Exercícios Fundamentos Python.ipynb

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    "### 1- Imposto a pagar no Lucro Presumido\n",
    "\n",
    "- 5% sobre faturamento de ISS (mensal)\n",
    "- 0,65% de PIS sobre faturamento, (mensal)\n",
    "- 3% de COFINS sobre faturamento, (mensal)\n",
    "- 4.8% de IR (trimestral)\n",
    "- 10% de IR Adicional sobre o que ultrapassar 20mil do faturamento (trimestral)\n",
    "- CSLL: 2,88% sobre faturamento (trimestral)"
   ]
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    "# Faturamento mensal\n",
    "faturamento = {\n",
    "    'jan': 'R$ 95.141,98',\n",
    "    'fev': 'R$ 95.425,16',\n",
    "    'mar': 'R$ 89.716,31',\n",
    "    'abr': 'R$ 78.459,99',\n",
    "    'mai': 'R$ 71.087,28',\n",
    "    'jun': 'R$ 83.911,06',\n",
    "    'jul': 'R$ 56.467,26',\n",
    "    'ago': 'R$ 88.513,58',\n",
    "    'set': 'R$ 66.552,49',\n",
    "    'out': 'R$ 80.164,07',\n",
    "    'nov': 'R$ 66.964,33',\n",
    "    'dez': 'R$ 71.525,25',\n",
    "}\n",
    "\n",
    "# Impostos mensais\n",
    "iss = 0.05\n",
    "pis = 0.0065\n",
    "cofins = 0.03\n",
    "# Impostos trimestrais\n",
    "ir = 0.048\n",
    "ir_acima_de_20mil_faturamento = 0.10\n",
    "csll = 0.0288\n",
    "\n",
    "def formatar_valor(valor):\n",
    "    return f'R$ {valor:,.2f}'.replace(',', 'X').replace('.', ',').replace('X', '.')\n",
    "\n",
    "def calcular_imposto(faturamento):\n",
    "    resultado = {}\n",
    "    trimestres = {\n",
    "        'Q1': ['jan', 'fev', 'mar'],\n",
    "        'Q2': ['abr', 'mai', 'jun'],\n",
    "        'Q3': ['jul', 'ago', 'set'],\n",
    "        'Q4': ['out', 'nov', 'dez']\n",
    "    }\n",
    "\n",
    "    for trimestre, meses in trimestres.items():\n",
    "        faturamento_trimestral = 0\n",
    "        for mes in meses:\n",
    "            valor = faturamento[mes]\n",
    "            valor_numerico = float(valor.replace('R$ ', '').replace('.', '').replace(',', '.'))\n",
    "            faturamento_trimestral += valor_numerico\n",
    "            \n",
    "            # Calcula os impostos mensais\n",
    "            iss_pagar = valor_numerico * iss\n",
    "            pis_pagar = valor_numerico * pis\n",
    "            cofins_pagar = valor_numerico * cofins\n",
    "            soma_impostos_mensais = iss_pagar + pis_pagar + cofins_pagar\n",
    "            resultado[mes] = (valor_numerico, soma_impostos_mensais)\n",
    "        \n",
    "        # Calcula os impostos trimestrais\n",
    "        ir_pagar = faturamento_trimestral * ir\n",
    "        if faturamento_trimestral > 20000:\n",
    "            excedente = faturamento_trimestral - 20000\n",
    "            ir_pagar += excedente * ir_acima_de_20mil_faturamento\n",
    "        csll_pagar = faturamento_trimestral * csll\n",
    "        \n",
    "        # Soma dos impostos trimestrais\n",
    "        soma_impostos_trimestrais = ir_pagar + csll_pagar\n",
    "        resultado[trimestre] = (faturamento_trimestral, soma_impostos_trimestrais)\n",
    "\n",
    "    return resultado\n",
    "\n",
    "impostos_calculados = calcular_imposto(faturamento)\n",
    "for periodo, valores in impostos_calculados.items():\n",
    "    faturamento_periodo, soma_impostos = valores\n",
    "    print(f'{periodo}: Faturamento = {formatar_valor(faturamento_periodo)}, Impostos = {formatar_valor(soma_impostos)}')\n"
   ]
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    "### 2 - Puxando informações de um banco de Dados"
   ]
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    "import pandas as pd\n",
    "\n",
    "# Informações de exemplo\n",
