:

<div class="highlight-default"><div class="highlight"><pre># in pylab.py

def text(*args, **kwargs):

ret = gca().text(*args, **kwargs)

draw_if_interactive()

return ret

</pre></div>

</div>

<a class="reference internal" href="../api/_as_gen/matplotlib.axes.Axes.text.html#matplotlib.axes.Axes.text" title="matplotlib.axes.Axes.text"><code class="xref py py-meth docutils literal">text()</code></a> in simplified form looks like this,

i.e., it just passes all <code class="docutils literal">args</code> and <code class="docutils literal">kwargs</code> on to

<code class="xref py py-meth docutils literal">matplotlib.text.Text.__init__()</code>:

<div class="highlight-default"><div class="highlight"><pre># in axes/_axes.py

def text(self, x, y, s, fontdict=None, withdash=False, **kwargs):

t = Text(x=x, y=y, text=s, **kwargs)

</pre></div>

</div>

and <code class="xref py py-meth docutils literal">__init__()</code> (again with liberties for

illustration) just passes them on to the

<a class="reference internal" href="../api/_as_gen/matplotlib.artist.Artist.update.html#matplotlib.artist.Artist.update" title="matplotlib.artist.Artist.update"><code class="xref py py-meth docutils literal">matplotlib.artist.Artist.update()</code></a> method:

<div class="highlight-default"><div class="highlight"><pre># in text.py

def __init__(self, x=0, y=0, text='', **kwargs):

Artist.__init__(self)

self.update(kwargs)

</pre></div>

</div>

<code class="docutils literal">update</code> does the work looking for methods named like

<code class="docutils literal">set_property</code> if <code class="docutils literal">property</code> is a keyword argument. i.e., no one

looks at the keywords, they just get passed through the API to the

artist constructor which looks for suitably named methods and calls

them with the value.

As a general rule, the use of <code class="docutils literal">**kwargs</code> should be reserved for

pass-through keyword arguments, as in the example above. If all the

keyword args are to be used in the function, and not passed

on, use the key/value keyword args in the function definition rather

than the <code class="docutils literal">**kwargs</code> idiom.

In some cases, you may want to consume some keys in the local

function, and let others pass through. You can <code class="docutils literal">pop</code> the ones to be

used locally and pass on the rest. For example, in

<a class="reference internal" href="../api/_as_gen/matplotlib.axes.Axes.plot.html#matplotlib.axes.Axes.plot" title="matplotlib.axes.Axes.plot"><code class="xref py py-meth docutils literal">plot()</code></a>, <code class="docutils literal">scalex</code> and <code class="docutils literal">scaley</code> are

local arguments and the rest are passed on as

<a class="reference internal" href="../api/lines_api.html#matplotlib.lines.Line2D" title="matplotlib.lines.Line2D"><code class="xref py py-meth docutils literal">Line2D()</code></a> keyword arguments:

<div class="highlight-default"><div class="highlight"><pre># in axes/_axes.py

def plot(self, *args, **kwargs):

scalex = kwargs.pop('scalex', True)

scaley = kwargs.pop('scaley', True)

if not self._hold: self.cla()

lines = []

for line in self._get_lines(*args, **kwargs):

self.add_line(line)

lines.append(line)

</pre></div>

</div>

Note: there is a use case when <code class="docutils literal">kwargs</code> are meant to be used locally

in the function (not passed on), but you still need the <code class="docutils literal">**kwargs</code>

idiom. That is when you want to use <code class="docutils literal">*args</code> to allow variable

numbers of non-keyword args. In this case, python will not allow you

to use named keyword args after the <code class="docutils literal">*args</code> usage, so you will be

forced to use <code class="docutils literal">**kwargs</code>. An example is

<code class="xref py py-meth docutils literal">matplotlib.contour.ContourLabeler.clabel()</code>:

<div class="highlight-default"><div class="highlight"><pre># in contour.py

def clabel(self, *args, **kwargs):

fontsize = kwargs.get('fontsize', None)

inline = kwargs.get('inline', 1)

self.fmt = kwargs.get('fmt', '%1.3f')

colors = kwargs.get('colors', None)

if len(args) == 0:

levels = self.levels

indices = range(len(self.levels))

elif len(args) == 1:

...etc...

</pre></div>

</div>

<h3>Developing a new backend<a class="headerlink" href="#developing-a-new-backend" title="Permalink to this headline">¶</a></h3>

If you are working on a custom backend, the backend setting in

<code class="file docutils literal">matplotlibrc</code> (<a class="reference internal" href="../users/customizing.html#customizing-matplotlib">Customizing matplotlib</a>) supports an

external backend via the <code class="docutils literal">module</code> directive. if

<code class="file docutils literal">my_backend.py</code> is a Matplotlib backend in your

<a class="reference internal" href="../faq/environment_variables_faq.html#envvar-PYTHONPATH"><code class="xref std std-envvar docutils literal">PYTHONPATH</code></a>, you can set it on one of several ways

<ul>

<li>in <code class="file docutils literal">matplotlibrc</code>:

<div class="highlight-default"><div class="highlight"><pre>backend : module://my_backend

</pre></div>

</div>

</li>

<li>with the <a class="reference internal" href="../faq/environment_variables_faq.html#envvar-MPLBACKEND"><code class="xref std std-envvar docutils literal">MPLBACKEND</code></a> environment variable:

<div class="highlight-default"><div class="highlight"><pre>> export MPLBACKEND="module://my_backend"

> python simple_plot.py

</pre></div>

</div>

</li>

<li>from the command shell with the <code class="xref py py-obj docutils literal">-d</code> flag:

<div class="highlight-default"><div class="highlight"><pre>> python simple_plot.py -dmodule://my_backend

</pre></div>

</div>

</li>

<li>with the use directive in your script:

<div class="highlight-default"><div class="highlight"><pre>import matplotlib

matplotlib.use('module://my_backend')

</pre></div>

</div>

</li>

</ul>

</div>

<h3>Writing examples<a class="headerlink" href="#writing-examples" title="Permalink to this headline">¶</a></h3>

We have hundreds of examples in subdirectories of

<code class="file docutils literal">matplotlib/examples</code>, and these are automatically generated

when the website is built to show up both in the <a class="reference external" href="../examples/index.html">examples</a> and <a class="reference external" href="../gallery.html">gallery</a> sections of the website.

Any sample data that the example uses should be kept small and

distributed with Matplotlib in the

<code class="xref py py-obj docutils literal">lib/matplotlib/mpl-data/sample_data/</code> directory. Then in your

example code you can load it into a file handle with:

<div class="highlight-default"><div class="highlight"><pre>import matplotlib.cbook as cbook

fh = cbook.get_sample_data('mydata.dat')

</pre></div>

</div>

</div>

Last updated on May 10, 2017.

Created using <a

href="http://sphinx-doc.org/">Sphinx</a> 1.5.5.

</div>

</body>

</footer>

</html>

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

FilesExpand file tree

contributing.html

Latest commit

History

contributing.html

File metadata and controls