Exercices de POO - série 4

Exercice 1 : Élève en POO⚓︎

On souhaite dans cet exercice créer une classe Eleve ayant quatre attributs :

un prénom prenom de type str ;
un nom nom de type str ;
une classe classe de type str ;
des moyennes moyennes de type dict. Ce dictionnaire associe à des intitulés de matières (str), les moyennes correspondantes (au format int ou float).

Cet exercice est en plusieurs parties et demande de compléter la classe Eleve en ajoutant différentes méthodes. Il est progressif, il ne faut pas passer à la question suivante sans avoir terminé celle en cours.

Constructeur

Lors de la création d'un objet de type Eleve, on fournit les valeurs des attributs prenom, nom et classe (dans cet ordre).

L'attribut moyennes est initialement vide.

Compléter le constructeur de la classe Eleve.

Exemple

>>> albert = Eleve("Albert", "Einstein", "Te2")
>>> albert.prenom
'Albert'
>>> albert.nom
'Einstein'
>>> albert.classe
'Te2'
>>> albert.moyennes
{}

Version videVersion à compléter

Évaluations restantes : 5/5

.128013ldy1,4{k/eibmc:_35}aPr =of.gt26sShE)(punv050c0k0D0u0l0b0G0x0o0b0u0G0G0y010D0l0M010406050G0N0n0n0u0w0d040H0z0b0N0*0z0O050j0;0?0^0`0/0M04051a131d0j1a0/0c0l0P0Y0!0$0(0I0l0C0I0b1r0I0D0-050T0m0b0k1m0#0%011q1s1u1s0D1A1C1y0D0w1b0D0I0Y0}0G0M0u0O0(0E011E1o010A0V0k0O0u0n0k1y1X1Z1(1G1+1C1.1:0-0a0x0v0w0z0M0z0G0l100O0x0R1V0w0w0k0o28131?0O1b0j1T2l1Q1S1R1z0c1^0(1u0O1-251y1j1l0Z1F2v0l2x0O0z2B1y0M2e1b2j2l2P0:1Y292D1)2I0w0@0b0-0e2i2T0.2S1@2V1G2X2Z0-0E2%1Z2)2j2u012.0u2!040r2=2k0/2^2,0(2{2}0g302@2T2_360-0s39323b342`0z2Y2|0-0F391e2N132B2o0c1S2t3j0o2J1;1b3u1c3s2R142(053A0R2O3i1n1G0i0-2,390x2*2U3P350o0-0J1C0P0k3q333Y010,040p3g0x3=3V3+2E013R040R0A3U3W2_0A0n0-0q0q2G27453*3O3_3.0L4a2+3,0m3.0G0k0b3~3I2?403j3.0f3 3^2W0-2M2y0n4f3X4c0-4t4o2k3@4b4w042I4A4G3N4g4D044F2P4I4Q4K2,3)4O4q3,3.0K3:4O063?4,4V4C1)4i0-4k4m4B2_0z0-0B4^3j0O4x2e4M4u4J1G4`040y534W2-504z3;4-3=4#3_4;044?4n2R4v554{4}3,4 4L0z4N4U5h1)56584O4.3c0-524*5f5g5o0(5j5l5r3_564|4!5K2`3S3P4Z5x5T5A594/5b044Y5e5f5y1G5M4l5m3J5Z5q5S54350-0n0z0d1-2x0G5#4_0-5B5Y5^3-0-0h0t3g133L0k2l4y2l3E2m3w132p6l0u1B6e3t1k2)0j0R0T0V0G04.

Évaluations restantes : 5/5

.128013ldy1,4{k/eibmc:_35}aPr =of.gt26sShE)(punv050c0k0D0u0l0b0G0x0o0b0u0G0G0y010D0l0M010406050G0N0n0n0u0w0d040H0z0b0N0*0z0O050j0;0?0^0`0/0M04051a131d0j1a0/0c0l0P0Y0!0$0(0I0l0C0I0b1r0I0D0-050T0m0b0k1m0#0%011q1s1u1s0D1A1C1y0D0w1b0D0I0Y0}0G0M0u0O0(0E011E1o010A0V0k0O0u0n0k1y1X1Z1(1G1+1C1.1:0-0a0x0v0w0z0M0z0G0l100O0x0R1V0w0w0k0o28131?0O1b0j1T2l1Q1S1R1z0c1^0(1u0O1-251y1j1l0Z1F2v0l2x0O0z2B1y0M2e1b2j2l2P0:1Y292D1)2I0w0@0b0-0e2i2T0.2S1@2V1G2X2Z0-0E2%1Z2)2j2u012.0u2!040r2=2k0/2^2,0(2{2}0g302@2T2_360-0s39323b342`0z2Y2|0-0F391e2N132B2o0c1S2t3j0o2J1;1b3u1c3s2R142(053A0R2O3i1n1G0i0-2,390x2*2U3P350o0-0J1C0P0k3q333Y010,040p3g0x3=3V3+2E013R040R0A3U3W2_0A0n0-0q0q2G27453*3O3_3.0L4a2+3,0m3.0G0k0b3~3I2?403j3.0f3 3^2W0-2M2y0n4f3X4c0-4t4o2k3@4b4w042I4A4G3N4g4D044F2P4I4Q4K2,3)4O4q3,3.0K3:4O063?4,4V4C1)4i0-4k4m4B2_0z0-0B4^3j0O4x2e4M4u4J1G4`040y534W2-504z3;4-3=4#3_4;044?4n2R4v554{4}3,4 4L0z4N4U5h1)56584O4.3c0-524*5f5g5o0(5j5l5r3_564|4!5K2`3S3P4Z5x5T5A594/5b044Y5e5f5y1G5M4l5m3J5Z5q5S54350-0n0z0d1-2x0G5#4_0-5B5Y5^3-0-0h0t3g133L0k2l4y2l3E2m3w132p6l0u1B6e3t1k2)0j0R0T0V0G04.

