|
303 | 303 | "print(fnew(3))" |
304 | 304 | ] |
305 | 305 | }, |
| 306 | + { |
| 307 | + "cell_type": "markdown", |
| 308 | + "metadata": { |
| 309 | + "collapsed": false |
| 310 | + }, |
| 311 | + "source": [ |
| 312 | + "## Lambdas" |
| 313 | + ] |
| 314 | + }, |
| 315 | + { |
| 316 | + "cell_type": "markdown", |
| 317 | + "metadata": {}, |
| 318 | + "source": [ |
| 319 | + "Lambdas are \"disposible\" functions. These are small, nameless functions that are often used as arguments in other functions.\n", |
| 320 | + "\n", |
| 321 | + "Ex, from the official tutorial:" |
| 322 | + ] |
| 323 | + }, |
306 | 324 | { |
307 | 325 | "cell_type": "code", |
308 | | - "execution_count": null, |
| 326 | + "execution_count": 3, |
| 327 | + "metadata": { |
| 328 | + "collapsed": true |
| 329 | + }, |
| 330 | + "outputs": [], |
| 331 | + "source": [ |
| 332 | + "pairs = [(1, 'one'), (2, 'two'), (3, 'three'), (4, 'four')]\n", |
| 333 | + "pairs.sort(key=lambda p: p[1])" |
| 334 | + ] |
| 335 | + }, |
| 336 | + { |
| 337 | + "cell_type": "code", |
| 338 | + "execution_count": 4, |
309 | 339 | "metadata": { |
310 | 340 | "collapsed": false |
311 | 341 | }, |
| 342 | + "outputs": [ |
| 343 | + { |
| 344 | + "data": { |
| 345 | + "text/plain": [ |
| 346 | + "[(4, 'four'), (1, 'one'), (3, 'three'), (2, 'two')]" |
| 347 | + ] |
| 348 | + }, |
| 349 | + "execution_count": 4, |
| 350 | + "metadata": {}, |
| 351 | + "output_type": "execute_result" |
| 352 | + } |
| 353 | + ], |
| 354 | + "source": [ |
| 355 | + "pairs" |
| 356 | + ] |
| 357 | + }, |
| 358 | + { |
| 359 | + "cell_type": "markdown", |
| 360 | + "metadata": {}, |
| 361 | + "source": [ |
| 362 | + "Here we use a lambda in a extract from a list (with the filter command)" |
| 363 | + ] |
| 364 | + }, |
| 365 | + { |
| 366 | + "cell_type": "code", |
| 367 | + "execution_count": 12, |
| 368 | + "metadata": { |
| 369 | + "collapsed": false |
| 370 | + }, |
| 371 | + "outputs": [ |
| 372 | + { |
| 373 | + "data": { |
| 374 | + "text/plain": [ |
| 375 | + "[0,\n", |
| 376 | + " 36,\n", |
| 377 | + " 144,\n", |
| 378 | + " 324,\n", |
| 379 | + " 576,\n", |
| 380 | + " 900,\n", |
| 381 | + " 1296,\n", |
| 382 | + " 1764,\n", |
| 383 | + " 2304,\n", |
| 384 | + " 2916,\n", |
| 385 | + " 3600,\n", |
| 386 | + " 4356,\n", |
| 387 | + " 5184,\n", |
| 388 | + " 6084,\n", |
| 389 | + " 7056,\n", |
| 390 | + " 8100,\n", |
| 391 | + " 9216]" |
| 392 | + ] |
| 393 | + }, |
| 394 | + "execution_count": 12, |
| 395 | + "metadata": {}, |
| 396 | + "output_type": "execute_result" |
| 397 | + } |
| 398 | + ], |
| 399 | + "source": [ |
| 400 | + "squares = [x**2 for x in range(100)]\n", |
| 401 | + "sq = list(filter(lambda x : x%2 == 0 and x%3 == 0, squares))\n", |
| 402 | + "sq\n" |
| 403 | + ] |
| 404 | + }, |
| 405 | + { |
| 406 | + "cell_type": "code", |
| 407 | + "execution_count": null, |
| 408 | + "metadata": { |
| 409 | + "collapsed": true |
| 410 | + }, |
| 411 | + "outputs": [], |
| 412 | + "source": [] |
| 413 | + }, |
| 414 | + { |
| 415 | + "cell_type": "code", |
| 416 | + "execution_count": null, |
| 417 | + "metadata": { |
| 418 | + "collapsed": true |
| 419 | + }, |
312 | 420 | "outputs": [], |
313 | 421 | "source": [] |
314 | 422 | } |
315 | 423 | ], |
316 | 424 | "metadata": { |
317 | 425 | "kernelspec": { |
318 | | - "display_name": "Python 2", |
| 426 | + "display_name": "Python 3", |
319 | 427 | "language": "python", |
320 | | - "name": "python2" |
| 428 | + "name": "python3" |
321 | 429 | }, |
322 | 430 | "language_info": { |
323 | 431 | "codemirror_mode": { |
324 | 432 | "name": "ipython", |
325 | | - "version": 2 |
| 433 | + "version": 3 |
326 | 434 | }, |
327 | 435 | "file_extension": ".py", |
328 | 436 | "mimetype": "text/x-python", |
329 | 437 | "name": "python", |
330 | 438 | "nbconvert_exporter": "python", |
331 | | - "pygments_lexer": "ipython2", |
332 | | - "version": "2.7.10" |
| 439 | + "pygments_lexer": "ipython3", |
| 440 | + "version": "3.4.3" |
333 | 441 | } |
334 | 442 | }, |
335 | 443 | "nbformat": 4, |
|
0 commit comments