    "informacoes = [(1, 'NATHANIEL FORD', 'GENERAL MANAGER-METROPOLITAN TRANSIT AUTHORITY', 167411.18, 0.0, 400184.25, None, 567595.43, 567595.43, 2011, '', 'San Francisco', ''), \n",
    "               (2, 'GARY JIMENEZ', 'CAPTAIN III (POLICE DEPARTMENT)', 155966.02, 245131.88, 137811.38, None, 538909.28, 538909.28, 2011, '', 'San Francisco', ''), \n",
    "               (3, 'ALBERT PARDINI', 'CAPTAIN III (POLICE DEPARTMENT)', 212739.13, 106088.18, 16452.6, None, 335279.91, 335279.91, 2011, '', 'San Francisco', ''), \n",
    "               (4, 'CHRISTOPHER CHONG', 'WIRE ROPE CABLE MAINTENANCE MECHANIC', 77916.0, 56120.71, 198306.9, None, 332343.61, 332343.61, 2011, '', 'San Francisco', ''), \n",
    "               (5, 'PATRICK GARDNER', 'DEPUTY CHIEF OF DEPARTMENT,(FIRE DEPARTMENT)', 134401.6, 9737.0, 182234.59, None, 326373.19, 326373.19, 2011, '', 'San Francisco', ''), \n",
    "               (6, 'DAVID SULLIVAN', 'ASSISTANT DEPUTY CHIEF II', 118602.0, 8601.0, 189082.74, None, 316285.74, 316285.74, 2011, '', 'San Francisco', ''), \n",
    "               (7, 'ALSON LEE', 'BATTALION CHIEF, (FIRE DEPARTMENT)', 92492.01, 89062.9, 134426.14, None, 315981.05, 315981.05, 2011, '', 'San Francisco', ''), \n",
    "               (8, 'DAVID KUSHNER', 'DEPUTY DIRECTOR OF INVESTMENTS', 256576.96, 0.0, 51322.5, None, 307899.46, 307899.46, 2011, '', 'San Francisco', ''), \n",
    "               (9, 'MICHAEL MORRIS', 'BATTALION CHIEF, (FIRE DEPARTMENT)', 176932.64, 86362.68, 40132.23, None, 303427.55, 303427.55, 2011, '', 'San Francisco', ''), \n",
    "               (10, 'JOANNE HAYES-WHITE', 'CHIEF OF DEPARTMENT, (FIRE DEPARTMENT)', 285262.0, 0.0, 17115.73, None, 302377.73, 302377.73, 2011, '', 'San Francisco', '')]\n",
    "\n",
    "# Descrição das colunas\n",
    "descricao = ['Id', 'EmployeeName', 'JobTitle', 'BasePay', 'OvertimePay', 'OtherPay', 'Benefits', 'TotalPay', 'TotalPayBenefits', 'Year', 'Notes', 'Agency', 'Status']\n",
    "\n",
    "# Criando o DataFrame com os nomes das colunas\n",
    "tabela = pd.DataFrame.from_records(informacoes, columns=descricao)\n",
    "\n",
    "# Construindo o texto do corpo do e-mail para o RH\n",
    "texto_rh = \"RH, segue a lista dos funcionários:\\n\\n\"\n",
    "for index, row in tabela.iterrows():\n",
    "    texto_rh += f\"{row['EmployeeName']}, Cargo: {row['JobTitle']}\\n\"\n",
    "\n",
    "print(texto_rh)\n"
   ]
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    "### 3 - Extração dos links de Download de Vídeos do Vimeo\n",
    "\n",
    "- Precisamos pegar os links em 1080p, 720p e 540p para importar os vídeos para uma nova plataforma"
   ]
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   "source": [
    "# para pegar o dicionario do vimeo, use:\n",
    "from dic import dicionario_vimeo\n",
    "\n",
    "# você precisa chegar em:\n",
    "# videos = [\n",
    "#     {'uri': video_uri, 'nome': nome_video, 'duracao': duracao, 'link540p': link540p, 'link720p': link720p, 'link1080p': link1080p},\n",
    "# ]\n",
    "\n",
    "videos = []\n",
    "\n",
    "for video in dicionario_vimeo['data']:\n",
    "    video_info={\n",
    "        'uri': video['uri'],\n",
    "        'nome': video['name'],\n",
    "        'duracao': video['duration'],\n",
    "        'link540p': video.get('player_embed_url') + '&quality=540p',\n",
    "        'link720p': video.get('player_embed_url') + '&quality=720p',\n",
    "        'link1080p': video.get('player_embed_url') + '&quality=1080p',\n",
    "    }\n",
    "    videos.append(video_info)\n",
    "    \n",
    "for video in videos:\n",
    "    print(video)"
   ]
  }
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