Méthode modifie_moyenne

La méthode modifie_moyenne prend deux paramètres, un intitulé de matière (str) et une moyenne (au format int ou float) et ajoute ce couple (clé: valeur) à l'attribut moyennes d'un objet Eleve.

Écrire la méthode modifie_moyenne.

Exemple

>>> carl = Eleve("Carl Friedrich", "Gauss", "Te3")
>>> carl.modifie_moyenne("arithmétique", 20)
>>> carl.modifie_moyenne("chimie", 12)
>>> carl.moyennes
{'arithmétique': 20, 'chimie': 12}
>>> carl.modifie_moyenne("chimie", 13)
>>> carl.moyennes
{'arithmétique': 20, 'chimie': 13}

Version videVersion à compléter

Évaluations restantes : 5/5

.128013ldy1,4{]k/eibmc:_35}aPr 7=9o[f.gt286sShE)(punv050c0l0H0v0m0b0L0y0p0b0v0L0L0A010H0m0R010406050L0S0o0o0v0x0d040M0C0b0S0/0C0T050k0_0{0}0 0@0R04051f181i0k1f0@0c0m0U0%0)0+0-0N0m0G0N0b1w0N0H0=050Y0n0b0l1r0*0,011v1x1z1x0H1F1H1D0H0x1g0H0N0%120L0R0v0T0-0I011J1t010E0!0l0T0v0o0l1D1$1(1-1L1:1H1?1^0=0a0y0w0x0C0R0C0L0m150T0y0W1!0x0x0l0p2d181{0T1g0k1Y2q1V1X1W1E0c1}0-1z0T1=2a1D1o1q0(1K2A0m2C0T0C2G1D0R2j1g2o2q2U0^1%2e2I1.2N0x0|0b0=0e2n2Y0?2X1|2!1L2$2(0=0I2,1(2.2o2z012?0v2)040s2`2p0@2}2;0-30320g352|2Y2~3b0=0t3e373g392 0C2%310=0K3l2/2Z1s2=3q2@040z3v383y3a3A3s040J3E3n3G3p3r320B3e1j2S182G2t0c1X2y3o0p2O1_1g3X1h3V2W192-053%0W2T3N2J010j0=2;3e0y3w3h0p0=0O1H0U0l3T3F3_0;040q3l0y4f3 491.3{040W0E3~403o0E0o0=0r0r2L2c4u483^1.4b0Q4z2:3O0n4b0L0l0b4n3/2{4p3O4b0f4o4i2=0=2R2D0o4E3x4a0=4S4N2p4h4A4V042N4Z4)3@4F4$044(2U4+4?2#3|3y474;4P4@0P4d4;064g584{4#1.4H0=4J4L4!2~0C0=0F5h3o0T4W2j4/4T4,0-5j040A5s4|4-4X5r56594g525c4I4K4M2W4U5u5k5m3O5o4.0C4:4`5G1L5v5x4;5a3h0=5C2U575E5#3o5d045f5K3:5M015v5l515?5R2;505V5?5Y5y5b4-5}4e5+5W0-5.5:5P3_5^6c4}040o0C0d1=2C0L625i0=5Z5 5t014b0h0u3l5*4f683`0=4m6o5n0E0=6i1o1:0l0r6i6k0T2C6f1L4C6S695I5g5`6t4R6F5Q6I0v0/0l2j6V6u4%6$3_5R6O6l5~5=6!0=54665E6B6a5J6-6e6Z5z3a6I6j6@6n74630-4b0D6-6=6)0m6+6^4O5?4b0i6:1.615!6B6=786Q7l36183=0l2q4X2q3+2r3Z182u7J0v1G7C3W1p2.0k0W0Y0!0L04.

Évaluations restantes : 5/5

.128013ldy1,4{]k/eibmc:_35}aPr 7=9o[f.gt286sShE)(punv050c0l0H0v0m0b0L0y0p0b0v0L0L0A010H0m0R010406050L0S0o0o0v0x0d040M0C0b0S0/0C0T050k0_0{0}0 0@0R04051f181i0k1f0@0c0m0U0%0)0+0-0N0m0G0N0b1w0N0H0=050Y0n0b0l1r0*0,011v1x1z1x0H1F1H1D0H0x1g0H0N0%120L0R0v0T0-0I011J1t010E0!0l0T0v0o0l1D1$1(1-1L1:1H1?1^0=0a0y0w0x0C0R0C0L0m150T0y0W1!0x0x0l0p2d181{0T1g0k1Y2q1V1X1W1E0c1}0-1z0T1=2a1D1o1q0(1K2A0m2C0T0C2G1D0R2j1g2o2q2U0^1%2e2I1.2N0x0|0b0=0e2n2Y0?2X1|2!1L2$2(0=0I2,1(2.2o2z012?0v2)040s2`2p0@2}2;0-30320g352|2Y2~3b0=0t3e373g392 0C2%310=0K3l2/2Z1s2=3q2@040z3v383y3a3A3s040J3E3n3G3p3r320B3e1j2S182G2t0c1X2y3o0p2O1_1g3X1h3V2W192-053%0W2T3N2J010j0=2;3e0y3w3h0p0=0O1H0U0l3T3F3_0;040q3l0y4f3 491.3{040W0E3~403o0E0o0=0r0r2L2c4u483^1.4b0Q4z2:3O0n4b0L0l0b4n3/2{4p3O4b0f4o4i2=0=2R2D0o4E3x4a0=4S4N2p4h4A4V042N4Z4)3@4F4$044(2U4+4?2#3|3y474;4P4@0P4d4;064g584{4#1.4H0=4J4L4!2~0C0=0F5h3o0T4W2j4/4T4,0-5j040A5s4|4-4X5r56594g525c4I4K4M2W4U5u5k5m3O5o4.0C4:4`5G1L5v5x4;5a3h0=5C2U575E5#3o5d045f5K3:5M015v5l515?5R2;505V5?5Y5y5b4-5}4e5+5W0-5.5:5P3_5^6c4}040o0C0d1=2C0L625i0=5Z5 5t014b0h0u3l5*4f683`0=4m6o5n0E0=6i1o1:0l0r6i6k0T2C6f1L4C6S695I5g5`6t4R6F5Q6I0v0/0l2j6V6u4%6$3_5R6O6l5~5=6!0=54665E6B6a5J6-6e6Z5z3a6I6j6@6n74630-4b0D6-6=6)0m6+6^4O5?4b0i6:1.615!6B6=786Q7l36183=0l2q4X2q3+2r3Z182u7J0v1G7C3W1p2.0k0W0Y0!0L04.

Méthode moyenne_de

La méthode moyenne_de prend en unique paramètre un intitulé de matière (str) et renvoie la moyenne de cet élève dans cette matière.

Si l'élève ne possède pas de moyenne dans cette matière, la fonction renverra None.

Écrire la méthode moyenne_de.

Exemple

>>> donald = Eleve("Donald", "Knuth", "Te7")
>>> donald.modifie_moyenne("informatique", 20)
>>> donald.modifie_moyenne("musique", 13)
>>> donald.moyenne_de("informatique")
20
>>> donald.moyenne_de("musique")
13
>>> donald.moyenne_de("lancer de javelot")
>>>

Version videVersion à compléter

Évaluations restantes : 5/5

.1280130ldy1,48{Aê]ké/weibmc:_35qaPr} 7=9o[f.;tRg26sShE()pNunv050d0r0O0B0s0c0T0F0v0c0B0T0T0H010O0s0Z010406050T0#0u0u0B0D0e040U0J0c0#0{0J0$0F020B0u0Z0N0F0P0r150D0A0#0r0T050p12141618100Z04051D1w1G0p1D100d0s0%0:0=0@0_0V0s0Q0V0c1U0V0O0~050+0t0c0r1P0?0^011T1V1X1V0O1%1)1#0O0D1E0O0V0:1b0T0Z0B0$0_0R011+1R010L0-0r0$1j0r1#2123281-2b1)2e0u2g040a0F0C0D0J0Z0J0T0s1e1g0)1 0D0D0r0v2B1w2i0$1E0p1}2N1`1|1{1$0d2k0_1X0$2d2y1#1M1O0;1,2X0s2Z0$0J2%1#0Z2G1E2L2N2^11221g2)292.0D150c0~0F0f2K2|0 2{2j2~1-3032340R3723392L2W013e0B33040F0y3i2M103l3c0_3o3q0F0h3u3k2|3m3A340z3E3w3G3y3n0J313p340S3L3a2}1Q3d3Q3f3r0G3V3x3Y3z3!3S3r0i3(3N3*3P3R3B0I3:3b3=3I040f0b3`3X2*3?3#0f361x383M3{433}0f3h483j4a422 3,3q0f3t4g3v3W3H4l0~0f3D4p3F4b4k3@4u3K4x1H2?1w2%2Q0d1|2V3O0v2/2q0(1N1E2=0r2@383E054O0)4W4z1-0n0~3c3E0F4r3O0$0v0~0W1)0%0r4Y3)430}040w3L0F514-4{294)040)0L4,4.3=0L0u0~0x0x2,2A5g4`3;4|0~0X5l4%0_0t4}0T0r0c594E541-4}0g5a5A3z0~4U2.0u5q4j5B0~5D4x535m2 0~5J5L3m5C5E5S3d4*3Y4_5z5!0_4}0Y4 4x06525;5R5r015t0~5v5x5W3O0J0~0M5}3|5H2G5V5Q5b435 040H5Z5@0$642!5K5/5=5268295_045{5y2`5F016a615)6e5U0J6i2^5?5M0_6a6c676t6f04662^5:6k6D3m6o6q6269606U5T043c5(6C6m1-6G6d6E3n5$1,6#496P6Q3O6S5w6r4X6t6v6X5#040u0J0e2d2Z1v6I5*6u0~6H6$6t4}0j0E3L6O516%0_56586*3H0L0~701M2b0r0x70720$2Z6}5+5o7A5^5u6^7D5Y766y6 0B0{0r2G7H5O7n4/7q71736/3j7j015,5.6N6;7Z6@5|6x6+6|7,3H7U7x747Q040K7D6K157N7P7/3O4}0m7S3=6)7J6+7{7V7y7X3v7h6=3=7l0r6_3j8e4c7p6 892Z0x0)7@5p7 3=7*8i2M7Z7I7b777{7M0s7O8b4$6+7#506P7Z560s8x3r7Z8D7}8H8k290J0q0~2,83438w7D7.6s8C7;7W758+5@4}7$6:6;6l6t562G0O0#0D0$8$6n7F7+8:7-6W8u4c8-8a8/6`774}7_986Y7|8F7~955X0~826j8M8`0~5w5v7@8?4h8^8_778{0*8~90863m0n4;040!1f8H100p4!4V4F9R0p4I1w0O4K9W2T2O0B1(9T4I1C8I3m2G0u0x0L0B0n7u0V0y0~1o1q1s1u0F9x8y1J391D9L0O1f0T0g0F1s002d2t0e1}1fa80#2Z0F0L1f2I0s1f0F0T230/4Z4P3m1/1W1Y1!9+3O9C8}8 4Y9P4P3r650%0J8F0F220D0F0d0o9:1d4-9Qaw1Y1;1Z2h9B9J9L7z4EaH4#6w1K1F040k2,2z0F1)1 2D2=0o0v0o0)0$0OaO0J8~0D0,b20l1`1*a}0D2Aaqasa^1*au2D3Oaxa!aA8N9t0.8H1w9Q3r1s0saq7Ob70F0Q0o0D0o0F0s1k1X0v2A1p2db25.a/2%aY1:az2;4G2`4Ebubp578h913d8m7w7W8qbs7c7C9h1-8(b:7B045P8B7K9j8G7@5-8L7i9s048Pb%5G7L8Uc56u8Zc39Fb`6+b=9m5~97ch638n7=1u9wc05=b!8|9Ec9cg9d5@8*cx879a7?b?7!0~9gck99c79kb-9e9o3Va,9T4U2N9)4H0*0,0.04.

Évaluations restantes : 5/5

.1280130ldy1,48{Aê]ké/weibmc:_35qaPr} 7=9o[f.;tRg26sShE()pNunv050d0r0O0B0s0c0T0F0v0c0B0T0T0H010O0s0Z010406050T0#0u0u0B0D0e040U0J0c0#0{0J0$0F020B0u0Z0N0F0P0r150D0A0#0r0T050p12141618100Z04051D1w1G0p1D100d0s0%0:0=0@0_0V0s0Q0V0c1U0V0O0~050+0t0c0r1P0?0^011T1V1X1V0O1%1)1#0O0D1E0O0V0:1b0T0Z0B0$0_0R011+1R010L0-0r0$1j0r1#2123281-2b1)2e0u2g040a0F0C0D0J0Z0J0T0s1e1g0)1 0D0D0r0v2B1w2i0$1E0p1}2N1`1|1{1$0d2k0_1X0$2d2y1#1M1O0;1,2X0s2Z0$0J2%1#0Z2G1E2L2N2^11221g2)292.0D150c0~0F0f2K2|0 2{2j2~1-3032340R3723392L2W013e0B33040F0y3i2M103l3c0_3o3q0F0h3u3k2|3m3A340z3E3w3G3y3n0J313p340S3L3a2}1Q3d3Q3f3r0G3V3x3Y3z3!3S3r0i3(3N3*3P3R3B0I3:3b3=3I040f0b3`3X2*3?3#0f361x383M3{433}0f3h483j4a422 3,3q0f3t4g3v3W3H4l0~0f3D4p3F4b4k3@4u3K4x1H2?1w2%2Q0d1|2V3O0v2/2q0(1N1E2=0r2@383E054O0)4W4z1-0n0~3c3E0F4r3O0$0v0~0W1)0%0r4Y3)430}040w3L0F514-4{294)040)0L4,4.3=0L0u0~0x0x2,2A5g4`3;4|0~0X5l4%0_0t4}0T0r0c594E541-4}0g5a5A3z0~4U2.0u5q4j5B0~5D4x535m2 0~5J5L3m5C5E5S3d4*3Y4_5z5!0_4}0Y4 4x06525;5R5r015t0~5v5x5W3O0J0~0M5}3|5H2G5V5Q5b435 040H5Z5@0$642!5K5/5=5268295_045{5y2`5F016a615)6e5U0J6i2^5?5M0_6a6c676t6f04662^5:6k6D3m6o6q6269606U5T043c5(6C6m1-6G6d6E3n5$1,6#496P6Q3O6S5w6r4X6t6v6X5#040u0J0e2d2Z1v6I5*6u0~6H6$6t4}0j0E3L6O516%0_56586*3H0L0~701M2b0r0x70720$2Z6}5+5o7A5^5u6^7D5Y766y6 0B0{0r2G7H5O7n4/7q71736/3j7j015,5.6N6;7Z6@5|6x6+6|7,3H7U7x747Q040K7D6K157N7P7/3O4}0m7S3=6)7J6+7{7V7y7X3v7h6=3=7l0r6_3j8e4c7p6 892Z0x0)7@5p7 3=7*8i2M7Z7I7b777{7M0s7O8b4$6+7#506P7Z560s8x3r7Z8D7}8H8k290J0q0~2,83438w7D7.6s8C7;7W758+5@4}7$6:6;6l6t562G0O0#0D0$8$6n7F7+8:7-6W8u4c8-8a8/6`774}7_986Y7|8F7~955X0~826j8M8`0~5w5v7@8?4h8^8_778{0*8~90863m0n4;040!1f8H100p4!4V4F9R0p4I1w0O4K9W2T2O0B1(9T4I1C8I3m2G0u0x0L0B0n7u0V0y0~1o1q1s1u0F9x8y1J391D9L0O1f0T0g0F1s002d2t0e1}1fa80#2Z0F0L1f2I0s1f0F0T230/4Z4P3m1/1W1Y1!9+3O9C8}8 4Y9P4P3r650%0J8F0F220D0F0d0o9:1d4-9Qaw1Y1;1Z2h9B9J9L7z4EaH4#6w1K1F040k2,2z0F1)1 2D2=0o0v0o0)0$0OaO0J8~0D0,b20l1`1*a}0D2Aaqasa^1*au2D3Oaxa!aA8N9t0.8H1w9Q3r1s0saq7Ob70F0Q0o0D0o0F0s1k1X0v2A1p2db25.a/2%aY1:az2;4G2`4Ebubp578h913d8m7w7W8qbs7c7C9h1-8(b:7B045P8B7K9j8G7@5-8L7i9s048Pb%5G7L8Uc56u8Zc39Fb`6+b=9m5~97ch638n7=1u9wc05=b!8|9Ec9cg9d5@8*cx879a7?b?7!0~9gck99c79kb-9e9o3Va,9T4U2N9)4H0*0,0.04.

Méthode moyenne_simple

La méthode moyenne_simple calcule et renvoie la moyenne générale de l'élève. Celle-ci se calcule en effectuant la moyenne des moyennes.

Si l'élève n'a aucune moyenne, la fonction renverra None.

Écrire la méthode moyenne_simple.

Exemple

>>> jane = Eleve("Jane", "Goodall", "Te3")
>>> jane.modifie_moyenne("éthologie", 20)
>>> jane.modifie_moyenne("théorie des groupes", 1)
>>> jane.moyenne_simple()
10.5

Version videVersion à compléter

Évaluations restantes : 5/5

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Évaluations restantes : 5/5

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Méthode moyenne_ponderee

La méthode moyenne_ponderee prend comme unique paramètre un dictionnaire coeffs associant des intitulés de matières (str) à des coefficients (au format int ou float).

Cette fonction calcule la moyenne pondérée de l'élève en appliquant les coefficients fournis en paramètre.

Si l'élève n'a aucune moyenne, la fonction renverra None.

On garantit que dictionnaire coeffs contient toutes les clés correspondant aux matières du dictionnaire moyennes.

Écrire la méthode moyenne_ponderee.

Exemple

>>> margaret = Eleve("Margaret", "Hamilton", "Te5")
>>> margaret.modifie_moyenne("études spatiales", 20)
>>> margaret.modifie_moyenne("maths", 14)
>>> coeffs = {"études spatiales": 1, "maths": 0.5}
>>> margaret.moyenne_ponderee(coeffs)
18.0

Version videVersion à compléter

Évaluations restantes : 5/5

.128013Cy1{ê]/wi_}qP+r 79f;gR2àhE()pNn0ld,*4Akéebmc:35a=o[.8t6sSuxv050I0P0$0W0j0H0(0q0S0H0W0(0(0X010$0j0D010406050(0*0R0R0W0p0c040)0Y0H0*100Y0F0q020W0R0D0u0q0w0P1a0p0m0*0P0(050h17191b1d150D04051I1B1L0h1I150I0j0,0^0`0|0~0z0j0v0z0H1Z0z0$13050:0Q0H0P1U0{0}011Y1!1$1!0$1,1.1*0$0p1J0$0z0^1g0(0D0W0F0~0x011:1W010t0=0P0F1o0P1*26282d1=2g1.2j0R2l040a0q0n0p0Y0D0Y0(0j1j1l0.240p0p0P0S2G1B2n0F1J0h222S1 21201+0I2p0~1$0F2i2D1*1R1T0_1;2$0j2(0F0Y2,1*0D2L1J2Q2S2}16271l2.2e2?0p1a0H130q0d2P3114302o331=3537390x3c283e2Q2#013j0W38040q0U3n2R153q3h0~3t3v0q0L3z3p313r3F390V3J3B3L3D3s0Y363u390%3Q3f321V3i3V3k3w0r3!3C3%3E3)3X3w0#3-3S3/3U3W3G0s3^3g3`3N040d0G3 3$2/3{3*0d3b1C3d3R4048420d3m4d3o4f47343;3v0d3y4l3A3#3M4q130d3I4u3K4g4p3|4z3P4C4n4x4G433Z4J4w3T4i3,4P3.4h4y433@4U3_4W4M0d3~4!4E3(4M0x454*4o4,3*0x4c2}4K4R4X0x4k4_4Q414|4t4 4V4F4?4B544#563=0x4I594+3:4-4O5f4;5h4?4T5k4L4?4Z5p4{4-4)5t514M0U4/5x4$3*0U4^3d1M2{1B2,2V0I212!3T0S2@2v0-1S1J2`0P2|5H4C055R0.5Z5g010N133h3J0q504h0S130A1.0,0P3J5;2e12040T3Q0q635:551=5,040.0t5/5}2q0R130k0k2;2F6h5|660~5 0B6m5a1=0Q5 0(0P0H6b5#6n015 0J6c6B0F135X2?0R6r5*6D6F6s3E136K6M5l6C136E4C656Q3s5-3%5{6A6#5 0C614J646:6!5*6u136w6y6U3r0Y130!6{4R6I2L6T6Z6d0~6}040X6P5*6H046J0Y6L6/6;6376016@046_6z2 6B786 6*7c6S7g7b6V787a756G7x7h4_7j7k6B7n7p703`7t7N4h6%1;6)2}6=7A137C7V7l7d3h7U4e7I7W3r7L6x7q5H7s6~7Q34130R0Y0c2i2(1A7D6#7B7z3r5 0e0l3Q066:7l686a824R0t7^2@0j2g0P0k7_7{0F2(7?1=6p8q0~7-6`7v6V6O7 7w041a100P2L8t6W046Y7!7E8C7`7|7(3o7l6,6.7H7I7l8v7/8R7;047u7r6#7d8m8P7~8(6N130Z8H8*0W8E8G8x83130g8d7O7Y8~7R8N8n8p4J88648a138c8A6V0F8f938P0k0.8H8s8`3T8Y9k6X917@8C8@0j8F8Q2R8S136-628W6B688i9r3i7^9u9w9H770i132;9M7m6v7.8H7P9m418g941z9p609C7*7J6#682L0$0*0p0F9R9o9X489W8.9d9Z8,9$8;9@9s8D9v8_9`8{048}96899E9a0P8Z2R7+8e9|8o8k2E1p1.9$6qa06t9T8wa53T8T9(6;99049G9c3M0Q132sao8H9?au8 8$8=ai7}9$0C9R78020v0$0u9R0R0j135B7:6+138U7)9)9*8B0$0Y0:0HaS90aC3TaZa#ax7*az0t3V9R8*7`aS9OaA9;a^3`aJa%5*9_bb9{9gaj8-be6|7=aq6R040,3u1ybi8!a(040B9B7ia,aa8)13a/a;a?040o7Z3dag9Y93a|9D9+139-9/b78LbB04bD3ubF0hb1aE04aGbm8IapaK48babtbcblb,a18ObhaQ87bA5*8badb19f8+aj0k2C0F0.2L9x5)8y13b+bj9nasaec9a68KbJ7#5-0Yad0tbs9y6BawbyayabaAcgbK4hb$b(b=8rcbaIcf9Vb;cdbLc1aPb)6,bFaUaWaYa!04a$b/ca9%cua}8MbXa=b89^a@bU5*a`cVbN7jclbWa:3u0k5Rcocq3w7l81c)2ec.cW3Abzcz2e68a 0pb19J8^c8d61=0Yb59Qd0ar6^9Ub)bdcX3MaO9#cOa)c:9)c=c%bFbH9=cHdocJdq71bgcNcD6o8:aN9tdd9$a8c,7X040Kdb04c`0tcp9~dNa29Ldua7dwc#bVc%c_cndZc|df7713dBdkbndYd!d)9 dK6$dOa3c89zd*c!bOb|bQ0/bSdWdzd`0178b!ef7dd.d|c|97c;cw6x6w9$a*4md5azbR9:9R0N5?040E1kc8150h5%5Y5IeK0h5L1B0$5NeP2Y2T0W1-eM5L1Hch3T2L0R0k0t0W0N8k0z0U131t1v1x1z0qeu9y1O3e1I0b7g2u0q2;1R1x0O0q0I280@0H000P0+8F0S0j0S1/2`0O0S0O0.0F0$0J0q1.e@7ke`eZ5U2-3`1@1#1%1)5W5J2 5#eJe!3`68ere4csdv6Zeod?5+ea9.ezefeB13eE954 eI5S2S5X2SeY0D0P1i0q0f1 1/7g0j0(7u1P1K040M2;2Efq1/eJ0qfifkfm0$0q1zg70O1x1S3u2ig70ye@1M3e2,3rfz1_1(2_fE5!2 fHaz9bdS3Mc0b@2(c31kc60PfMbuccdGb9dDe08zgxdHemaQe^14b{6V9Fcy7#cB2iaHb)b.cr80dFg(8BcMdtgM9AcQaVaXefd2etdwdyc@c(gOaLbI3ofRg^e7a-bfeld:d}g~c*79cTa{h4fRd8b0ejdce3b49PbTck7KgLcKhb8%hsb?9!c|e5gSfQd,a.g|dAh0af8XhrgJhtd$gAg.hvcE04d hPbnd%a4hT8IdRhpg)dUdWgQd~d$9KhWhK5~8|d+98c$g|d/c{hFh%h8hyfNhRh*dPd)hZeve8gVfTechjc?bEefehedh?h(f#gu1O5JeN5VeH0.0:0=0(04.

Évaluations restantes : 5/5

.128013Cy1{ê]/wi_}qP+r 79f;gR2àhE()pNn0ld,*4Akéebmc:35a=o[.8t6sSuxv050I0P0$0W0j0H0(0q0S0H0W0(0(0X010$0j0D010406050(0*0R0R0W0p0c040)0Y0H0*100Y0F0q020W0R0D0u0q0w0P1a0p0m0*0P0(050h17191b1d150D04051I1B1L0h1I150I0j0,0^0`0|0~0z0j0v0z0H1Z0z0$13050:0Q0H0P1U0{0}011Y1!1$1!0$1,1.1*0$0p1J0$0z0^1g0(0D0W0F0~0x011:1W010t0=0P0F1o0P1*26282d1=2g1.2j0R2l040a0q0n0p0Y0D0Y0(0j1j1l0.240p0p0P0S2G1B2n0F1J0h222S1 21201+0I2p0~1$0F2i2D1*1R1T0_1;2$0j2(0F0Y2,1*0D2L1J2Q2S2}16271l2.2e2?0p1a0H130q0d2P3114302o331=3537390x3c283e2Q2#013j0W38040q0U3n2R153q3h0~3t3v0q0L3z3p313r3F390V3J3B3L3D3s0Y363u390%3Q3f321V3i3V3k3w0r3!3C3%3E3)3X3w0#3-3S3/3U3W3G0s3^3g3`3N040d0G3 3$2/3{3*0d3b1C3d3R4048420d3m4d3o4f47343;3v0d3y4l3A3#3M4q130d3I4u3K4g4p3|4z3P4C4n4x4G433Z4J4w3T4i3,4P3.4h4y433@4U3_4W4M0d3~4!4E3(4M0x454*4o4,3*0x4c2}4K4R4X0x4k4_4Q414|4t4 4V4F4?4B544#563=0x4I594+3:4-4O5f4;5h4?4T5k4L4?4Z5p4{4-4)5t514M0U4/5x4$3*0U4^3d1M2{1B2,2V0I212!3T0S2@2v0-1S1J2`0P2|5H4C055R0.5Z5g010N133h3J0q504h0S130A1.0,0P3J5;2e12040T3Q0q635:551=5,040.0t5/5}2q0R130k0k2;2F6h5|660~5 0B6m5a1=0Q5 0(0P0H6b5#6n015 0J6c6B0F135X2?0R6r5*6D6F6s3E136K6M5l6C136E4C656Q3s5-3%5{6A6#5 0C614J646:6!5*6u136w6y6U3r0Y130!6{4R6I2L6T6Z6d0~6}040X6P5*6H046J0Y6L6/6;6376016@046_6z2 6B786 6*7c6S7g7b6V787a756G7x7h4_7j7k6B7n7p703`7t7N4h6%1;6)2}6=7A137C7V7l7d3h7U4e7I7W3r7L6x7q5H7s6~7Q34130R0Y0c2i2(1A7D6#7B7z3r5 0e0l3Q066:7l686a824R0t7^2@0j2g0P0k7_7{0F2(7?1=6p8q0~7-6`7v6V6O7 7w041a100P2L8t6W046Y7!7E8C7`7|7(3o7l6,6.7H7I7l8v7/8R7;047u7r6#7d8m8P7~8(6N130Z8H8*0W8E8G8x83130g8d7O7Y8~7R8N8n8p4J88648a138c8A6V0F8f938P0k0.8H8s8`3T8Y9k6X917@8C8@0j8F8Q2R8S136-628W6B688i9r3i7^9u9w9H770i132;9M7m6v7.8H7P9m418g941z9p609C7*7J6#682L0$0*0p0F9R9o9X489W8.9d9Z8,9$8;9@9s8D9v8_9`8{048}96899E9a0P8Z2R7+8e9|8o8k2E1p1.9$6qa06t9T8wa53T8T9(6;99049G9c3M0Q132sao8H9?au8 8$8=ai7}9$0C9R78020v0$0u9R0R0j135B7:6+138U7)9)9*8B0$0Y0:0HaS90aC3TaZa#ax7*az0t3V9R8*7`aS9OaA9;a^3`aJa%5*9_bb9{9gaj8-be6|7=aq6R040,3u1ybi8!a(040B9B7ia,aa8)13a/a;a?040o7Z3dag9Y93a|9D9+139-9/b78LbB04bD3ubF0hb1aE04aGbm8IapaK48babtbcblb,a18ObhaQ87bA5*8badb19f8+aj0k2C0F0.2L9x5)8y13b+bj9nasaec9a68KbJ7#5-0Yad0tbs9y6BawbyayabaAcgbK4hb$b(b=8rcbaIcf9Vb;cdbLc1aPb)6,bFaUaWaYa!04a$b/ca9%cua}8MbXa=b89^a@bU5*a`cVbN7jclbWa:3u0k5Rcocq3w7l81c)2ec.cW3Abzcz2e68a 0pb19J8^c8d61=0Yb59Qd0ar6^9Ub)bdcX3MaO9#cOa)c:9)c=c%bFbH9=cHdocJdq71bgcNcD6o8:aN9tdd9$a8c,7X040Kdb04c`0tcp9~dNa29Ldua7dwc#bVc%c_cndZc|df7713dBdkbndYd!d)9 dK6$dOa3c89zd*c!bOb|bQ0/bSdWdzd`0178b!ef7dd.d|c|97c;cw6x6w9$a*4md5azbR9:9R0N5?040E1kc8150h5%5Y5IeK0h5L1B0$5NeP2Y2T0W1-eM5L1Hch3T2L0R0k0t0W0N8k0z0U131t1v1x1z0qeu9y1O3e1I0b7g2u0q2;1R1x0O0q0I280@0H000P0+8F0S0j0S1/2`0O0S0O0.0F0$0J0q1.e@7ke`eZ5U2-3`1@1#1%1)5W5J2 5#eJe!3`68ere4csdv6Zeod?5+ea9.ezefeB13eE954 eI5S2S5X2SeY0D0P1i0q0f1 1/7g0j0(7u1P1K040M2;2Efq1/eJ0qfifkfm0$0q1zg70O1x1S3u2ig70ye@1M3e2,3rfz1_1(2_fE5!2 fHaz9bdS3Mc0b@2(c31kc60PfMbuccdGb9dDe08zgxdHemaQe^14b{6V9Fcy7#cB2iaHb)b.cr80dFg(8BcMdtgM9AcQaVaXefd2etdwdyc@c(gOaLbI3ofRg^e7a-bfeld:d}g~c*79cTa{h4fRd8b0ejdce3b49PbTck7KgLcKhb8%hsb?9!c|e5gSfQd,a.g|dAh0af8XhrgJhtd$gAg.hvcE04d hPbnd%a4hT8IdRhpg)dUdWgQd~d$9KhWhK5~8|d+98c$g|d/c{hFh%h8hyfNhRh*dPd)hZeve8gVfTechjc?bEefehedh?h(f#gu1O5JeN5VeH0.0:0=0(04.

D'après un exercice de Nicolas Revéret